FAST LOGISTICS IN THE B2C eCOMMERCE: A GLOBAL OVERVIEW FORTIN… · fast logistics in the b2c ecommerce: a global overview 1 politecnico di milano school of industrial and information

FAST LOGISTICS IN THE B2C eCOMMERCE: A GLOBAL OVERVIEW

1

POLITECNICO DI MILANO

SCHOOL OF INDUSTRIAL AND INFORMATION ENGINEERING

MASTER OF SCIENCE IN MANAGEMENT ENGINEERING


CANDIDATE: SUPERVISOR: Veronica Fortini (842408) Prof. Riccardo Mangiaracina

CO-SUPERVISORS: Dott. Samuele Fraternali Dott.ssa Denise Ronconi

Academic Year 2016/2017


2


3

Index

ABSTRACT 9

EXECUTIVE SUMMARY 10

1. Introduction 18

2. Literature Review 21

2.1 Methodology 21

2.1.1 Scope of the analysis 21

2.1.2 Selection process 21

2.1.3 Review method 22

2.2 Summary of review and discussion 23

2.2.1 Main characteristics of the papers examined 24

2.2.2 Research methods used 27

2.3 Discussion of themes arising from the review 29

2.3.1 Research area 30

2.3.2 First matrix classification: speed of delivery – type of activity 32

2.3.3 Second matrix classification: speed of the logistics process -field

of application 50

2.4 Conclusions from literature review and directions for future

research 58

3. Research objective and methodology 65

3.1 Objective 66

3.2 Methodology 67

4. Empirical analysis 77

4.1 First empirical analysis: single-variable classifications 77

4.1.1 Global context 77

4.1.1.1 Merchants’ sample size 77

4.1.1.2 Breakdown by channel, web technology and commodity

sector 78

4.1.1.3 Split by delivery speed 80

4.1.1.4 Service providers 83

4.1.2 United States 84


sector 85


4.1.2.3 In-depth analysis of logistics providers, related cost,

coverage and type 88


4

4.1.2.4 Logistics technologies and alternatives to last-mile

delivery 91

4.1.2.5 Additional services: real-time tracking, date/time choice

and pre-delivery contacts 92

4.1.3 United Kingdom 93


sector 94





delivery 97



4.1.4 Other European countries (France, Germany, Italy , Spain) 100


sector 101





delivery 112



4.1.5 Asian countries (China, India, Japan and South Korea) 116


sector 117





delivery 129



4.1.6 Conclusions and insights from first empirical classifications 133

4.2 Second empirical analysis: double-variable classifications 139

4.2.1 Commodity sector – merchant’s business nature 140

4.2.1.1 Next Day 140

4.2.1.2 Same Day 143

4.2.1.3 Less than six hours 146

4.2.2 Commodity sector – geographical coverage 148


5

4.2.2.1 Next Day 148

4.2.2.2 Same Day 148


4.2.3 Commodity sector – type of logistics service 152

4.2.3.1 Next Day 152

4.2.3.2 Same Day 155


4.2.4 Commodity sector – used transportation means 159

4.2.4.1 Next Day 159

4.2.4.2 Same Day 160


4.2.5 Conclusions and insight from second empirical analysis 162

5. Final conclusions 165

BIBLIOGRAPHY 168

SITOGRAPHY 172


6

TABLES INDEX Table 1 – main characteristics of the examined papers 31

Table 1 - Area of research of papers examined 37

Table 2 – first classification: addressed activities vs. speed of delivery 41

Table 3 - second classification: speed of logistics vs. application field 58

Table 4 - global merchants' quantity 81

Table 5 - global merchants' excluded non-interesting cases 82

Table 6 - global merchants' market channel 83

Table 7 - global merchants' web technology 83

Table 8 - global merchants' sector 84

Table 9 - global merchants' delivery time 85

Table 10 - global merchants' service providers

88

Table 11 - US merchants' market channel 89

Table 12 - US merchants' web technology 89

Table 13 - US merchants' sector 90

Table 14 - US merchants' delivery time

90

Table 15 - US merchants' service providers 92

Table 16 - US merchants' delivery cost

93

Table 17 - US merchants' geographic coverage 94

Table 18 - US merchants' logistics type 95

Table 19 - US merchants' transportation means 96

Table 20 - US merchants' last-mile alternatives

96

Table 21 - US merchants' tracking systems 97

Table 22 - US merchants' time choice 97

Table 23 - US merchants' contacts 97

Table 24 - UK retailers' market channel 98

Table 25 - UK retailers' web technology 98

Table 26 - UK retailers' sector

99

Table 27 - UK retailers' delivery time 99

Table 28 - UK retailers' service provider 100

Table 29 - UK retailers' delivery cost 100

Table 30 - UK retailers' geographic coverage

101

Table 31 - UK retailers' logistics type 101

Table 32 - UK retailers' transportation means 101


7

Table 33 - UK retailers' last-mile alternatives 102

Table 34 - UK retailers' tracking systems 103

Table 35 - UK retailers' day/time choice 103

Table 36 - UK retailers' contacts 104

Table 37 - European merchants' market channel 105

Table 38 - European merchants' web technology 106

Table 39 - European merchants' sector 108

Table 40 - European merchants' delivery time 109

Table 41 - European merchants' service providers 112

Table 42 - European merchants' delivery cost 114

Table 43 - European merchants' geographic coverage 115

Table 44 - European merchants' logistics type 116

Table 45 - European merchants' transportation means 117

Table 46 - European merchants' last-mile alternatives 118

Table 47 - European merchants' tracking system 119

Table 48 - European merchants' day/time choice 119

Table 49 - European merchants' contacts 120

Table 50 - Asian retailers' market channel

122

Table 51 - Asian retailers' web technology 123

Table 52 - Asian retailers' sector 124

Table 53 - Asian retailers' delivery time 125

Table 54 - Asian retailers' service providers 128

Table 55 - Asian retailers' delivery cost 129

Table 56 - Asian retailers' geographical coverage

131

Table 57 - Asian retailers' logistics type 132

Table 58 - Asian retailers' transportation means 134

Table 59 - Asian retailers' last-mile alternatives 135

Table 60 - Asian retailers' tracking system

136

Table 61 - Asian retailers' day/time choice 137

Table 62 - Asian retailers' contacts 138

Table 63 - sector vs. channel next day global 145

Table 64 - sector vs. channel next day US 145

Table 65 - sector vs. channel next day UK 146

Table 66 - sector vs. channel next day Europe 147

Table 67 - sector vs. channel next day Asia 147

Table 68 - sector vs. channel same day global 148

Table 69 - sector vs. channel same day US 148


8

Table 70 - sector vs. channel same day UK

149

Table 71 - sector vs. channel same day Europe 149

Table 72 - sector vs. channel same day Asia

150

Table 73 - sector vs. channel <6h global 150

Table 74 - sector vs. channel <6h US 151

Table 75 - sector vs. channel <6h Europe 151

Table 76 - sector vs. channel <6h Asia 152

Table 77 - sector vs. coverage next day global 152

Table 78 - sector vs. coverage same day global 153

Table 79 - sector vs. coverage same day US 153

Table 80 - sector vs. coverage same day UK

154

Table 81 - sector vs. channel same day Europe 155

Table 82 - sector vs. coverage same day Asia 156

Table 83 - sector vs. coverage <6h global 156

Table 84 - sector vs. logistics next day global 157

Table 85 - sector vs. logistics next day US 157

Table 86 - sector vs. logistics next day Europe 158

Table 87 - sector vs. logistics next day Asia 159

Table 88 - sector vs. logistics same day global 160

Table 89 - sector vs. logistics same day US 160

Table 90 - sector vs. logistics same day Europe

161

Table 91 - sector vs. logistics same day Asia 162

Table 92 - sector vs. logistics <6h global 163

Table 93 - sector vs. vehicles next day global 164

Table 94 - sector vs. vehicles same day global 165

Table 95 - sector vs. vehicles <6h global 166

FIGURES INDEX Figure 1 - two-dimensional classification along with research method 41 Figure 2 - two-dimensional classification along with research method 59

Figure 3 - extract from database: merchants' number, name, service provider,

country, market channels and web technology 70

Figure 4 - extract from database: retailers' sector, delivery time and other time

features 72

Figure 5 - extract from database: delivery cost and its characteristics 73


9

Figure 6 - extract from database: geographic coverage and delivery area's details74

Figure 7 - extract from database: logistics service type, operator, name and

vehicles used 75

Figure 8 - extract from database: last-mile alternatives and real-time tracking 76

Figure 9 - extract from database: day/time choice and duration, contacts before

delivery and useful websites 77


10

ABSTRACT This research aims at providing an in-depth analysis of the current initiatives

of fast delivery in the eCommerce business. Given the strong growth of the

Internet in the last decades and the corresponding development of the channel of

online sales, one of the most challenging topics that merchants have to face

regards the way in which they have to organize and manage their logistics

fulfillment processes, that are much more complex in the eCommerce with

respect to the traditional channels.

The methodology adopted for providing this overview comprehends a first

analysis of the existing literature about this topic: articles have been collected

from the most utilized scientific libraries and they have been analyzed first

according to their area of research, then through a matrix in which the speed of

the delivery process they described was crossed with the type of activities tackles;

lastly, another matrix have been provided in order to match again the speed of

the logistics process subject of the article with the main field of application of the

contribution.

Having then outdrawn comments on findings, from the main gaps

highlighted in the literature review a second analysis have been performed

having as subject of research the sample of main merchants actually working in

the eCommerce; rankings on top players in the sector have allowed to find which

the most important players were and the an extensive research on the most

common web browsers have been performed for each of them in order to collect

a huge amount of data about the delivery services they offered, which have been

collected in a database.

Data have been previously analyzed by considering one single field of the

database at a time and then have been crossed together in some double-variable

classifications in which mainly similarities and differences according to the

commodity sector of belonging of the merchants have been investigated.

All the analyses made on real examples have provided a complete overview of

the up-to-date online market for what concerns fast and non-fast delivery

options, providing some interesting insights for practitioners’ development.


11

EXECUTIVE SUMMARY

Premise

This research aims at providing an in-depth analysis of the up-to-date

situation in relation to initiatives of fast delivery in the eCommerce business.

Given the strong growth of the Internet in the last decades and the

corresponding high development of the channel of online sales, one of the most

challenging topics that merchants have to face regards the way in which they

have to organize and manage their logistics fulfillment processes, that are much

more complex in the eCommerce with respect to the traditional channels made

of physical stores. As next day delivery initiatives have almost become a common

trend at a worldwide level, the disruption resulting from same day delivery

services’ diffusion will be even greater, having the potential of fundamentally

changing the way online shopping is performed. Therefore, the trend of fast

deliveries is under development in these years and it represents a rich source of

cases.

Research objective

The objective of the research is the one of collecting and classifying most

interesting initiatives in order to provide not only directions for future research

to academicians, but also to allow market practitioners to get insights from

existing cases for their own services’ development, increasing more and more the

diffusion of such practices in the actual context and improving the service level.

In an attempt to provide a complete picture of the current situation for what

concerns fast logistics in business-to-consumer eCommerce, the objective of the

thesis has been formalized in the following questions:

1) Which are the most relevant real examples of merchants operating in the

eCommerce at a worldwide level?

2) How many of these merchants carry out their e-fulfillment process not

going beyond the next day from order reception? And how many among

them offer even faster options?

3) Which commonalities and/or differences exist among initiatives belonging

to different geographical areas?

4) Which commodity sectors are interested by this kind of initiatives? Are

there any commonalities and/or differences in the initiatives’ feature

among the industries?

5) What are the latest trends about the main features of logistics activities

and about the technologies employed for the provision of this kind of

services?


12

Methodology

The first action taken for taking an updated picture has been a literature

review focused on a set of 52 selected papers published from 2001 to 2017 in 39

international journals. Among these contributions, some other literature reviews

dealing with internet shopping and home deliveries were found, but the majority

of them presented a number of limitations related either to their put in writing

time (i.e. lack of recent contributions, e.g. Lee and Whang, 2001) or to their

content (i.e. focus on last-mile shipment only and its impact on city logistics,

without addressing the whole process from order receipt; e.g. Visser et al., 2014;

Savelsbergh and Van Woensel, 2016). Just one paper proposed a recent review

(2016) and tackled all supply chain management activities in eCommerce, from

order picking to final delivery, but it was providing a set of practices

implemented by real companies without addressing fast delivery issue in a

comprehensive manner (Yu et al., 2016). So this review was carried out in order to

overcome the above-mentioned limitations and was organized into three main

sub-sections: discussion of main characteristics (i.e. year of publication, journal

title and type, regions addressed), research method and content of each paper.

This review presented a number of gaps not adequately addressed yet or not

considered at all.

First, the analyzed literature refers primarily to few industries such as grocery,

food in general and consumer electronics, while other sectors such as clothing,

books, cosmetics have not been examined at all. This represents a gap, especially

for what concerns clothing industry, because it is the one having seen the highest

growth in sales in the last years and also having experienced a significant growth

of companies approaching same day or next day deliveries, especially in big cities

and in case of last-minute orders (e.g. on Christmas or other holiday occasions);

additionally, its supply chain is of relevant complexity.

Second, most attention is paid to the management of the delivery activity

alone, from the moment in which the order leaves the distribution center to the

end customer’s reception of it; even if it is surely a very complex activity to be

performed and its last portion, the one occurring inside cities and having the

name of last-mile, is complex and the one representing the service performance

directly experienced by the customer, other activities are part of the delivery

process too and should be tackled with more attention: picking has an impact too

on the overall order cycle time and for sure a comprehensive approach which

considers both picking and delivery could get to larger benefits.

Third, while contributions about cycle times of more than two days are

common, a little has been written about faster processes. Longer delivery options

have now been overcome by same day and next day deliveries, which are

becoming (or already are, in more developed areas) industry standards


13

(Hausmann et al., 2014); this means that a lot of cases are spreading and these

practices need to be deeply studied and carefully analyzed as they could provide

very interesting insights and drive future development of the business-to-

consumer eCommerce field.

Lastly, too much space is occupied by empirical contributions (i.e. case

studies and surveys), especially for what concerns fast and same day delivery

classes: a wider investigation in the field will allow academics to gather a relevant

number of data and examples so as to develop articles of more general validity,

which could be used by practitioners as frameworks in order to guide their

operative strategies.

All these gaps have been useful in order to formalize the research questions.

Then starting from these highlighted gaps, a depth research has been

performed by investigating examples of delivery options offered by real

merchants operating in the eCommerce channel through the access to the digital

edition of a guide on top 2013 e-retailers; it is called “Internet retailer – portal to

eCommerce intelligence” and it provides profiles, statistics, contacts and analyses

of the largest retailers in a certain geographical area; in particular its versions

split by continent have been utilized, having so one ranking for European

countries, one for Asian continent and the third dedicated to United States

situation only. For Asian and European countries, top 25 players in the ranking

were identified for further research (with the exception of Spain, which was a bit

poorer in terms of relevant online players and the ranking only involved 14

retailers); for US instead, the field was so big that the analysis was extended to

the group of first 60 actors in the national ranking. So for each nation, all

websites belonging to the group of identified top merchants were searched on the

Internet and deeply studied, with a particular attention to the process of orders’

fulfillment and final delivery to customers. Then, all collected information have

been inserted in a database organized according to the following fields:

number in the national ranking: allowing to have an idea of merchants’

relevance inside their country of belonging in terms of sales;

merchant name;

service provider name;

country of belonging of the merchant;

Dot Com/traditional player;

pure player/multichannel retailer;

desktop/mobile website;

commodity sector: sector in which the player operates, identifying in a

precise manner the type of products sold and moved during the service’

supply; we have Clothing, Cosmetics & Perfumery, General, Grocery,

Home & Furniture, Informatics & general electronics, Publishing sectors


14

and then other industries of minor presence among which we can find

Childcare, Drugs, Eyewear, Flowers, Music stores and Office supplies;

time for the delivery service: considering services which take more time

than what represents our interest area, we can find different hours’ ranges

surpassing the 24 hours for service provision (e.g. web retailers delivering

in between 48 and 96 hours, others in 48 hours, others between 24 and 72

hours or between 24 and 48 hours); moving instead towards faster

services, we first find merchants operating within the next day or the next

morning (if they are able to assure delivery within lunch time of the day

after order submission); then we have same day operators; in the end,

there is a cluster of websites offering deliveries which do not overcome 6

hours for the whole service provision (some declare of taking less than 6

hours for delivery but without specifying a fixed time, while some others

assure services operating in between 1 and 2 hours or even taking less than

1 hour to be performed). Among all the websites examined, we found also

merchants not offering express services at all (i.e. typically serving

customers in not less than 2 or 3 days and even more), that have been

classified as “non fast” and for which data collection activity has stopped at

this stage as they do not represent the focus of the research. In addition,

there were also websites which were impossible to access and about which

no information could be found even searching through the more

traditional web browsers, together with sites of retailers providing services

and not physical items (and so not arranging any picking and delivery

activity for their business’ nature) and finally websites shut down (it could

be because after some test time they closed the online channel resorting to

more traditional ones or because they went bankrupt); all these cases were

obviously immediately excluded from the database;

additional time information;

hour limit in order to get on-time delivery;

delivery timeframes;

cost type: the delivery service has usually an own cost which adds up to

the one of bought items; this cost can be fixed, variable, fixed but

becoming free once reached a certain expense for the goods (and the same

can happen in case of variable cost) or in few cases offered for free no

matter the expense’s amount;

criteria taken into consideration for variable cost;

exact value of the delivery expense;

exact value of items’ expense to be reached in order to get free delivery;

minimum expense imposed for order submission;

price peculiarities: filled only if some peculiarities exist (e.g. a phone

number is provided and only by calling it the customer can know the exact


15

delivery expense or money-back guarantee is assured to customers if the

order is not delivered by the promised time window or if a maximum

number of articles which can be bought within one order exist, etc.);

international coverage;

national coverage;

local coverage;

coverage area;

logistics type (internal/outsourcing/crowd-sourcing): variable identifying

if all the logistics activities are performed internally by the retailer itself

(or at most by a logistics spin-off appositely created for serving a specific

e-retailer and belonging to the same owning group) or if they are left to an

external operator found on the logistics market or lastly, if they are

performed according to the crowd-sourcing model (i.e. there is an external

entity which doesn’t operate as a physical distributor owning assets and

fleets and having couriers working under its direct dependence, but it only

works as an inter-change platform, collecting independent couriers who

work autonomously with their own transportation means and connecting

them with retailers in search of someone to perform home delivery);

preferred logistics operator;

service name;

transportations means’ peculiarity: filled in case a web merchant (or in its

place the provider of the logistics service) resorts to a very specific type of

means only. We can find cases in which more traditional means as vans or

refrigerated vans only are adopted; then we have cases in which the

preferred vehicle utilized is the car. Moving to two-wheeled vehicles we

can find retailers employing indiscriminately bicycles and motorbikes,

while others provide their couriers exclusively with bicycles; there is also

the eco-friendly option in which couriers use electric bicycles for

performing final delivery. In the end moving to air transportation we have

cases in which the airplane is the only mean utilized or innovative

merchants putting in place delivery by drones;

click & collect in-store (as first last-mile delivery alternative);

parcel locker’s pickup (as second last-mile delivery alternative);

other collection point (additional diverse last-mile alternatives);

additional information on last-mile alternative: descriptive variable in

which all information regarding every delivery alternative offered by a

retailer (and explained in its website) are collected; it provides the

alternative description (in case it doesn’t involve in-store collection and/or

parcel locker) (e.g. convenience stores agreed upon collection service with

the retailer and having a terminal dedicated to collection of online orders;

or terminals belonging to a particular logistics operator allied with the


16

retailer such as UPS, Colissimo, Chronopost, Hermes points, etc.; or again

delivery in the store’s car park or directly inside vehicle’s trunk; etc.), the

hourly limit for order submission in order to get the alternative or the

specific time window taken by the alternative to be performed;

real-time tracking;

choice of the day/timeframe of delivery;

chosen timeframe duration;

pre-delivery contacts: descriptive variable in which, if present (otherwise

the value is “no”), the moment in which customers have the opportunity of

being directly in contact with the courier carrying their order with

him/her is identified. It could be just a notification to confirm that an

order has been received or a notification of goods pickup in the warehouse

and then of shipment; or it can be the opportunity of speaking with the

courier before he/she starts its delivery tour in order to arrange all the

details for an efficient delivery; or it can even be the option of receiving,

together with delivery details, also courier’s name and image to make the

delivery process always easier;

information on pre-delivery contacts: it reports the nature of contacts with

logistics operators and the technological mean utilized for the

communication (e.g. call, e-mail, text or notification on the website and

details about the exact time in which this communication takes place); of

course this field is filled in only when a pre-delivery contact occurs;

useful websites.

With the data collected in the database, some classifications and analyses

have been performed.

First of all single-variable classifications have been carried out by considering

one database’s field at a time and giving a first overview at a worldwide level,

then deeply investigated by splitting for different geographies of interest.

A second analysis have been carried out by crossing two variables: the first

one was always the commodity sector and the second ones have been selected in

order to find out if some commonalities and/or differences existed among

merchants belonging to different industries; they are the merchant’s business

nature (Dot Com pure player/traditional multichannel actor), the geographic

coverage of the service, the logistics’ type of the provider and lastly the

peculiarity (if any) of vehicles utilized for performing the distribution activity.


17

Results

All the aforementioned analyses got to the formalization of the following

answers to the research questions:

1) The most relevant cases of actual merchants operating in the eCommerce

nowadays belong to United States, immediately followed by United

Kingdom and then, some steps away, by France and Germany. The rest of

the European continent and the Asian countries represent a still too

under-developed context with respect to the first players (especially in

comparison with the United States). The worldwide market is still in

general strongly characterized by traditional retailers having added

eCommerce as their secondary or even third business, in an attempt of

implementing a multichannel strategy in order to increase their often

already stable market share; however, most of them have already

understood the potential of mobile devices’ diffusion and have developed

applications to increase the degree of pervasiveness into the market. Most

relevant actors in the actual context still belong to already strongly web

developed sectors of Clothing and Informatics, but other more recent

industries such as General and Grocery sectors are moving forward.

2) The portion of merchants performing deliveries in which the e-fulfillment

process lasts less than twenty-four hours at worldwide level corresponds

to an almost 46 percent of all the eCommerce merchants; of course this

value changes depending on the geography: it is a bit higher in the US

continent (52 percent), balanced a lower value in the Asian continent (38

percent). The European context, if United Kingdom is excluded, reports an

amount of cases not far from the one of oriental countries (37 percent),

but if adding the British merchants (which provide fast services in the 88

percent of national cases) the overall situation of Europe moves close to

the worldwide average value (reaching a 48 percent). Again United

Kingdom and United States provide the highest quantity of cases of

interest. However splitting these cases into more precise time windows

needed for delivery service provision, we find out that most of really fast

initiatives (i.e. the ones taking less than six hours) do not have a precise

country of belonging as they mainly are few sporadic cases or pilot

projects spread in almost all the global territory; instead interesting to

notice is the fact that while most of initiatives in American and European

countries relate to next day options, the most developed trend in the

Asian geographies is the one of same day deliveries.

3) Some of the insights got in order to answer to this question have been

already reported below. We can add that while for next day deliveries no

significant differences among countries can be found (excepted for the fact


18

that Dot Com next day players are in limited number in Asia and in the

US, while they constitute a more significant portion of the European

market), same day deliveries differentiate themselves according to the

country of development: indeed, while United States and Europe see a

limited diffusion of these delivery options, Asian countries led by India

report a huge development of same day services. In addition, while almost

all cases of interest can reach only a local coverage, in the United Kingdom

and in some Asian countries (mainly China and Japan) some merchants

are able to offer also more spread options that reach a more national

coverage.

4) The main sectors interested by fast initiatives in general are Clothing and

Informatics, but we can observe some dedicated trends according to the

country and the delivery timing. In fact, for what regards same day

deliveries, while in the US and Europe overall we can mainly find projects

in commodity sectors of recent development (such as Grocery and Others)

Asia provides a higher amount of examples belonging to sectors such as

Informatics and General, that in the other countries have experienced a

precedent development but then have often remained stuck to the next

day delivery timings. Additionally, some sectors comprehend merchants

that are able to cover higher distances with their fast delivery services

(maybe due also to the peculiarity of items transported), which are

Grocery sector in the UK context and Informatics industry in the Asian

continent.

5) The most delivery services increase their speed, the most we can observe

that retailer leave the recourse to outsourced logistics operators in favor of

internal infrastructures properly developed for providing a more

personalized and controlled service; another interesting trend which

ensures a certain speed of the overall e-fulfillment process avoiding big

investments is represented by the crowd-sourcing model application, but

it remains quite under-developed, with a relevant presence only in the

United States. For what concerns vehicles utilized in transportation, vans

(or refrigerated vans in the case of grocers) are leaving the ground to

lighter and faster means such as bicycles and/or motorbikes, especially

individually owned ones for the crowd-sourcing cases. Few cases of major

interest can be found (one of use of electric bicycles and the other project

with drones), but they only represent an almost irrelevant amount of pilot

and testing projects under development.


19

1. Introduction In the last decades, the Internet has emerged as a dynamic medium for

channeling transactions between customers and firms in a virtual

marketplace. The growth of the Internet has been phenomenal, and there has

been a corresponding growth in eCommerce market (i.e. the online market

channel). (Cho et al., 2008). The rise of online Internet sales and eCommerce

gave a big boost to retail companies’ sales and gave rise to new and different

business models. According to the “Euromonitor” the global non-store internet

retail sales or internet shopping reported a 14.8% growth from 2007 to 2012, while

the total retail growth was just 0.9% over the same period (Visser et al., 2014).

Estimates reported by the ECommerce Foundation (2015) show that business-to-

consumer (B2C) eCommerce sales worldwide reached $1.9 trillion in 2014,

representing a doubling in sales compared to 2011 (Savelsbergh and Van Woensel,

2016). Mainly following the spread of IT systems such as laptops, tablets, smart

phones and other technologies, today about 45% of all European consumers shop

online (Morganti et al., 2014). The market share of internet shopping will

continue to grow and will substitute traditional shopping. This is more evident by

the fact that by 2020 up to one third of the total shops at shopping centers in

European developed countries like the Netherlands will be closed down due to

the economic crisis and competition from web shops (Visser et al., 2014).

One of the challenging questions that online retailers now face is how to

organize the logistics fulfillment processes during and after order receipt.

Compared with traditional retailers, online retailers are at a disadvantage in that

when a shopper purchases an item from a physical store, the product can

immediately be taken home. However, in the case of online retailers, the

customer must wait for the shipment to arrive (Gong and de Koster, 2008). Jeff

Bezos of Amazon.com notes: “The logistics and the customer service – the

non‐glamorous parts of the business – are the biggest problem with

e‐commerce. A lot of these companies that are coming online spend all their

money and effort building a beautiful website and then they can't get the

stuff to the customer” (US News & World Report, 1999). In line with Bezos’

thought, in a research carried out by European consumers' organizations, it was

found that logistics aspects such as delivery lead times were not met by a

substantial part of the investigated Internet companies (de Koster, 2003). This is

due to the fact that eCommerce requires a new logistics approach in which

small order size, increased daily order volumes, small parcel shipments, and

same‐day shipments are common. Getting goods delivered to a customer's

doorstep in a timely manner is a complicated task and the success of firms in

the eCommerce market depends on the efficiency of their distribution

networks. The effective and efficient movement of goods is critical in the

http://www.emeraldinsight.com/doi/full/10.1108/09600030810882825


20

eCommerce logistics supply chain (Cho et al., 2008) and this has generated

significant demand for dedicated delivery services to the end customers.

All the aforementioned requirements have resulted in an increasing

fragmentation of shipments into different parts, with a strong attention paid to

the “last-mile” - the final leg in a business-to-consumer delivery service whereby

the consignment is delivered to the recipient, either at the recipient's home or at

a collection point (Ducret R.,2014) and a tremendous innovation in how this last-

mile delivery takes place (Morganti et al., 2014). Today, algorithm-driven delivery

models and analytics enable urban customers to get products delivered faster,

more flexibly, and sometimes less expensively than in the past. Options will

continue to proliferate in the future, with innovative delivery vehicles such as

drones, robots, and driverless vehicles, reducing or perhaps eliminating someday

the need for delivery personnel (Lee et al., 2016). This sector is also seeing the

diffusion of alternative pickup and delivery options (e.g., locker-boxes and parcel

shops) and speed will be the main push in this evolution (Hausmann et al., 2014).

There is an increasing requirement for punctuality and efficiency of express

delivery services. Due to the fact that all customers may have different time

schedules, it is especially important for an express company to deliver goods

punctually as customers expect. At the same time, the express companies

certainly hope to minimize the total travel time for a courier. Therefore, a courier

is facing a though problem and he needs to design the task schedule reasonably

at the beginning of a day’s work, which should not only satisfy all the customers’

appointment times but also make the total time minimized (Sun et al., 2016).

Customers tend to order more frequently, in smaller quantities, and they require

customized services. Companies tend to accept late orders while still

needing to provide rapid and timely delivery within tight time windows (thus the

time available for single preparation activities, such as order picking, is shorter).

In general, lead times are under pressure (Gong and de Koster, 2008). In addition,

the consumer is allowed more and more to take part in defining the e-logistics

that suits him/her, in terms of price, quality, time, green and/or fair practices.

That is, the “logsumer” has more and more power to dictate how the last-mile

needs to be organized (Savelsbergh and Van Woensel, 2016). Now that

eCommerce catches on as a favorable way of making purchases, customers have

increased the pressure they put on retailers and merchants to rapidly supply

products. In such a market, filling orders within a 24 hours time window has

become a standard since some years in many industries, including the

pharmaceutical, food and beverage, office supply and furniture industries

(Gagliardi et al., 2008). Nevertheless, consumers are demanding even more

convenience when delivery is concerned. They want to have multiple delivery options

to choose from, and to receive their products as fast as possible. Once consumers have

experienced a superior service level, they are usually reluctant to return to the


21

previous inferior level. Few people would be willing to wait four days for a digital

camera they have ordered online if they can get Amazon to deliver it the next day

(assuming both options are free). Judging from recent survey results, younger

generations (e.g., “millennial”), people living in small households, those working long

hours and consumers with higher incomes are among those particularly willing to pay

for more convenience and speed (Hausmann et al., 2014).

Next day or two-days delivery is currently the industry standard in all developed

countries, but the next evolutionary step is affordable same day delivery. With same

day delivery, orders are delivered within a few hours after purchasing them, or in a

chosen time window on the same day. The Senior Vice President of a logistics

company stated that: “Same day delivery is a game changer because it combines

the immediate product availability of retail with the convenience of ordering

from home” (Hausmann et al., 2014). In recent years, many e-tailers have started

to offer their customers a same day delivery option, sometimes even going down

to 1-hour or 2-hour delivery options (see, e.g., Amazon Prime in selected US

cities) (Savelsbergh and Van Woensel, 2016). Since many online purchases are

impulse buys and, as customers can change their minds and legally cancel the

order within a certain time horizon, a fast response is critical, next day delivery is

no longer enough and different retailers (e.g. the Datch operators Centraal

Boeekhuis, Wehkamp and Albert) had to put in place same day delivery services

in order to stay competitive. Additionally, often the customer specifies a certain

time window for delivery and retailers use different pricing schemes according to

different windows (Gong and de Koster, 2008). As groundbreaking as the

emergence of leading online retailers was in the 1990’s, the impending disruption

that will result from same day delivery will be greater. Same day delivery, if

executed correctly, can provide expansive options for consumers and brands

hoping to grow their business. While critics may see same day delivery as a

downfall for smaller retailers, it can potentially offer competitive advantage for

businesses of all sizes. The logistics required for making same day delivery a

reality are daunting. Supply chain, delivery, customer support, advanced

eCommerce software and warehouse facilities are all crucial to make the new

tactic a reality (Sareen, 2013). Same day delivery has the potential to fundamentally

change the way we shop. It integrates the convenience of online retail with the

immediacy of bricks-and-mortar stores. In recent years an increasing number of

companies have started piloting and operating new models of same day delivery,

including incumbent logistics providers such as DHL, DPD, FedEx, and UPS.

Demand is expected to increase significantly given the compelling value proposition

of same day delivery for consumers because consumers clearly attach a value to it.

The availability of same day delivery is actually expected to further support

eCommerce adoption and drive the online sales of product categories not yet bought

online on a large scale (such as groceries) (Hausmann et al., 2014).


22

2. Literature review Coherently with the above premises, the present literature review aims to analyze and

categorize the articles on fast delivery options in B2C eCommerce from an up-to-date

perspective, including more recent contributions to the topic. The objective of this

chapter is twofold: first, to classify researches on this topic made by practitioners and

academics and second, to identify gaps in the research in order to propose directions

for future studies.

2.1 Methodology

2.1.1 Scope of the analysis

This review concerns the examination of the literature related to business-to-

consumer eCommerce with a particular focus on fast deliveries. More specifically,

the viewpoint is that of retailers and merchants which operate in such a fast

delivery context, in order to understand how they decide to organize and conduct

their activities in order to be able to meet customers’ expectations. The main

activities which are investigated are picking after order receipt and delivery of the

goods to the end customer, with a particular attention to the last “leg” of the

delivery process, called “last-mile”. Furthermore, for what concerns order lead

time, not only articles about same day or even faster timings (e.g. about a few

hours) are taken into consideration, but also literature on deliveries made in 24

hours or more, if they are considered to significantly contribute to the topic of

operations’ optimization and activities’ time minimization.

2.1.2 Selection process

First, we established the classification context used to categorize the

material (i.e. logistics management of fast deliveries in the eCommerce

industry);

then the unit of analysis was identified as a single scientific paper or a

white paper published on an international journal;

we consequently conducted a search by keywords using library databases

(e.g. Science Direct, Scopus, Emerald Insights, Google Scholar, etc.). This

search has been carried out using keywords and strings (e.g. “fast picking

eCommerce”, “last-mile delivery”, “same day delivery”, “fast logistics

eCommerce”, “next day delivery”, etc.) and their combinations, that have

been sought in the abstract, title and main body of the scientific papers. In

order to avoid the omission of other potentially significant papers, the

majority of the contributions were also cross-referenced. This method

allowed to analyze the main logistics and transportation journals, as well


23

as journals about environment, information systems and computer

science, social and behavioral sciences (e.g. International Journal of

Physical Distribution and Logistics Management, International Journal of

Production Research, International Journal of Production Economics,

International Journal of Logistics Research and Applications, Journal of

Operations Management, Logistics Information Management,

Transportation Research Method, Transportation Science, European

Journal of Operational Research, Business and Information Systems

Engineering, Industrial Management and Data Systems, Information

Technology Journal, Production Planning and Control, Mathematical

Problems in Engineering, Studies in Computational Intelligence, etc.). In

this way, it was possible to assure adequate coverage of the actual body of

research in the field;

we first selected all the papers that in some way dealt with picking and

delivery activities’ management in the context of eCommerce, in order to

collect as many contributions as possible. Then, from this wide base, only

the papers specifically focused on activities’ optimization in terms of order

cycle time minimization and/or provision of a fast delivery offer to

customers where deeply analyzed. As such, the subset of contributions

lastly selected and considered for an in-depth investigation was made of 52

papers published from 2001 to 2017. The number of publications reviewed

in this study can be considered adequate given the fact that this topic has

been particularly developed in the last few years, so it is quite recent and it

is not easy to find many significant contributions on this field;

at this point, the literature was analyzed and categorized. During this

stage, a two-dimensional approach was chosen in order to provide a clear

classification of the examined papers.

2.1.3 Review method

For the purpose of this review, the selected contributions were classified

based on: their main characteristics (i.e. year of publication, journal title and

type, countries addressed), the research methods adopted, and the content area.

All of the papers were categorized according to these review criteria, in order to

identify patterns suggesting possible gaps and themes of interest for future

contributions (Perego et al., 2011; Mangiaracina et al., 2015).


24

2.2 Summary of review and discussion

Table I, based on Natarajarathinam et al. (2009), summarizes the main

attributes of each paper. According to Perego et al. (2011), the papers are listed in

chronological order to show the temporal evolution of the issue of fast response

to customers related to B2C eCommerce.

2.2.1 Main characteristics of the papers examined

Table 96 - main characteristics of the examined papers

1 First author’s country

S. no.

Author (year)

Country1 Journal Title Research

method

1 Lee and Whang (2001)

USA MIT sloane management review

Winning the last mile of eCommerce

Literature review

2 Punakivi et al. (2001)

Finland International journal of physical distribution and logistics management

Solving the last mile issue: reception box or delivery box?

Simulation

3 Kamarainen et al. (2001)

Finland International journal of physical distribution and logistics management

The reception box impact on home delivery efficiency in the e-grocery business

Simulation

4 de Koster (2002)

Netherlands International journal of physical distribution and logistics management

Distribution structures for food home shopping

Analytical model

5 Delaney-Klinger et al. (2003)

USA TQM magazine The return of online grocery shopping: a comparative analysis of Webvan and Tesco’s operational methods

Case study

6 Tarn et al. (2003)

USA Logistics information management

E-fulfillment: the strategy and operational requirements

Simulation

7 de Koster (2003)

Netherlands IEEE transactions on engineering management

Distribution strategies for online retailers

Survey

8 Mitrovic-Minic and Laporte (2004)

Canada Transportation research part B: methodologies

Waiting strategies for the dynamic pickup and delivery problem with time windows

Analytical model

9 Lasserre (2004)

Canada Journal of transport geography

Logistics and the internet: transportation and location issues are crucial in the logistics chain

Analytical model

10 Boyer and Hult (2005)

USA Journal of operations management

Extending the supply chain: integrating operations and marketing in the online grocery industry

Survey

11 Lunce et al. (2006)

USA Industrial management and data system

Success and failure of pure-play organizations: Webvan versus Peapod, a comparative analysis

Case study

12 Scott and Scott (2008)

USA Proceedings of the annual Hawaii

Online grocery order fulfillment tradeoffs

Conceptual framework


25

international conference on system sciences

13 Gagliardi et al. (2008)

Canada International journal of production economics

Space allocation and stock replenishment synchronization in a distribution center

Case study

14 Cho et al. (2008)

USA International journal of physical distribution and logistics management

Logistics capability, logistics outsourcing and firm performance in an eCommerce market

Survey

15 Gong and de Koster (2008)

Netherlands IIE transactions A polling-based dynamic order picking system for online retailers

Simulation

16 Song et al. (2009)

UK Transportation research method

Addressing the last mile problem: transport impacts of collection and delivery points

Case study

17 Ghiani et al. (2009)

Italy Transportation research part E: logistics and transportation review

Anticipatory algorithms for same day courier dispatching

Analytical model

18 Hu and Chang (2009)

China Journal of the Chinese institute of industrial engineers

An innovative logistics model for multi-channel retailing

Analytical model

19 Hu and Chang (2010)

China International journal of advanced manufacturing technology

An innovative automated storage and retrieval system for B2C eCommerce logistics

Analytical model

20 Agatz et al. (2011)

Netherlands Transportation science

Time slot management in attended home delivery

Analytical model

21 Runciman (2011)

UK ITNOW: Oxford journals

Do IT yourself? Case study

22 Durand and Gonzalez-Feliu (2012)

France Procedia – social and behavioral sciences

Urban logistics and e-grocery: have proximity delivery services a positive impact on shopping trips?

Simulation

23 Xiao et al. (2013)

China Information technology journal

B2C eCommerce vehicle delivery model and simulation

Simulation

24 Vanelslander et al. (2013)

Belgium International journal of logistics research and applications

Commonly used eCommerce supply chains for fast moving consumer goods: comparison and suggestions for improvement


25 Sareen (2013) USA Wired Once refined, same day delivery will be commonplace


26 Morganti et al. (2014)

France Transportation research procedia

The impact of eCommerce on final deliveries: alternative parcel delivery services in France and Germany

Case study

27 Morganti et al. (2014)

France Research in transportation business and management

Final deliveries for online shopping: the deployment of pickup point networks in urban and suburban areas

Case study

28 Wang et al. (2014)

China Mathematical problems in engineering

How to choose “last mile” delivery modes for e-fulfillment

Simulation

29 Gruber et al. Germany Research in A new vehicle for urban Simulation


26

(2014) transportation business and management

freight? An ex-ante evaluation of electric cargo bikes in courier services

30 Cleophas and Ehmke (2014)

Germany Business and information systems engineering

When are deliveries profitable?: considering order value and transport capacity in demand fulfillment for last-mile deliveries in metropolitan areas

Case study

31 Ehmke and Campbell (2014)

USA European journal of operational research

Customer acceptance mechanisms for home deliveries in metropolitan areas

Simulation

32 Visser et al. (2014)

Netherlands Procedia – social and behavioral sciences

Home delivery and the impacts on urban freight transport: a review

Literature review

33 Ducret (2014) France Research in transportation business and management

Parcel deliveries and urban logistics: changes and challenges in the courier express and parcel sector in Europe – the French case

Case study

34 Hausmann et al. (2014)

Germany McKinsey & company Same day delivery: the next evolutionary step in parcel logistics


35 Xu et al. (2014)

China Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2014

Logistics scheduling based on cloud business workflows

Analytical model

36 Kumagai (2014)

USA IEEE spectrum A day in the life of digi-key Case study

37 Wang and Xiao (2015)

China Journal of transport geography

Co-evolution between etailing and parcel express industry and its geographical imprints: The case of China


38 Koster et al. (2015)

Germany Transportation research procedia

Cooperative traffic control management for city logistic routing


39 Li et al. (2015)

China Lecture Notes in Computer Science

Towards fast and accurate solutions to vehicle routing in a large-scale and dynamic environment

Analytical model

40 Zu and Sun (2015)

China Lecture Notes in Computer Science

Optimization of order picking work flow at the eCommerce logistics centers


41 Tsamis et al. (2015)

UK Studies in Computational Intelligence

Adaptive storage location assignment for warehouses using intelligent products

Simulation

42 Wang et al. (2016)

China Transportation Research Part E: Logistics and Transportation Review

Towards enhancing the last-mile delivery: An effective crowd-tasking model with scalable solutions

Analytical model

43 Sun et al. (2016)

China Proceedings - 2016 IEEE International Conference on Web Services, ICWS 2016

A personalized service for scheduling express delivery using courier trajectories

Analytical model


27

The 52 papers examined where published in 39 different journals, with a mean

value of about 1.3 contributions per journal. We found different types of journals,

i.e. engineering operations and activity management journals (28 percent),

logistics and transportation journals (20 percent), computer and system sciences

journals (20 percent), information and communication technologies journals(9

percent), business

management, accounting and consulting journals (9 percent), applied

mathematics journals (7 percent), social and behavioral sciences journals (5

percent) and environmental sciences journals (2 percent).

Focusing on the year of publication, we can see a pretty stable trend with one,

two or at maximum three papers published each year from 2001 (with the

exception of 2007 in which there were no contributions to consider); but year

2014 brought a dramatic change: in fact, the big majority of the papers, almost 70

percent, were published from that year on. The reasons that justify this pattern

might be explained as follows. On the one hand, since the emergence of the

Internet as a powerful medium to channel customers and firms in a virtual

marketplace in the last 1990s, there has been a continuous, although moderate,

interest in the optimization of the activities in the B2C eCommerce. The whole

44 Savelsbergh and Van Woensel (2016)

USA Transportation Science

City logistics: Challenges and opportunities

Literature review

45 Schrotenboer et al. (2016)

Netherlands International Journal of Production Research

Order picker routing with product returns and interaction delays

Analytical model

46 Liu et al. (2016)

China Engineering Optimization

A capacitated vehicle routing problem with order available time in eCommerce industry

Analytical model

47 Harrington et al. (2016)

UK Production Planning and Control

Identifying design criteria for urban system last-mile solutions -A multi-stakeholder perspective


48 Saskia et al. (2016)

Germany Transportation research Procedia

Innovations in e-grocery and Logistics Solutions for Cities

Case study

49 Van Duin et al. (2016)

Netherlands Transportation research Procedia

Improving Home Delivery Efficiency by Using Principles of Address Intelligence for B2C Deliveries


50 Yu et al. (2016)

China Procedia CIRP ECommerce Logistics in Supply Chain Management: Practice Perspective

Literature review

51 Lee et al. (2016)

USA Stanford business school

Technological disruption and innovation in last-mile delivery


52 Li et al. (2017)

China International Journal of Production Research

Joint optimisation of order batching and picker routing in the online retailer’s warehouse in China

Analytical model


28

supply chain have been investigated: algorithms have been developed in order to

optimize activities inside the firms’ warehouses/plants (addressing stock

allocation, stock replenishment and order picking) but also outside plants’ walls

(delivery scheduling and courier routing, with a particular attention to the last-

mile of the delivery process); business models of different operators’ have been

analyzed and compared, to understand which ones were better able to answer to

more and more challenging customers’ needs, especially in terms of speed; the

daily schedule of couriers operating for online merchants has been addressed in

order to optimize routes, minimize delivery times and maximize the number of

points touched in one tour; additionally, new solutions have been studied to

improve the efficiency of home deliveries. But the real revolution towards same

day or faster delivery services has started in 2014 with the first ground-breaking

pilot projects of Amazon: they have pushed a lot of other online retailers or

logistics companies to invest in such projects, leading a wave in which everybody

was trying to keep the pace and follow this new trend in order to stay competitive

in the market.

Finally, looking at the countries addressed, the number of papers in which the

first author is from China is 13 (corresponding to 25 percent), followed by 12

contributions of researchers from USA (i.e. 23 percent) and 7 contributions of

researchers from the Netherlands (i.e. 13 percent). Then other papers were

written by authors from Germany (five), France (four), UK (four), Canada (three),

Finland (two), Belgium (one) and Italy (one). This result is consistent with the

current fast growing adoption of eCommerce in China, which represents the

most promising emerging market, and the leading position kept by USA in this

industry for years. Interesting also to notice the relevance of contributions from

Netherlands, Germany, France and UK as most innovative and developed

European countries in this field.

2.2.2 Research methods used

Contributions were also classified on the basis of their research methodology.

Categories used for this classification belong to a study by Meixell and Norbis

(2008) who identified seven research methods: analytical/mathematical models,

conceptual models or frameworks, case studies, interviews, surveys, simulations

and others.

As shown in Table I, many papers present analytical or mathematical models

(14), but there are also many based on case studies (11) or presenting conceptual

models and frameworks (10) or simulations (10). For what concerns the remaining

methodologies, some papers are literature reviews aimed at representing the

state-of-the-art of scientific research on a certain topic in the moment they were

written (4), while some others are based on data collected from surveys (3).


29

First, the possibility of finding a link between the research method and the

year of publication was investigated: results show that contributions based on

surveys are the less recent ones and no significant papers following this method

have been written after 2008; on the contrary, writings reporting conceptual

models and frameworks follow the opposite trend, because no contributions were

made before 2008 and the large majority of papers (90 percent) belong to the

years from 2013 on. The first pattern could be explained by the fact that the

practices of fast and same day delivery in B2C eCommerce are quite recent and

not already widespread as customers’ requests; this could make hard the job of

submitting surveys and collecting a so relevant number of responses allowing to

draw significant and generally valid conclusions. Instead, the second trend of

conceptual frameworks may be justified by the interest of researchers in

developing theoretical models with a wide-ranging relevance, so that they could

be considered valuable and be studied and applied by a lot of different operators

that want to be competitive.

Then, a possible connection between the type of research method and the

theme addressed was investigated. A specific relationship could not be identified,

but some prevailing themes were found according to the research method. For

example, empirical papers (i.e. case studies or surveys) often address the theme

of supply chain structure, analyzing the whole operations’ chain of one (e.g.

Kumagai J., 2014), two (e.g. Delaney-Klinger K. et al., 2003; Lunce S.E. et al., 2006)

or more firms’ realities (de Koster R., 2003; Boyer K.K. and Hult G.T.M., 2005).

For what concerns case studies alone, they present also the theme of last-mile

delivery in the 36 percent of papers (e.g. Song R. et al., 2009; Runciman B., 2011;

Morganti E. et al., 2014; Cleophas C. and Ehmke J.F., 2014); the interest is mainly

got by failed first-time home deliveries and the study of cases in which alternative

delivery methods are applied, such as pickup points and automatic lockers, in

order to reduce the risk of failure. Analytical and mathematical models in almost

65 percent of cases deal with the theme of delivery scheduling and routing

arrangement for couriers. Some models and algorithms are developed in order to

solve dynamic vehicle dispatching or vehicle routing problem, to minimize time

and cost spent for delivery and maximize the number of touch-points in one

courier’s tour (e.g. Ghiani G. et al., 2009; Agatz N. et al., 2011; Sun Y. et al., 2016);

in some cases these algorithms are also time dependent (i.e. a certain time

window is set as a constraint and specifies the order available time) (e.g. Xu R. et

al., 2014; Li Y. et al., 2015;; Liu L. et al., 2016), while in other cases they focus on

the implementation of a specific delivery technology, such as air cargo (e.g.

Lasserre F., 2004). Then we find some models aimed at solving dynamic pickup

problems to optimize pickers’ activity for orders’ preparation (e.g. Schrotenboer

A.H. et al., 2016); finally, some other papers address both pickup and delivery

issues (e.g. Mitrovic-Minic S., Laporte G., 2004). Interesting to notice the


30

significant contribution made by Chinese authors in this field of mathematical

modeling (57 percent of the total). Dealing with simulations, a notable portion

(40 percent) of papers addresses the theme of last-mile delivery: most of them

simulate scenarios in which alternative technologies to attended home delivery

are exploited (i.e. reception box, delivery box and collection-and-delivery points)

in order to compare their performance in terms of cost and service levels (e.g.

Punakivi M. et al., 2001; Kamarainen V. et al., 2001; Wang X. et al., 2014); some

others compare performances of different transportation means, e.g. assessing

the outstanding value of electric and traditional bikes (e.g. Gruber J. et al., 2014).

In conclusion, literature reviews in 75 percent of cases are based on the state-of-

the-art analysis of trends in the couriers and logistics operators’ industry, often

grouped by continent or nation, in order to keep the pace with the last practices

and get useful insights about future possible developments (e.g. Visser J. et al.,

2014; Savelsbergh M. and Van Woensel T., 2016; Yu Y. et al., 2016).

2.3 Discussion of themes arising from the review

2.3.1 Research area

Table 97 - Area of research of papers examined

Areas Papers

Courier delivery scheduling & routing

Mitrovic-Minic and Laporte (2004) Xu et al. (2014)

Lasserre (2004) Koster et al. (2015)

Ghiani et al. (2009) Li et al. (2015)

Agatz et al. (2011) Sun et al. (2016)

Xiao et al. (2013) Schrotenboer et al. (2016)

Cleophas and Ehmke (2014) Liu et al. (2016)

Ehmke and Campbell (2014) Van Duin et al. (2016)

Couriers and logistics operators trends

Visser et al. (2014) Wang and Xiao (2015)

Ducret (2014) Savelsbergh and Van Woensel (2016)

Hausmann et al. (2014) Yu et al. (2016)

Distribution centers structure and cost

de Koster (2002) Saskia et al. (2016)

Last-mile delivery Lee and Whang (2001) Morganti et al. (2014)

Punakivi et al. (2001) Wang et al. (2014)

Kamarainen et al. (2001) Gruber et al. (2014)

Song et al. (2009) Wang et al. (2016)

Runciman (2011) Harrington et al. (2016)

Morganti et al. (2014) Lee et al. (2016)

Operations performance assessment

Cho et al. (2008) Sareen (2013)

Picking Gong and de Koster (2008) Zu and Sun (2015)

Hu and Chang (2010) Li et al. (2017)

Storage Tsamis et al. (2015)

Storage & picking Gagliardi et al. (2008) Hu and Chang (2009)

Supply chain structure Delaney-Klinger et al. (2003) Scott and Scott (2008)

Tarn et al. (2003) Durand and Gonzalez-Feliu (2012)

de Koster (2003) Vanelslander et al. (2013)

Boyer and Hult (2005) Kumagai (2014)

Lunce et al. (2006)


31

The papers were also analyzed on the basis of their content (i.e. the issues

they tackle). By looking only at the area of research, we can see that 14 of them

(corresponding to the 27 percent) deal with the theme of delivery scheduling &

routing arrangement in order to optimize couriers’ daily job; as previously stated,

most of them (64 percent) are analytical or mathematical models, but we find

also some conceptual models and some simulations. Their aims are multiple:

finding the best delivery technology able to squeeze at maximum delivery time

(e.g. Lasserre F., 2004); managing the fleet in real-time, without recurring to an a-

priori data preparation phase, to solve problems of optimization of vehicles’ load

(i.e. have vehicles as fully-loaded as possible), assign requests and state routings

for each vehicle (e.g. Mitrovic-Minic S. and Laporte G., 2004; Ghiani G. et al.,

2009; Xiao H. et al., 2013; Cleophas C. and Ehmke J.F., 2014; Ehmke J.F. and

Campbell A.M., 2014; Xu R. et al., 2014; Li Y. et al., 2015; Sun Y. et al., 2016; Liu L.

et al., 2016); selecting the time slots to be assigned to each zip code delivery area

in order to reach cost-effectiveness while, at the same time, keeping an adequate

service performance for customers (e.g. Agatz N. et al., 2011); studying solutions

of traffic control management (i.e. TM) allowing courier express and parcel

services (i.e. CEP) to integrate management of their last mile deliveries with city

traffic conditions (e.g. Koster F. et al., 2015); developing routing decisions for

pickers inside the warehouse, for both activities of simultaneous picking of

ordered products and putting away of returned items and considering also

interactions among pickers working in the same time (e.g. Schrotenboer et al.,

2016); finally, investigating modeling techniques that apply address intelligence

in order to use historical delivery data for identifying and predicting potential

improvements in the choice of zip code delivery areas (e.g. van Duin J.H.R. et al.,

2016).

Then, 12 papers (corresponding to the 23 percent of the total) face different

aspects of last-mile delivery; the research methods they present are numerous,

but case studies and simulations constitute a relevant portion. In many of them,

the issue of unattended and failed first-time home delivery is tackled and

advantages and disadvantages of alternative network designs (such as the

introduction of the reception box, the delivery box, consolidation centers, pickup

points, automatic lockers or the recourse to a crowd-tasking model with a pool of

citizen workers who complete the delivery) are analyzed in order to find a way to

minimize the cost of failure (i.e. cost of repeated delivery for the carrier and/or

cost of customer trips to retrieve the item from depots) (e.g. Punakivi M. et al.,

2001; Kamarainen et al., 2001; Song R. et al., 2009; Morganti E. et al., 2014; Wang

X. et al., 2014; Harrington T.S. et al., 2016; Wang Y. et al., 2016). In other

contributions, the theme of optimization of the last-mile delivery (i.e. pursuing

cost and time reduction while keeping a high service level) is addressed by

looking at the means of transportation and assessing the convenience of


32

alternative means that are already in use nowadays and/or which will encounter a

widespread diffusion in the future; examples of these are bikes and electric cargo

bikes, drones, robots and driverless vehicles (e.g. Gruber J. et al., 2014; Lee H.L. et

al., 2016). In the end, one paper (Runciman B., 2011) is focused on analyzing the

positive impact, in terms of last-mile delivery time reduction, of a cloud

infrastructure that operates as a platform to integrate the API web service with

eCommerce, point of sales, mobile and telephone channels of different retailers;

this tool is analyzed in the case of a specific operator (i.e. Shutl) which is now

able to serve its customers within a very short time window.

Moving on with the classification, we can find 9 papers out of the total 52 (so,

the 17 percent of them) dealing with the theme of supply chain structure, taking a

look at the operations strategy and/or the business model applied by one or more

operators along the whole chain. The majority of contributions is made of

frameworks or simulations which propose general logistics models and discuss

typical e-fulfillment strategies, without referring to real cases (e.g. Tarn J.M. et

al., 2003; Scott J.E. and Scott C.H., 2008; Durand B. and Gonzalez-Feliu J., 2012);

one of them analyzes the supply chain not only in terms of activities’

management and operations, but its main aim is to find out the distribution of

logistics costs along the chain (Vanelslander T. et al., 2013). Some papers take

data from case studies or surveys of online retailers in order to investigate

strategies of these different types of retailers; the focus is especially on the choice

of where to fulfill customer orders (from existing stores or dedicated warehouses

and their location) and the choice of the delivery method (direct to the

customer's home/office or indirect via customer pickup or outsourcing to third-

party logistics provider) and delivery area (e.g. de Koster R., 2003; Boyer K.K. and

Hult G.T.M., 2005). In addition, some other papers focus on a fewer number of

cases having so a comparison between two real models implemented by

companies , one of success and one of failure, in order to attempt to identify the

critical success factors that contributed to their different performances; the

analysis does not stop at a level of activities’ strategic management and logistics

infrastructure, but looks also at the match between operations and marketing

strategies (e.g. Delaney Klinger K. et al., 2003; Lunce S.E. et al., 2006). Finally, one

paper provides an in-depth look at operations of a single company working as an

online electronic components’ distributor (Kumagai J., 2014).

On the contrary, 7 papers (i.e. the 13 percent) do not make a global overview

of the whole chain models, but concentrate on the study of the internal activities

of storage and picking inside distribution centers. Most of them (4 out of 7)

address the picking activity: they propose algorithms and models for order

picking optimization, considering both order batching and picker routing, in

order to reduce the operational cost of an eCommerce logistics center and

enhance the order picking operation management level (e.g. Zu Q. and Sun B.,


33

2015; Li J. et al., 2017) or they simulate the introduction of new technologies, such

as informative Dynamic Picking System (DPS) or Automated Storage/Retrieval

System (AS/RS), comparing their performances to the ones of traditional manual

systems (e.g. Gong Y. and De Koster R., 2008; Hu K.Y. and Chang T.S., 2010). One

paper focuses only on the storage activity and in particular aims to identify a

potential solution by developing a distributed adaptive strategy for storage

location assignment problem (Tsamis L. et al., 2015). The last two articles deal

with both storage and picking activities, so analyzing in the same time product

location and replenishment strategy in a distribution center; one is directed to

the case of a pick-to-belt system (Gagliardi J.P. et al., 2008), the other is applied

to the case of an automated multi-floor distribution center (AMDC) adopting a

picker-to-part model (Hu K.Y. and Chang T.S., 2009).

We have then 6 papers (corresponding to 12 percent of the total) addressing

the theme of couriers’ and logistics operators’ trends: the objective is the one of

presenting the state-of-the-art of eCommerce logistics in supply chain

management from a view of practice perspective. These contributions basically

consist of literature reviews (e.g. Visser J. et al., 2014; Ducret R., 2014; Savelsbergh

M. and Van Woensel T., 2016; Yu Y. et al., 2016) and conceptual frameworks (e.g.

Hausmann L. et al., 2014; Wang J.J. and Xiao Z., 2015) in order to analyze CEP (i.e.

Courier, Express and Parcel) sector’s changes and drivers, reviewing current and

anticipated challenges and providing opportunities and future perspectives. Some

of these papers also put an eye on city logistics, looking at impacts of eCommerce

on transportation within urban areas.

Two papers deal only with the distribution activity: they look at the typical

distribution structure (made of stores and different warehouses’ types) employed

by companies, in order to find a link among the distribution infrastructure, the

companies’ operational complexity and their web-based orientation and provide

comparisons of different alternatives (de Koster R., 2002; Saskia S. et al., 2016).

Lastly, two papers have the objective of carrying out a performance

assessment of e-operations: logistics capabilities of different operators are studied

in order to assess their impact on firms’ performances in the eCommerce industry

(Cho J.J.K. et al., 2008) and key factors are investigated to assess success or failure

of a specific delivery strategy (Sareen H., 2013 which lists key variables affecting

the development of a good same day delivery strategy).

2.3.2 First matrix classification: speed of delivery – type of activity

After the content analysis, a two-dimensional approach was used to provide a

clear classification of the articles examined. The two axes considered for the

categorization are: first, the speed of the delivery process which can be also

described as the order cycle time (i.e. the time lag between order reception and

product delivery to the final customer); second, the type of activity and/or


34

Table 98 – first classification: addressed activities vs. speed of delivery

Picking Delivery Picking & delivery

Fast Gong and de Koster (2008)

Runciman (2011); Morganti et al. (2014); Ehmke and Campbell (2014); Ducret (2014); Wang et al. (2016)

Yu et al. (2016)

same day Mitrovic-Minic and Laporte (2004); Ghiani et al. (2009); Visser et al. (2014); Koster et al. (2015); Savelsbergh and Van Woensel (2016); Lee et al. (2016)

Sareen (2013); Hausmann et al. (2014); Kumagai (2014)

24 hours Gagliardi et al. (2008) Punakivi et al. (2001); Kamarainen et al. (2001); Morganti et al. (2014); Wang et al. (2014); Sun et al. (2016)

Tarn et al. (2003); Scott and Scott (2008)

Others de Koster (2002); Hu and Chang (2009); Hu and Chang (2010); Zu and Sun (2015); Tsamis et al. (2015); Schrotenboer et al. (2016); Li et al. (2017)

Lee and Whang (2001); Lasserre (2004); Cho et al. (2008); Song et al. (2009); Agatz et al. (2011); Xiao et al. (2013); Gruber et al. (2014); Xu et al. (2014); Wang and Xiao (2015); Li et al. (2015); Liu et al. (2016); Harrington et al. (2016); Saskia et al. (2016); van Duin et al. (2016)

Delaney-Klinger et al. (2003); de Koster (2003); Boyer and Hult (2005); Lunce et al. (2006); Durand and Gonzalez-Feliu (2012); Vanelslander et al. (2013); Cleophas and Ehmke (2014)

Figure 1 - two-dimensional classification along with research method

: simulation : case study

: conceptual framework : analytical model

: literature review : survey


35

activities addressed in the paper. For what concerns the second variable, the

focus of contributions was distinguished among “picking only”, “delivery only” or

“picking and delivery”; since the scope of our work is to analyze how operations

are managed and carried out in the eCommerce industry, all these three

categories were of same interest for our purpose. Addressing instead the first axis,

a distinction was made among four different speed categories, presented in

increasing order of time required for delivery: “fast”, “same day”, “24 hours” and

“others”; in this case, the attention paid to papers is greater when the order cycle

time decreases, due to the fact that the goal of the work is on studying the trend

of fastening eCommerce deliveries; this is why contributions categorized as

“others” were addressed with less interest than ones labeled as “fast” or “same

day”.

Before going on with the classification, it could be useful to provide a sort of

definition for each of these speeds. Dealing with “fast” deliveries, it is not possible

to define them in a unique way, since different authors provide very different

timings. Gong Y. and de Koster R. (2008) speak about some online retailers

adopting personalized material flows in order to achieve a fast response to gain

competitive advantage and the examples they show are of orders served in 45

minutes (in the case of the online Finnish retailer Nettymarket) or in 2 hours (for

the Chinese retailer China online shopping, operating in the consumer

electronics industry). Differently, Ducret R. (2014) addresses this theme by

writing about express companies, among which he lists providers operating in 90

minutes (such as DPD in Germany and Royal Mail in UK) but also same-hour

delivery developers as the UK firm Shutl or the German Tiramizoo. Another

example is the one of JingDong, the second largest eCommerce company in

China, which among its logistics services offers also a fast one, delivering

products in 3 hours (Yu Y. et al., 2016). On the contrary, Mitrovic-Minic S. and

Laporte G. (2004) do not provide real cases, but they present a conceptual model

of a system using a neural network as learning module and able to operate all the

activities from order receipt in 2 hours, with 30 minutes dedicated to picking and

90 minutes to delivery. Also Savelsbergh M. and Van Woensel T. (2016) write

about 1-hour and 2 hours delivery options, as the case of Amazon Prime in

selected US cities. Finally, moving to more recent technologies, we can report

pilot projects by Google and Amazon Prime Air testing delivery with drones in

less than 30 minutes (in particular, Google announced of being able to fully start

the drone delivery service this year 2017); we also have delivery robots, which

could be used for delivering small packages, groceries, laundry, pizza, and more,

able to make deliveries within 5 to 30 minutes, addressing so customers’ need for

speedy services (e.g. SideWalk company started tests of its robot in Lithuania in

2015, aiming at expanding soon to Germany and Denmark, for e-food platforms,

restaurants, cafes and flower shops and was able to offer a service referred to as


36

“instant city delivery” working in more or less 15 minutes) (Lee H.L. et al., 2016).

So we can conclude that no unique timing is precisely assigned to the term “fast”

delivery, but we can affirm that we are referring to services assuring customers’

reach in less than a few hours (two or maximum three).

Moving to same day services, it was easier to find an exact definition: with

same day delivery, orders can be delivered within a few hours after purchasing them

or at maximum in a chosen time window on the same day. In an interview, the SVP

of a logistics company stated that “same day delivery is a game changer

because it combines the immediate product availability of retail with the

convenience of ordering from home.” (Hausmann L. et al., 2014). Same day

delivery operations have a dynamic nature which makes the situation harder, not only

for what concerns the dynamic vehicle routing, but also because it refers to

dynamic receiving of orders that need to be delivered in a restricted time and

there are few, if any, opportunities to accommodate additional deliveries after a

delivery vehicle has left the depot (because the vehicle would have to return to

the depot to pick up the additional deliveries). In fact, two natural features of

same day delivery have to be considered: (1) all orders have to be delivered by the

end of the day, and (2) all orders have to be delivered within a given period after

receiving the order. So the critical decisions are when to dispatch a vehicle, what

orders the vehicle should serve and in what sequence they should be served.

(Savelsbergh M. and Van Woensel T., 2016). Among the contributions analyzed,

different examples of same day delivery were found: from the Dutch company

Ahold with its Internet home delivery service Albert (Gong Y. and de Koster R.,

2008), to E-bay, Google and Amazon in the United States, soon followed by

national postal service USPS in San Francisco (Ducret R., 2014), again to Amazon

in Japan and the Japanese company Yamato which is able to deliver products to

customers by 8 p.m. for orders received in the morning (Visser J. et al., 2014),

until the most innovative case of UberRUSH, currently available in Chicago, San

Francisco and New York, which implies a massive use of bicycles by couriers or

travels by foot and is able to pose a big threat to giants such as UPS, FedEx and

USPS (Lee H.L. et al., 2016).

It is even easier to define “24 hours” services, which are also referred to as

next day deliveries: they assure the receiving of orders within a 24-hours delivery

window from the moment of order reception by the retailer; so, orders issued by

the customer at a certain time one day are received by him/herself before the

same time the following day. Some examples found in the papers are provided by

Centraal Boekhuis warehouse, which distributes the orders of Dutch BOL.com

and Wehkamp, the largest online retailer in the Netherlands, within a 24-hour

delivery window. (Gong Y. and de Koster R., 2008).

Lastly, in the category “others” we collected all the cases in which order cycle

times are going beyond the next day delivery limit, usually from two days on.


37

Let’s have a look now at the classification, deeply describing the two axes and

then also observing if a potential connection could be found among these two

variables and the papers’ research method used.

(1) Speed of the delivery process. As previously mentioned, based on the speed at

which the whole process is performed, from order reception to product

delivery, we can identify four different categories: fast delivery, same day

delivery, 24 hours delivery and others.

Fast delivery is the least tackled theme in literature, being it the most

recent research field, it has not been fully addressed yet: in fact, only 7 out of

the total 52 papers analyzed concern this topic. Looking first at the research

method, we can notice a balanced presence of case studies on the one hand (3

out of 7) and simulations/analytical frameworks on the other (overall 3 out of

7 papers): this result is the proof of the fact that some authors are starting to

develop theoretical models to understand how this type of delivery could be

arranged in general terms and are also beginning to test and simulate their

frameworks; but, due to the fact that the development of this practice is quite

recent, a significant contribution is also provided by the study of cases of real

companies which have put in place the system, in an attempt to learn from

successful past experiences. Most papers (5 out of 7) deal only with the

delivery activity: we have case studies of companies which have been able to

develop such effective infrastructures for last-mile deliveries to perform

activities in very fast times: for example we can see the cloud platform

implemented by UK company Shutl to aggregate capacity in the same day

courier market, which allows deliveries to be performed in 90 minutes or in a

one-hour time window chosen by the customer (Runciman B., 2011) or the

network of pickup points (PP) which has viewed a widespread diffusion in

France as an alternative to optimize parcel deliveries, making products

accessible for customers’ pickup in few minutes (Morganti E. et al., 2014) or

cases of other city couriers or parcel providers which have become very

interesting in the eyes of online giant retailers to provide city express services

(e.g. German DPD, US Postal Service or UK Royal Mail) (Ducret R., 2014);

then we also have a simulation framework which compares different

acceptance mechanisms applied by couriers to schedule order deliveries with

the aim of being able to accomplish tasks in less than one hour (Ehmke J.F.

and Campbell A.M., 2014) and a paper proposing a crowd-delivery model

which utilizes a large pool of citizens to enhance last-mile delivery, taking as

reference companies which perform fast last-mile delivery such as UberRUSH

(Wang Y. et al.,2016). One paper only addresses the single picking activity,

simulating the application of dynamic polling-based picking and assessing its

benefits in terms of service level (i.e. shorter order throughput times and


38

higher on-time service completion ratios) with respect to traditional batch

picking systems; as examples for the simulation, real cases are used of

merchants which need this optimization framework to provide a fast delivery

service (e.g. 45 minutes-service for Dutch Nettymarket and 2 hours-service for

Chinese China online shopping) (Gong Y. and de Koster R., 2008). Finally, the

most recent paper looks for a wider perspective, addressing both picking and

delivery activities and providing a complete review of worldwide

implementations and corresponding models currently implemented by

eCommerce global logistics companies; applied techniques are reviewed so as

to get insights from them and, for what concerns delivery speed, the real case

of Asia-Pacific company JingDong, able to put in place a service of 3 hours

delivery, is provided (Yu Y. et al., 2016).

Few more contributions were found about same day delivery (9 out of 52

papers), but still in a quite scarce number. Looking at the research method,

the majority of them describes conceptual models or frameworks (4 out of 9

papers), then there are a couple of mathematical models, a couple of

literature reviews and just one case study; this phenomenon could be

interpreted as a proof of the fact that, even if it is still a quite recent topic and

the amount of papers is scant, it is less recent than fast delivery issue and few

years more of research have allowed to bring scientific discussion at a higher

level: there are not only case studies of pilot projects or actions implemented

by few ground-breaking players, the topic has had the opportunity of being

further analyzed and conceptualized and contributions have a wider and

more general validity. No papers among these address the only picking

activity, while most of them (6 out of 9) study the delivery activity alone. We

have some models on waiting strategies or anticipation strategies to solve

dynamic vehicle dispatching problems for pickups and deliveries; these

algorithms are expressively related to models of same day couriers

transporting small parcels and are stimulated by the recent advances in

information and communication technologies which allow data on courier

locations and customer requests to be obtained and processed in real time

(Mitrovic-Minic S. and Laporte G., 2004; Ghiani G. et al., 2009); another

model refers again to the express couriers and parcel service industry and

looks at the optimization of their travel times, but through the coordination

with traffic control management (TM) systems which report city traffic

conditions (Koster F. et al., 2015). Lastly few other papers review the latest

trends about internet shopping and home deliveries affecting city and last-

mile logistics and among the various challenges and opportunities analyzed,

same day delivery is addressed: its definition and own particular features are

provided, some emerging technologies allowing this service to work always

better and faster are analyzed, together with the business models


39

implemented by some key and successful entrants in this field (Visser J. et al.,

2014; Savelsbergh M. and Van Woensel T., 2016; Lee H.L. et al., 2016).

More or less the same number of contributions is about 24 hours delivery

(8 out of 52), so still a moderate presence. More than a half of them report

analytical (1) or conceptual (1) models or simulations of alternative models (4

out of 8), while there are just a couple of case studies; this is an even clearer

evidence of the fact that by moving towards slower and less recent delivery

services, the presence of well structured and conceptualized models becomes

far more relevant than the one of case studies and surveys, meaning that the

body of research has been deeply analyzed and the collection of a significant

amount of cases and data has led to the realization of general models. Just one

paper addresses the picking activity and in particular analyzes different

strategies for product location and replenishment in order to manage storage

and picking activities as most efficiently as possible; these strategies are

compared by using a real case of a distribution center with a pick-to-belt

system for the distribution of snacks and this center manages orders in a 24-

hours time window (Gagliardi J.P. et al., 2008). Most papers (5 out of 8) tackle

the delivery activity and in particular the issue of unattended home deliveries:

different solutions to improve attended delivery efficiency are proposed and

simulated, studying their advantages and disadvantages in terms of

implementation cost for the retailer and service level to the customer; the

alternatives taken into consideration are the reception box and the delivery

box (i.e. insulated box containing the goods which is delivered to the

customer and attached securely in a locking device bolted on the building

wall; the empty box is then collected the day after delivery or later) (Punakivi

M. et al., 2001; Kamarainen V. et al., 2001), collection-and-delivery or pickup

points located in stores (which are also studied in different scenarios with

varying population density) (Wang X. et al., 2014) and networks of automated

lockers (which have seen a significant penetration in France and Germany)

(Morganti E. et al., 2014). Another paper deals with delivery but it presents a

model to personalize the scheduling of express deliveries in the last-mile, in

order to satisfy customers’ appointment time and concurrently minimize the

total travel time (Sun Y. et al., 2016). All the aforementioned contributions

refer to couriers which carry out one day or next day delivery, which can be

considered an express service compared to traditional logistics providers’

services (usually taking between two and five days for shipments), but it is far

away from the faster services which represent the focus of this work. Finally,

two papers take a wider look at the e-fulfillment process, addressing all the

activities along the chain, including both picking and delivery; their aim is the

one of identifying a generally valid model for the design of an eCommerce

fulfillment system, with specific steps to be followed and particular issues and


40

tradeoffs to consider (e.g. for what concerns items’ storage, tradeoffs of

productivity, capacity, real estate cost, items’ freshness, etc.) (Tarn J.M. et al.,

2003; Scott J.E. and Scott C.H., 2008).

The last category for what concerns speed of the delivery process is

represented by those papers which are classified as “others” because they

relate to processes taking more than 24 hours. These are the very large

majority of the contributions collected, corresponding to almost the 54

percent of them (28 papers out of the total 52). We can at once notice that

this is the mostly addressed category, the one which has seen the wider

development, even thanks to the fact that deliveries in more than one day

have become a widespread phenomenon since many years. As we could

expect, by looking at the research method we found a significant amount of

analytical and mathematical models (10), conceptual models (5) and modeling

simulations (4); there are also some case studies (5), while less relevant is the

contribution of surveys (3) and literature reviews (1). The reason for this

pattern could be the same we have described for the previous category:

deliveries in two, three or more days have become an industry standard since

years, every actor has been able to put in place a system working within this

time windows, not only few ground-breaking players; this huge diffusion has

allowed research on these topics to develop deeply and to move from few

proofs of practical examples or cases to a well theorized framework of models

and algorithms of global application. 7 papers (corresponding to the 25

percent) focus on the picking activity and they report all mathematical

models or simulations. Some of these contributions relate to the design of

automated distribution centers with automated storage/retrieval systems,

together with the application of ant colony system algorithms for optimal

pickers’ routing within the center; their implementation provides greater

storage space to solve problems of inventory management and also more

efficient and flexible operations for what concerns handling of customer

orders; the benefit of these systems in the eCommerce context, which is

demanding more and more speed every day, is clear but no references to

really fast delivery processes (i.e. less than one day) are present in these

papers (Hu K.Y. and Chang T.S., 2009; Hu K.Y. and Chang T.S., 2010). Then

we have other papers presenting simulations of newly developed algorithms

for the optimization of different activities inside the walls of a distribution

center: one paper focuses on the storage location assignment problem of

newly delivered products and provides a dynamic solution to it, overcoming

the limitations of a-priori static allocation (Tsamis N. et al., 2015); another

contribution proposes a joint optimization algorithm of both order batching

and picker routing with the objective of minimizing the total travel distance

involved in the process (Li J. et al., 2017); other two papers study


41

mathematical models for order picking optimization as it is considered the

bottleneck activity of the whole supply chain due to the overlapping of

products’ pickup in response to consumers’ orders, returned products’

delivery back to storage locations and order pickers’ interactions for routing

decisions inside the area (Zu Q. and Sun B., 2015; Schrotenboer A.H. et al.,

2016). Again all of these articles, dealing with optimization techniques, bring

to the reach of more reliable and faster processes, minimizing cost and time

of the single activities, but no reference to fast or same day or next day

delivery processes is provided. One last paper investigates the link between

operational complexity and distribution structure of a company operating in

the eCommerce sector, mainly looking at the distinction between companies

having prevalently a store infrastructure to carry out storage and picking

activities and firms relying on an infrastructure made of warehouses only; the

fastening of the delivery process is not addressed (de Koster R., 2002).

The same number of papers (7 out of 28) deal with both activities of

picking and delivery and in this case we can see a clear prevalence of case

studies (3) and surveys (2) with respect to simulations (1) and conceptual

models (1): trying to explain this pattern, we could infer that if applying a

universally valid model to a single activity is quite simple and can lead to

measurable efficiency results, when looking at the management of a complex

chain of activities the application of a single algorithm is no more possible;

more useful information can be conversely obtained by observing the actions

undertaken by some successful companies and clever insights could be got in

order to develop then a personalized strategy. In fact by looking at the

content of these contributions, a big role is played by comparisons of different

business models implemented by real companies: comparisons can be

between two actors (one having achieved success and the other having failed

in its strategy, e.g. Webvan versus Tesco or again Webvan versus Peapod) and

mainly focusing on e-operations’ strategic management (with respect to

traditional business operations) and its alignment with marketing strategy

(Delaney-Klinger K. et al., 2003; Lunce S.E. et al., 2006); or three most

common supply chain scenarios can be investigated, in one case with the aim

of analyzing the impact of new forms of proximity deliveries on city logistics

and consumers’ shopping trips (Durand B. and Gonzalez-Feliu J., 2012), while

in the other case to carry out an analysis of costs’ distribution over different

processes in the chain (Vanelslander T. et al., 2013); or more data coming from

surveys (one based on 55 online retailers, the other based on 4 Internet-

ordering and home-delivering grocers and their 2440 customers) are used to

address the logistic fulfillment process, comparing different choices on where

to fulfill customer orders (existing stores versus dedicated distribution

centers) and on the delivery method (direct to customers’ house/office or


42

indirect via customer pickup or via third-party logistics provider) (de Koster

R., 2003; Boyer K.K. and Hult G.T.M., 2005). Just one contribution addresses a

more theoretical framework, presenting an iterative solution in which

acceptance or rejection of delivery requests is first performed (based on

forecasted expected delivery requests and cost-minimizing routing) and then

the routing solution is updated in order to minimize costs of delivery

(Cleophas C. and Ehmke J.F., 2014). Few of the aforementioned papers cite the

theme of delivery speed but no cases faster than 48-hours delivery are

presented; however the large majority of them look at the best chain in terms

of minimum cost or minimum distance travelled or maximum activities’

efficiency and of course all of these results have a positive impact in terms of

time savings, but no interest is posed on the trends of delivery in less than one

day.

Lastly, the most tackled activity is delivery: in fact it is the theme of half

of the papers classified as “others” (14 out of 28) and they mainly consist of

analytical models (5), conceptual models (3) and algorithms’ simulations (2),

while a small portion of them is dedicated to case studies (2), surveys (1) and

literature reviews (1); this is in line with the aforementioned thought that it is

quite simple to apply a model or to verify an algorithm when one single

activity is addressed (in this case, just management of the delivery process,

most often only looking at the last-mile portion of it). We can find algorithms

to solve time-dependent vehicle routing problem for a large number of

delivery locations in a dynamic manner (i.e. without an initial data

preparation phase) (Xu R. et al., 2014; Li Y. et al., 2015; Liu L. et al., 2016),

other algorithms for logistics distribution scheduling based on workflows and

vehicles’ load under the constraints of traffic conditions and time window

(Xiao H. et al., 2013; Xu R. et al., 2014), while some others deal again with

scheduling but focusing on the selection of time slots to offer in each zip code

of the served regions and on potential improvements in the choice of zip

codes to be served through address intelligence (Agatz N. et al., 2011; van Duin

J.H.R. et al., 2016). All the previous mathematical models have activities’

optimization as final aim, so they imply a reduction of time for activities’

management but they do not refer to fast deliveries taking place in one day or

less; in some cases they can refer to the selection of specific time windows

within a certain day or week, but it only regards the agreement on the

moment of delivery with the customer, not the speed of the whole process

from order placement to final distribution. Then there are some more

theoretical frameworks which study the emerging trends in eCommerce

transportation for what concerns mainly means of transport and technologies

developed to make faster and more efficient deliveries: air transportation

infrastructure is one of these transportation means (but no services faster


43

than three days delivery are cited) (Lasserre F., 2004), another example are

electric cargo bicycles employed by individuals messengers or couriers to

replace own traditional bicycles or car (it surely refers to daily deliveries of

messengers or small parcel couriers, but no reference is made to the length of

the whole order cycle time and its speed) (Gruber J. et al., 2014). Other papers

analyze innovative concepts for optimization of urban traffic and final

deliveries (avoiding unattended ones) developed by the different actors

involved in eCommerce logistics services (e.g. e-grocers, parcel express actors,

e-retailers in general, etc.): among these last-mile innovations we found

attended collection/delivery points (CDPs) such as convenience stores, petrol

stations, post offices, etc. (applied to the case of UK West Sussex region)

(Song R. et al., 2009) and consumer choice portal-package consolidation

centers within densely populated geographical areas (Harrington T.S. et al.,

2016). Finally, some contributions follow a more theoretical framework to

analyze trends, opportunities and threats in logistics choices about

eCommerce; we have a review of main e-fulfillment strategies implemented

by players operating in the last-mile step of the supply chain (Lee H.L. and

Whang S., 2001); a research on the relationships between logistics capabilities,

logistics outsourcing and global performance in firms engaging in eCommerce

(Cho J.J.K. et al., 2008); a comparison between the main operational models

applied by merchants operating in the e-tailing business and in the parcel

express industry in China (with a clear distinction among supply chain-based

merchants, e-marketplace-based e-tailers and third party logistics providers)

(Wang J.J. and Xiao Z., 2015); a research on the main challenges faced by

traditional grocers who want to enter the business of online food sales

(mainly logistics and transportation issues) with a focus on French and

German cases and the trends around customers’ adoption of this non-

traditional purchasing process (Saskia S. et al., 2016). Even if these last

contributions analyze also some quite recent trends (especially the last two

papers cited), the challenges of same day or even faster delivery are not

addressed.

(2) Type of activity/activities addressed. As previously stated, the second variable

used for the classification is the definition of the one or more supply chain

activities which constitute the focus of the papers. Picking alone is the least

addressed process: just 9 papers out of the total 52 (corresponding to 17

percent) only analyze the handling activities occurring inside distribution

centers, dealing with the phases of order preparation. The research methods

found in the majority of these contributions are mathematical/analytical

models (5 papers) and simulations (2), while only one conceptual framework

and one case study are present. About speed of delivery, we can notice that


44

just one paper is about fast delivery and none of them addresses the theme of

same day delivery; again one paper only studies the process of 24 hours or

next day delivery, while the most part (7 out of 9) shows the presence of

papers classified as others. The fact of finding so many algorithms and models

can be linked to the huge presence of “others” contributions about delivery: in

fact, this means that picking has been mostly studied in case of standard

eCommerce delivery processes, the ones which have been in place for most

years and have had the opportunity of being deeply investigated and

optimized; on the contrary, when dealing with faster order cycle times (i.e.

less than 24 hours) in eCommerce, scarce attention has been paid to the

management of activities inside distribution centers, typically storage and

picking. This means that for what concerns fast deliveries there is a lot of

room available for the analysis and the optimization of picking activity; in

fact, being fast does not only imply reaching the customer at the highest

possible speed, but also preparing the order rapidly, having it ready to leave

the distribution center as soon as possible. Most of the papers introduce

models for the optimization and time reduction of activities in traditional

processes: some analyze the introduction of automated systems for items’

storage and retrieval (Hu K.Y. and Chang T.S., 2009; Hu K.Y. and Chang T.S.,

2010); some focus on clustering of orders’ batches (Zu Q. and Sun B., 2015; Li J.

et al., 2017) or on optimizing pickers’ routing (Schrotenboer A.H. et al., 2016;

Li J. et al., 2017); others address the optimization of items’ storage locations’

assignment (Tsamis N. et al., 2016) or of fulfillment centers’ distribution and

structure (de Koster R., 2002). The paper which deals with next day delivery

proposes the case study of a really existing distribution center for snacks’

distribution and simulates different alternatives for products’ allocation in the

warehouse, replenishment strategies and picking activities in order to be

compliant with the industry standard of 24 hours for order fulfillment

(Gagliardi J.P. et al., 2008). Lastly, one contribution introduces the need for

picking information to be conveyed in real time, in order to arrange dynamic

picking inside the warehouse (i.e. with the operator picking orders arriving in

real time during the picking operations and information continuously

changing during a picking cycle) instead of traditional pre-arranged batch

picking processes; this model helps companies to be on-time offering services

which can be surely considered as fast deliveries (in fact, examples of a

merchant delivering in 45 minutes and of another operating in three hours

are provided) (Gong Y. and De Koster R., 2008).

Few more contributions (13 out of 52, corresponding to 25 percent) address

both activities of picking and delivery; by looking at the research method, we

can notice an opposite pattern with respect to the one of “only picking”

papers: most of them are conceptual frameworks (4) or case studies (4) and


45

surveys (2), just two are the simulations, one literature review and no

mathematical models are provided. We can so assert that the trend of

addressing more activities along the supply chain (not only what happens

going out from the distribution centers, but also what occurs before inside) is

still under development and significant contributions are provided by real

companies which show their operations management example; in some cases

it has been possible to develop more general frameworks or models, but they

analyze activities in a conceptual manner; quite difficult instead is to build

integrative mathematical algorithms able to concurrently optimize two

activities so different one from the other. The fact of being this topic still

under development is confirmed by looking at the delivery speed on which

these papers focus: in fact, an increasing number of contributions (with

respect to the one of papers about picking) pay attention to recent fastening

processes, having one paper about fast delivery, three about same day and two

about 24 hours (or next day delivery); more than a half (7 out of 13) still

belong to the “others” category, but a growing interest in fast order cycle

times has to be underlined. Starting from papers categorized as “others”, they

mainly regard comparisons of different business models implemented by real

companies: we can find some case studies comparing operations of two

Internet grocers, one success and one failure, firstly looking at the strategic

alignment between operations and marketing strategies, then giving an

overview also at the characteristics of e-operations (particularly at logistics

infrastructure and information technology deployment) (Delaney-Klinger K.

et al., 2003; Lunce S.E. et al., 2006); some surveys of many online retailers (55

in one case, 4 in the other) investigate different distribution strategies,

including both the choice of the distribution infrastructure used to serve

customers (existing stores’ warehouses or dedicated DCs) and the delivery

area/method (home delivery or customer pickup or recourse to third party

logistics provider) (de Koster R., 2003; Boyer K.K. and Hult G.T.M., 2005);

another paper simulates three scenarios related to e-grocery distribution

strategies, combining different picking logics (in-warehouse and in-store)

with various proximity delivery approaches and studies their impact on city

logistics and customers’ trips (Durand B. and Gonzalez-Feliu J., 2012); a paper

presents a framework to assess logistics costs’ distribution throughout the

most commonly used supply chains for online grocery sales, from order

picking at the supplier to delivery to customer’s doorstep (Vanelslander T. et

al., 2013); finally, a case study of a German metropolitan area is provided, in

which both decisions upon acceptance or refusal of orders based on

transportation capacity and upon routing solution in order to pursue cost

minimization are made (Cleophas C. and Ehmke J.F., 2014). All the previous

papers’ aim is the optimization of activities, through times and cost


46

minimization; in some cases they relate to daily couriers’ deliveries or choice

of time slots for the last-mile portion of distribution, but none of them

addresses fast order cycle time, none staying within the 24-hours time frame

for the whole process. Then we can find two papers addressing the theme of

next day (or 24 hours) delivery: the first designs the transformation process

from a traditional warehouse into an e-fulfillment center (together with its

strategic and operational requirements) in the case companies want to

implement a multi-channel strategy and add to their traditional business the

business-to-consumer eCommerce, being able to offer a service which

requires one day to be carried out (Tarn J.M. et al., 2003); the second paper

introduces an algorithm for stock allocation along the distributive

infrastructure of e-grocers with the final aim of reducing overall delivery

times (referring to order cycle times which stay around one day) and

considering tradeoffs between picking and delivery activities’ cost (Scott J.E.

and Scott C.H., 2008). The most recent papers, instead, deal with same day

and fast deliveries: there are two conceptual frameworks describing some

relevant operators and/or merchants which carry out same day deliveries,

exploring some key factors determining the success or failure of their

operations (addressing picking, packing and last-mile distribution) in order to

stay within the same day time window (Sareen H., 2013; Hausmann L. et al.,

2014); another paper presents the case study of a really existing company

which operates as an online electronic components’ distributor, deeply

describing the way all activities are carried out in order to offer a same day

delivery service (Kumagai J., 2014). Lastly, we have a literature review of the

state-of-the-art of eCommerce logistics along the whole supply chain from a

practice perspective, with a review of typical North-American, European and

Asia-Pacific eCommerce logistics companies so as to get lessons from their

operations management and to understand future opportunities and possible

developments of this business (Yu Y. et al., 2016); being it a very current

contribution, among the companies many examples of the fast delivery trend

can be found, with processes lasting overall a few hours.

The last category for what concerns the type of activity addressed deals

with delivery alone and it is the most copious one: it is made of 30

contributions out of the total 52 (corresponding to 58 percent), which means

that most attention is paid to this topic, especially to its final portion that is

the last-mile at the customer doorstep. For what concerns the research

method, a significant portion of these papers belong to the category of

analytical/mathematical models (9) and simulations (6), then there are also

many case studies (6) and conceptual frameworks (5) while only a residual

portion is left to literature reviews (3) and surveys (1); globally, theoretical

papers about models (made by the sum of analytical models, conceptual


47

frameworks and simulations, which are 20) largely overcome the empirical

ones (case studies and surveys, which together are just 7) and this means that

the topic of delivery has been subject of deep investigation, which has allowed

to collect a sufficient amount of data in order to develop frameworks of

general interest, not only applicable to few disparate cases. The presence of so

many developed frameworks can be linked to the fact that almost a half of the

contributions (14 out of 30) deal with the least recent trend about delivery

speed, the one categorized as “others” and subjected to researches for many

years; but, there is also a relevant part of the papers addressing the last

developments in terms of speed: in fact, five papers deal with 24-hours (or

next day) delivery, six address the theme of same day delivery and again five

belong to the category of fast delivery. It becomes evident that the activity of

delivery is not only the one investigated the most since the very beginning

and spread of eCommerce, but it is also the one mostly studied when dealing

with new opportunities and trends in the industry. In fact, this activity

implies the delivery of small items at a huge number of different locations,

with all the constraints that traffic imposes to the tour and the need of having

someone attending the delivery location; for sure this is the most complex

activity to be managed and the one which requires huge efforts in terms of

optimization techniques; we can easily understand why it has always been the

main research focus, while activities inside the warehouse have been of lower

interest from researchers’ viewpoint.

Starting with “others” category, first there are some mathematical models

or simulations providing algorithms for the optimization of different

activities: a pair of them look at vehicle routing problem considering a specific

order available time as main constraint, computing the best path in a dynamic

way (i.e. without recurring to an a priori data preparation phase) and aiming

at minimizing total vehicle completion time (Li Y. et al., 2015; Liu L. et al.,

2016); another model addresses not only optimal route issue, but introduces

also a distribution scheduling algorithm in order to solve the problem of

tracking a huge amount of express deliveries on the basis of the workflow (Xu

R. et al., 2014); one simulation takes into consideration traffic conditions and

available time windows as constraints with the objective of solving

optimizations and scheduling issues of non –fully-loaded vehicles for home

deliveries, trying to load them as much as possible within a certain time frame

and delivery tour (Xiao H. et al., 2013); the last model presents a fully

automated method to select the best set of time slots to be offered in each of

the zip codes’ areas of a specific served region, pursuing cost-effectiveness

(Agatz N. et al., 2011). All the aforementioned models refer to daily or weekly

time windows, with a general goal of respecting available times or even

minimizing them, but no reference is made to the ability of arranging next


48

day deliveries, neither faster ones. Then, there are some more theoretical

contributions dealing with the general topic of logistics strategies for e-

fulfillment: one literature review lists five possible strategic alternatives (i.e.

logistics postponement, dematerialization, resources exchange, leveraged

shipments and brick-and-mortar model) and their match with different

companies’ typologies (Lee H.L. and Whang S., 2001); one research collects

data via a survey in order to examine the possible relations among firms’

logistics capabilities, logistics outsourcing strategy and the assessment of

firms’ operational performance (Cho J.J.K. et al., 2008); one framework

specifically focuses on development of e-tailing industry in China, analyzing

operational models put in place by parcel couriers (more precisely, e-tailers

operating a supply chain-based business and others working in an

emarketplace-based environment) and the different trends which are found in

terms of geographic coverage of the distributive infrastructure (Wang J.J. and

Xiao Z., 2015); another framework is developed to design and evaluate

different last-mile solutions, based on design criteria taken from supply chain

and operations management literature, and particularly demonstrating

convenience of implementing Consumer Choice Portal-Package

Consolidation Centers (i.e. a portal enabling consumers’ choice to resort to a

packaging consolidation center for supporting home deliveries) within

densely populated urban geographies (Harrington T.S. et al., 2016); one last

case study addresses logistics solutions and innovative distributive structures

put in place by e-grocers, comparing the cases of two European countries (i.e.

France and Germany) in which e-grocery has arisen almost at the same time

but it has developed with considerable differences (Saskia S. et al., 2016). Also

these contributions, even if describing distribution strategies and deeply

looking at operations management, do not address the trend of fast deliveries.

Two papers deal with the topic of failed-first-time home deliveries and

provide proposals for solving this phenomenon: one paper studies the

convenience of CDPs’ (Collection and Delivery Points) implementation with

respect to the traditional delivery method in the real case of an household

retailer operating in West Sussex (UK) (Song R. et al., 2009), the other

research implies address intelligence (and the application of multiple linear

regression techniques) using historical delivery data in order to predict future

delivery results and improve its efficiency (van Duin J.H.R. et al., 2016); both

papers consider deliveries carried out within specific time slots or on pre-

arranged dates, focusing so on the compliance with available times but with

no reference at all to systems working within next day limits. Lastly, two

contributions provide examples of transportation means able to reduce

shipping times (but again, not considering fast overall order cycle time): the

first studies the introduction of air cargos into parcel couriers’ offer, but it


49

refers to speed trends of more than a decade ago and the maximum speed

able to be offered is three days (Lasserre F., 2004), the second analyzes

electric cargo bikes’ use by individual couriers or instant messengers in their

daily delivery tour in order to assess convenience of these means and factors

influencing individual willingness to utilize them (Gruber J. et al., 2014).

Moving to papers categorized as “24h”, they mostly consist of simulations

(3) and then we have one analytical model and one case study. Four out of the

five contributions belonging to this class address the topic of inefficiency of

unattended home deliveries: two simulations present different alternatives for

receiving goods, specifically reception box and delivery box approaches’, and

assess the service level they are able to offer to consumers together with their

cost from the retailers’ viewpoint; they both refer to e-grocery industry and

they consider the real case of Finnish areas in which grocers perform next day

deliveries (Punakivi M. et al., 2001; Kamarainen V. et al., 2001). One paper

considers again e-grocery and next day delivery and applies vehicle routing

and genetic algorithms to assess operations’ efficiency and cost of three last-

mile alternatives (i.e. attended home delivery, reception box and collection-

and-delivery point), simulating them in scenarios with different population

density and order quantity (Wang X. et al., 2014); the fourth paper studies the

case of France and Germany in which parcel delivery operators have

successfully developed pickup points and parcel lockers as alternatives to

home delivery, analyzing the key drivers of their development and providing

real examples of merchants carrying out deliveries in 24 hours (Morganti E. et

al., 2014). The fifth paper is a mathematical model and proposes an algorithm

to personalize scheduling of express deliveries, in order not only to guarantee

delivery punctuality to customers but also to have the total completion time

minimized; it explicitly refers to one-day delivery service and it is evaluated

by analyzing GPS trajectories of more than one thousand couriers over a

period of two months in Beijing (Sun Y. et al., 2016).

For what concerns the “same day” category, there is an equal presence of

analytical models (2), conceptual frameworks (2) and literature reviews(2).

The two mathematical models propose algorithms to solve dynamic pickup

and delivery problem with time windows faced by local area courier

companies delivering letters or small parcels; one is more focused on the way

waiting times are distributed along vehicle routes, comparing so four different

waiting strategies (Mitrovic-Minic S. and Laporte G., 2004), the other employs

anticipatory algorithms and considers real time fleet management in a more

comprehensive way, addressing requests’ assignment to vehicles, routing,

scheduling of routes and relocation of idle vehicles (Ghiani G. et al., 2009);

they both refer explicitly to parcel delivery operators who carry out same day

service. The two literature reviews focus on the latest developments of


50

internet shopping and home delivery and their impacts on city logistics:

challenges and opportunities affecting transport within urban areas comprise

traffic congestion, safety, environmental-friendly vehicles powered by

alternative fuels, etc. and they are completely different from one country to

another; both papers expressly analyze also city logistics’ challenges and

opportunities brought by same day deliveries with real examples (Visser J. et

al., 2014; Savelsbergh M.and Van Woensel T., 2016). While for what concerns

conceptual frameworks, one addresses again the topic of city logistics,

underlines the benefits that courier express and parcel services (CEP) could

get from a cooperative planning with traffic control management (TM)

systems which control city traffic flows and simulates the best path for home

deliveries performed within a single day (Koster F. et al., 2016); the other

presents four innovations which are expected to strongly influence last-mile

deliveries in the next five to seven years (i.e. advanced algorithms and

analytics, drones, robots and driverless vehicles) and analyzes the case of

some market entrants developing these technologies and their business

models, with various examples of operators implementing these innovative

tools in order to make their same day delivery service even faster and more

reliable (Lee H.L. et al., 2016).

Looking at the last category of “fast” deliveries, most papers (3 out of 5) are

case studies, but we can also find one mathematical model and one

simulation. Two of the case studies focus on European courier express and

parcel sector, with a specific attention to France: one analyzes the

organization of the network of pickup points implemented in Paris and its

region and describes how this infrastructure is able to allow deliveries to be

accessible in some minutes (Morganti E. et al., 2014); the second uses

interviews of French players in the sector and compares them to players of

other European countries in order to make an overall evaluation of sector’s

changes, drivers and future prospects, based on real examples and figures

among which we can find couriers performing same-hour delivery (Ducret R.,

2014). The third case focuses on a single new UK service, called Shutl,

consisting of a platform which aggregates couriers’ capacity in the same day

market and allowing retailers to offer delivery options which stay within a 90

minutes’ time window (Runciman B., 2011). The simulation aims at comparing

some acceptance mechanisms, differing in the amount of travel time

information that has to be collected and considered in order to decide

whether to accommodate a delivery request or not; the final objective is the

one of accepting as many requests as possible, considering the tradeoff

between the cost for information collection and usage and the service level,

which in many cases guarantees deliveries in less than one hour (Ehmke J.F.

and Campbell A.M., 2014). Finally, the analytical model proposes a large scale


51

mobile crowd-tasking model in which a large pool of citizen workers are used

to perform last-mile delivery within a city, in order to minimize global

travelling cost but also assure delivery efficiency and reduce unattended home

deliveries’ rate; experiments of this model are conducted by using Singapore

and Beijing datasets, in which many operators performing deliveries in few

hours or even less can be found.

2.3.3 Second matrix classification: speed of the logistics process – field of application

Table 99 - second classification: speed of logistics vs. application field

Another interesting classification can be made by looking at the application field of the articles: we can first consider separately the group of papers dealing with logistics in general terms and the subset of them which addresses the area of fast logistics (difference which has been deeply explained in the previous pages); for both the two classes, we can try to understand the field which logistics is applied to. In fact, logistics can specifically relate to eCommerce field and to the management of activities to be performed in order to have this channel working (more from a retailer’s perspective); or, logistics can address customer experience, looking at the performances of the delivery process perceived by consumers, no matter the channel used in order to serve them; or in the end, both fields of eCommerce and customer experience can represent an area of interest.

traditional logistics fast logistics

eCommerce Lee and Whang (2001); de Koster (2002); Delaney-Klinger et al. (2003); Tarn et al. (2003); de Koster (2003); Lunce et al. (2006); Scott and Scott (2008); Cho et al. (2008); Song et al. (2009); Hu and Chang (2009); Hu and Chang (2010); Durand and Gonzalez-Feliu (2012); Xiao et al. (2013); Vanelslander et al. (2013); Xu et al. (2014); Wang and Xiao (2015); Zu and Sun (2015); Tsamis et al. (2015); Liu et al. (2016); Li et al. (2017)

Gagliardi et al. (2008); Gong and de Koster (2008); Sareen (2013); Morganti et al. (2014); Morganti et al. (2014); Wang et al. (2016); Yu et al. (2016); Lee et al. (2016)

customer experience Lasserre (2004); Wang et al. (2014); Gruber et al. (2014); Cleophas and Ehmke (2014); Li et al. (2015); Sun et al. (2016); Harrington et al. (2016); van Duin et al. (2016)

Mitrovic-Minic and Laporte (2004); Ghiani et al. (2009); Runciman (2011); Ehmke and Campbell (2014); Koster et al. (2015); Savelsbergh and Van Woensel (2016)

eCommerce & customer experience

Punakivi et al. (2001); Kamarainen et al. (2001); Boyer and Hult (2005); Agatz et al. (2011); Schrotenboer et al. (2016); Saskia et al. (2016)

Visser et al. (2014); Ducret (2014); Hausmann et al. (2014); Kumagai (2014)


52

First of all, as we could expect also from previous analyses, most of the articles

(34 out 52, corresponding to 65 percent) address logistics in its general terms,

without a clear reference to the process timing. On the contrary, 18 papers

(corresponding to the remaining 35 percent) deal with fast logistics and so

processes which are carried out within twenty-four hours; going into details, two

of these writings are about next day deliveries (Gagliardi J.P. et al., 2008 aimed at

studying storage and picking activities for next day delivery provision; Morganti

E. et al., 2014 contrarily focused on transportation activities and in particular last-

mile portion). Half of these papers (9 out of 18) deal instead with same day

processes: one third of them present algorithms and/or simulations for

scheduling and routing of last-mile delivery activities from couriers’ viewpoint

(Mitrovic-Minic S. and Laporte G., 2004; Ghiani G. et al., 2009; Koster F. et al.,

2015); another third consist of frameworks describing most recent trends and

technologies applied by logistics operators for what concerns city logistics and

last-mile delivery, with a particular attention to innovations in the vehicles used

(Visser J. et al., 2014; Savelsbergh M. and Van Woensel T., 2016; Lee H.L. et al.,

2016); the last third present, in a more or less deepened way, cases of merchants

performing same day deliveries and have a look at the whole operations process,

Figure 2 - two-dimensional classification along with research method

: simulation : case study

: conceptual framework : analytical model

: literature review : survey


53

from picking and storage activities until the final leg of last-mile at customers’

doorstep (Sareen H., 2013; Hausmann L. et al., 2014; Kumagai J., 2014). Finally, 7

out of the 18 articles deepen the theme of fast deliveries (i.e. requiring just few

hours to be performed): four of them present case studies of logistics operators

building up innovative methods in order to carry out fast last-mile deliveries

(such as, for example, pickup points for items’ collection by consumers or crowd-

sourcing models with independent couriers working with their own means of

transport) (Runciman B., 2011; Ducret R., 2014; Morganti E. et al., 2014; Wang Y. et

al., 2016); one stays in the field of delivery but provides a simulation in which

different order acceptance mechanisms are compared in order to optimize

couriers’ scheduling activity (Ehmke J.F. and Campbell A.M., 2014); another paper

simulates alternatives of dynamic order picking for delivery performances which

stay within the timeframe of one hour (Gong Y. and De Koster R., 2008); lastly

one article proposes a review of cases of merchants operating few hours deliveries

by analyzing picking activities together with delivery options (Yu Y. et al., 2016).

Starting then from the most copious group (i.e. articles about logistics

without time limitations), we can notice that big part of them (20 out of 34

papers, corresponding to 59 percent) refer to the field of eCommerce. Five papers

propose cases of grocers which expand their traditional business by

implementing an e-grocery channel; all of them address tradeoffs that these

players face in the implementation of the whole e-fulfillment process, from

picking to final delivery and in some cases provide examples of success’ practices

in opposition to practices which have conversely led to failure; this means that

significant contributions exist when talking about grocery industry which enters

the eCommerce and they are also quite well structured as they analyze the overall

supply chain and not only portions of it; however, a big lack is represented by the

fact that none of these cases report fast processes: e-grocers often offer the choice

of the date and time of delivery, by they usually require many days in order to be

arranged and they have to be booked in advance (Delaney-Klinger K. et al., 2003;

Lunce S.E. et al., 2006; Scott J.E. and Scott C.H., 2008; Durand B. and Gonzalez-

Feliu J., 2012; Vanelslander T.et al., 2013). Other five papers address alternatives of

operations and e-fulfillment strategies in order to best suit the characteristics of

different merchants; a pair of them considers the whole supply chain, from the

management of stores/warehouses to the choice of the delivery infrastructure

and area (Tarn J.M. et al., 2003; De Koster R., 2003), while the others are

particularly focused on the distribution strategy and they stress the attention on

the fact that two main kinds of logistics operators and/or retailers exist

(traditional multichannel operators and Internet-based pure players) and each

category requires a differentiated operational approach when dealing with the

design of the e-fulfillment strategy (Lee H.L. and Whang S., 2001; De Koster R.,

2002; Wang J.J. and Xiao Z., 2015); they are very different research methods


54

(conceptual frameworks, literature reviews, analytical models or surveys) all

aimed at answering to te question of how to organize the logistic fulfillment

process when an online transaction takes place but none of them deals with the

concept of process’ speed. Other five articles are just focused on players

operating only into the eCommerce context, the ones which have entered this

new business from scratch: three of them analyze the couriers and logistics

operators’ context and they propose simulations/analytical models aimed at

optimizing scheduling of non-fully loaded vehicles and vehicles’ routing with

order available time as constraint, so as to improve efficiency of business-to-

consumer eCommerce delivery (Xiao H. et al., 2013; Xu R. et al., 2014; Liu L. et al.,

2016); conversely, the remaining two papers deal with retailers just operating in

the eCommerce business: in one case firms’ performances are examined and in

particular the impact on them of the choice of leveraging on internal firms’

logistics capabilities versus resorting to logistics outsourcing (Cho J.J.K. et al.,

2008); in the other case the impact that failed first time home deliveries have on

retailers’ service performances is studied and the cost convenience of collection

and delivery points as an alternative to additional carriers’ journeys and/or

customers’ trips to stores is supported (Song R. et al., 2009). These last two

papers are less theoretical than previous models (i.e. they are one survey and one

case study), so they present examples of real cases but again none of them

explicitly address the theme of fast deliveries. Lastly, five papers regard the

storage and picking activities alone, without any reference to delivery options.

Two of them present analytical models for the development of automated storage

and retrieval systems in the case of traditional retailers deciding to add the online

channel to their business; their aim is minimizing picking times when the choice

of being multichannel retailers inevitably makes the service harder to be

managed, but they do not refer to really fast services as next day or even shorter

(Hu K.Y. and Chang T.S., 2009; Hu K.Y. and Chang T.S., 2010). The other three

articles look at activities’ management inside a logistics center operating for the

eCommerce channel only: again they are algorithms and their goal is the one of

optimizing items’ storage, orders’ batching and pickers’ routing for a well-

functioning e-fulfillment service, even if very fast processes are not yet taken into

considerations (Zu Q. and Sun B., 2015; Tsamis N. et al., 2015; Li J. et al., 2017). So

we can infer that, when dealing with standard logistics services, eCommerce

represents a quite widely investigated field along the whole supply chain process

and for many different types of players with the objective of entering this

business.

The second topic addressed is customer experience: 8 out of the 34 papers

about traditional logistics (corresponding to 23 percent) deal with the assessment

of service performances not applied to eCommerce but to traditional channels.

Three of them are about last-mile delivery and they compare through simulations


55

convenience of different delivery options for last-mile (e.g. reception boxes,

collection and delivery points, consolidation centers or traditional attended

home deliveries) or of alternative transportation means for reaching customers’

doorstep (e.g. traditional bicycles or even electric ones versus cars’ use); they all

compare performances of different couriers’ delivery services from customers’

viewpoint (Wang X. et al., 2014; Gruber J. et al., 2014; Harrington T.S. et al., 2016).

Other three writings consist of analytical or conceptual frameworks which

propose personalized services for scheduling couriers’ inter-city delivery: one

focuses on the development of a dynamic path computation which optimizes

routing process by eliminating a time-consuming a-priori data collection phase

(Li Y. et al., 2015); another offers personalized travel time estimation by studying

GPS trajectories usually followed by couriers (Sun Y. et al., 2016); the third applies

address intelligence in order to identify the set of zip codes’ areas served which

enable parcel companies to optimize their service (van Duin J.H.R. et al., 2016).

One paper faces the theme of increasing geographical distance between retailers

and the markets they serve and through an analytical model it assesses the

advantage of delivery technologies such as air cargos; however, the fastest service

analyzed does not stay within the boundary of three-days delivery (Lasserre F.,

2004). Lastly, there is one computational study from a German metropolitan area

which provides a combined approach for delivery requests’ acceptance and, based

on that, cost-minimizing routing solution; it is the only paper considering

together picking and delivery activities’ performances (Cleophas C. and Ehmke

J.F., 2014). We can affirm that papers about customer experience are not so

copious and they mainly present algorithms enabling couriers to optimize their

delivery paths; there is a lack of contributions about employable technologies

and/or means of transport which can be perceived as a value-adding solution also

in the final customers’ eyes and moreover, picking activity is almost forgotten.

The left 6 papers out of the 34 about standard logistics (i.e. 18 percent)

concern together customer experience and eCommerce fields. Two of them are

simulations about the topic of last-mile delivery, analyzing service and cost level

of eCommerce delivery alternatives (i.e. reception and delivery boxes as an

alternative to traditional attended home delivery): one applies to the case of a

Finnish e-grocer (Punakivi M. et al., 2001), the other describes the case of logistics

operators working in the Helsinki area (Kamarainen V. et al., 2001). Other two

papers apply to the context of e-grocers only and their delivery options: the first

is a model aimed at selecting the optimal set of time slots to offer in each zip

code area, pursuing together cost-effectiveness but also an acceptable service

level (Agatz N. et al., 2011); the second compares delivery solutions for e-grocery

industry introduced in France and Germany (Saskia S. et al., 2016). One paper

deals only with picking activity and assesses the impact that different routing

techniques for pickers working inside the same picking area have on the delivery


56

time of eCommerce orders (Schrotenboer A.H. et al., 2016). In the end, one

survey uses data collected from 2440 customers in order to compare strategies of

four different e-grocers in terms of choice of fulfillment center and of delivery

method, integrating so storage/picking and delivery activities (Boyer K.K. and

Hult G.T.M., 2005). From this cluster of articles we can observe that almost all

activities of the supply chain are tackled; but a significant portion of

contributions comes from e-grocery business and a lot of information should be

collected for what concerns customer experience in eCommerce for other

strongly developed industries (e.g. informatics and consumer electronics,

clothing, etc.).

Moving to the second cluster, the one of papers about fast logistics (which are

18 out of the total 52 as previously written), 8 of them (corresponding to 45

percent) deal with the business of eCommerce. Half of these 8 articles address

the topic of last-mile delivery: two are case studies of alternatives to home

delivery developed by European parcel operators, especially French and German

ones, analyzing the key drivers of the development of pickup points’ and parcel

lockers’ networks to improve efficiency in case of online orders (Morganti E. et

al., 2014; Morganti E. et al., 2014); one is a conceptual framework in which four

innovations expected to influence development of same day deliveries in the

following years are described (i.e. advanced algorithms and analytics, drones,

robots and driverless vehicles), so as to provide forecasts on future innovations in

terms of technologies and business models applied for improving same day

services for eCommerce (Lee H.L. et al., 2016); the fourth paper proposes an

algorithm for developing a crowd-sourcing model in which a large pool of

citizens can participate and perform last-mile deliveries in very fast times (few

hours) and it is experimented with Singapore and Beijing datasets of online

customers (Wang Y. et al., 2016). Two papers instead regard the picking activity:

one presents the case study of a real distribution center which employs a pick-to-

built system to perform e-fulfillment of orders in 24 hours, analyzing different

heuristics for product locating, replenishing and picking (Gagliardi J.P. et al.,

2008); the other simulates the application of a dynamic order picking system (i.e.

system in which workers pick orders arriving in real-time during picking

operations and information can dynamically change during the picking cycle) to

warehouses operating for eCommerce industry only, providing examples of real

operators who, by applying this type of system, are able to provide deliveries in a

very short time (3 hours in the case of one merchant, only 45 minutes for the

other) (Gong Y. and de Koster R., 2008). The last two papers about eCommerce

deal with both activities of picking and delivery and are both conceptual

frameworks: one describes some cases of merchants performing same day

deliveries and explores some key factors for operations’ management which

contribute to success or failure of this type of service (Sareen H., 2013); the other


57

review presents the state-of-the-art of eCommerce logistics in supply chain

management from the viewpoint of practitioners (i.e. couriers and other logistics

operators), describing North American, European and Asia Pacific

implementations and corresponding models so as to get insights from best

practices also in terms of fast deliveries (various examples of merchants operating

in few hours are provided) (Yu Y. et al., 2016). Among the aforementioned 8

papers, one fourth belong to the group of articles about next day delivery, a

second fourth deals with same day services while a half of them addresses fast

deliveries; this means that when speaking about eCommerce channel, not only all

the supply chain activities’ (i.e. picking, delivery and the union of the two), but

also all the kinds of fast delivery services are tackled with a certain interest,

especially the most innovative ones working at highest speed.

The second theme addressed is customer experience: 6 out of the 18 papers

about fast logistics (corresponding to 33 percent) do not relate to eCommerce

industry, but assess performances of supply chain activities for orders fulfillment

in traditional channels. All the papers concern the delivery activity only and

describe practices of couriers and other logistics operators to arrange home

delivery. There are two analytical frameworks presenting algorithms to solve

dynamic vehicle dispatching problem with pickups and deliveries within given

time windows evaluating different strategies for all the issues involved in real-

time fleet management (i.e. requests’ assignment to vehicles, vehicles’ routing,

scheduling of routes and relocation of idle vehicles); empirical studies are

conducted using real-life data from courier companies operating same day pickup

and delivery of letters and small parcels in order to show advantages of this type

of models (Mitrovic-Minic S. and Laporte G., 2004; Ghiani G. et al., 2009).

Another modeling simulation deals with couriers’ delivery scheduling and

routing but considers only different requests’ acceptance mechanisms according

to the amount of travel information which are taken into consideration in order

to decide whether to accommodate a request or not; profit and service quality are

the variables compared in the case of different mechanisms’ implementation and

a real-world inspired simulation framework is used to carry out this comparison;

situations in which collection of more travel time information may be worth the

additional effort are investigated, being able to perform fast deliveries which can

be made also in less than one hour (Ehmke J.F. and Campbell A.M., 2014). There

is another framework dealing with couriers’ delivery scheduling and routing, but

this is a conceptual one; it investigates the impact of the activities of traffic

control management (TM) in the context of city logistics for determination of

travel times by courier express and parcel service providers (CEP); this tool helps

optimizing the daily delivery schedule of logistics operators considering city

traffic conditions and expressly refers to delivery routes which have to be

performed within one day (Koster F. et al., 2015). One interesting paper presents


58

the case study of Shutl, a new British delivery company able to offer to its

customers two very fast delivery options (90 minutes or 1 hour delivery, with

different cost for each option); this was made possible by operating a platform

which aggregates capacity in the same day courier market via a web service,

resorting to a crowd-sourcing model for last-mile delivery management

(Runciman B., 2011). The most recent literature contribution reviews and

discusses current and anticipated challenges and opportunities regarding

efficient and effective goods’ transportation within urban areas, while taking into

account negative effects of city logistics on traffic congestion and environment; a

variety of logistics operators’ trends is addressed, including crowd-shipping

models and multimodal delivery options, with a particular attention to the theme

of same day delivery (Savelsbergh M. and Van Woensel T., 2016). Even if almost

all research methods can be found within this cluster of papers, a strong

limitation can be noticed: no articles relate to the picking activity or to the whole

order fulfillment process (from picking to delivery), meaning that services

described in these contributions do not take into consideration the time required

for order preparation before the delivery takes place; speaking about same day or

fast services could so be incorrect, because home delivery is just one portion of

the operative supply chain from order issuing to final goods’ provision and it may

require relevant additional time which may make these services no more fast. In

addition, just one case of company being able to really operate at high speed (i.e.

within two or three hours) is reported; the most addressed topic is the one of

same day delivery, very well investigated and deepened so as to allow the

development of general models or frameworks on it; a strong contribution of very

innovative delivery companies’ examples is missed.

The last cluster of papers about fast logistics deal with customer experience

specificly applied to the industry of eCommerce and it consists of 4 papers

(corresponding to 22 percent of the overall articles on fast services). Two of them

address the delivery activity alone: one is a literature review of latest trends

regarding internet shopping and related home delivery and their effects on city

logistics; the negative effect of increased traffic congestion is noticed, but at the

same time recent developments have provided opportunities for the employment

of vehicles powered by alternative fuels supporting sustainability concerns; since

trends are not the same worldwide, single examples for each nation are provided

and an emblematic case of a Japanese merchant operating same day deliveries is

of relevant interest (Visser J. et al., 2014). The other paper about delivery

investigates key factors of the evolution of European Courier, Express and Parcel

sector (CEP); the focus is on French CEP sector’s and urban parcel delivery

sector’s players, developing then comparisons with other European countries so

as to provide an accurate picture of practices’ examples for this under-studied

sector; current changes together with future prospects are investigated and


59

significant cases of players serving not only within the same day, but also within

the same hour of order request are described (Ducret R., 2014). The other two

papers provide an overview of all the supply chain activities, from order picking

to items’ delivery, and they both relate to same day services. The first one relates

again to recent parcel sector’s trends and in particular discusses limitation of low-

cost carriers’ models in a context such as the eCommerce in which innovative

services such as same day deliveries, even if they may require additional costs, are

considered as value-adding from customers’ viewpoint; this framework describes

a large number of logistics operators and of its customer companies (i.e. the

merchants resorting to external couriers to perform deliveries for their online

channel) which work within same day of order receipt, considering all activities

of order picking, packing and last-mile home delivery (Hausmann L. et al., 2014).

Lastly, interesting is the case study of Digi-Key Corp., a large electronic

components’ distributor which is able to perform same day delivery; its internal

activities are deeply described in this paper, from order receipt activity to

warehouse operations’ management, moving then to the distributive structure in

order to arrange a process working at high speed (Kumagai J., 2014). Within this

last cluster, picking activity finds stronger attention and in many cases the whole

operative supply chain is investigated; however, most contributions (75 percent

of them) relate to services carried out within one day and only one paper

addresses faster services; in addition, this last paper is about delivery activity, so

no contributions of overall fulfillment processes performed in very fast times are

provided.

2.4 Conclusions from literature review and directions for future research

Given the importance of logistics operations in business-to-consumer

eCommerce supply chain and the growing interest in making the whole process

always faster by offering to end customers express delivery services as an

alternative to standard ones, the aim of this literature review was to make an up-

to-date analysis of the topic of fast deliveries in B2C eCommerce. The review

focused on a set of 52 selected papers published from 2001 to 2017 in 39

international journals. Among these contributions, some other literature reviews

dealing with internet shopping and home deliveries were found, but the majority

of them presented a number of limitations related either to the timeframe they

consider (i.e. they lack of recent contributions, e.g. Lee and Whang, 2001) or to

their content (i.e. they just focus on last-mile shipment and its impact on city

logistics, without addressing the whole process from order receipt; e.g. Visser et

al., 2014; Savelsbergh and Van Woensel, 2016). Just one paper proposed a recent


60

review (2016) and tackled all supply chain management activities in eCommerce,

from order picking to final delivery, but it was providing a set of examples of

practices implemented by real companies without addressing fast delivery issue

in a comprehensive manner and not being able to draft, starting from these

practices, a generally valid business model used as reference for this service’s

implementation (Yu et al., 2016). So this review was carried out in order to

overcome the above-mentioned limitations and was organized into three main

sub-sections: discussion of main characteristics (i.e. year of publication, journal

title and type, regions addressed), research method and content of each paper.

The identified papers were mainly published in engineering operations and

activity management journals (28 percent), logistics and transportation journals

(20 percent) and computer and system sciences journals (20 percent). For what

concerns year of publication, the trend was pretty stable from 2001 to 2013, with

two or three papers published each year (with the exception of 2007 in which no

papers were found), while from 2014 on a big boost in the number of publications

can be observed (11 contributions in 2014, 5 in 2015, 10 in 2016; for 2017 just one

paper was found but we have to consider that the analysis was carried out at the

beginning of the year and for sure we can expect to find additional contributions

provided in the following months). Then, looking at the countries addressed, it

should be noted that the number of papers in which the first author is from

China corresponds to 25 percent of the total, followed by a 23 percent of first

researchers coming from USA; this is consistent with the fact that these countries

are experiencing the most significant growth in terms of eCommerce diffusion

and fast delivery technologies. Interesting to notice that relevant portion of first

authors come also from Netherlands (13 percent), Germany (10 percent), France

(8 percent) and UK (8 percent), as these regions are the most developed

European ones in this field.

In terms of methodologies used, most papers present analytical or

mathematical models (27 percent), but there are also many case studies (21

percent). A significant portion also presents conceptual models and frameworks

(19 percent) or simulations (19 percent). For what concerns the remaining

methodologies, some papers are literature reviews aimed at representing the

state-of-the-art of scientific research on a certain topic (8 percent), while some

others are based on data collected from surveys (6 percent).

With regard to content, several interesting areas of research were identified.

Specifically, 27 percent of papers deal with the theme of delivery scheduling and

routing arrangement in order to optimize couriers’ daily job; 23 percent address

the topic of last-mile delivery in different aspects (i.e. alternatives of network

design with the aim of reducing failed first-time deliveries, alternatives of

transportation means in order to make faster deliveries or introduction of new


61

information technologies for optimizing couriers’ delivery performances); 17

percent deal with overall supply chain structure, looking at the business and

operational models applied by operators along the whole chain; 13 percent of

contributions concentrate on the study of activities internal to distribution

centers, which are storage and picking; 12 percent gives a general overview of

actual couriers’ and logistics operators’ trends, with the aim of providing a

practical perspective of the state-of-the-art of eCommerce logistics; lastly,

residual attention is paid to the distribution structure of companies (4 percent)

and to performance assessment of e-operations (4 percent).

After a general content analysis, articles were first classified according to a

two-dimensional approach in which the first variable taken into consideration is

the speed of the delivery process (from order receipt to item delivery to end

customer, so corresponding to the order cycle time) and the second variable is

the type of activity and/or activities addressed in the paper. For what concerns

the first axis, four classes were identified: fast deliveries (not defined in a unique

way, but expressed by a number of different examples, in any case always staying

within two or maximum three hours for the whole process to be carried out);

same day deliveries (which have a more clear definition: they have to be delivered

by the end of the day and within a given period after receiving the order); 24

hours deliveries (for which the whole process is performed by the end of the day

following order submission; also called next day deliveries); others (the residual

portion of delivery options, going beyond the next day delivery limit and taking

more than two days to be carried out). While dealing with the second variable,

three categories have been defined: picking (if the only activity addressed in the

paper is picking or at maximum storage, in any case just order preparation

activities occurring inside distribution centers); delivery (if on the contrary the

only activity analyzed in the paper is the shipment from the distribution center to

the customer’s doorstep); picking + delivery (if both activities are tackled, in a

more comprehensive approach).

More than a half of papers (54 percent) belong to “others” category,

expressing the fact that this category is the one having seen the wider research

development, even thanks to the fact that these “slow” delivery options are the

ones being performed by almost every company and being in place for many

years. The fact that among these papers, large majority is represented by

mathematical models (36 percent), conceptual frameworks (18 percent) and

simulations (14 percent) is again a proof of the widespread diffusion of these

delivery methods, so as to allow the development of a wide framework of

theorizations and algorithms. By looking also at the activity addressed, half of

“others” papers deal with delivery activity only, while the remaining half is

uniformly spread between papers addressing picking activity and contributions

about picking and delivery together.


62

Moving on, the other three speed categories contain pretty much the same

number of papers: in fact, a 15 percent of contributions belong to 24 hours

category, 17 percent stays within the same day class and 13 percent belongs to fast

delivery category. The most important classes are the ones dealing with fast and

same day deliveries. While clusters addressing delivery activity count an

acceptable number of contributions (five in case of fast delivery, six in the class of

same day and five for what concerns 24 hours process), clusters addressing only

picking or picking + delivery are really scarcely populated: in fact, we can find

just one paper in the “picking + delivery-fast” quadrant, three in the “picking +

delivery-same day” and two in the “picking + delivery-24 hours” quadrant; even

less numerous papers deal with picking activity: only one belongs to fast

quadrant, no one in the same day quadrant and again one in the 24 hours

quadrant.

Then, a second two-dimensional classification was carried out, using as first

variable the speed of the logistics process (divided into “fast” logistics for

processes performed in less than 24 hours or “standard” logistics when logistics

processes requiring more time to be performed are involved) and as second

variable the field of application for the aforementioned logistics processes. For

what concerns this last variable, in the first group logistics is explicitly applied to

the field of eCommerce; in the second cluster the addressed theme is customer

experience related to logistics processes performances in all the channels of

commerce; the third group refers to papers about both fields, so customer

experience in the eCommerce industry specificly. Most of these contributions (34

out of 52, corresponding to 65 percent) address logistics in its general terms,

without a reference to the process timing. On the contrary, 18 papers

(corresponding to the remaining 35 percent) deal with fast logistics and so

processes which are carried out within twenty-four hours. Going into details, two

of these writings are about next day deliveries; half of these papers (9 out of 18)

deal instead with same day processes; finally, 7 out of the 18 articles deepen the

theme of fast deliveries (i.e. requiring just few hours to be performed). We can

first notice that contributions about processes performed at high speed are surely

less numerous than standard ones; but we can consider it as at least relevant,

especially since same day and fast deliveries are quite sufficiently addressed

topics. Starting so the classification from the most copious group (i.e. articles

about logistics without time limitations), we can notice that big part of them (20

out of 34 papers, corresponding to 59 percent) refer to the field of eCommerce; it

represents a quite widely investigated field along the whole supply chain process

(in fact, all operational activities of picking, delivery and both together are

addressed) and for many different types of players. The second topic addressed is

customer experience: 8 out of the 34 papers about traditional logistics


63

(corresponding to 23 percent) deal with the assessment of service performances

not exclusively applied to eCommerce but also to more traditional channels; they

are not so copious and they mainly present algorithms enabling couriers to

optimize their delivery paths; there is a lack of contributions about employable

technologies and/or means of transport which can be perceived as a value-adding

solution also in the final customers’ eyes and moreover, picking activity is almost

forgotten. The left 6 papers out of the 34 about standard logistics (i.e. 18 percent)

concern together customer experience and eCommerce fields; almost all activities

of the supply chain are tackled, but a significant portion of contributions comes

from e-grocery business and a lot of information should be collected for what

concerns other strongly developed industries in eCommerce context (e.g.

informatics and consumer electronics, clothing, etc.).

Moving to the second cluster, the one of papers about fast logistics (which are

18 out of the total 52 as previously written), 8 of them (corresponding to 45

percent) deal with the industry of eCommerce; in these contributions, not only

all the supply chain activities’, but also all the kinds of fast delivery services are

tackled with a certain interest, especially the most innovative ones working at

highest speed (in fact, two papers address same day deliveries and four relate to

even faster services). The second theme addressed is customer experience: 6 out

of the 18 papers about fast logistics (corresponding to 33 percent) do not relate to

eCommerce business only, but assess performances of supply chain activities for

orders fulfillment in traditional industries. Even if almost all research methods

can be found within this cluster of papers, a strong limitation can be noticed: no

articles relate to the picking activity or to the whole order fulfillment process

(from picking to delivery), meaning that services described in these contributions

do not take into consideration the time required for order preparation before the

delivery takes place. In addition, just one case of company being able to really

operate at high speed (i.e. within two or three hours) is reported; the most

addressed topic is the one of same day delivery, very well investigated and

deepened so as to allow the development of general models or frameworks on it;

a strong contribution of very innovative delivery companies’ examples is missed.

The last cluster of papers about fast logistics deal with customer experience

applied to the industry of eCommerce and it consists of 4 papers (corresponding

to 22 percent of the overall articles on fast services); here picking activity finds

stronger attention and in many cases the whole operative supply chain is

investigated; however, most contributions (75 percent of them) relate to services

carried out within one day and only one paper addresses faster services; in

addition, this last paper is about delivery activity, so no contributions of overall

fulfillment processes performed in very fast times are provided.


64

This review has both academic and practical implications. From an academic

viewpoint, it contributes to knowledge in this topic by providing a classification

of the existing body of research for what concerns B2C eCommerce fast

deliveries, specifically looking at the management of logistics activities in order

to put in place such fast systems. This viewpoint is particularly valuable since it is

very difficult to know how this phenomenon has spread among companies and

the characteristics of its diffusion according to different geographies, population

densities, logistics operators and players, etc.

From a practical perspectives, this paper contributes to the understanding of

B2C eCommerce fast deliveries from different viewpoints. It communicates the

last trends of this eCommerce environment, especially the ones regarding order

cycle times, to practitioners who are still in this industry and to the ones who

want to enter the business, giving them the opportunity of staying competitive or

even reaching a higher development with respect to most competitors.

In addition, it provides practitioners with a more clear definition of what fast

delivery processes are and in which categories they can be classified; this can be a

valid contribution since it was not easy to find a specific definition of the terms

“same day”, “next day” and especially “fast” deliveries.

The review contributes also to understand, through a two-dimensional

classification, the actual level of development of the topic, presenting a picture of

all the relevant articles on the subject and allowing to focus on most important

ones. First, classifying papers according to the activity/activities they address has

helped identifying which activities need to be tackled when a company wants to

rearrange their operations and manage their supply chain; it allows also

companies to understand the difference in the approach they have to apply when

addressing one single activity (e.g. picking alone or delivery alone) or when

dealing with a more comprehensive process (picking + delivery): a wide set of

algorithms and mathematical models is easily applicable to a single activity and

allows to optimize it obtaining measurable results in terms of time minimization;

on the contrary, only conceptual tips derived from best practices of ground-

breaking practitioners represent a useful tool for improvement of longer

processes, taking into consideration more steps of the supply chain together.

Second, classifying contributions according to the speed of the delivery process

allows companies to know which practices they should concentrate on in order to

follow industry trends; it is also useful to understand if a difference exists among

technologies and tools belonging to each cluster (i.e. tools and business models

applied by companies to develop fast delivery options are different from the ones

allowing to perform next day delivery). A company, through the classification of

real examples, could find the operations’ design that best suits its features and

implement the related supply chain strategy.


65

Although a good picture of the extant literature has been formed, this review

presents a number of issues which have not been adequately addressed yet or

which have not been considered at all. This represents a limitations especially for

practitioners, who are not able to completely understand which moves to

implement in order to find and keep a position in this increasing developing

environment.

First, the analyzed literature refers primarily to few industries such as grocery,

food in general and consumer electronics, while other sectors such as clothing,

books, cosmetics have not been examined at all. This represents a gap, especially

for what concerns clothing industry, because it is the one having seen the highest

growth in sales in the last years and also having experienced a significant growth

of companies approaching same day or next day deliveries, especially in big cities

and in case of last-minute orders (e.g. on Christmas or other holiday occasions);

additionally, its supply chain is of relevant complexity.

Second, most attention is paid to the management of the delivery activity

alone, from the moment in which the order leaves the distribution center to the

end customer’s reception of it; even if it is surely a very complex activity to be

performed and its last portion, the one occurring inside cities and having the

name of last-mile, is complex and the one representing the service performance

directly experienced by the customer, other activities are part of the delivery

process too and should be tackled with more attention: picking has an impact too

on the overall order cycle time and for sure a comprehensive approach which

considers both picking and delivery could get to larger benefits.

Third, while contributions about cycle times of more than two days are

common, a little has been written about faster processes. Longer delivery options

have now been overcome by same day and next day deliveries, which are

becoming (or already are, in more developed areas) industry standards

(Hausmann et al., 2014); this means that a lot of cases are spreading and these

practices need to be deeply studied and carefully analyzed as they could provide

very interesting insights and drive future development of the business-to-

consumer eCommerce field.

Lastly, too much space is occupied by empirical contributions (i.e. case

studies and surveys), especially for what concerns fast and same day delivery

classes: a wider investigation in the field will allow academics to gather a relevant

number of data and examples so as to develop articles of more general validity,

which could be used by practitioners as frameworks in order to guide their

operative strategies.


66

3. Research objective and methodology

3.1 Objective

The objective of the thesis is the one of analyzing the state-of-the-art of

delivery initiatives set up by top retailers operating nowadays in the eCommerce

market in order to overcome limitations driven out by the previous literature

research.

The first limit was the one of having too many theoretical contributions which

provide mathematical models and/or simulative algorithms not easily linkable to

single cases of real companies because of context constraints and not so

commonly applicable; in addition, by looking at the speed of the delivery process,

these contributions deal for the biggest part with “slow” deliveries, requiring not

less than two days to be performed and they do not represent an interesting body

of research in most innovative environments. In order to solve these issues, this

thesis aims at finding top web retailers and classifying their services in order to

obtain insights from practices of immediate application in the practical world;

moreover, “slow” services won’t be considered at all and the focus will be just on

operators able to perform the whole process of order fulfillment at maximum

within the next day from order reception.

Secondly, the classification of activities tackled in literature articles showed a

strong presence of writings addressing delivery activity alone and a barely

sufficient number of papers involving also picking activity (alone or together with

delivery in a more comprehensive approach). The thesis does not want just to

focus on the business of couriers and logistics operators able to carry out

deliveries in little time considering only the process of physical items’

distribution, from the moment in which responsibility of products to be shipped

is assigned to couriers to the moment of customers’ reception of goods at their

doorstep (or all the available alternatives to home delivery). On the contrary, the

object of interest is the world of merchants, the retailers selling their products

online, receiving orders from web customers and managing the whole process

until the items reach final consumers’ hands; in this way, also activities occurring

within the walls of merchants’ warehouses are taken into consideration and

speed of the process is not related only to final delivery but to the whole order

fulfillment activities. In fact, we cannot consider of really experiencing next day,

same day or few hours processes if we just consider timing of the shipment, but

we should have the whole process staying within these time constraints.

Another theme regards the nation to which authors belong: as described in

the previous pages, literature writers come in bigger portion from China and US,

with a relevant presence also of UK and then other European countries such as

Germany and France. The point of the thesis is the one of investigating trends


67

according to their geographical presence and find out if any differences exist

among practices implemented in diverse countries. In addition, research

coverage is extended so as to consider not only single nations alone but their

development with respect to the one of the other most innovative countries of

their continent. In this way, not only American, Chinese and British practitioners’

processes will be studied, but Chinese situation will be compared with the one of

other compatibly developed South-East countries (i.e. India, Japan and South-

Korea) and similarly British practices will be analyzed together with the ones of

mostly developed European countries in the eCommerce context (i.e. France,

Germany, Italy and Spain). The aim is double: first of all, to find out if a

correspondence exists between most active countries in terms of provision of

literature contributions and most innovative ones for what concerns

implementation of fast eCommerce practices; second of all, to analyze

characteristics of services offered by different merchants within the same country

and then also from one country to another in order to find out if particular

similarities and/or discrepancies exist.

Additional topic to be tackled regards the commodity sectors to which

literature papers relate: as something has been found in literature about Grocery

and Informatics, but little or no information on other industries which can surely

present instead a relevant amount of real merchants (especially for what

concerns Clothing retailers which are much diffused at a worldwide level),

another objective of this research is the one of finding out which are the mostly

developed sectors in relation to eCommerce in general and then in particular to

fast logistics offers.

Lastly, the theoretical nature of the majority of papers analyzed implies a lack

of practical details of the services: if it was easy to find mathematical models for

optimization of vehicle routing inside urban traffic, little if no attention was paid

to technologies and transportation means employed in the process. Interesting

objective of the thesis instead is the one of going in depth in the study of delivery

services and describing the state-of-the-art of technologies implemented for the

provision of fast deliveries.

In conclusion, the objective of this thesis is to provide an updated picture of

most relevant cases of web retailers able to provide next day, same day or fast

deliveries up to now and analyze their features so as to build clusters and find out

similarities and differences among the offers. In this way not only the attention to

really fast services in their whole (focusing also on the first activities performed

just after order reception in addition to final delivery) will be brought to a higher

extent, but also the study will go in depth considering commodities sector,

geographical coverage and technological characteristics of different services

offered.

This whole thought can be summarized in the following research questions:


68

1) Which are the most relevant real examples of merchants operating in

the eCommerce at a worldwide level?


going beyond the next day from order reception? And how many

among them offer even faster options?

3) Which commonalities and/or differences exist among initiatives

belonging to different geographical areas?






services?

3.2 Methodology

In order to carry out this kind of analysis, as first thing the field of interest has

been defined: examples of real merchants actually operating in the eCommerce

channel and offering delivery options staying within the boundaries of twenty-

four hours for delivery to end customers.

Stated this, the research has been performed in a first moment by accessing

the digital edition of a guide on top 2013 e-retailers; it is called “Internet retailer –

portal to eCommerce intelligence” and it provides profiles, statistics, contacts and

analyses of the largest retailers in a certain geographical area. In particular, three

versions of this guide have been consulted, according to the different regions of

interest:

Asia 500 Guide Digital Edition 2013: providing information on the 500

largest retail web sites in Asia and the Pacific Rim, all ranked by annual

eCommerce sales;

Top 500 Guide Digital Edition 2013 (Europe): collecting business data,

profiles, rankings and analyses of Europe’s 500 largest retail web sites

ranked by annual eCommerce sales;

Top 500 Guide Digital Edition 2013: listing profiles, statistics and analyses

of America’s 500 largest retail web sites ranked by annual eCommerce

sales.

All the aforementioned guides, in addition to articles extensively describing

single cases of particular attention in the online channel scene, provide lists of

top eCommerce merchants for the three continents according to different

features: top merchants ranked by business category, also referred to as merchant

type (i.e. web only, consumer brand manufacturers, retail chains and catalog/call

centers), sites with the biggest growth in dollars in the year of analysis, fastest


69

growing e-retailers (still referring to development from the beginning to the end

of 2013) again by business category, top retailers ranked by sales’ volume (always

considering dollars as unit of measure) and others.

Among all of these rankings, the one which has been considered as the most

interesting according to this thesis’ objective provided a list of top web retailers

ranked by principal market, categorizing retail sites by country of belonging and

by principal market they serve. In this way, it was easy to focus just on those

countries representing a higher source of interest as came out from literature

review’s conclusions and to neglect all the cases from nations considered as

“minor” in the actual environment of fast home deliveries for online orders.

So, considering each guide alone:

from Asia 500 Guide Digital Edition 2013, China, India, Japan and South

Korea rankings were consulted;

for what concerns Top 500 Guide Digital Edition 2013 (Europe), the

analysis concentrated on United Kingdom, France, Germany, Italy and

Spain;

lastly, as regards Top 500 Guide Digital Edition 2013, the top 500 Guide

ranking was taken into consideration as it only refers to American e-

retailers and provides a classification on the basis of web sales’ volume,

monthly visits on the web site, customers’ conversion rate and average

order ticket.

For Asian and European countries, top 25 players in the ranking were

identified for further research (with the exception of Spain, which was a bit

poorer in terms of relevant online players and the ranking only involved 14

retailers); for US instead, the field was so bigger than the other countries that the

analysis was extended to the group of first 60 actors in the national ranking. So

for each nation, all websites belonging to the group of identified top merchants

were searched on the Internet and deeply studied, with a particular attention to

the process of orders’ fulfillment and final delivery to customers.

In order to carry out a complete analysis and to obtain comparable

information for further discussion and comparison, a database was created in

which some very specific features were collected from any initiative in any

country. The information collected, which describe deep down features of each

single initiative, were:

number in the national ranking: as previously stated, it goes from 1 to 25

for the majority of rankings, with the exception of Spain (in which it stops

to 14) and of US (ranging between 1 and 60); it allowed to have an idea of

their relevance inside their country of belonging in terms of sales;


70

merchant name: its proper name or the name of the online initiative in

case the company found in the ranking was the owner of different

businesses in different channels;

service provider name: filled in case the merchant provided explicit

information on a single logistics operator which it resorted to;

country: of belonging of the merchant, representing also its major market;

the alternative is among one of the nine countries already presented;

Dot Com/traditional: variable telling if the merchant was born as an

online retailer from scratch or if it was firstly a retailer operating in the

traditional sales’ channel and then enlarging its coverage by developing

also the web business;

pure player/multichannel: describing if the player operates only in the

eCommerce or if its business extends to many sales’ channels (almost in

every case, when a merchant is Dot Com it is also a pure player, while if it

is a traditional retailer it is multichannel too; so these two variables are in

some way strictly related)

desktop/mobile: it tells if the retailer has a website working for desktops

or if a mobile application has been developed in order to allow easy

shopping also from mobile devices;

commodity sector: sector in which the player operates, identifying in a

precise manner the type of products sold and moved during the service’

supply; we have Clothing, Cosmetics & Perfumery, General, Grocery,

Home & Furniture, Informatics & general electronics, Publishing sectors

Figure 3 - extract from database: merchants' number, name, service provider, country, market channels and web technology


71

and then other industries of minor presence among which we can find

Childcare, Drugs, Eyewear, Flowers, Music stores and Office supplies;

time for the delivery service: considering services which take more time

than what represents our interest area, we can find different hours’ ranges

surpassing the 24 hours for service provision (e.g. web retailers delivering

in between 48 and 96 hours, others in 48 hours, others between 24 and 72

hours or between 24 and 48 hours); moving instead towards faster

services, we first find merchants operating within the next day or the next

morning (if they are able to assure delivery within lunch time of the day

after order submission); then we have same day operators; in the end,

there is a cluster of websites offering deliveries which do not overcome 6

hours for the whole service provision (some declare of taking less than 6

hours for delivery but without specifying a fixed time, while some others

assure services operating in between 1 and 2 hours or even taking less than

1 hour to be performed). Among all the websites examined, we found also

merchants not offering express services at all (i.e. typically serving

customers in not less than 2 or 3 days and even more), that have been

classified as “non fast” and for which data collection activity has stopped at

this stage as they do not represent the focus of the research. In addition,

there were also websites which were impossible to access and about which

no information could be found even searching through the more

traditional web browsers, together with sites of retailers providing services

and not physical items (and so not arranging any picking and delivery

activity for their business’ nature) and finally websites shut down (it could

be because after some test time they closed the online channel resorting to

more traditional ones or because they went bankrupt); all these cases were

obviously excluded from the database;

additional time information: filled in case a website provided precise

information on the average delivery time or on the specific time taken by

each activity along the whole process;

hour limit in order to get on-time delivery: maximum hour for order

submission to be sure that the merchant will be able to provide goods by

the specific time explicated in the initiative (valid only in case of same day

services or at most in few next day options, but not always specified);


72

delivery timeframes: time windows in which operators are going to

perform home delivery (information found just in some websites);

cost type: the delivery service has usually an own cost which adds up to

the one of bought items; this cost can be fixed, variable, fixed but

becoming free once reached a certain expense for the goods (and the same

can happen in case of variable cost) or in few cases offered for free no

matter the expense’s amount;

criteria taken into consideration for variable cost determination (obviously

only in case the delivery service has a variable cost or variable but free by

reaching a certain shopping amount);

exact value of the delivery expense (expressed in the local currency and

only when the fee is fixed or at most variable but if its computation is

precisely explained on the site);

exact value of items’ expense to be reached in order to get free delivery

(only when expected and again expressed in the local currency);

minimum expense imposed for order submission (just in few cases);

Figure 4 - extract from database: retailers' sector, delivery time and other time features


73

price peculiarities: filled only if some peculiarities exist (e.g. a phone

number is provided and only by calling it the customer can know the exact

delivery expense or money-back guarantee is assured to customers if the

order is not delivered by the promised time window or if a maximum

number of articles which can be bought within one order exist, etc.);

international coverage: binomial variable which is “yes” if the service

concerned can be offered at an international level (i.e. in more than one

country) or “no” in the opposite case;

national coverage: “yes” if the delivery service in question has a national

geographical coverage (so every area of the country can be reached within

the same time window) or “no” contrarily;

local coverage: again binomial variable represented by a “yes” if the service

is only able to be provided in a limited local area (typically involving few

cities or even smaller); obviously this variable cannot be a “no”, otherwise

the service couldn’t exist;

coverage area: descriptive information exactly defining the local area of

service provision (only in case the service is not able to go beyond local

boundaries);

Figure 5 - extract from database: delivery cost and its characteristics


74

logistics type (internal/outsourcing/crowd-sourcing): variable identifying

if all the logistics activities are performed internally by the retailer itself

(or at most by a logistics spin-off appositely created for serving a specific

e-retailer and belonging to the same owning group) or if they are left to an

external operator found on the logistics market or lastly, if they are

performed according to the crowd-sourcing model (i.e. there is an external

entity which doesn’t operate as a physical distributor owning assets and

fleets and having couriers working under its direct dependence, but it only

works as an inter-change platform, collecting independent couriers who

work autonomously with their own transportation means and connecting

them with retailers in search of someone to perform home delivery);

preferred logistics operator: filled if a single external operator or a single

crowd-sourcing platform is exclusively resorted to by a web merchant;

service name: descriptive field reporting the name of the specific service

(only if this name exists; in general it is present when a retailer intends to

distinguish its express/fast service from the more standard one);

transportations means’ peculiarity: filled in case a web merchant (or in its

place the provider of the logistics service) resorts to a very specific type of

means only. We can find cases in which more traditional means as vans or

refrigerated vans only are adopted; then we have cases in which the

preferred vehicle utilized is the car. Moving to two-wheeled vehicles we

can find retailers employing indiscriminately bicycles and motorbikes,

while others provide their couriers exclusively with bicycles; there is also

the eco-friendly option in which couriers use electric bicycles for

performing final delivery. In the end moving to air transportation we have

Figure 6 - extract from database: geographic coverage and delivery area's details


75

cases in which the airplane is the only mean utilized or innovative

merchants putting in place delivery by drones;

click & collect in-store: binomial variable which is a “yes” in case the web

retailer offers items’ collection in store as an alternative to home delivery

and a “no” in the opposite case;

parcel locker’s pickup: “yes” if the merchant offers an alternative to

standard home delivery in which customers go and pickup their own stuff

from parcel lockers in which items have been previously positioned by

logistics operators; “no” if on the contrary this alternative doesn’t exist;

other collection point: again binomial variable represented by a “yes” if

another alternative to home delivery different from the two

aforementioned ones exist, “no” contrarily;

additional information on last-mile alternative: descriptive variable in

which all information regarding every delivery alternative offered by a

retailer (and explained in its website) are collected; it provides the

alternative description (in case it doesn’t involve in-store collection and/or

parcel locker) (e.g. convenience stores agreed upon collection service with

the retailer and having a terminal dedicated to collection of online orders;

or terminals belonging to a particular logistics operator allied with the

retailer such as UPS, Colissimo, Chronopost, Hermes points, etc.; or again

delivery in the store’s car park or directly inside vehicle’s trunk; etc.), the

hourly limit for order submission in order to get the alternative or the

specific time window taken by the alternative to be performed;

real-time tracking: binomial variable which is a “yes” in case a merchant

provides on its website (or at most on the one of its logistics operator) the

Figure 7 - extract from database: logistics service type, operator, name and vehicles used


76

opportunity of tracking order’s moves in real-time so as to have complete

and continuous visibility on its journey; it is a “no” if this option is not

available;

choice of the day/timeframe of delivery: it is a “yes” if customers have the

opportunity of choosing an exact day or an exact time window for order

reception and a “no” if they don’t have this opportunity;

timeframe duration: providing information on the length of the time

window which can be chosen by customers (of course available only when

the previous field reports a “yes” value and not even in any of these cases);

pre-delivery contacts: descriptive variable in which, if present (otherwise

the value is “no”), the moment in which customers have the opportunity of

being directly in contact with the courier carrying their order with

him/her is identified. It could be just a notification to confirm that an

order has been received or a notification of goods pickup in the warehouse

and then of shipment; or it can be the opportunity of speaking with the

courier before he/she starts its delivery tour in order to arrange all the

details for an efficient delivery; or it can even be the option of receiving,

together with delivery details, also courier’s name and image to make the

delivery process always easier;

information on pre-delivery contacts: it reports the nature of contacts with

logistics operators and the technological mean utilized for the

communication (e.g. call, e-mail, text or notification on the website and

details about the exact time in which this communication takes place); of

course this field is filled in only when a pre-delivery contact occurs;

Figure 8 - extract from database: last-mile alternatives and real-time tracking


77

useful websites: link/s of merchants’ websites or articles from which all the

previous information were collected.

After having collected all these information and filled in the database, most

interesting cases (i.e. the ones dealing with services not going beyond the next

day for being performed) were focused and their features were analyzed and

different database fields have been crossed so as to get insights about the actual

situation firstly by addressing one country at a time (single-variable analysis) and

then splitting also the analysis by commodity sector (double-variable analysis).

These numerous analyses got to some interesting conclusions about the state-of-

the-art of real companies’ delivery initiatives in fast eCommerce environment.

Figure 9 - extract from database: day/time choice and duration, contacts before delivery and useful websites


78

4. Empirical analysis

4.1 First empirical analysis: single-variable classifications

4.1.1 Global context

4.1.1.1 Merchants’ sample size

Table 100 - global merchants' quantity

Starting from the complete database with all the

websites object of the census, it is made of 275 web

retailers found in the national rankings; as previously

described, they are 25 for most countries, with the

exception of Spain with 14 cases censed and US with

61 rows because the first retailer is present two times

with very different business offers (it is Amazon,

which is considered one time for its Amazon Prime

Now business applied to the General sector and the

second time for Amazon Fresh Grocery service).

However among these censed merchants we can observe a portion of retailers out

of any interest; indeed, we can find that the traditional French retailer Group 3si,

operating in the General sector, which had enlarged its business by adding the

development in the online channel, after a little time has not found economic

convenience in pursuing a multichannel strategy and have decided to close its

eCommerce website. Then five merchants belonging to the rankings do not sell

physical items and so they do not have to perform any logistics activity for

customers’ order fulfillment: they are three Informatics companies selling

software solutions (the American Symantec and Micros and the South Korean

Ahnlab), still an Informatics online operator that acts just as a collector of

information from different merchants (the Chinese Sc4888.com) and the German

retailer Arcandor, which is classified in the Others industry because it sells

obligations. To follow, we can find six traditional multichannel retailers which

are business-to-business operators and so their logistics processes are completely

different from the ones of players having to perform home deliveries to final

single customers; they are five coming from US ranking (Office Max, W.W.

Granger, MSC Industrial Supply belonging to Others category and CDW

Corporation, PC Connection operating in the Informatics and general electronics

sector) and the German grocer Metro. Going on, 18 of the merchants included in

the 2013 rankings submitted to census have gone bankrupt and up to now have

closed their business: no cases of this type of players can be found in the US and

just one in the UK (the Dot Com merchant Rakuten, previously operating in the

Country Total

China 25 France 25 Germany 25 India 25 Italy 25 Japan 25 South Korea 25 Spain 14 UK 25 USA 61

Total 275


79

General industry and staying in fourteenth position in the national ranking);

more cases can be found in the rest of Europe: we can list jewelry French

traditional retailer Bijoudumois (thirteenth place in its national ranking), Spanish

informatics traditional merchant Bonacuista (fourteenth position) and three

cases of informatics Italian operators (all staying in relatively high place of the

Italian ranking, between fifth and thirteenth), multichannel Eldo Megastore

which have faced bankruptcy in 2014 and the two Dot Com actors YouBuy.it and

Bow (the last one carried into ePrice business through acquisition); however, the

most relevant portion of shut down businesses can be found in the Asian

countries: just one case can be found in Japan (Ec-current, previously occupying

the fifth position in the ranking in terms of sales’ volumes) and in South Korea

(Vanilla Mint clothes’ retailer in 18th position); three are instead the Chinese merchants having experienced business’ closure (general 360Mart in eight place, again general Mailebei in 13th place and 51sheyuan that was located at the end of the ranking); lastly, the highest number has been faced in India with seven merchants shutting down their businesses (Buytheprice, 100bestbuy, Zovi, Inkfruit, Seventy MM, Indiaplaza, Be Stylish that occupied places between the tenth and the twenty-third in 2013 ranking).

Table 101 - global merchants'excluded non-interesting cases

Overall, they are 30 websites which for their diverse reasons do not have the

prerequisites for being included in the database, so the real number of merchants

addresses in the coming classifications is 245.

4.1.1.2 Breakdown by channel, web technology and commodity sector

Dot Com/traditional pure player/multichannel Total

Dot Com pure player 94

traditional multichannel 151

Total 245 Table 102 - global merchants' market channel

Moving onto the next variable, we can see that 94 merchants are Dot Com,

while a larger stake is composed by traditional retailers (151); exactly the same

numbers come out from the categorization of cases into pure players or

multichannel, implying that every company born as a Dot Com one keeps the

online business alone, while traditional retailers expanded to eCommerce are by

definition multichannel as they keep also the initial ones. This analysis means

that even if a big portion of actors are born as online players and have built their

Country Total

China 21 France 23 Germany 23 India 18 Italy 22 Japan 24 South Korea 23 Spain 13 UK 24 USA 54

Total 245


80

business from scratch by jumping into the eCommerce channel, the majority was

born in the past as a retailer in more traditional channels and then has enlarged

the business by adding the development of the web market. Starting as a pure

web player implies the opportunity of developing an ad-hoc structure for

fulfillment of online orders, keeping low initial investments but a widespread

diffusion in the market considering the easiness of being known through the

Internet; this business model facilitates continuous improvement and inclination

to innovate the service and pursue most recent market trends. On the contrary,

companies in place for years as traditional ones, for sure have a stronger and

more steady presence in the environment as they enter also the online channel

(reducing the risk of being cannibalized by other bigger actors and of failure), but

they have to manage completely different models in the same time, often

compromising their attitude towards active management of eCommerce (in fact,

they often outsource the whole business or at least the logistics activities to

external operators) and internal development of innovative practices.

The following field is the one analyzing the type of technology supporting the

merchant’s website: 85 retailers provide their websites through connection from

desktops, while 160 have made available to customers an application accessible

from all mobile devices. The mobile version for sure makes easier the website’s

consultation at any time and increases customers’ willingness to submit orders;

but additionally, provides a stronger connection between the retailer (or its

courier if it is external) and the final consumer: in fact, mobile application will be

checked with more frequency than website on desktops, making the

communication flow more efficient and faster for orders’ tracking and

notifications on its status, reducing also the risk of having failed deliveries. In this

light, mobile access is a good tool for making fast delivery services spreading and

improving.

desktop/mobile Total

desktop 85

mobile 160

Total 245

Table 103 - global merchants' web technology


81

Going to the commodity

sector, we can observe that the

biggest portion of cases belongs to

the Clothing industry (61 out of

the 245 options under census,

corresponding to 25 percent),

followed by a similar quantity of

merchants coming from General

sector (i.e. retailers selling in the

same time a large amount of very

different items) (49 examples, corresponding to 20

percent). 48 (i.e. 19 percent of the total) are the cases belonging to Informatics &

general electronics sector. After this, there is a big jump in terms of size, passing

to Grocery sector which comprises 20 merchants (corresponding to 8 percent). It

is followed by Publishing industry, made of 15 cases (i.e. 6 percent) and then

Cosmetics & Perfumery with 10 examples (i.e. 4 percent). In closure, we can find 4

merchants coming from the Home and Furniture sector. A relevant portion of

cases (38, corresponding to 16 percent) are in the Others sector, collecting a vast

quantity of industries which alone counts a little, so not so many useful

information can be extrapolated from this group; however among theme we can

find Childcare, Drugs, Eyewear, Flowers, Music stores and Office supplies. From

this analysis we can find out that more developed industries in the online

channel are Clothing and Informatics, the one having developed first and having

gained high market shares until now. Another very relevant sector is General one,

comprising big merchants who have not specified their business by selling a

determined type of items, but instead have found their strength and their

strategy in enlarging as much as possible the offer. Even if separated by a relevant

amount of cases, an important place is occupied also by Grocery and Publishing

sectors, which are not as affirmed as Clothing and Informatics but are gaining

share in the eCommerce market.

4.1.1.3 Split by delivery speed

The following database’s field is the delivery time and many different values

can be found. In increasing order of time needed for order fulfillment, we have

one only merchant able to carry out the whole process in less than one hour: it is

the Japanese Dot Com retailer Rakuten with its express service “Rakubin”, whose

average service time is 60 minutes but in many cases is also able of offering faster

deliveries until a minimum amount of time required of 20 minutes. Then we can

find a group of seven retailers whose delivery services stay in the range of one-

two hours in order to be carried out: the fastest is the French merchant Carrefour

Commodity sector Total

Home & Furniture 4

Cosmetics & Perfumery 10

Publishing 15

Grocery 20

Others 38

Informatics & general electronics 48

General 49

Clothing 61

Total 245

Table 104 - global merchants' sector


82

which performs a process lasting one hour overall and called “Carrefour Now”. A

bit slower (always referring to average timings), the following five examples of

retailers whose order fulfillment processes stay between one and two hours in

order to be performed: the US Amazon with its Prime Now and Air options is

able to serve its customers by

overcoming a little the one hour

timeframe (even if the Air alternative

can reach in some situations minimums

of 30 minutes); second, the French

informatics retailer Darty declares of

being able to reach its final consumers

in an average time of exactly 78 minutes

by exploiting the crowd-sourcing

logistics model offered by Colisweb; the

third case is the one of Spanish El Corte Inglès, delivering its general items in

between one and two hours (service called “Click & Express”) or offering the

opportunity of selecting the exact delivery time but enlarging the available time

window to all the same day of order issuing; as fourth we find UK grocer

Sainsbury that takes advantage of an internally owned application called Chop

Chop in order to better manage couriers’ flows and to provide services always

lasting less than two hours; lastly, but not in terms of importance, Indian

informatics retailer The Mobile Store offers a pilot service called FED (“Fastest

Express Delivery”) not going beyond a two hours time window. Closing the 1-2h

cluster, just one retailer, the German Conrad that operates in the Informatics and

general electronics industry, affirms of being able to serve its customers in two

hours thanks to the directly owned branch Tiramizoo which has been

deliberately built up for accomplishing the retailer’s logistics activities.

After this, there are three players who are not able to offer services staying within

a so limited time window, but can however locate themselves in a range that do

not overcome six hours and so, together with all the previously mentioned

examples, can be considered to perform “fast” services that distinguish

themselves from the ones offering same day deliveries. All these three merchants

belong to the Informatics and general electronics industry and they are: the

American company Apple, that offers a delivery service with an average time of

four hours to be carried out in San Francisco and New York exploiting Postmates’

crowd-sourcing logistics platform (or considers as alternative the opportunity of

choosing the exact delivery time, but accepting a little slower service that in any

case stays beyond the same day limit); Indian Univercell, which has developed

internally a pilot project for delivering items in four hours in Chennai; lastly, the

Chinese company Jingdong with its Dot Com business 360Buy.com that with its

internal logistics service is able to perform delivery within three hours in six cities

Delivery time Total

< 1h 1

1-2h 7

< 6h 3

same day 51

next morning 5

next day 45

not fast 133

Total 245

Table 105 - global merchants' delivery time


83

(while in the rest of the country offers an Overnight service in which issuing the

order by 15:00, customers can receive their products in a three hour time slot

between 19:00 and 22:00). We can so observe that considering all these

aforementioned offers lasting less than six hours, “fast” delivery initiatives are in

total 11 out of the overall 245 cases under census, which represents a very small

portion of all the examined sample (corresponding to a 4 percent only).

Moving to the next value, we can find a considerably more populated group of

examples offering same day services: they are 51, representing the 21 percent of

the total; 16 of them come from US, 6 from UK, 9 from the rest of European

countries analyzed (three from France, two from Germany, two Italian and two

Spanish respectively). However, the biggest portion is represented by Asian cases:

in fact they are 20 overall and they are subdivided among 8 Japanese, 6 Indian, 3

Chinese and 3 South Korean initiatives. All these same day options will be deeply

described in the following analyses split by country.

To follow, we can observe a comparable group of initiatives (50 overall) in

which the order is delivered to customers within the day after order reception;

this group is made of five next morning cases (i.e. the items reach consumers’

home not after 13:00 of the following day with respect to order issuing) and 45

examples of next day deliveries. For what concerns the next morning options,

three of them come from the United Kingdom: there is the merchant of general

items John Lewis providing ordered products between 7:30 and 10:30 if the order

has been received by 20:00 of the preceding day, then the two informatics

retailers Misco and the Dot Com BT Shop (owned by Dabs company) delivering

items by 12:00 of the following day if the order has been received within late

afternoon (within 17:30 for Misco, 18:00 in the case of BT Shop); the other two

initiatives come from French operators: general retailer Rue du Commerce

reaches its customers in the morning in a time window included between 10:00

and 13:00, while informatics merchant LDLC is able to deliver products by 10:00

or by 13:00 according to the city in which it has to operate, but both players need

to have orders received in the first part of afternoon for assuring such a delivery

service (by 14:00 for both). Moving to the 45 next day initiatives, 10 of them

belong to US companies, 11 to British players, 15 to the rest of European

nationalities examined (6 for both France and Germany, 2 in Spain and just one

case from Italy) and 9 options coming from Asian business (5 from Japan, 2 from

South Korea and only one initiative in both India and China). Also these cases

will be more comprehensively tackled in the following split by country.

All cases that belong to categories presented before (i.e. fast, same day and

next day deliveries), which are a total of 112, represent the body of interest of the

thesis because of the limited timings in which these services are performed, so

they are object of further study and they are the only cases categorized and

described in a more deepened manner in the analyses to come.


84

For what concerns the remaining censed websites, that are 133 and correspond

to 54 percent of the overall 245, they do not represent interesting cases because

they perform delivery services which can be generically categorized as “not fast”.

26 of them belong to American ranking, while in the UK classification we can

find only 3 cases; 51 then are located in all the other European countries (10 from

France, 14 from Germany, 19 from Italy and 9 in Spain) and 53 come from Asia (10

in Japan, 18 in South Korea, 16 in China and 9 in India). Their delivery timings are

quite different, never going below one day and reaching seven, ten or even more

days in some cases; sometimes the delivery activity alone is quite fast but the

activities tacking most of the time or for what no specific information is available

are order picking and packing, while in some cases the opposite case occurs and

the activity lasting most of the time (often many days) is the physical distribution

of the items to final customers. Anyway, the examples are so various and copious

that they will be better explained in the coming analysis that is divided for each

country alone so as to go more in depth with the situation’s details.

4.1.1.4 Service providers

Before moving to the next

paragraph that describes in a more

complete way all the information

collected and organized in the database

through the separation of rankings by

single country, we can observe that

among the overall 245 eCommerce

merchants, just 26 declare of having a

single service provider to whom they

uniquely resort for the final delivery

activities. Among these known

providers, the most utilized service is

the one offered by Deliv (an US crowd-

sourced same day delivery startup,

which bridges the last-mile gap

between multichannel retailers and

their customers) which acts for 6

different merchants; then other most relevant cases are offered still in US by

Amazon (which has developed its own logistics for its business), in Germany by

Hermes (logistics branch of German Otto Group company, opened up in order

not only to serve all the sub-companies of the group in all the different channels,

Service provider Total

Cainiao 1

Chop Chop app 1

Colisweb 1

Deliv/Postmates 1

DHL 1

DPD 1

Dynamex 1

Ekart 1

Google 1

LaPoste 1

NBB courier 1

Tiramizoo 1

Yamato Transport 1

UberRush 2

Amazon 2

Hermes 2

Postmates 2

Deliv 5

Total 26

Table 106 - global merchants' service providers


85

but also for acting, to all intents and purposes, as a logistics operator for other

retailers) and again in US by Postmates (same crowd-sourcing nature of Deliv).

We can observe that no single format of service provider exists among most

ground-breaking merchants; but big groups having a very large market share

(number 1 in the ranking both for American Amazon and for German Otto

Group) have found out that the best and easiest way to innovate their service is

the one of building up their own logistics business; this huge investment is made

economically viable thanks to the dimension of company’s market share (and so

sales’ volume) or at least thanks to the opportunity of outsourcing the service to

other merchants, amortizing in this way fixed costs. Different is instead the case

of smaller retailers in the market (8 US companies occupying places between the

third and the fifty-sixth in the ranking and resorting to Deliv and/or Postmates’

services): for them such an investment would be too risky and so they resort to

innovative startups able to stay competitive in the actual scenario thanks to their

logistics models very much “lighter” in terms of assets owned.

4.1.2 United States

Starting from the most copious country, as previously stated the first 60

merchants of American ranking have been submitted to census, an higher

population with respect to the other countries to come; this choice is due to the

fact that the ranking was much more extended than the other ones, as

eCommerce has seen its strongest growth in this territory and the geographic

coverage of United States is so ample with respect to others that of course the

number of relevant initiatives has to be much higher. Moreover, the cases have

become 61 as the first merchant in the ranking, the giant Amazon, is counted two

times due to its development in two diverse industries with such a differentiated

service. Having however excluded two merchants not selling physical product

and so not arranging any handling and/or distribution activities (software’s

sellers Symantec and Micros), together with five business-to-business retailers

not performing home delivery (Office Max, CDW Corporation, W. W. Granger,

MSC Industrial Supply and PC Connection), the size of the studied sample is

equal to 54 merchants.





Total 54 Table 107 - US merchants' market channel


86

We can observe that only 22 percent of the cases (12 out of the total 54) is

represented by pure players Dot Com, while the large majority is composed by

traditional retailers who have chosen to put in place a multichannel strategy. This

means that in this country not so many are the new players explicitly born for

working in the online channel alone which have in the same time gained a

relevant portion of the market; most of actors found in the first positions of the

ranking by sales’ volume had already affirmed themselves in the traditional

business and then have decided to enlarge the business by adding up

eCommerce, but with a stable economical profile provided by years of existence

and of sales behind.

Then, by looking at the technologic

side, we can see that 13 merchants (i.e.

almost the 24 percent of the total) have

only a website which customers can

access to in order to issue their orders; the

biggest part of retailers (76 percent) have developed an application and provide

so their customers with a mobile access, in order to increase the frequency with

whom final consumers check retailers’ offer, made available by an easier

connection to the site from almost everywhere.

For what regards the

commodity sector, a big part (18

out of 54, corresponding to almost

33 percent) of players belong to

Others category, made of a

collection of very different minor

sectors which is difficult to

analyze due to the different nature

of actors inside of it. Moving so to

more uniform sectors within themselves, the most flourishing one is Clothing,

including 14 merchants (i.e. 26 percent), immediately followed by Informatics

and general electronics industry with its 8 cases (i.e. 15 percent). Separated in

terms of weight inside the ranking but still counting a significant number of

initiatives, we can then find General sector (made of 5 retailers, corresponding to

9 percent of the total), Grocery (4 cases, i.e. almost 7 percent) and also Cosmetics

and Perfumery (composed by 3 merchants, accounting for the 5 percent). In the

back end of the classification, we have just one player from Home and Furniture

and Publishing industries. From this database’s field we can infer that Clothing

and Informatics sectors are always the more developed ones in terms of online

initiatives by looking at their share in the market; but in addition to them, some

Desktop/mobile Total

Desktop 13

Mobile 41

Total 54

Table 108 - US merchants' web technology


Others 18

Clothing 14


General 5

Grocery 4


Home & Furniture 1

Publishing 1

Total 54

Table 109 - US merchants' sector


87

other industries are gaining an always more relevant position in the eCommerce

channel, especially General and Grocery and in the US also Cosmetics is

enlarging its footprint in the online environment.


The next information collected deals

with the time needed to carry out the

delivery process. We can observe that

we have just two cases which can be

classified as fast, corresponding

together only to the 4 percent of the

overall censed initiatives. In particular,

the first example is the one of Amazon with

its Prime Now service and the pilot project Air; it is a Dot Com giant (in fact it

occupies the first position in the ranking in terms of sales’ volume) operating in

the General sector that with its own logistics is able to reach customers living in

28 US cities in between one and two hours and also a very shorter time (on

average 30 minutes) in the case of its Air project under test in which drones are

utilized to perform final delivery. The second case instead regards the informatics

traditional multichannel player Apple, staying at the highest steps of the podium

too (third place in the sales’ ranking); contrarily to Amazon case, Apple hasn’t

developed its own logistics service but has instead resorted to the crowd-sourcing

platform offered by Postmates, employing its independent drivers with their own

vehicles (bikes, motorbikes or cars) in order to serve its customers located in New

York and San Francisco in four hours or in alternative accepting a longer delivery

time window (in any case staying within the same day of order issuing), but with

the possibility of choosing the exact delivery moment and be sure of not missing

the delivery in this way. So we can observe that, for putting in place a fast option,

the Dot Com pure player has decided to invest for having its own logistics

infrastructure and this can be comprehensible since its only business is the online

one and a completely dedicated strategy implying also large investments can be

explained by the size of the web business for this kind of company; on the other

hand, the traditional retailer, even if with a solid economic structure, has decided

not to make such an investment for the improvement of its online channel (as it

is not the most flourishing channel of the company probably) and has resorted to

a much more flexible strategy, characterized by the variable costs of single

couriers’ service and little fixed investments.

Moving then to same day operators, they account for the 30 percent, which

constitutes a relevant portion of the total. Only three of them are Dot Com pure

players (Amazon again with its grocery business Amazon Fresh, Etsy and 1-800-

Delivery time Total

1-2h 1

< 6h 1

same day 16

next day 10

not fast 26

Total 54

Table 110 - US merchants' delivery time


88

Flowers.com), while all the others are traditional retailers having added the

online channel to their offer. In addition to the four cases belonging to Others

sector, Clothing industry plays a leading role also in this group with 6 merchants,

followed by Grocery sector with 3 merchants; Informatics instead looses presence

having only one case. All these cases have a maximum hour by which the order

has to be issued in order to have same day delivery performed with the certainty

of not being late and this hour usually ranges between 12:00 and 15:00, with just

the exception of Etsy, a website in which individuals can sign up and sell

handmade and/or vintage objects, that can accept orders to be received until

19:00. For what concerns the timings of delivery, some websites (not all) specify a

time window within which the delivery is performed; in few cases it doesn’t go

beyond 19:00, while in many cases it can be carried out also until 20:00 or 21:00 or

even until 22:00 at night by distinguishing different delivery windows within the

day (for example, between 9:00 and 13:00 or between 13:00 and 17:00 and then the

last option between 18:00 and 22:00).

We have then 10 cases, corresponding to 18 percent, of next day retailers. They

are all traditional multichannel operators and they belong to pretty much all the

different sectors (three of them belong to Clothing industry, three to Others, two

to Cosmetics sector and then just one to Informatics and Grocery). They almost

in every case have a hourly limit for order issuing too, which in most situations is

later than ones of same day merchants, ranging between 15:00 and 22:00, with the

exception of two players (cosmetics’ seller Avon and clothes’ retail J Crew) who

require to receive orders by 12:30 and 12:00 respectively for assuring next day

delivery. While for what concerns delivery time windows, almost no information

has been found.

Collecting so together fast, same day and next day initiatives, they are a total

of 28, representing a bit more than a half of cases taken from the ranking (exactly

the 52 percent). In addition to these cases of interest, we can find 26 players

(corresponding to a significant 48 percent of the total) offering delivery services

which can be all categorized as “not fast”. Eight of these actors are Dot Com pure

players while the remaining 17 are traditional retailers operating also in the

online channel; most of them belong to the Others sector, but we also have

relevant participation on merchants from Clothing sector (5), Informatics (5) and

General (4). In six of these cases the critical activity regards picking and packing

of orders in order to be ready for distribution: in fact in all these cases

(informatics merchant Systemax, clothing Fanatics, others’ retailers Lowe’s, The

Home Depot and GameStop and home & furniture merchant Wayfair) next day

delivery could be performed thanks to express services of outsourcing logistics

operators, but then times for order preparation have to added in order to obtain

the overall order fulfillment lead time and they are not specified or limited in any

way. For other 8 players instead the critical activity is final delivery, which cannot


89

be performed before two of three days after order issuing (even four days in some

cases). For the remaining 12 initiatives no additional information regarding the

long timings have been found; in any case we can observe that quite a balanced

situation comes out between criticalities in handling portion of the process and

criticalities in the delivery part.

4.1.2.3 In-depth analysis of logistics providers, related cost, coverage and type

Looking then at the

communication of a specific

service provider, we can see that

14 merchants state that they have

a trusted service provider whom

they resort to exclusively. Among

these known cases, the mostly

utilized service is the one of Deliv,

a same day delivery startup that

has implemented a crowd-sourcing model and controls a platform in which

retailers’ demand for logistics providers is matched with the offer of independent

single couriers who connect themselves to the platform when they are available

and carry out final home deliveries with their own transportation means (mostly

their car) in a lot of cities spread all over the national territory; in this way the

logistics structure is completely flexible and no actor has to make investments in

logistics infrastructures, vehicles’ fleets and so on. Another crowd-sourcing

service quite diffused is the of Postmates, which again covers many different US

cities, but differentiates itself from Deliv for what concerns transportation means

employed by couriers: in fact, cars are still utilized, but in many cases they leave

floor to the usage of motorbikes or even bicycles in order to gain some time by

nimbly crossing urban traffic. The third most employed service is UberRush,

again a crowd-sourcing platform more similar to Postmates in terms of means

utilized: in fact independent couriers can autonomously decide to use their

bicycle, motorcycle, car or van to perform delivery. Contrarily, two are the cases

of the logistics service directly developed and owned by Amazon for serving its

different businesses and which is characterized by different options (as we will

see later); then one case of merchant resorting to Google Express, a logistics

service developed by Google in order to act as provider for other retailers that

want to outsource their activities. Lastly, we can find the case of Dynamex, which

is a Texan logistics provider offering its services to Target grocer in Boston and

Minneapolis, involving the usage of refrigerated vehicles due to the nature of

retailer’s industry. We can so observe that when a unique trusted service provider


Amazon 2

Deliv 5

Deliv/Postmates 1

Dynamex 1

Google 1

Postmates 2

UberRush 2

Total 14 Table 111 - US merchants' service providers


90

is chosen by an online merchant, in few cases it is a traditional logistics company;

most companies that decide to strongly link themselves to single providers, if

they are not able to develop their own logistics service (as the case of Amazon),

choose to resort to innovative crowd-sourcing platforms which allow agile and

flexible services at very low fixed costs.

For what concerns the next variables in the database, they analyze more in

depth the kind of service offered, so from now on the not fast initiatives will be

excluded from further investigation.

Focusing so on the 28

examples staying below 24 hours,

12 of them impose a fixed cost of

delivery regardless the expense for

bought products and the distance

to be travelled; most of these cases

are same day ones (8 out of 12)

and then we have three next day merchants

and the one staying below 6 hours. The interval of values in which this fixed

amount ranges is quite large, moving from a minimum of 5$ in the case of drugs’

retailer Walgreen and clothes’ seller Foot Locker (both resorting to Deliv for their

deliveries) to a maximum of more than 20$ for clothing merchants that sell items

of usually higher unitary cost with respect to others (22$ in the case of Gap, 25$

for J Crew and 26$ for Victoria’s Secret). We have also the case of Avon which

imposes a quite high fixed fee of 20,90$ but allows customers to have delivery for

free if their expense overcomes a threshold of 40$. On the contrary, 10 retailers

apply a variable fee for delivery which usually depends on the amount paid for

bought items or on the dimension and weight of the package to be delivered or

on the distance covered by couriers. Among these cases, no merchants belonging

to Clothing industry can be found, while many come from Others group and also

Grocery and Informatics; half of them performs next day deliveries, but there are

also four cases of same day merchants and Amazon case. The fee in most options

stays between 10$ and 20$ (with the exception of HP that applies higher fees

between 30$ and 80$ which are in line with the higher monetary value of

products delivered, since the total expense may reach even 4000$), while it is

lower for Amazon that applies a 7,99$ fee if customers want to receive their order

in one hour or give it for free if they accept to have the delivery window enlarged

to two hours. There are also the four cases of the grocer Amazon Fresh, the

publishing retailer Barnes&Nobles, the clothes’ seller Neiman Marcus and Office

Depot applying a variable fee that however disappears in case the expense

reaches a certain threshold (between 25$ and 50$). Finally, Gilt clothing merchant

offers a same day delivery with no fee applied. We can observe that for next day

Cost Total

fixed 12

variable 10

variable + free beyond threshold 4

fixed + free beyond threshold 1

free 1

Total 28 Table 112 - US merchants' delivery cost


91

deliveries a variable fee is applied that depends on different criteria related to the

particular features of the delivery journey, while for same day services the

application of a higher fixed fee is often needed in order to pay back costs of

service provision.

Analyzing then the geographical

coverage of the service, we can observe

that the majority of initiatives (18 out of

28) cannot reach the whole national

territory and are implemented only at

local level. These initiatives, as could be imagined, comprehend the two fast

cases, 15 out of the 16 same day options and just one next day delivery merchant.

In some cases the areas in which the service can be offered involve many US cities

or many US zip codes (e.g. 28 cities reached by fast Amazon Prime Now service;

many zip codes covered by Walmart grocer and Clothing merchants Macy’s and

Victoria’s Secret; more than five of the major American cities served by Amazon

Fresh, informatics Best Buy, Kohl’s Corporation and Foot Locker with their same

day options). However, seven are the cases in which the service is implemented

in one, two or maximum three centers (same day services by Staples, Target,

Barnes&Nobles, Nordstrom, Walgreen and Neiman Marcus and four hours

delivery performed by Apple) or even only some zip codes within the city of New

York (same day options by Saks, Etsy and Gilt). We can observe that merchants at

the highest places of the ranking (considering market share) are able to cover

wider territories with their fast services than retailers in the back. Regarding

instead the other 10 initiatives, they are performed in the whole country but of

course they mainly regard next day delivery options, with the exception of 1-800-

Flowers.com same day initiative that probably has to be performed within the

day due to the perishable nature of the products sold.

Going to the variable that identifies

the typology of logistics provider

performing necessary activities for

orders’ arrival at customers’ doorstep, 11

merchants (corresponding to 39

percent of the total) resort to outsourcing to

external providers specialized in logistics activities; most of these are next day

initiatives (8 out of 11), while just three are the cases of same day deliveries

outsourced. For what concerns next day cases, only three declare of relying on a

preferential traditional courier (FedEx for HP, USPS for Musician’s friend and

UPS for J Crew), while in all the other initiatives different couriers are chosen

indistinctively; instead same day merchants turn to more innovative providers of

National coverage Total

No 18

Yes 10

Total 28 Table 113 - US merchants' geographic coverage

Logistics type Total

outsourcing 11

crowd-sourcing 11

internal 6

Total 28

Table 114 - US merchants' logistics type


92

specifically developed express services (e.g. grocer Target resorts to Dynamex

Rush Delivery option, while Barnes&Nobles relies on Google Express). The exact

same percentage is made of merchants turning to crowd-sourcing platforms for

deliveries; almost all among these cases relate with same day deliveries (10 out of

11), with the addition of Apple’s fast option. The providers of crowd-sourcing

models, in decreasing order of presence in the ranking, are Deliv, Postmates and

UberRush; as previously introduced, they collect couriers that autonomously

decide to candidate themselves for a certain delivery and use their personal

means of transport; as these couriers are independent, they (and their means) do

not represent a fixed cost for anyone but are only paid a variable price for each

delivery they perform. In the end, six are the cases of merchants having built up

their own logistics infrastructure for performing always faster and more

personalized delivery services; half of these cases are the ones of grocers (Amazon

Fresh, Walmart and Peapod) that need a personalized fleet of refrigerated

vehicles due to the perishability of transported goods; in addition, there are cases

of big players in the market (Amazon Prime Now, Staples and Office Depot) that

have found economically viable and strategically convenient the choice of

investing in a personal infrastructure.

4.1.2.4 Logistics technologies and alternatives to last-mile delivery

Moving on, 17 merchants have

declared of preferably utilizing

one or more specific means of

transport. In 7 cases cars are used

and mostly own personal cars, as

almost all of these (6 out of 7) are

same day initiatives relying on

crowd-sourcing models; the

seventh is represented by an outsourced operator preferably using cars for same

day deliveries (Google Express). Then in other four same day crowd-sourcing

cases couriers are left free of choosing among their own bikes or motorbikes

preferably (even if the opportunity of using their own car is still available). Then

two are the cases of van only employment and other two of refrigerated vans (it is

the case of grocers) all for initiatives in which logistics activities are performed

internally by merchants. One is the crowd-sourcing case in which only bikes are

employed in a preferable way. Finally, we can find Amazon Air initiative in which

more innovative technologies as drones are employed for performing the fastest

service among the ones under examination. If internal logistics allows merchants

to have complete control on the whole process (including transportation means

used and conditions of items’ journey on them) and crowd-sourced logistics often

Transportation means Total

car 7

bicycle/motorbike 4

van 2

refrigerated van 2

bicycle 1

drones 1

Total 17 Table 115 - US merchants' transportation means


93

involves the utilization of faster means for navigating into traffic conditions

(especially bikes and motorbikes), outsourcing logistics in most of the cases does

not allow to have visibility on the transportation means.

By looking at the last-mile alternatives offered, we can observe that 11

merchants offer to their customers the option of issuing the order online and

collecting it in store in order to reduce together delivery costs for the merchant

and the probability of having unattended home deliveries. Most of the in-store

pickups can be performed the same day in which the order is made or at most the

next day (thing that represents a valid alternative to fast home deliveries), with

also some cases of even faster pickups (few hours after the order) but just for

items already available in store; just a couple of merchants make orders ready to

be picked up only after some days (usually between three and seven days). No

other alternatives can be found in the US, nor employment of parcel lockers’

systems, neither of other collection points.

4.1.2.5 Additional services: real-time tracking, date/time choice and pre-delivery contacts

More than a half of initiatives

(corresponding to 61 percent) provide

customers the chance of tracking in real-time

their order during its journey, in order to have more visibility on the exact

timings and reduce the probability of incurring in failed deliveries, more or less

knowing when the order is close to home.

Only five merchants give the opportunity

to final customers of choosing the exact time

window for order reception. This timeframe

can be of two, three or at most four hours and almost half of these initiatives are

related to grocery business, due to the higher inconvenience of incurring in

unattended home deliveries for the perishables transported.

Click&collect in store Parcel locker Other collection points Total

No No No 17

Yes No No 11

Total 28 Table 116 - US merchants' last-mile alternatives

Real-time tracking Total

No 11

Yes 17

Total 28 Table 117 - US merchants' tracking systems

Time window choice Total

No 23

Yes 5

Total 28

Table 118 - US merchants' time choice


94

In the end, 13 merchants (corresponding to 46 percent) declare of having some

kind of contact with final customers before the delivery takes place, always with

the aim of increasing visibility and reducing delivery failure. Six are the cases of

same day options offered by crowd-sourcing platform Deliv that, through an

email and the app, provide customers with name and picture of the courier to

whom their order has been assigned and all the relevant information about

delivery. In two cases details

are arranged before the

delivery is performed

through a phone call or a

text directly exchanged with

the courier. Then we have

some cases in which

notifications at different

stages of the delivery process are provided to customers through email: in one

case just the order confirmation is noted, while in two cases also delivery is

signaled and in other two cases a note for shipment of the package is sent too;

most of these cases relate to traditional logistics providers to whom retailers

resort in a outsourcing strategy.

4.1.3 United Kingdom

The second country addressed is the United Kingdom, for which the first 25

merchants of the national ranking have been submitted to census on most

traditional web browsers. It is analyzed separately from the rest of European

countries investigated because it accounts a much higher number of significant

initiatives with respect to them. Only one merchant belonging to the ranking

(the general retailer Rakuten) has been excluded from the database since he has

shut down its business in the UK; so the cases object of following analyses will be

24.


Pre-delivery contacts Total

courier's name, picture and delivery info 6

details arranged before delivery 2

confirmation and delivery note 2

confirmation, shipment & delivery note 2

confirmation note 1

Total 13

Table 119 - US merchants' contacts




Total 24 Table 120 - UK retailers' market channel


95

By looking at the market strategy, 6 out of the 24 retailers (corresponding to

25 percent) are Dot Com pure players and they all offer mobile access to

customers: three of them belong to Clothing industry, two come from

Informatics sector and then one case in Grocery and one other in General

industry. On the contrary, the remaining 72 percent is made of traditional

retailers which have added the online channel to their business; the share of

retailers belonging to Clothing industries is lower in this group (three cases),

equal to the one of grocers and merchants operating in the general sector, while

four are the merchants belonging to Informatics and general electronics and

Others sectors. Also in UK, more numerous are the cases of players not

exclusively born for the web channel but that have just enlarged their already

consolidated business (in fact, eight of the top ten players in terms of sales’

volumes belong to this multichannel category).

For what concerns technological

tools for connection with customers,

just 4 out of the 24 examined

merchants (representing the 17 percent)

have only a desktop access to their

website, while in the 83 percent of cases (20 examples) a mobile application has

been developed for improving and increasing the share of customers’ contact

with retailers’ offer. The percentage of mobile initiatives is higher in the UK than

in the US, implying a higher attention at keeping high frequency of contacts from

consumers side.

Analyzing the commodity

sector, we can find a quite

equilibrated presence of all

industries, from Clothing and

Informatics (6 cases for both,

corresponding to a 25 percent

each) to General, Grocery and

Other industries (counting for an almost 17

percent each). This means that all main sectors are quite well developed and

present in the list of most relevant cases in the online sector.

Desktop/mobile Total

Desktop 4

Mobile 20

Total 24

Table 121 - UK retailers' web technology


Clothing 6


General 4

Grocery 4

Others 4

Total 24

Table 122 - UK retailers' sector


96


Moving to the analysis of delivery

times, we can observe one case

belonging to the fast cluster: it is the

case of Sainsbury traditional grocer,

which have added the eCommerce

channel to its offer and thanks to its

internal logistics infrastructure and the

Chop Chop app is able to serve its customers

in a time included between one and two hours until 20:00 in the evening. Then 6

are the merchants offering same day deliveries: they are all traditional

multichannel retailers, two belonging to Informatics sector (Currys, owned by

Dixons company, and Farnell), two general merchants (Argos and Next), Tesco

grocer and the merchant Wickes belonging to Others cluster. They all have a

maximum hourly limit to respect in order to receive items the very same day and

this limit is much varied, moving from early in the morning (9:30 for Currys) to

late morning (12:00 and 13:00 for Next and Tesco respectively) until late afternoon

(17:00 for Wickes, 18:00 for Argos and even 20:00 in the case of Farnell). Time

windows available for delivery in most cases are quite late, reaching 22:00-23:00

at night and consider different time slots, the last one ranging between 16:00 and

23:00. However, the biggest portion of merchants offer next morning (3 cases) or

next day (11 initiatives) deliveries, accounting together for a 56 percent of the

total. Among these there is a strong prevalence of retailers belonging to Clothing

(the six cases of Shop Direct, Marks & Spencer, Asos, The Hut Group, Debenhams

and Arcadia) and to Informatics & general electronics sectors (the four players

Misco, Carphone Warehouse, eBuyer and Dabs); the remaining cases come from

General (John Lewis and JDWilliams) and Others clusters (B&Q and Boots). Also

these cases have a maximum hour for issuing the order which is later than same

day initiatives, staying in an interval between 17:30 and 24:00, while options for

delivery windows are many and much different one from the other. We can so

observe that Clothing retailers do not offer services faster than next day, while

the other industries are more developed towards fast and innovative services. The

remaining cases are three not fast services with delivery times not below two or

four days (the grocers Asda and Ocado and Findel that belongs to Others

category). Interesting to notice that little cases among the top 25 for sales’

volume do not represent an interesting object and 21 are subject to further

description as their services are all performed in less than 24 hours.

Delivery time Total

1-2h 1

same day 6

next morning 3

next day 11

not fast 3

Total 24

Table 123 - UK retailers' delivery time


97


Starting from the analysis of

service providers, we can observe

that only one merchant has one

specific service provider which resorts to,

differently from the higher amount of cases found in the US (14 merchants); this

is the case of grocer Sainsbury, that not only relies uniquely on its internal

logistics, but exploits the application realized by Chop Chop provider for

managing its deliveries. This implies that services of retailers operating in the fast

eCommerce environment in the UK are less personalized and differentiated with

respect to US situation.

In the large majority of cases

(72 percent) a fixed delivery fee is

applied, ranging between 3,95£

and 9,95£ in almost all the

options, with the exception of the

last player in the ranking

(informatics Dabs) applying a little higher fee

of 13,48£. In two cases (Asos and B&Q) the fee, which is around 5£, is deleted if a

certain threshold is reached for the expense 100£ and 50£ respectively). Just three

retailers instead offer delivery at a variable fee, depending on the amount of the

expense or on the weight of the order to be managed: they are the grocer Tesco

and the two informatics merchants Farnell and Misco, in which fees reach higher

values due to the unitary value of items sold. In the end, only Carphone

Warehouse informatics player offers delivery for free. With respect to US

situation, the share of retailers imposing a fixed fee is much higher, implying that

more merchants need to impose a fixed amount, although limited, in order to

experience economic viability.

Looking at the geographic coverage

of the services, we can see that,

conversely from what happened in the

US situation, the biggest part (17 out of

21 retailers, corresponding to 81 percent)

are able to cover all the national territory with their service; of course American

overall territory is not comparable at all with British one, but in any case a 81


Chop Chop app 1

Total 1 Table 124 - UK retailers' service provider

Cost Total

fixed 15

variable 3


free 1

Total 21

Table 125 - UK retailers' delivery cost

National coverage Total

No 4

Yes 17

Total 21 Table 126 - UK retailers' geographic coverage


98

percent of national coverage is a big value. The remaining four cases can in any

case reach many selected postcodes for what concerns same day and next day

options, while the only case available only in London is the one performed in a

couple of hours by Sainsbury.

Moving then to the typology of

logistics provider, five merchants have

built up their own logistics

infrastructure and it is the case of

merchants in the first positions of the

ranking, the two grocers Tesco (ranked 2nd) and Sainsbury (4th), the general

merchant Argos (ranked 1st) and the two informatics merchants Farnell and

Misco (11th and 12th respectively); their strong market share and/or the type of

industries in which they operate (Grocery with the peculiarity of perishable items

to be managed and Informatics involving products of high monetary value and

often occupying much space) have driven these operators’ choice in facing

investments for the development of a personalized infrastructure. The other 16

retailers (corresponding to 76 percent) instead resort to outsourcing logistics

strategy and it regards mainly next morning or next day options (13 out of the 16);

in most cases they rely on different operators without a preferential partner,

while in few cases merchants declare of resorting preferentially to DPD logistics

provider. No cases of crowd-sourcing models can be found in this country,

meaning that innovative and differentiated services are not diffused in the UK.


By looking at the peculiarity of

transportation means employed in

the service, more than a half of

the cases (corresponding to 57

percent) doesn’t specify anything

about it. On the contrary, nine

merchants provide specific information

on the technological tools utilized: in most of those cases (six out of nine, so the

67 percent) the preferentially employed mean is the van or at most a fleet of vans

at controlled temperature in the case of Tesco grocer; they mostly are cases in

which logistics providers in outsourcing are chosen for performing deliveries

(with the exception of the aforementioned dedicated refrigerated infrastructure

of Tesco and the internal logistics developed by top player in the ranking Argos),

implying that merchants have decided to resort to a generic service, not

personalized at all since vans are a traditional and not so fast way of transporting

Logistics type Total

outsourcing 16

internal 5

Total 21

Table 127 - UK retailers' logistics type

Transportation means Total

van 6

refrigerated van 1

bicycle 1

airplane 1

Total 9 Table 128 - UK retailers' transportation means


99

products. Moving then to faster services, we can find the case of informatics

company Farnell which has developed an internally owned logistics service made

by plane with the aim of assuring very fast deliveries (within the same day of

order issuing) in the whole national territory for such hardly manageable items

due to their size and weight. Lastly, the fastest service at all (the one offered by

grocer Sainsbury and carried out in between one and two hours within London

city) is made possible by providing internally employed couriers with bicycles for

navigating with agility within traffic congestion and handling little packages to

final customers, changing so the way they approach grocery shopping: instead of

doing big shopping once in a while, in this way they can make smaller shopping

of fresh products more frequently and have it delivered in two hours at their

home. So, excepted for this last very innovative case, most UK merchants do not

rely on particular technologies for improving their service.

Click&collect in store Parcel locker Other collection points Total

No No No 4

No No Yes 3

Yes No No 9

Yes No Yes 4

Yes Yes No 1

Total 21 Table 129 - UK retailers' last-mile alternatives

By analyzing the presence of last-mile alternatives in the offer, 14 out of the total

21 cases (corresponding to 67 percent) offer click & collect in store. Just few cases

allow customers to go and pickup their orders by the same day in which they

have made the online expense (or even in few hours) and it occurs usually only in

case the ordered items were already available in store; most merchants don’t

make the order available for being picked up before the next day if it has to be

fulfilled from a different location (usually the central warehouse), or even it may

take two or three days. Among these 14 retailers, four offer also the opportunity

of finding the order ready in another point of collection, different from the

traditional store owned by the merchant; this collection point in most cases is a

convenience store partnered by the retailer, such as gas stations and little local

shops, while in one case it is the collection point of property of the partnered

logistics provider (Collect+ that is partner of John Lewis merchant); also these

collections cannot be performed before the next day of order issuing or even

later. Also among merchants not offering pickup in store there are three cases in

which a different collection point is offered: they are all cases of outsourced

logistics providers that make their own pickup points available (Collect+ and

Doddle) all the next day of the order. Lastly, one merchant (Tesco grocer), in

addition to in store pickup the same day after 16:00 (if orders are issued by 13:00),


100

offers the chance to customers of finding their packages inside parcel lockers by

InPost provider located at the Tube stops, making impossible to fail deliveries

from logistics providers’ side. In this sense, UK situation about last-mile

alternatives for improving delivery efficiency is much more developed with

respect to US one.


14 out of the 21 analyzed merchants

(corresponding to 67 percent) offer the

chance of having real-time information about

tracking of the order, which is a useful information for increasing deliveries’

success and it is close to the percentage of the same merchants in the United

States.

Moving on, we can find that almost

a half of the interesting merchants offer

the chance of choosing the exact

delivery date and/or time. Five are the

cases of retailers normally performing

deliveries the next day or allowing customers to select another precise day of

their choice (Marks & Spencer, Carphone Warehouse, B&Q, Boots and Dabs); this

of sure means that the service goes out from the field of interest, lengthening the

delivery timings even up to two or three days. Conversely, retailers at the highest

positions of the ranking offer the choice of a specific delivery time slot within a

day or even the choice of both day and time. Next day clothes’ seller Shop Direct

allows to choose a different day (increasing so the lead time) but also of a precise

time during the day; in the other five examples instead (Argos, Tesco, Currys,

Farnell and Wickes) customers are left free to select a delivery time slot within

the same day of order issuing which can last one/two hours with an additional

cost for this service or it can be a larger slot of about three/four hours for a

cheaper and more flexible service. Compared to US, the service of time slots’

choice is much more spread in UK.

Pre-delivery contacts Total

delivery note 9

Total 9 Table 132 - UK retailers' contacts

Real-time tracking Total

No 7

Yes 14

Total 21

Table 130 - UK retailers' tracking systems

Day/time window choice Total

No 10

Yes 11

Total 21

Table 131 - UK retailers' day/time choice


101

Lastly, about the possibility of having contact with the courier before final

delivery, nine merchants are somehow developed in this direction, but they only

provide customers with a notification of delivery when it is almost going to occur,

which can be sent in different ways: by email, text, call to communicate the exact

time slot or 30 minutes before the delivery takes place. The analysis highlights a

presence of more developed and efficient ways to keep contacts with customers

and reduce occurrence of failed deliveries in US compared to United Kingdom.

In conclusion, innovation in delivery services is quite less widespread in UK

with respect to United States, regarding at the same time speed of the delivery

process offered by merchants, choice of a logistics provider with which

partnering for personalization of services and logistics infrastructure put in place

(i.e. means employed and last mile alternatives). However, even if not notably

fast and innovative, almost every retailer with a relevant market share offers a

kind of express delivery (at least next day) with a large geographic coverage in the

whole country.

4.1.4 Other European countries (France, Germany, Italy and Spain)

The third geographic area of interest is represented by the other censed

European countries; they are France, Germany, Italy and Spain and they are

grouped for the analysis because together they account for a number of

interesting cases which is comparable to the one of United States or UK alone.

First, the total number of websites submitted to research for these territories is

89: in fact, top 25 merchants of the national ranking have been investigated for

what concerns French, German and Italian situation, while for Spain only 14

retailers have been taken into consideration as this was the total quantity of

players involved in its related Top 500 Guide’s ranking.

Numerous are however the merchants that has to be excluded from the

database. Indeed, in France the general merchant Group 3si, after having

enlarged its diffusion by adding the online channel to the traditional one, has

decided to stop its eCommerce business, probably for an economic strategy of

specialization on the best selling channel; differently, Bijoudumois has

completely disappeared from every type of market. For what regards the German

situation, one retailer is not selling physical objects and so is not arranging any

activity for distribution (it is the Dot Com actor Arcandor which sells

obligations); another is the grocer Metro which works according to a business-to-

business logic and so goes out from our focus on final deliveries to single

individuals. One is the Spanish case which has shut down its whole business (the

last player in the ranking Bonacuista), while three are the merchants belonging to


102

the Italian ranking that up to now have shut down their operations and they all

worked in the Informatics industry (Dot Com player YouBuy.it, the other Dot

Com Bow that has been absorbed by Gruppo Banzai’s ePrice business and the

traditional Eldo Megastore which experienced bankruptcy in 2014). So eight are

the overall European players out of interest, reducing the total merchants’ sample

in the database to 81 cases.


Table 133 - European merchants' market channel

Country Dot Com/traditional pure player/multichannel Total

France Dot Com pure player 7


France Total 23

Germany Dot Com pure player 9


Germany Total 23

Italy Dot Com pure player 9


Italy Total 22

Spain Dot Com pure player 6


103

Moving then to the technological degree of diffusion channels, we can see

that France is the country with the lowest presence of pure players Dot Com (7,

corresponding to 30 percent, against the 70 percent of traditional retailers). The

percentage increases in Germany (39 percent), Italy (41 percent) and Spain (46

percent), going always closer to the half. As we can observe, French overview

outlines a situation same as United Kingdom and comparable also to US, in

which online business is dominated by retailers that only once having established

themselves in more traditional channels and having gained a strong market

position, have decided to add up a web channel for a wider diffusion; the only

difference noted in France regards the commodity sector: indeed, while Dot

Come players see a higher presence in sectors such as Informatics and General in

English-speaking countries, here Clothing sector is much less linked to

traditional shops and more projected towards a new path of online sales’ only,

marking an innovative intent. The other three European countries instead, which

are the ones experimenting a later and lower development of web sales, show a

retail market in which online only actors have significantly left their footprint,

meaning that the more actual trend for companies showing up lately is the one of

channel differentiation and focus on the web exclusively, which allows to enter

the market rapidly (without having to invest too much time and effort in physical

infrastructure realization) and even more rapidly reaching a high and widespread

diffusion.

However, the limitation is that being more recent and less economically strong,

online pure players in these countries are also the ones offering the slowest

delivery services up to now, so less interesting cases for the research’s objective.


Spain Total 13

Total 81

Country desktop/mobile Total

France desktop 6

mobile 17

France Total 23

Germany desktop 8

mobile 15

Germany Total 23

Italy desktop 16

mobile 6

Italy Total 22

Spain desktop 0

mobile 13


104

Addressing then the

commodity sector, we

can find differences among these

four European countries. France experiments a majority of retailers working in

the Clothing industry (8 out of 23, corresponding to 35 percent), followed by

Informatics and general electronics sector (22 percent), Grocery and the group of

Other minor sectors (accounting both for a 13 percent); smaller is the presence of

cases belonging to General industry (9 percent) and there is just one initiative for

both Home and Furniture and Publishing industries. From this sectors’

distribution we can see that France is the expression of a quite traditional

situation in which the most developed industries in the web market are still

Clothing and Informatics. Clothing has the stongest presence also in Spanish

environment, accounting alone for almost one half of the initiatives in the

ranking (46 percent exactly) and leaving small portions to all the remaining

sectors (2 the cases in General, Grocery and Publishing industries; only one for

Informatics cluster). Germany instead sees the predominance of two sectors

together: Informatics and General, accounting each one for the 26 percent of

cases, followed by Clothing and Others classes (13 percent each); smaller space is

left to Grocery and Cosmetics industries (9 percent each) and lastly Publishing

sector (1 merchant).

Interesting to note the peculiarity of Italian situation: the majority of online

merchants operate in the Publishing sector with its 7 initiatives (i.e. 28 percent),

followed by a relevant presence of the Informatics sector (23 percent) and then

General (18 percent). Then less space is left to Clothing (13 percent) and just few

sporadic cases can be found for what concerns Cosmetics and Perfumery, Grocery

and Other sectors (one merchant each). Globally, we can surely affirm that the

most developed industries in the online channel remain Clothing and

Informatics, with different single weights in the diverse countries; the other

sectors kind of lag behind, even if General and Grocery ones are experiencing a

growth in the market presence, especially in France and Germany, according to

what is happening also in UK and US realities. Less developed remains the

situation in Spain and Italy, in which there is one commodity sector weighing

Spain Total 13

Total 81 Table 134 - European merchants' web technology

Country Commodity sector Total

France Clothing 8

General 2

Grocery 3

Home & Furniture 1


Others 3

Publishing 1


105

much (Clothing for Spanish case,

Publishing in Italy) and then only residual attention left to the others (original

the case of Italian Publishing industry, which accounts for a big portion but it is

also the one including the least innovative and interesting initiatives, mostly

involving delivery timings that go far beyond even the next day).


Country Delivery time Total

France 1-2h 2

same day 3

next morning 2

next day 6

not fast 10

France Total 23

Germany 1-2h 1

same day 2

next day 6

not fast 14

France Totale 23

Germany Clothing 3


General 6

Grocery 2


Others 3

Publishing 1

Germany Totale 23

Italy Clothing 3


General 4

Grocery 1


Others 1

Publishing 7

Italy Totale 22

Spain Clothing 6

General 2

Grocery 2


Publishing 2

Spain Totale 13

Total 81 Table 135 - European merchants' sector


106

Germany Total 23

Italy same day 2

next day 1

not fast 19

Italy Total 22

Spain 1-2h 1

same day 2

next day 2

not fast 8

Spain Total 13

Total 81 Table 136 - European merchants' delivery time

Coming to the focus of the research, the delivery timing, we can see a

situation that distinguishes itself from UK case pretty much: not more than

almost a half of the initiatives in the ranking can be considered of interest in each

of the four examined countries (or also much less in some particular cases), even

if there are some differences between one and the other. France is the one

including the highest number of services staying below the next day time

constraint; in total they are indeed 13, corresponding to 57 percent of the total.

Two are the really fast services, not taking more than two hours at most to be

performed: one is the one hour service offered by Carrefour grocer through the

recourse to LaPoste logistics infrastructure of vans that deliver in the Parisian

territory up to 22:00 at night; the other takes between one and two hours (with

an average counted time of 78 minutes) and it is performed by Darty informatics

retailer together with the crowd-sourcing logistics service of Colisweb working

from 9:30 to 20:00 and guaranteed only if orders are received before 16:30. Three

then are the merchants offering same day service: the informatics C-Discount

(owned by the top player in the ranking Casinò) and the two clothes’ sellers Le

Bon Marchè (property of the LVMH group) and Brand Alley; they all rely on

diverse outsourced couriers to deliver items within the same day of order issuing

(starting from 16:00, but only if the order is received by a hourly limit ranging

between 10:00 and 14:00) pretty much in the Parisian region alone. After, putting

together next morning and next day retailers, we have another 35 percent of

initiatives; among these, we can find retailers belonging to many different

commodity sectors, from General (Rue du Commerce and Oxybull) to Clothing

(Yoox, Showroomprivè and Sarenza) with some cases also in Grocery (Auchan),

Informatics (LDLC) and Publishing sectors (France Loisirs). In order to not

overcome the following day for delivery, most of these retailers impose a time

constraint for order issuing which goes from 11:00 in the case of Showroomprivè

to mainly first hours of the afternoon (14:00 or 16:30). For next morning services

deliveries are carried out between 10:00 and 13:00, while for the others couriers


107

operate along the whole day and usually not before the afternoon; in any case, all

these services are performed by outsourced logistics providers. A big role

however is played by those merchants that with their delivery services can be

categorized as “not fast”: they are 10, corresponding to a 43 percent of the overall

ranking. They belong to almost all the commodity sectors and for them both

activities of order preparation and distribution are critical: indeed, order

preparation takes between one and three days (when specified, because in many

cases the retailer is not even able to provide a forecast on this time), but also

delivery lead time is usually reaches the 48 hours, or even one week. French case

can so be considered the most developed, with a significant amount of initiatives

carried out in less than 24 hours, but it lags behind UK and US in any case,

mainly due to the fact that the majority of cases is not faster than next day or at

most next morning.

The secondly addressed country is Germany and here we can find a lower

number of interesting cases: only one is the merchant offering a fast delivery

initiative and it is the informatics Conrad that is able to serve its customers in

two hours (it identifies three two-hours time window within which deliveries are

performed: 10:00-12:00, 14:00-16:00 and 18:00-20:00) in many cities thanks to its

internally developed logistics branch Tiramizoo; then there is a couple of same

day cases, one of the informatics player Notebooksbilliger and the other of

Cosmetics & Perfumery company Douglas, both relying on outsourced providers

(NBB courier and DHL respectively) for reaching customers’ homes in an evening

timeslot comprised between 18:00 and 22:00 if the order is received by the hourly

limit imposed by the retailer for guaranteeing the same day service (ranging

between 11:00 and 15:00 according to the different city). Lastly, six are the

initiatives occurring in less than 24 hours, with a prevalence of General

merchants (Otto Group, Baur Versand, Printus and Schneider), one clothing

(Klingel) and one informatics company (Cyberport); also here, excepted for the

number one player in the ranking that has developed its own logistics service, we

can find mostly outsourced providers for the orders’ handling and delivery

activities, offering a quite homogeneous service of next day delivery if the order is

received by a certain time boundary going from 11:00 to 18:30. We can so notice

that only 9 out of the 23 merchants (corresponding to 39 percent) belong to the

group of services under focus of this research. The biggest portion of cases is

indeed represented by non-fast merchants: they are 14 (i.e. the 61 percent of the

total) and they belong to all the different commodity sectors, from most

developed Clothing (Esprit and Adidas) and Informatics (Medion, GetGoods and

Pearl) to Grocery (Tengelmann and Lidl), General (Brands4friends, Tchibo)

passing by Other minor industries (Delticom, Musikhaus, Zooplu) as also

Publishing (Weltbild) and Cosmetics (Sanicare); they include also many players

occupying high positions in the ranking in terms of market share and their


108

criticality is mainly linked with the delivery activity (in fact, even if order

preparation timing is not specifically identified in some cases, delivery is most of

the time performed in an interval of one/three or two/four days with no more

specific clues and sometimes it may take also weeks). So surely Germany has

much to learn from the previously described countries for what concerns delivery

timings reduction.

The third place in terms of amount of cases of interest is occupied by Spain,

even if they are only five overall (accounting for the 38 percent): general

multichannel retailer El Corte Inglès is the only one offering a fast service,

reaching customers in one/two hours through its internal logistics infrastructure

or same day by choosing the exact time in which they want to receive their

products and delivering from 12:00 to 22:00; the following interesting initiatives

instead are all given to custody of outsourced providers: two are the same day

merchants (clothing actor Massimo Dutti and publishing retailer Casadellibro)

operating until 22:00 for delivering orders the very same day they are issued if

this has happened by 12:00; again two are the next day initiatives, all belonging to

clothing industry (Esdemarca and Adolfo Dominguez) both imposing a hourly

limitation for order submission in order to be sure of receiving items the

following day (15:00 and 13:00 respectively). For what concerns the other

merchants, eight offer non-fast services: they belong to almost all the different

commodity sectors (clothing with Privalia, BuyVip and Ofertix; informatics with

TPO Informatica; grocery with Grupo Eroski and Mercadona; general with

Dreivip; publishing with Agapea), many of them have even high sales’ volumes

and again, similarly to what has been found in the German situation, the issue for

them is related to distributive process, as most merchants need at least 48 hours

and up to few weeks to finalize delivery. Therefore also Spanish situation is

lagging behind, with most big players in the online business not able to or not

interested in setting up fast delivery services.

Lastly, the least interesting country in this light is Italy with its three out of 22

merchants (corresponding only to 14 percent): two are the same day services,

provided by informatics Gruppo Banzai and general D-Mail which, by ordering

within 13:00 and 12:00 respectively, allow customers to receive their items by the

end of the day (before 22:00) by exploiting outsourced logistics operators; then

one is the case in which, by ordering within 16:30, clothes’ seller Yoox Group

guarantees next day delivery always through the activity of an outsourced

provider. However, the large majority of merchants (19 out of 22, i.e. the 86

percent) belong to the not fast category: most of them belong to publishing

(Mondadori, Libreria Universitaria, Feltrinelli, Webster, Hoepli, IBS Network and

Unilibro) and informatics sectors (MediaWorld, Euronics, Marco Polo which is

now called Expert and Monclick) but few cases of all the other sectors can also be

found. In all these cases both order preparation and distribution activities are


109

performed in a slow manner: the time required to prepare the order before it

leaves the retailers’ warehouse is mainly not measured and not specified, while in

few cases it is expressly stated that it may take up to two days to be ready for

starting its distributive journey; in addition, delivery timing is blurred, included

in a range of 24/72 hours that depend on the logistics provider chosen (but

customers often have no clue on which is until they receive the items). The fact

that also the first online player in the ranking belongs to this cluster says much

about the Italian backwardness in the fast eCommerce context and highlights a

gap from the rest of mostly developed European countries.

The study of delivery timings have brought to the selection of 30 merchants

for the overall European context (13 French, 9 German, 5 Spanish and 3 Italian)

for which delivery services stay within the 24 hours threshold and that will

represent the focus of the following analyses.


Starting from the analysis of the presence of service providers uniquely affiliated to a certain retailer, we can see that the situation is different inside Europe. No cases at all can be found regarding Italy and Spain; very few cases also in France: LaPoste is the official outsourced distributor for grocer Carrefour and offers a delivery service which takes only one hour to reach Paris’ customers; differently, Colisweb logistics operator provides a crowd-sourcing model always utilized by Darty informatics retailer for performing final deliveries in about one/two hours in different French cities. We can so observe that in these three aforementioned countries the recourse to partnership with service providers is a non-diffused practice, resembling the situation found in the United Kingdom, even if when implemented takes to the best results in terms of delivery timings’ reduction (as

we can see from the two French cases, which are the fastest initiatives in the country), meaning that much can be done in the future for service improvement.

Country Service provider Total

France Colisweb 1

LaPoste 1

France Total 2

Germany DHL 1

DPD 1

Hermes 2

NBB courier 1

Tiramizoo 1

Germany Total 6

Total 8

Table 137 - European merchants' service providers


110

A little different is instead German situation, in which we can find a greater

diffusion of the practice: in fact, 6 out of the overall studied web merchants have

a single trusted logistics provider which they resort to. Also here, the fastest

national initiative at all belongs to this cluster and it is represented by Tiramizoo,

an internal branch of Conrad informatics company specifically developed by the

retailer itself for responding to its logistics needs; by having built up such a

specific and personalized service, Conrad is able to serve citizens of many cities

across the German territory within two hours. The same strategy has been

applied by top player in the ranking, Otto Group merchant that belongs to the

General commodity sector: it has built up its own logistics service under the

name of Hermes company and it offers the service also in outsourcing to other

competitor retailers (e.g. Baur Versand) in order to have a sort of control on the

service level offered by actors in the market (which up to now is next day, but the

company has acquired some stakes also of Liefery distributive operator and has

manifested the intention of moving to a faster same day service, always through

internal ownership and control). The other three cases are represented by players

occupying lower positions in the ranking, which resort to a specific outsourced

logistics operator (which can be NBB courier for Notebookbilliger informatics

merchant, DHL for cosmetics retailer Douglas and DPD for general retailer

Printus) for putting in place same or next day delivery services. So Germany

results more developed in this direction with respect to its European neighbors,

moving close to US in terms of number of initiatives but not in terms of their

type: indeed while United States see an almost exclusive presence of crowd-

sourcing models, Germany is still much dependent on outsourcing or at most to a

few cases of internal development but stays far from the innovation and the

speed of services built up in partnership in the American continent.

Country Cost Total

France free 2

fixed 7

variable 2


France Total 13

Germany fixed 6

variable 3

Germany Total 9

Italy fixed 1


variable 1


111

Table 138 - European merchants' delivery cost

By looking at costs imposed to customers for this kind of delivery services, we can see that the majority of merchants in all European countries imposes a fixed fee in order to pay back the efforts for such types of services’ arrangement (excepted for Italy, that can be however considered as partially relevant as the reduced number of cases it presents makes difficult to identify a particularly diffused trend). For what concerns French situation, 7 out of 13 merchants (corresponding to 54 percent) apply a fixed delivery fee and it is the case of also most of the fastest services (two hours service by Darty and same day by C-Discount and Le Bon Marchè), independently from the commodity sector; this cost varies a lot from one retailer to the other, with a minimum value of 5€ for C-Discount, passing by between 10 and 15€ for Oxybull, France Loisirs and Darty, until a higher fee that goes beyond 30€ for more fashion and luxury retailers such as Yoox, Rue du Commerce and Le Bon Marchè. Four then are the merchants applying a variable fee and they consist of mostly next day or at least next morning initiatives; the fee depends on the amount of the expense in bought items and on the city to serve and in two cases delivery is given for free if the expense reaches a certain threshold which has however to be quite high (150€ for grocer Auchan and 300€ for informatics company LDLC). One next day merchant, the clothes’ seller Sarenza, is always giving delivery for free and the same is valid also for the most interesting case in terms of delivery time (the one of Carrefour), as it is a newly developed service built up as a pilot project in only 9 arrondissements of French capital. Moving to German analysis, 6 out of 9 merchants (i.e. 67 percent) apply a fixed fee ranging from a minimum of 7,95€ for clothing company Klingel to a maximum of 39,95€ for voluminous items by general retailer Baur Versand; they mainly include next day services, but also the fastest one performed by Conrad. The other 3 merchants offer delivery at a variable fee which only depends on the expense (in ant case it never overcomes the 11,90€ applied by Douglas), including all the two same day merchants and one

Italy Total 3

Spain fixed 5

Spain Total 5

Total 30


112

next day. In Spain we can only find retailers applying a fixed fee, no matter the service’s speed, always staying below 9,95€ applied by same day operators Massimo Dutti and Casadellibro (also the faster service by El Corte Inglès is cheaper). Lastly, the small population of Italian cases reports a variety in which two merchants choose to apply a fixed fee (12€ for Yoox Group, 6.50€ for D-Mail but becoming free once reached the 60€ of expense) and only one resorts to a variable fee (Gruppo Banzai). Globally, we can state that the application of fixed fees is often needed in order to set up faster services in the European context independently from the peculiarity of the speed, mainly because of the prevalent recourse to logistics services in outsourcing which cannot be amortized and do not allow to reach scale or scope economies to merchants.

Moving to the geographic coverage, we can see that in almost all countries the

majority of merchants is able to offer its express service in the whole national

territory. This is due to the fact that most cases are not faster than next morning

or next day, so they have a sufficient time available to cover longer distances. If

we look instead at the fast and same day services they usually are performed only

in a smaller local territory: in France the one/two hours service by Darty is the

only one being able to reach 8 cities thanks to the flexibility of Colisweb’s crowd-

sourcing model exploited, while the other fast and same day merchants resorting

to outsourcing providers can mostly reach the Parisian region only (or even a part

of it); this happens also in Germany, where fast and same day retailers can offer

their services only in some selected cities or postcodes; the same situation can be

found in Spain, where same day players can cover just one city (Barcelona for

Massimo Dutti and Madrid for Casadellibro), while El Corte Inglès thanks to its

internal logistics infrastructure can perform its fast services in more cities but

always staying far from an homogeneous national coverage. The only exception

can be found in Italy, in which although ePrice same day delivery can be found

Country National coverage Total

France no 5

yes 8

France Total 13

Germany no 3

yes 6

Germany Total 9

Italy no 1

yes 2

Italy Total 3

Spain no 3

yes 2

Spain Total 5

Total 30 Table 139 - European merchants' geographic coverage


113

just in the Milan area, D-mail retailer is able to cover with its same day service

the national territory resorting to preferential outsourced courier BRT. In any

case, the reason why national coverage is so much present among these countries

can be found in the predominant slowness of express options (mostly next day).

Addressing then the type of logistics providers employed, easy to notice is the

strong prevalence of outsourced actors. Crowd-sourcing models are almost

unknown in the European context, with the only exception of Colisweb French

case offered to Darty informatics retailer in which single citizens or small courier

companies can autonomously make themselves available for delivery through the

platform. Three are the overall cases in which the retailer has invested in an

internal logistics infrastructure to personalize and internally support its online

business (the two German Otto Group and Conrad and the Spanish El Corte

Inglès); they are all cases of market giants that in some cases (the German ones)

can also start to outsource the logistics service born only for internal reasons and

enlarge in this way their business. The rest of merchants (26 out of 30, so

definitely the biggest portion) rely on external logistics providers for their mainly

same day and next day services, in most of the cases not even one preferential

operator that they pickup preferentially. Mostly cited couriers however are

Colissimo and Chronopost in France, DHL and DPD in Germany and BRT in

Italy. This situation can be identified as the main source of poor innovation in

fast web services, since the recourse to a generic and often changing external

operator provides a strong limitation to the improvement of the service to

customers.

Country Logistics type Total

France crowd sourcing 1

outsourcing 12

France Total 13

Germany internal 2

outsourcing 7

Germany Total 9

Italy outsourcing 3

Italy Total 3

Spain internal 1

outsourcing 4

Spain Total 5

Total 30 Table 140 - European merchants' logistics type


114


Country Transportation means Total

France bicycle 1

bicycle/motorbike 1

refrigerated van 1

France Total 3

Germany van 2

Germany Total 2

Total 5 Table 141 - European merchants' transportation means

As we could expect from the low degree of logistics services’ personalization

and specialization and also from the generally limited speed of delivery services,

the utilization of some specific transportation means is a not diffused practice.

We can find just three merchants in France declaring of resorting to some

vehicles: the two fastest services explicit the preferential use of bicycles for their

deliveries across the city of Paris, that in one case it’s an exclusive use (LaPoste

handles for Carrefour grocer orders which are small enough to allow the use of

bicycle as the unique mean for the service), while in the second case it is

accompanied by the recourse to other means (mostly motorbikes) due to the size

and weight of most items sold (indeed it is Darty informatics merchant); we have

also the other grocer, Auchan, which needs to exploit a fleet of temperature-

controlled vans due to the perishable nature of its products (since the service is

not so fast as Carrefour and products remain in the distributive process for even

24 hours). Two instead are the German retailers providing a specific description

of the vehicles they employ, but in both cases it regards only traditional vans

(even for the fast two-hours service offered by Conrad through its internal

logistics Tiramizoo, probably because again it deals with informatics business and

therefore big size products mostly). Excepted for these few initiatives, no other

retailers declares or is even aware of the means utilized for the distribution of its

products.

Moving to the research of last-mile alternatives to traditional home delivery

implemented by European web merchants, we can observe that very few are the

cases of retailers offering no alternative ways of receiving ordered items. Click

and collect in store practices find a sufficient diffusion in almost all countries

excepted for Italy: indeed, 5 out of 13 (corresponding to 38 percent) actors

provide this solution in France, a similar percentage (33 percent) can be found in

Germany, while it regards almost the totality of Spanish retailers (4 out of 5).


115

Country Click&collect in

store Parcel locker Other collection

point Total

France no no no 2

yes 6

yes no no 1

yes 4

France Total 13

Germany no no no 4

yes 2

yes no no 2

yes 1

Germany Total 9

Italy no no no 1

yes 2

Italy Total 3

Spain no no yes 1

yes no no 3

yes 1

Spain Total 5

Total 30 Table 142 - European merchants' last-mile alternatives

Just a couple of merchants let customers know that the pickup in store is

available in few hours after the moment of order insertion (both French cases,

products can be collected after one hour at Auchan stores and after three hours

in Oxybull shops) and not much more are the ones offering click & collect same

day or at most next day (same day for German informatics retailer Conrad and

Spanish El Corte Inglès, while next day for French clothes’ seller Le Bon Marchè

and German Cyberport) and these faster pickups are often available only if

ordered items are already physically present in store; all the other half cases take

at least a couple of days in order to fulfill the stores with ordered products, so

cannot be considered, to all intents and purposes, as real express alternatives. If

we look instead at other collection points offered, more than a half of overall

European studied retailers (17 out of 30) makes available at least one kind of point

in which customers can go and personally collect their orders. 10 of these cases

come from France and they mainly involve pickup points of logistics service

providers chosen by retailers (mostly Chronopost in 24 hours or at most next day

and Colis/Colissimo points needing however at least 48 hours for finding orders

ready to be collected); interesting to notice the case of Auchan which, in addition

to pick-up inside the store and collection in Chronopost points, have added an

original service called Auchandrive that allows customers to find bought items

inside their car’s trunk, without the need of leaving the parking area and entering

the store. For what concerns Germany, all the three merchants (Otto Group, Baur


116

Versand and Douglas) exploit mainly the presence of Hermes Paketshops in

which ordered pachages can be collected starting from 24 hours after the order

issuing; Italy and Spain instead presents cases in which products are collected at

the logistics courier’s collection point, that can be UPS or TNT or BRT or

whatever is chosen by the retailer, but usually not before three/five days from

order reception. Lastly, no cases at all can be found of parcel lockers’ initiatives.

We can so further confirm the level of logistics backwardness of these countries

in terms of last-mile.


Dealing with the availability of a real-time tracking system, we can see that

also most of European merchant provide this type of visibility on orders’ journey

to their customers, in line with a more global trend; the only exception is

represented by Spain, in which 3 out of 5 retailers do not allow to track moves of

the orders, increasing so the probability of occurrence of failed deliveries.

Country Real-time tracking Total

France no 4

yes 9

France Total 13

Germany no 1

yes 8

Germany Total 9

Italy no 1

yes 2

Italy Total 3

Spain no 3

yes 2

Spain Total 5

Total 30 Table 143 - European merchants' tracking system


117

Addressing

the topic of time

choice, only one

third of the

merchants offers

this option. Five

retailers are

French and

represent the 38

percent of the

national

initiatives; a

couple of them allows to arrange an appointment by selecting a specific date and

hour, but in advance of some days, while the other merchants offer the

opportunity of selecting, within the same day of order insertion, a delivery time

slot which can be of 2 hours (in the case of Brand Alley clothing company) but

also of only 30 minutes (in the fastest option offered by Carrefour). The other five

initiatives are from Germany and there they represent more than a half of the

total national cases; in addition, they all allow customers to select a time window,

which can be only a distinction between morning and afternoon

(Notebooksbilliger) or the identification of a specific 4 hours slot among 7:00-

11:00, 10:00-14:00 and 13:00-18:00 (the merchants served by Hermes logistics) or

even a shorter 2 hours slot distributed along the whole day until later hours such

as 18:00-20:00 or 20:00-22:00 (Douglas). Considering so France and Germany, we

can observe that some actions have been taken in order to increase efficiency of

delivery services and customers’ satisfaction at the moment of orders reception.

No cases at all can be noticed instead for what concerns Italian and Spanish

situations.

Country Day/time window choice Total

France no 8

yes 5

France Total 13

Germany no 4

yes 5

Germany Total 9

Italy no 3

Italy Total 3

Spain no 5

Spain Total 5

Total 30 Table 144 - European merchants' day/time choice

Country Pre-delivery contacts Total

France confirmation and delivery note 4

confirmation note 1

delivery note 3

France Total 8

Germany delivery note 3

Germany Total 3

Italy confirmation and delivery note 1

Italy Total 1

Spain confirmation and delivery note 1

delivery note 2

Spain Total 3

Total 15 Table 145 - European merchants' contacts


118

The last variable tackled regards the nature of contacts with people in charge

of the delivery process before it is performed. France reports the higher number

of cases of this kind, with 8 merchants overall out of 13 (corresponding to 62

percent) providing at least order confirmation and/or a notification for occurring

delivery , in most cases via text or at least via e-mail. In Spain too the majority of

merchants (3 out of 5) offer this kind of pre-delivery contact to customers, mainly

through a notification of delivery only and in one case with also a notification for

order confirmation, sent by text or at least by e-mail. Italy lags behind, with only

one case of merchant allowing customers to receive a notice of order

confirmation and then of occurring delivery, always via e-mail or text. Lastly, the

most interesting cases can be found in Germany, even if they represent a smaller

portion of the overall retailers addressed (3 out of 9). They all advice customers of

the moment in which delivery is really going to take place, in one case through a

simple text (Douglas); on the contrary Otto Group in addition to the text/e-mail

for communicating moment and point of delivery/collection when it comes to

that, arranges a call the evening before (being the service a next day one, it is

therefore the same day of order issuing) in order to inform the customer if the

courier (which is an internal Hermes employee) is going to perform delivery in

the morning or in the afternoon. The third case instead is the one of Baur

Versand, which can guarantee that the text or the e-mail notifying that delivery is

going to be carried out is sent half an hour before it actually happens. We can

therefore drive out that internally controlled logistics is a driver of better

communication and contact with final customers, which can surely be perceived

by individual buyers as an added value to the service, reducing uncertainty

around the effective moment of delivery and squeezing the phenomenon of

unattended deliveries; in this direction, Germany has a significant role with

respect to its European neighbors, resembling more to American and British

examples.

4.1.5 Asian countries (China, India, Japan and South Korea)

Changing completely the geographical focus, the last continent constituting

an object of research for this thesis is the Asian one and four countries have been

specifically identified as the most developed once in terms of participation to the

online market and therefore have been included in the analysis to provide a more

global view of the state-of-the-art situation; these countries are China, India,

Japan and South Korea and also for them the first 25 actors of the national top

web retailers’ ranking in terms of sales’ volumes have been submitted to research,

for a total of 100 merchants.

Some of them however has to be immediately excluded from the database.

Four Chinese retailers belong to the category of non-interesting merchants for


119

further analysis: first, Sc4888.com is a website providing information on the

Internet and therefore does not arrange any logistics activities for provision on

products to final consumers; then, two players in the General industry (360Mart

and Mailebei) and one in the Others cluster (51sheyuan) have shut down their

whole activities after 2013. Moving to India, we find that the online market has

changed much from 2013 since 7 out of the 25 taken from the ranking have closed

at least their online business (Buytheprice, 100bestbuy, Zovi, Inkfruit, Seventy

MM, Indiaplaza and Be Stylish). Only one instead is the Japanese retailer present

in the ranking having shut down the business (Ec-current). Finlly in South

Korean context we have one Informatics company (Ahnlab) of no interest since it

only sells software solutions and one clothes’ retailer (VanillaMint) having shut

down its Dot Com business since 2013. Therefore, overall cases that must be

taken out from the actual database with respect to 2013 situation are 14, reducing

the sample size from 100 to 86 retailers addressed.


Country Dot Com/traditional pure player/multichannel Total

China Dot Com pure player 16


China Total 21

India Dot Com pure player 12


India Total 18

Japan Dot Com pure player 3


Japan Total 24

South Korea Dot Com pure player 14


South Korea Total 23

Total 86 Table 146 - Asian retailers' market channel

The first variable to be tackled regards the nature of retailers’ business. From

the table we can observe that Japan has a great majority of merchants which are

traditional ones having enlarged their business by adding the online channel (21

cases out of 24, corresponding to 88 percent) and it regards pretty much all the

commodity sectors; this situation, although a little taken to extremes, resembles

occidental countries in which many are the players in the ranking born many

years ago as traditional retailers and having strengthen their position in the

market for years before deciding to follow the more recent trend of resorting also

to the web channel. In the three other Asian countries the situation instead is the

opposite: indeed big is the portion of Dot Com pure players in the ranking,


120

representing a 61 percent of the cases in South Korea, a bigger 67 percent in India

and even reaching the 76 percent in China. These online players have

experienced a widespread diffusion in all the industries, with a particularly clear

relevance in the General sector (which can be comprehensible as traditional

shops selling all the possible types of products are more difficult to be managed

with respect to an online market for them) and especially in the Clothing

industry (much innovative fact with respect to US and Europe). This

phenomenon expresses again the scarce presence of big giants in the Asian online

market and since the market is still far from being developed and most actors are

newly entrants, it is a representation of the need for companies to born with a

very flexible and web-suitable model in order to enter the market competitively

and not leaving it too soon.

This just described

situation is similarly

reflected in the choice

of the technology to

support the company’s

web channel: in Japan

most of the players,

corresponding to a 79

percent of the overall

cases and being almost

all traditional

multichannel retailers,

provide their

customers with a website that can only be

accessed by fixed desktops; on the contrary the few merchants offering a mobile

access are also the ones performing the fastest delivery services (at most same

day). Almost balanced situation can be found in South Korea, where 11 (i.e. 48

percent) allow customers to navigate the website and submit their orders from

mobile devices and they also represent the great majority of retailers carrying out

services faster or at most equal to next day, while the remaining 52 percent is

made of merchants with desktop only access. For what concerns China and India

instead, much higher percentages of mobile players can be found: indeed, 78

percent of Indian retailers and 86 percent of Chinese ones (mostly Dot Com pure

players) have a mobile application available for customers to increase visit

frequency and lever on impulse buys; the remaining small portions consist of

actors offering desktop access only, but they mostly belong to General and

Others sectors (while a strong presence of Clothing and Informatics players can

be found in the mobile cluster) and they offer services classified as “not fast”.

Country desktop/mobile Total

China desktop 3

mobile 18

China Total 21

India desktop 4

mobile 14

India Total 18

Japan desktop 19

mobile 5

Japan Total 24

South Korea desktop 12

mobile 11


Total 86 Table 147 - Asian retailers' web technology


121

Again, China and India, which are more recently developed and less

“Occidentalized”, follow a differentiated trend.

For what regards mostly populated commodity sectors in the online Asian

market, both in China and India we can notice a strong predominance of the

General industry (10 cases in China, corresponding alone to a 48 percent; 8 in

India therefore a 44 percent); Informatics and Clothing industries have up to now

conquered small shares of the market (in China a 19 percent for Informatics and

general electronics and a 14 percent for Clothing; in India they count for a 22 and

17 percent respectively), a little higher than poorly diffused industries such as

Country Commodity sector Total

China Clothing 3

General 10

Grocery 2

Home & Furniture 1


Others 1

China Totale 21

India Clothing 3

General 8


Others 2

Publishing 1

India Totale 18

Japan Clothing 4


General 3


Others 5

Publishing 1

Japan Totale 24

South Korea Clothing 11


General 5

Grocery 2

Home & Furniture 1

Others 1

Publishing 1

South Korea Totale 23

Total 86

Table 148 - Asian retailers' sector


122

Grocery (present only in China with a 10 percent), Others (one retailer in China

and two in India), Home & Furniture (one only case in China) and Publishing

(one case too but in India). So most of the retailers born lately in these two

countries have the market objective of not specify themselves in a particular

products’ category but offer a great variety of items. A different situations, that

pretty much resemples the one of occidental countries can be instead found in

Japan where, excepted for the less significant cluster of Other industries, the

most part of retailers belong to Informatics (38 percent) and Clothing sectors (17

percent), with also a presence of General actors (13 percent) before the sporadic

cases in Cosmetics (2 out of 24) and Publishing sectors (only 1). Interesting to

notice that the situation is similar also in South Korea, because even if

Informatics is absent, the biggest part of market is occupied by Clothing sector

alone with its 11 merchants (corresponding to a 48 percent); then also some cases

from General (5 and therefore a 22 percent), Cosmetics & Perfumery (2 retailers)

and Grocery (again 2), while the others are definitely lagging behind with just one

case. The development of online market in South Korea is so following a trend

which is closer to occidental countries, but it is absolutely driven by Clothing

retailers, most of which have setup their business quite recently following a pure

Dot Com model and represent the biggest sales. We can find overall that

Informatics sector finds less relevance in Asian countries with respect to

American and European continent and especially Grocery industry, which

presents also interesting cases in the occidental world for what concerns

innovation in terms of speed and delivery features, is almost absent in the online

market of these countries.


The following database’s field is much important and defines the speed of the delivery process. Starting from Chinese situation, we can find just one fast retailer that is the Informatics Dot Com 360Buy.com website of Jingdong company and that is able to serve its customers in five cities within three hours (or at most offering an Overnight delivery service in which products are received between 19:00 and 22:00 if they are ordered before 15:00 the same day) thanks to its internally owned logistics infrastructure. Then three are the cases of same day operators: one is the ranking top player Tmall, grocer belonging to Alibaba company and delivering items in two Chinese cities by 22:00 of the same day of order issuing again exploiting its internal logistics branch Cainiao and its fleet of refrigerated vans; the other two cases are both belonging to Informatics sector and are able to offer this type of service almost on the whole national territory, but one has its own logistics (Gome Electrical Appliances) while the other exploits an outsourced operator (Dangdang); in any case, all the three same day retailers impose customers to submit orders by 11:00 in the morning if they want to be sure to receive items within the day.


123

One only merchant instead provides a next day delivery service and it is again

an Informatics one, the traditional merchant Suning, imposing a hourly limit for

order submission at 13:00 in order to do not overcome the following day for

delivery and resorting to an outsourced logistics provider. Finally a 76 percent of

merchants can be considered as “not fast, sometimes because of unspecified

timings for order preparation but mostly due to the fact that delivery in such a

large country takes at least two/three days and reaching peaks of also six/seven

days in few cases.

Moving to India we can find a higher portion of overall interesting retailers

for the foucus of this research: in fact, two offer services performed in few hours,

six stay beyond the same day and one beyond the next day limit for the

accomplishment of final delivery, accounting for a 50 percent globally. The two

fast services are not offered by merchants at the top positions of the ranking, but

the two Informatics companies Univercell (that is ranked 11th) and The Mobile

Store (ranked 21st); they both exploit internal logistics and in particular the first is

developing a pilot project for delivery in 4 hours in Chennai, while the second

delivers in two hours in many different cities and carries out distribution

activities up to 22:00, but asking customers to not submit orders after 20:00 for

Country Delivery time Total

China < 6h 1

same day 3

next day 1

not fast 16

China Total 21

India 1-2h 1

< 6h 1

same day 6

next day 1

not fast 9

India Total 18

Japan < 1h 1

same day 8

next day 5

not fast 10

Japan Total 24

South Korea same day 3

next day 2

not fast 18


Total 86

Table 149 - Asian retailers' delivery time


124

receiving this type of very fast service. The six same day cases involve retailers of

different sectors, mostly General (Snapdeal, TV18 Home Shopping and Infibeam)

but also Informatics with Flipkart, Clothing with Myntra and Others with Firstcry

(that in particular sells products for baby care); the two retailers with highest

market share (Flipkart and Myntra) have developed an internal logistics

infrastructure for the performance of this service, while the other four players

have to rely on externally outsourced operators; all of them impose a limitation

to the time of order submission in order to guarantee that same day delivery is

respected and this limitation varies between 11:00 and 14:00 at most, while they

mainly operate until 21:00 with the exception of Firstcry, whose couriers

distribute products until midnight. One only is then the next day retailer,

Lenskart, but little information are available. Going out of the area of interest,

nine are the merchants not offering fast delivery services and again identifying

the distribution activity as the most critical one, taking from 1/3 up to even 7 days

to be performed (and sometimes no information are even available).

To follow, Japan is the Asian country with the highest percentage of retailers

operating in less than 24 hours (14 overall, corresponding to a 58 percent); just

one is fast (top player in the ranking Rakuten, a Dot Com operator belonging to

Others sector, distributing products 24 hours a day to serve customers in Tokyo

in an average time of 60 minutes (but reaching also minimums of 20 minutes)

with its internal logistics), while eight are the same day retailer and five are the

next day ones. Same day retailer mainly belong to the Informatics sector

(BicCamera, Dospara, Pasoclom Club, Sound House and SourceNext), while a

couple comes from Clothing industry (Start Today and Uniqlo) and Yamada

Denki to the General sector; they mostly resort to outsourcing logistics (excepted

for the case of Dospara that has its internal system) and apply times’ limitations

for order submission that are much different one from the other (moving from

6:00 and 9:00 in the morning for Sound House and Start Today respectively to

15:00 at 17:00 for BicCamera and SourceNext). Also next day retailers are mainly

informatics ones (Yodobashi, NTT-X and Mouse Computer), with the addition of

General company Neowing and of the clothes’ seller Point only; they all rely on

outsourced couriers and do not have a similar behavior for what concerns hourly

time limitations for order issuing (some have a limit at 13:00 or 15:00, e.g. Mouse

Computer and NTT-X, while some others have no limitation at all). We can so

notice that, even if really fast cases are not so present, Japan reports a significant

number of interesting cases which attest its degree of development already

comparable with the one of many occidental countries. Then we can find a 42

percent of cases of not fast retailers, again mostly highlighting a time window

around 2/4 days (but reaching also 5 or even 10 days in some specific cases) for

delivery.


125

Lastly, a 22 percent of interesting players can be found also in South Korea,

where no operators perform deliveries faster than same day, but then three offer

the same day service (the three top players in the ranking, the two grocers Lotte

Mart and E-mart exploiting their internal logistics infrastructure and the

Publishing company Yes24 resorting to an external courier, all imposing a time

limitation for order submission blurring between 10:00 and 15:00 also according

to the city in which the process takes place), while two actors at the end of the

ranking (Clothing retailers Gaenso and Minsshop) ship products through an

outsourced operators that reach customers on the following day if the order is

issued by 13:00 for the first and by 17:00 for the second. Interesting to notice how

South Korea is the only Asian country in which Grocery not only has a presence

in the online market, but it is also the source of most innovative services. Out of

this group a great majority of cases is instead represented by “slow” delivery

services (78 percent), among which we mostly find the big number of Clothing

merchants that were present in the ranking, in which order preparation can even

be specifically performed within the same day of submission, but the criticality is

linked to the infrastructure for domestic shipments, that allow orders to be

received in a quite large timeframe, from 2/3 days up to 10 days. To sum up, we

can find a significant number of retailers belonging to the field of interest of

services faster than next day, comparable with the one of the other previously

addressed territories: indeed they are 33, with a strong contribution of mainly

Japan (14) and India (9), but also a relevant presence of China and South Korea (5

merchants each), even if very fast services are unfortunately quite rare. For the

following analyses we will therefore address these 33 retailers only.


Tackling the list of

service providers

chosen to be the

unique operators for a

specific merchant with

whom building a

strong partnership to

personalize the service,

we can see that it is very short, including

just one case for each country excepted for South Korea in which no retailers

have developed such a relationship with their logistics providers. The Chinese

merchant belonging to this cluster is the number one player in the ranking T-

Mall, a Dot Com grocer under the ownership of Alibaba that, even due to the

Country Service provider Total

China Cainiao 1

China Total 1

India Ekart 1

India Total 1

Japan Yamato Transport 1

Japan Total 1

Total 3 Table 150 - Asian retailers' service providers


126

peculiarity of items managed (which are perishable if fresh or that need to be

kept in very restricted temperature conditions in order not to interrupt the cold

chain and preserving their characteristics), has developed internally a logistics

sub-company called Cainiao whose fleet of refrigerated vans and services are

exclusively exploited by T-Mall itself. Also the Indian retailer Flipkart, Dot Com

seller of informatics and general electronics products and second player in the

national ranking, have established an internal logistics company called Ekart to

which it uniquely resort for all its handling and distribution activities. Differently,

Japanese clothing retailer Start Today, at the second place of its national ranking

too, relies on the external logistics company Yamato Transport only. All these

merchants are able to offer, thanks to these partnership, quite fast services (all

same day); however, the fact that they occupy the very first positions in terms of

sales’ shares means that only the few really biggest Asian companies are

economically able to put in place such a kind of relationships, evidently having a

high bargaining power and representing a highly appealing business for logistics

companies partnering with them (in the case of external operators) or having a

so strong economic and financial position to make them able to undertake such a

kind of huge investments. Merchants having the possibility of doing this are

evidently much less in Asia than what happens in American and European

countries.

Country Cost Total

China fixed + free beyond threshold 1

variable 3


China Total 5

India fixed 1


free 3

variable 3

India Total 9

Japan fixed 7


free 1

variable 1

Japan Total 14

South Korea fixed + free beyond threshold 1

variable 4

South Korea Total 5

Total 33 Table 151 - Asian retailers' delivery cost


127

Starting from the description of the kind of fee applied for the delivery service

provision, we can immediately observe a huge component of fixed fees for what

regards Japanese retailers: in fact 12 out of the 14 retailers in this country impose a

fixed additional amount of money for delivery to their customers, which at most

in five cases can disappear by reaching a certain expense’s threshold; this fee

stays in a large range which goes from around 200/300 Yen in the cheapest cases

(mainly Clothing companies and next day services) up to 2000 Yen (4000 Yen to

reach more remote islands) for each bought item in the most expensive cases

(Informatics providers of same day services). Also the threshold to reachin order

to have delivery given for free is much vary, from a minimum of 1500 Yen (in the

case of Sound House) up to 10000 Yen (for Neowing retailer), according to the

courier employed. This situation makes Japan much looking alike the other

European countries (mainly due to the recourse to external providers). Only

Pasoclom Club Informatics company applies a fee which is variable depending on

the type of product and the distance to be covered, while BicCamera does not

impose any additional fee for delivery. An opposite situation can be found instead

in China and South Korea with a prevalence of the variable fee: indeed four

companies for each country apply a fee which changes according to the amount

of money paid for products, the distance travelled, the single retailer (as often

these Dot Com companies act as collectors of offers from many small retailers) or

also on the degree of fidelity of customers (and therefore its profile according to

the number of orders that he/she has already made through the same website); in

one only case the fee can be deleted by reaching a minimum expense of 400$ (it’s

the case of Suning informatics retailer). Both countries report only one case each

of merchant applying a fixed fee, which however can become free by reaching a

certain threshold: they are the Chinese informatics Gome Electrical Appliances

(fee of 5 Yen, given for free if at least 99 Yen of products are ordered, which all

things considered represent a very low fee) and the South Korean Clothing

retailer Minsshop (again a low value, with 2,50$ of fee but deleted if at least 50$

are paid for products)and they are the last players in the national ranking by

considering cases of our focus, so the ones with the smallest market position.

This means that Chinese and Korean online operators have structures flexible

enough to avoid the imposture of fixed expenses, maybe also due to the fact that

they are smaller an younger players with respect to already more established

Japanese ones. India represents instead an example of perfect equilibrium, with

three cases for each of the fixed, variable and free fee clusters: players in the

lowest ranking positions, even if among them there is also the fastest service,

unexpectedly are the ones not imposing any fee for delivery; the Flipkart,

Snapdeal and TV18 Home Shopping apply a variable fee according to the items’

expense staying around 100 Rs per article in the General sector and 200 Rs per

item in the Informatics sector; the remaining three merchants apply a fixed fee


128

(40 Rs in the General case, 69 Rs in the Informatics case and 199 Rs in the

Clothing one) which can become free in two cases after having reached a certain

threshold (500 Rs for General Infibeam, a higher boundary of 999 Rs for Clothing

Myntra). Difficult is therefore to provide a clear identification for the Indian

situation in terms of costs.

By looking at the area served, we can observe a comparable presence of

national and local initiatives in almost all countries excepted for India, in which

faster initiatives have mostly an only local development. Starting from China, the

three Informatics retailers’ initiatives (which are mostly outsourced excepted for

Gome) find a wider national coverage, while fastest and most innovative

initiatives (i.e. the three hours service by Jingdong and the same day grocery of

Tmall, both internally performed) are available just in few cities (6 for the first

merchant, only Beijing and Shanghai for the second).

Moving to Japan,

we can see that more

than a half of retailers

(again mainly

Informatics ones) are

able to cover the whole

national territory with

their same or next day

services; on contrary,

six retailers (which are

mostly same day and

report also the fast

service by Rakuten) can

be performed in an area which can

include at most a dozen of cities (Start Today, Sound House and Point service

that can reach the whole Kanto area or more) or Tokyo city alone (some wards

for same day initiatives by BicCamera and Uniqlo, while only four wards for less-

than-one-hour Rakuten service). Also South Korea reports a quite expectable

situation, with next day merchants able to reach the whole national coverage,

while same day ones cannot overcome the area around few cities. Different

instead is the case of India: only one retailer has a national coverage, but it is also

the only one providing next day delivery; all the remaining eight merchants offer

fast or same day services and this is the reason why they are not able to reach

more than local territories: it could be many selected cities in case of especially

same day operators or a single city (e.g. only Delhi for Snapdeal and Chennai for

the pilot project by Univercell). We can globally infer that the more limited

Country National coverage Total

China No 2

Yes 3

China Total 5

India No 8

Yes 1

India Total 9

Japan No 6

Yes 8

Japan Total 14

South Korea No 3

Yes 2

South Korea Total 5

Total 33 Table 152 - Asian retailers' geographical coverage


129

coverage of Asian retailers with respect to American and European one could be

explained by the lower degree of development of logistics services and their

related infrastructures for the online channel.

Moving to the analysis of the typology of logistics provider performing the

delivery and all the other handling activities needed for the provision of the order

to the final customer, we can again notice how the Japanese situation differs from

the one of its Asian neighbors: in fact, while in the other countries there is a

relevant share of companies having developed an internal logistics infrastructure

and service, in Japan the 86 percent of retailers relies on an external operator.

Internal logistics characterize as always two of the fastest services, which are

informatics retailer Dospara’s same day and in particular the only fast initiative of

the country, the one of top player Rakuten with its internally developed sub-

company Rakubin that differentiates itself from the offers of other merchants by

reaching customers in less than one hour and by performing deliveries all day

long (24/24h). For what concerns the other 12 Japanese actors, their services are

quite homogeneous one with the other, offering quite standardized same day and

next day initiatives as they rely on outsourcing of logistics activities to external

providers which are almost the same for each retailer: in fact, the two mostly

addressed courier companies are Yamato Transport and Sagawa Express with its

particularly employed shipping service by air. Japanese context of little

specialization of the offer and general homogeneity on timings which can sound

good to customers but do not suggest the opportunity of further improvement

much resembles the one of European countries as France, Germany, Italy and

Spain and lacks of innovative intention for future development of the services.

Country Logistics type Total

China internal 3

outsourcing 2

China Total 5

India internal 5

outsourcing 4

India Total 9

Japan internal 2

outsourcing 12

Japan Total 14

South Korea internal 2

outsourcing 3

South Korea Total 5

Total 33 Table 153 - Asian retailers' logistics type


130

Differently from this, in the other three Asian countries we can find an

interesting percentage of merchants resorting to internal efforts for serving their

customers: indeed they represent the 40 percent of South Korean overview, the

56 percent in India and up to a 60 percent in China. In all these countries, all the

fast solutions rely on internal logistics; they are the Indian FED (Fastest Expert

Delivery) service offered by informatics The Mobile Store in less than two hours,

pilot project of informatics Univercell in four hours and again an informatics

company Jingdong with its three hour service in China. We can also find many

same day initiatives involving again informatics merchants such as Chinese Gome

Electrical Appliances and the Indian Flipkart with its logistics sub-company Ekart

specifically built up, but also a relevant portion of retailers belonging to the

Grocery industry and having therefore particular needs for what regards products

they handle: in this group we can find the Chinese Tmall with its internal

logistics branch Cainiao and the two South Korean grocers Lotte Mart and E-

mart. One only merchant, the Indian Lenskart, is offering a service called

Lightning Fast Delivery through its own internal infrastructure that reaches

customers on the next day of order submission. We can observe how the top

two/three players of the ranking for each of these countries are included in this

group on internal logistics, meaning that they have reached such a position in the

market to justify the efforts in developing a specialized own service. The recourse

to outsourcing can be found instead for most of the merchants offering next day

and same day initiatives, most of them Dot Com players occupying more

backward positions in the ranking, meaning that they are players not having a so

strong presence in the market and/or an economic solidity to justify an

investment in a personalized logistics system. In addition, the externally sourced

services are not even homogeneous among themselves as almost no preferential

couriers are indicated by merchants, excepted for XpressBees operator cited by

Indian Firstcry company and GTX provider by South Korean Yes24. Probably the

more recent development of the online market in these last three countries and

their higher degree of specialization in the channel with so many Dot Com pure

players born are reasons that explain this relevant share of internal logistics,

leaving room to the assumption that many will continue to be these cases and

that these services may probably continue to improve and squeeze their timings.

Interesting to lastly notice that crowd-sourcing models have not been found at all

among the merchants constituting the sample of research.


131


Country Transportation means Total

China electric bikes 1

refrigerated vans 1

China Total 2

Japan airplane 4

van 1

Japan Total 5

South Korea refrigerated vans 2

South Korea Total 2

Total 9 Table 154 - Asian retailers' transportation means

Little can be said instead for what regards the peculiarity of transportation

means exploited in the delivery service provision, but also here we can observe

the difference of Japanese situation with respect to others. In fact, a relevant

portion of same and next day services (corresponding to a 29 percent of the total)

is carried out by utilizing air shipments and this is the case of the merchants

resorting preferably to Sagawa Express logistics. It is a way of transporting items

which can surely be put in place only by an external logistics operator serving

many merchants and amortizing therefore the investment in such a great

infrastructure; it also allows to cover longer distances in a limited time, but due

to the timings needed for items’ boarding, landing and all the other related

handling activities, together with the obvious necessity of adding another

distributive methodology in order to perform the last-mile part of the delivery

process, it cannot be associated with services shorter than at least same day. Then

one is the case in which the retailer declares of resorting to vans only for its

delivery and this kind of control on the mean utilized can be assured by the fact

that it is Dospara merchant and its logistics process is internally owned. The

remaining part of retailers instead, corresponding to 64 percent of the overall

cases, do not have any visibility on which means will be exploited for arranging

the orders’ distribution. Excepted for the air transportation options, it much

resembles the German situation, in which no relevantly innovative or

personalized vehicles and/or initiatives can be found. For what regards the other

countries, a couple of cases of refrigerated vans’ usage can be observed in South

Korea and one in China, corresponding to the online grocers which have

developed their own infrastructure in order to keep continuous control over the

conditions of products’ journey. One only case of particular interest is present in

China and is related to the fast three hours delivery service offered by Jingdong

informatics retailer: in fact, in order to cover in little time distances in the six

cities of Beijing, Shanghai, Guangzhou, Chengdu, Wuhan and Shenyang not only

traditional vans are utilized, but internally employed couriers often resort to the


132

use of electric bicycles, which represent an ecological-friendly way of avoiding

urban traffic conditions for offering such a sustainable and efficient service that is

very interesting to be noted in the Chinese context. However, India do not even

have one case of merchant declaring to utilize a particular vehicle for distribution

activities, so we can generally observe that this phenomenon doesn’t reach a

sufficient presence in the Asian continent.

Country Click&collect in

store Parcel locker Other collection

point Total

China no No no 4

yes No no 1

China Total 5

India no No no 7

yes no 1

yes No no 1

India Total 9

Japan no No no 8

yes 1

yes No no 4

yes 1

Japan Total 14

South Korea no No no 3

yes No no 2

South Korea Total 5

Total 33 Table 155 - Asian retailers' last-mile alternatives

Also the presence of relevant alternatives to last-mile home delivery is quite

limited: in fact only 9 merchants overall out of the total 33 (corresponding to a 27

percent), most of them (5 out of 9) coming from Japan, offer to customers the

opportunity of ordering items online and then collecting them at the stores; but

in some cases the pickup in store can be performed in fast times, within the same

day of order submission on the website (in the example of Korean grocers Lotte

Mart and E-Mart) or even after only thirty minutes if the items are already

available in stock (the case of Yodobashi Japanese informatics retailer); in most of

the other cases the date for the pickup can be agreed between merchant and

customer or at least a phone call is provided to the last one to let him/her know

that the order is ready to be collected. This represents a quite well developed

situation, in which pickup in store last-mile alternative can also be better

managed than what happens in many other European countries. Just two instead

are the cases in which another collection point different from the shops owned by

the merchant is offered to customers for the collection of his/her personal orders,

but they are of particular interest: indeed the first one is provided by the Japanese

retailer Rakuten through its own logistics Rakubin and it allows customers to


133

insert at the moment of the order whichever delivery address they want, even if it

doesn’t correspond to their home or office but to a shop, a restaurant or even a

park in which they are going to be at the moment of delivery; this is surely made

possible by a very well managed delivery process, that keeps a pretty much

continuous contact with the customer up to 15 minutes before delivery. The

second case is the one of another Japanese company, the general retailer

Neowing, that has some convenience stores partnered with terminals for

collection. The phenomenon of parcel lockers is instead absent in the Asian

continent, thing that happened also in the European one. So we can say that even

if lagging behind the more innovative US and UK examples, situation of last-mile

alternatives is not so much backward with respect to European context and the

present cases, even if limited in number, are noteworthy for their particular

management and also speed.


Moving to the analysis of the typology of logistics provider performing the delivery and all the other handling activities needed for the provision of the order to the final customer, we can again notice how the Japanese situation differs from the one of its Asian neighbors: in fact, while in the other countries there is a relevant share of companies having developed an internal logistics infrastructure and service, in Japan the 86 percent of retailers relies on an external operator. Internal logistics characterize as always two of the fastest services, which are informatics retailer Dospara’s same day and in particular the only fast initiative of the country, the one of top player Rakuten with its internally developed sub-

company Rakubin that differentiates itself from the offers of other merchants by reaching customers in less than one hour and by performing deliveries all day long (24/24h). The availability of

systems for real-time

tracking of orders is

pretty much developed

also in the Asian

countries, reporting a

situation of control over the progress of products along the various steps of their

journey which has nothing to envy to the European context: in fact, a 55 percent

of Indian merchants, a 78 percent of Japanese ones, an 80 percent of Chinese

Country Real-time tracking Total

China no 1

yes 4

China Total 5

India no 4

yes 5

India Total 9

Japan no 3

yes 11

Japan Total 14

South Korea yes 5

South Korea Total 5

Total 33 Table 156 - Asian retailers' tracking system


134

actors and up to a 100 percent of South Korean ones offer this type of visibility to

final customers.

For what regards the agreement between retailer and final customer upon the

exact date and/or time window for the delivery, we can see a relevant amount of

this kind of initiatives in almost all the Asian countries, with the exception of

India with only one case. Just one is the case of merchant allowing to choose only

the date of delivery, arranging an appointment with some days of advance (it’s

the case of the Chinese informatics retailer Dangdang). In many cases the

customer is left free to chose among different time windows of few hours each

within the day; in fact the five Japanese merchants Dospara, NTT-X, Neowing,

SourceNext and Point offer the choice among many quite short time windows

(8:00-12:00, 12:00-14:00, 14:00-16:00, 16:00-18:00 and 18:00-21:00), the Chinese

operator Gome allows to chose among less and longer timeframes (9:00-13:00,

13:00-18:00 and 18:00-21:00), while other actors offer a last time window later in

the evening (it’s the case of Chinese TMall and Jingdong) or even a very short

midnight window between 23:30 and 00:15 (the only Indian case of Infibeam

retailer). The remaining seven merchants, most of them belonging to Japanese

context and the other two are the South Korean grocers, allow instead to set the

exact date and time during the day. Therefore, the issue of unattended home

delivery is quite well addressed by Asian countries.

Country Day/time window choice Total

China no 1

yes 4

China Total 5

India no 8

yes 1

India Total 9

Japan no 4

yes 10

Japan Total 14

South Korea no 3

yes 2

South Korea Total 5

Total 33 Table 157 - Asian retailers' day/time choice


135

Dealing lastly with the description of contacts established before the final

delivery fulfillment between courier and customers, we can observe that the

situation is quite poor, excepted for some more numerous cases found in the

Japanese country. Unfortunately, most of these Japanese cases (the three

merchants providing confirmation and delivery notification and one of the two

noting delivery only) are just sending an e-mail for notifying the reach of a

certain step in the delivery process, which is the most impersonal and least

effective method of connecting with customers. Opposite is the case of the fifth

Japanese merchant, Rakuten, which via mobile application not only provides a

forecast of the expected time for the delivery process at the moment of order

confirmation, but then advices the customer 15 minutes before the delivery is

going to occur. South Korean case of Gaenso clothes’ seller just involves the

dispatch of a text as notification of order confirmation, while the same

notification is provided by Indian The Mobile Store but through a phone call

made by a retailer’s employee 10 minutes after the order has been taken in

charge. Lastly, the Chinese traditional informatics retailer Suning sets up a phone

call between the final customer and its assigned courier in order to arrange all the

details regarding the delivery. We can therefore conclude that from the side of

direct contacts with customers, the Asian offer is quite poor of interesting cases,

with the exception of the particularly innovative initiative set up by the Japanese

Rakuten.

4.1.6 Conclusions and insights from first empirical analysis

The single-variable classifications have allowed to answer to all the questions,

while the double-variable analyses have provided additional and more deep

information on the last three questions.

Starting with single-variable classifications, we can summarize, variable by

variable, the obtained insights:

Country Pre-delivery contacts Total

China details arranged before delivery 1

China Total 5

India confirmation note 1

India Total 9

Japan confirmation and delivery note 3

delivery note 2

Japan Total 14

South Korea confirmation note 1

South Korea Total 5

Total 33 Table 158 - Asian retailers' contacts


136

Service provider: the practice of partnering with one logistics operator

exclusively in order to build a strong relationship, to personalize and

improve the service together is not much diffused among merchants

operating in the online sector. Only the United States account for a at

least sufficient number of cases (23 percent of the overall merchants), but

only because they resort to crowd-sourcing logistics models and therefore

they are linked to one specific operator providing its mobile application

and its network of couriers, which has to be matched with the merchants’

needs. An higher recourse to partnerships, when retailers are not able to

perform their own logistics activities by themselves, could be a way of

making delivery services always more specific and fast.

Nature of the merchants’ business (i.e. Dot Com/traditional): Dot Com

retailers represent a minority of the overall cases in American and

European countries; Germany, Spain and Italy reports a bit higher

percentages of online pure players with respect to United Kingdom and

United States, but they correspond to the merchants offering the slowest

services (most of them not constituting an object of interest because they

take more than 24 hours to be performed); while US, UK and French Dot

Com retailers, even if representing a smaller share of the national overall

actors, account for interesting services in terms of delivery timing,

especially in the field of Clothing commodity sector. Japan follows a trend

which is in line with the one of these three just mentioned countries (with

a strong occidental characterization), while for the other Asian countries

the situation is exactly the opposite: in fact they report a majority of Dot

Com cases. So we can observe that online markets developed earlier in

time are characterized by a strong presence of traditional players, while

lately born online contexts are theatre of a strong contribution of newly

born actors specialized in the eCommerce only.

Technologic devices’ support (i.e. desktop/mobile): the situation is more

mixed for what concerns this variable. The percentage of merchants

having developed a mobile access for increasing the degree of market

penetration and the frequency of access is pretty high in almost all

American and European countries (excepted for Italian situation, which is

less developed with respect to its neighbouring countries). In the Asian

continent instead we can find two countries with a strong penetration of

mobile applications among web retailers (India and China), an almost

equilibrated context between mobile and desktop technological support in

South Korea (there is a little higher presence of merchants offering access

to their website via desktop only), while mobile accesses find very low

development in the Japanese country. Being the market less developed

and players having a weaker market position in economic terms, Asian


137

retailers find less advantages in developing such technologies or probably

customers do not attach a so significant added value to them. Overall, the

mobile apllications’ penetration is quite high and so same are the

advantages implied.

Sectors: the two sectors counting overall the highest amount of web

merchants are Clothing and Informatics & general electronics; this

happens in particular in the American and European continents, even if

the share between the two can vary; in fact Clothing occupies the first

position (if we exclude the group of minor sectors collected in the Others

cluster and not internally homogeneous) in US, UK, France and Spain,

while Germany and Italy report a higher share of the Informatics sector.

Also General has a significant presence in some European countries (e.g.

United Kingdom and Germany) and we can notice the interesting case of

Italy with a strong presence of merchants operating in the Publishing

industry (which is a quite unusual sector for web development and in fact

it comprehends all the slowest delivery services). As seen before for the

nature of the business, Japan is closer to the occidental situation than to

the oriental one also on this variable, with Informatics and Clothing as

most populated industries. For what regards the other Asian countries

instead the situation is different: Clothing sector finds a big presence only

in the South Korean territory, while in China and India the mostrly

populated industry is the General one; Informatics too loses relevance.

This suggests a differenciated approach for further moves: while these last

Asian countries need to increase their footprint in more traditional

globally developed sectors, in order also to make themselves competitive

on a worldwide level, the other countries objective has to be the one of

populating with online initiatives new industries such as Grocery and

Others, in order to increase the offer as mush as possible.

Delivery timings: the biggest portion of US online merchants offers same

day delivery options, while for most of the other occidental countries the

most served option is the next day one. Asian countries instead report a

situation which is closer to the American one, offering mainly same day

services. Really fast deliveries instead (i.e. the one taking less than six

hours in order to be carried out) represent a small percentage of the

overall retailers and we can find few interesting cases mostly in the United

States, France and India, with a poorer participation of United Kingdom,

Germany, Spain, China and Japan. While this trend of fast deliveries is so

uncommon in all the countries and will surely be object of future

investments everywhere, the main limitation is related to the relative

slowness of European cases with respect to the other continents, which

can be a sign of low degree of experimentation and innovation up to now.


138

Costs: most countries impose a fixed delivery fee in order to be sure of

paying back efforts for the delivery service provision (especially if it is

outsourced) no matter the amount of money paid for ordered items; this

happens in fact in the United States, all the European countries and also

Japan, always more following occidental trends. The other three Asian

countries instead apply in most cases a fee which varies according to the

amount of money paid for the order, the size and weight of the products

to be transported and the distance to be covered; this is the expression of a

more flexible service, which allows customers to have a sort of “control” on

their fee. A variable fee is the mirroring image of a variable cost structure

for most Asian web companies, which in this way are also able to offer fast

services without incurring in too high investments; on contrary, US and

Europe (together with Japan) are more stuck in a situation of fixed

investments, which makes them less willing to innovate in flexible and fast

services.

Geographical coverage: almost in all countries the percentage of

merchants able to offer their delivery services in the whole national

territory is higher than the one of retailers with only a local coverage, with

the exception of India in which the number of local operators far

overcomes the one of national ones (8 out of the total 9 retailers). This

means that all countries have developed a certain degree of homogeneity

in the service provision, but it is also due to the fact that many initiatives

are next day and therefore have a significant amount of time available for

reaching also the further territories.

Logistics type: while crowd-sourcing innovative models are applied only in

the US context (excepted for one French case), in all the European

countries and in Japan outsourced logistics operators play a major role in

the eCommerce. Opposite is instead the case China, India and South

Korea in which a much relevant portion of merchants have developed

their own internal logistics. The strong recourse to outsourcing in Europe

and Japan sets a limitation to the development of the delivery services,

imposing a way of working which is standardized and homogeneous

among all market actors in a certain country. In order to be competitive

for what regards speed of the service, a more personalized model is

required, that is represent in the Asian continent by internal logistics

(mainly due to the lack of a widespread diffusion of the technology and

the infrastructures needed for the application of crowd-sourcing in

countries such as China and India), while in the United States it coincides

with crowd-sourcing.

Transportation means: few are the merchants openly declaring of

exploiting one or more particular kind of vehicles for the delivery service


139

provision. By concentrating on this limited amount of retailers, we can

observe as in almost all the European and Asian countries the employed

means are nothing very innovative: in fact we find vans, refrigerated vans

for the Grocery sector and airplanes in few cases of outsourced operators

having an air fleet for fast transportation over long distances. In France we

can see the rise of a couple of cases in which merchnats’ couriers have also

the bicycle as an alternative and this use of individual transportation

means such as bicycle, motorbike and car finds its biggest diffusion in the

United States, pushed by the development of crowd-sourcing models and

therefore to the recourse by independent couriers to their own owned

vehicles. This expresses again the limitation in services speed up in the

European countries, where almost no vehicles allowing to skip the city

traffic congestion are employed. The most innovative cases are

represented by drones in the US, that eliminate the need of a courier and

the condition of traffic, and electric bicycles in China, with a particular

interest to eco-friendly ways, but much has to be still done in this

direction.

Last-mile alternatives: the most diffused alternative to traditional home

delivery is represent by Click & Collect solutions, in which orders are

issued online and then personally collected by customers in the physical

stores (meaning that we are referring to traditional multichannel

retailers); it is spread in all the examined countries, but it often involves

not very fast timings, going beyond the next day availability if orders are

not already present in the store at the moment of order submission, while

they are usually offered in faster timings in the Asian countries. Some

merchants offer also other points for collection of ordered items, which

usually are collection points owned by the outsourced logistics operators

employed in the delivery services or convenience stores such as petrol

stations, little shops, etc; this mainly happens for those Dot Com player

not owning a network of physical stores for collection and mainly in

European countries. Another alternative is represented by the parcel

locker, which constitutes a big advantage as it doesn’t require that courier

and customer find each other at the same time in the delivery location,

but allows order delivery and pickup to occur in different moments,

increasing delivery efficiency; however this alternative is present in just

one British merchant. The issue of unattended home deliveries is therefore

not enough tackled among actual web retailers and a lack of really fast

alternatives (such as fast pickup in store or parcel lockers or other even

more innovative methods) can be reported in every country; this

represents a strong limitation, especially in those countries which present


140

the highest degree of development (i.e. United States which have no other

alternative excepted for Click & Collect in long times).

Real-time tracking: the tracking of the order in all its steps along the

delivery journey is instead an option offered by many players in every

country.

Date/time window choice: the arrangement of an appointment or, even

better, the choice of a specific time window for delivery reception is not a

much diffused option in most countries, especially in the United States (in

which only few cases of time slot choice are available) and the European

countries other than United Kingdom, in which the majority of merchants

allows to arrange an appointment date. In the Asian countries instead, or

at least in China and Japan, the majority of retailers offers not only the

opportunity of choosing a date, but also of selecting a very specific time

slot (lasting two hours in the better case and more or less four in the

worst) for delivery, being so sure of not missing the moment of order

arrival. This again represents a lack of service improvement for what

concerns delivery failure in those countries which are expected to perform

the best services.

Pre-delivery contacts: even if not so copious, there is a sufficient number

of merchants establishing a contact with customers before the delivery

takes place, always with the general objective of increasing service

efficiency and satisfaction and reducing failure; mainly these contacts

consist of a text or an e-mail for sending notifications in the moment of

order confirmation or beginning of shipment/delivery process; in few

cases instead the courier calls the customer in order to arrange all the

details before the process starts, while in some other cases (which

correspond to the employment of crowd-sourcing models) a lot of

information about the courier are made available to the customer,

including his/her name, picture and phone number. These cases are the

most interesting ones as they actually establish a real contact and they

mainly occur in the United States. For the other countries instead more

standard notifications are sent.

4.2 Second empirical analysis: double-variable classifications


141

In order to perform a deeper analysis and classification of the overall 112

merchants selected from the top national rankings by sales’ volumes and

constituting an object of interest for deep study as they carry out logistics

services for final home delivery to customers that take not more than the next

day with respect to order submission to be finalized, a second empirical analysis

has been executed, in which not only one single variable of the database is

described alone, but two variables are crossed in order to get additional insights

on these initiatives.

The commodity sector has been fixed as one of the two variables considered

in all the crossings, in order to highlight particular differences among industries

in the same geography and also to observe how similarly or differently the

retailers belonging to the same business sector could behave depending on other

context features. Then according to what has been driven out from previous

classifications, four are the crossings that have been made as expectations of

getting additional insights from those were particularly high:

A) Commodity sector versus merchants’ business nature (Dot Com pure

player or traditional multichannel retailer);

B) Commodity sector versus geographic coverage (national or local);

C) Commodity sector versus type of logistics provider (internal, crowd-

sourcing or outsourcing);

D) Commodity sector versus peculiarity of utilized transportation

means.

Each of these categorizations has been made in a first moment on a global

scale and then has been split according to the same geographic clusters that has

been considered for the previous classifications as they have showed to be pretty

much comparable one with the other in terms of internal homogeneity and

amount of relevant initiatives found (i.e. United States, United Kingdom, rest of

European countries including France, Germany, Italy and Spain and Asian

continent grouping together China, India , Japan and South Korea).

An additional subdivision has also been applied because different timings of

delivery have been discovered to present much diverse features; therefore, this

second more focused analysis has been carried out by considering next day

merchants alone as well as same day deliveries’ providers alone and then another

distinct attention has been paid to the group of merchants providing fast

services, which can be globally addressed to as the ones taking less than six hours

in order to be completed.

4.2.1 Commodity sector – merchants’ business nature


142

4.2.1.1 Next Day

Global

Commodity sector Dot Com pure

player Traditional

multichannel Total

Clothing 9 10 19

Cosmetics & Perfumery

2 2

General 1 8 9

Grocery

2 2 Informatics & general electronics 3 8 11

Others

6 6

Publishing

1 1

Total 13 37 50 Table 159 - sector vs. channel next day global

Starting from the slowest cases among the ones under focus (the merchants

offering next day delivery services, which are also the most copious cluster), we

can observe how the presence of Dot Com pure players is particularly relevant in

the Clothing industry (accounting for almost a half of its actors). Informatics &

general electronics sector too reports the presence of some Dot Com players

(corresponding to its 27 percent), while for all the other industries actually no

online pure players are present (with the exception of the one single case in the

General industry). This trend may be explained by the fact that Clothing and

Informatics sectors are the ones having experienced up to now the highest

development in the online channel with respect to others, therefore for newly

entrants companies the strategy of selecting that channel only could bring to

lower market risks in terms of sales’ potential with respect to all the other

sectors.

Let’s then give a more specific view to each geographical zone separately.

US

Commodity sector Traditional Total

Clothing 3 3

Cosmetics & Perfumery 2 2

Grocery 1 1

Informatics & general electronics 1 1

Others 3 3

Total 10 10 Table 160 - sector vs. channel next day US

Focusing on the US situation only, we can see that no retailers offering next

day delivery services to their customers are Dot Com pure players. This

phenomenon could be due to the fact that US pure online players represent the

best practices worldwide in terms of service level and therefore they are all able

of providing faster and more personalized services; while next day merchants are


143

all traditional actors that have just added the online channel to its business but

they do not consider it as their core business and so their strategy of web service

improvement is not so pushed. We can also observe as this happens in all the

commodity sectors interested by next day deliveries, first among the others

Clothing sector, followed by the group of Other minor industries and then by

Cosmetics & Perfumery, with a smaller presence of Informatics and Grocery.

Clothing sector is so the one experiencing the most of next day services, meaning

that it is the one for which the provision of faster options may represent a lower

perceived added value in the eyes of final consumers with respect to other

industries.

UK

Commodity sector Dot Com Traditional Total

Clothing 3 3 6

General

2 2 Informatics & general electronics 2 2 4

Others

2 2

Total 5 9 14 Table 161 - sector vs. channel next day UK

Differently from US situation, a relevant presence of Dot Com operators can

be found in the United Kingdom, in which they represent a 36 percent of the

overall cases. However the trend is exactly the one described for the general

overview, that is the presence of online specific actors only in the Clothing and

Informatics sectors (on top, accounting for a half of the overall cases in both

industries), while in no other sector merchants put in place the strategy of

focusing on the online channel only.

Other European countries (France, Germany, Italy and Spain)

Opposite situation for what concerns the other European countries: Dot Com

pure strategy remains very little diffused among merchants operating in the next

day delivery context, excepted for few sporadic cases in the industries accounting

for the biggest portion of initiatives, which are Clothing in the French context

and General sector for what concerns Germany.


144

Table 162 - sector vs. channel next day Europe

Not much relevant are the Italian and Spanish situations, in which it could

seem to have a prevalence (in Italy) or at least a half presence (in Spain) of Dot

Com pure players, but the number of overall next day initiatives is so limited that

it is difficult to drive out generally valid conclusions from this analysis. What

could be instead surely noticed is that also in these two countries Dot Com

merchants operate in the Clothing sector, which is also the only industry whose

actors offer next day delivery services.

Asian countries (China, India, Japan and South Korea)

Country Commodity sector Dot Com Traditional Total

China Informatics & general electronics

1 1

China Total 1 1

India Others

1 1

India Total 1 1

Japan Clothing

1 1

General

1 1

Informatics & general electronics 1 2 3

Japan Total 1 4 5

South Korea Clothing 2

2

South Korea Total 2 2

Total 3 6 9 Table 163 - sector vs. channel next day Asia


France Clothing 2 1 3

General

2 2

Grocery

1 1

Informatics & general electronics

1 1

Publishing

1 1

France Total 2 6 8

Germany Clothing

1 1

General 1 3 4


1 1

Germany Total 1 5 6

Italy Clothing 1

1

Italy Total 1 1

Spain Clothing 1 1 2

Spain Total 1 1 2

Total 5 12 17


145

The Asian situation is almost similar to the one of most European countries

and US, with a predominance of traditional multichannel merchants for the next

day initiatives. Indeed, no Dot Com players can be found in the Chinese and

Indian countries, while one only case is present in Japan and it belongs to the

quite well developed Informatics sector. Interesting to notice how instead South

Korea distinguishes itself from its Asian neighbors by having Dot Com pure

players only in the next day context, both belonging to the Clothing industry; this

phenomenon could be explained by the relatively more recent development of

the online market; Dot Com actors are experiencing therefore a degree of

innovation which is a bit back warded with respect to other countries and so up

to now they are not able to manage services faster than next day.

4.2.1.2 Same day

Global


Clothing 1 11 12


1 1

General 2 5 7

Grocery 2 5 7


Others 2 5 7

Publishing 1 2 3

Total 12 39 51 Table 164 - sector vs. channel same day global

For merchants arranging same day deliveries the overall percentage of Dot

Com and traditional players is similar to the one of next day operators (24

percent of Dot Com and 76 percent of traditional). However differently from

what has been found in the next day environment, the commodity sectors

comprehending the highest amount of initiatives is Informatics & general

electronics (one third of the total Dot Com). In addition, much more numerous

are the sectors in which at least one Dot Com pure player is present, including

not only Clothing but also less developed industries in relation to the online

channel such as General, Grocery, Publishing and Others which include

Furniture and Flowers). We can therefore conclude that more industries are

interested by the presence of merchants specialized in the online channel and

offering services occurring within one day.


146

US


Clothing

6 6

Grocery 1 2 3


1 1

Others 2 3 5

Publishing

1 1

Total 3 13 16 Table 165 - sector vs. channel same day US

The number of same day Dot Com cases is not very relevant in the United

States (just the 18 percent). But it’s interesting to notice the fact that the only

industries with few pure online initiatives are not the ones more developed in

general: in fact, Clothing and Informatics report no merchants at all, while we

can observe players in Grocery and Other sectors (which consist in detail of

Home & Furniture and Flowers).

UK

Commodity sector Traditional Total

General 2 2

Grocery 1 1


Others 1 1

Total 6 6 Table 166 - sector vs. channel same day UK

Dot Com players have an even less relevant presence in the UK same day

context with respect to the next day one, rather they are absent at all; United

Kingdom continue to present a really scarce amount of online pure players. An

interesting observation regards the fact that in general in the same day context of

this country more traditionally developed industries, especially Clothing,

completely lose their relevance.

Other European countries (France, Germany, Italy and Spain)

Also same day context in the other European countries reports a prevalence of

traditional multichannel retailers, excepted for a couple of cases in France and

Italy belonging to the Informatics sector.


147


France Clothing

2 2


1

France Total 1 2 3

Germany Cosmetics & Perfumery

1 1


1 1

Germany Total 2 2

Italy General

1 1


1

Italy Total 1 1 2

Spain Clothing

1 1

Publishing

1 1

Spain Total 2 2

Total 2 7 9 Table 167 - sector vs. channel same day Europe

Asian countries (China, India, Japan and South Korea)


China Grocery 1

1


China Total 2 1 3

India Clothing 1

1

General 2 1 3


1

Others

1 1

India Total 4 2 6

Japan Clothing

2 2

General

1 1


5 5

Japan Total 8 8

South Korea Grocery

2 2

Publishing 1

1

South Korea Total 1 2 3

Total 7 13 20 Table 168 - sector vs. channel same day Asia

Significantly higher amount of Dot Com players in the Asian geography for

what concerns same day options. The most interesting countries in this sense are

China and India, reporting a 67 percent of initiatives each; some of the populated

industries are the generally more developed Clothing and especially Informatics,

but there are also some relevant cases in Grocery and mainly General sectors.


148

Evidently being countries of more recent development and spread in the online

market, it has been easier to born as Dot Com players instead of moving from a

more traditional to an online specialized business. Japan instead had a sooner

development of the web channel, more resembling the European context and this

is reflected in the table, in which we can observe that every retailer operating in

the online market has also a traditional channel of physical stores. South Korea

sees too a majority of traditional merchants and in general presents cases of same

day initiatives only in a very unusual sector, which is Publishing, showing a

certain backwardness in this sense with respect to its Asian neighbors.

4.2.1.3 Less than six hours

Global


General 1 1 2

Grocery

2 2


Others 1

1

Total 3 8 11 Table 169 - sector vs. channel <6h global

Also in this fastest context of deliveries made in very short timings (only few

hours), we can observe a prevalence of traditional merchants. Players operating

this kind of services are mainly companies belonging to the Informatics & general

electronics industry (with one only case of Dot Com retailer), together with

Grocery sector (that however remains a sector typically multichannel), General

(few cases, but there is a presence of both pure Dot Com and multichannel

merchants) and one pure online player in another minor industry. Very

interesting to notice that the strongly online developed Clothing industry is

completely excluded from this cluster of services, meaning that it doesn’t

represent a sector in which few hours deliveries constitute a real value added for

customers, because otherwise (especially in some countries as US and UK)

companies could have invested in putting in place such kind of services.

US


General 1

1


1 1

Total 1 1 2 Table 170 - sector vs. channel <6h US

The two fast cases in the United States are perfectly equilibrated, one Dot

Com player belonging to the General sector, the other operating in the


149

Informatics industry but a traditional merchant working in more market

channels.

European countries (UK included)

Country Commodity sector Traditional Total

France Grocery 1 1


France Total 2 2

Germany Informatics & general electronics 1 1

Germany Total 1 1

Spain General 1 1

Spain Total 1 1

UK Grocery 1 1

UK Total 1 1

Total 5 5 Table 171 - sector vs. channel <6h Europe

For European countries (with the exception of Italy that doesn’t even present

cases of merchants performing fast deliveries) there are only companies initially

born as traditional and then expanded in the eCommerce business. Interesting to

notice as Informatics & general electronics plays a role in this context, again

together with Grocery and General.

Asian countries


China Informatics & general electronics 1

1

China Total 1 1

India Informatics & general electronics

2 2

India Total 2 2

Japan Others 1

1

Japan Total 1 1

Total 2 2 4 Table 172 - sector vs. channel <6h Asia

Also in the Asian continent there is a country (i.e. South Korea) not

presenting any initiative of this kind of speed. In addition, India accounts only

traditional multichannel players. However, China and Japan represent a different

case of interest because the only operator they have able to serve its customers in

such limited times is also a pure Dot Com player; it deals only with companies

which are actually born to offer such fast options in a very specific channel that is

the eCommerce.


150

4.2.2 Commodity sector – geographical coverage

4.2.2.1 Next day

Global

Commodity sector Local Coverage National Coverage Total

Clothing 3 16 19


2 2

General

9 9

Grocery

2 2


11 11

Others

6 6

Publishing

1 1

Total 3 47 50 Table 173 - sector vs. coverage next day global

For what concerns next day deliveries, the very biggest majority of merchants is

able to cover with its service the whole national territory. Only three are the cases

of retailers not able to go beyond a local coverage and they all belong to the

Clothing industry: the Japanese Point operates its service only in some selected

cities (Tokyo, Kanagawa, Saitama, Chiba, Ibaraki, Gunma, Tochigi, Yamanashi),

reaching however a certain coverage (even if not national); on the contrary, the

American Victoria’s Secret and the English Marks & Spencer can deliver products

on the next day of order submission just in few selected postcodes, covering

shorter distances.

The geographical split is irrelevant due to the homogeneity of this national

coverage trend almost worldwide.

4.2.2.2 Same day

Global


Clothing 12

12


1

General 4 3 7

Grocery 6 1 7


Others 5 2 7

Publishing 3

3

Total 39 12 51 Table 174 - sector vs. coverage same day global

We can observe a definitely opposite direction moving to same day deliveries:

indeed, the 76 percent of merchants is not able to offer its services if in a limited


151

zone. The sectors in which the higher number of retailers is able to work at a

national level are Informatics and General, with few cases in Grocery (particularly

interesting due to the high degree of perishability of products involved in the

delivery process) and Other sectors (which are Home & Furniture and Flowers).

On the opposite case coverage is exclusively local for all the other sectors, in

particular Clothing (100 percent of merchants) and Grocery (6 cases out of 7).

US


Clothing 6

6

Grocery 3

3


1

Others 4 1 5

Publishing 1

1

Total 15 1 16 Table 175 - sector vs. coverage same day US

In the United States, considered the huge dimension of the overall national

territory, the only operator able to offer same day delivery in the whole country is

1-88-Flowers.com Inc., which exploits Deliv service provides and its densely

populated network of independent couriers found through a crowd-sourcing

model. In the Clothing industry (corresponding to the 38 percent) the biggest

part of same day retailers relies on external logistics providers (first of all Deliv

and Uber Rush) and of their crowd-sourcing networks, but they are not able to go

beyond the boundaries of local coverage; some can serve different cities (e.g. Foot

Locker together with Deliv serves Glendale, Los Angeles, San Francisco, San Jose

and Santa Clara; Neiman Marcus and Nordstrom instead resort on Uber Rush for

deliveries in Chicago, New York and San Francisco the first, while in Seattle and

Chicago the latter), while others can reach within the very same day of order

submission only few New York postcodes (e.g. Gilt and Saks). Also in the Grocery

sector (accounting for a 19 percent of the overall same day merchants) coverage is

local, especially due to the fact that logistics in most cases is internally owned

and managed (with the exception of Target which serves Boston and Minneapolis

by resorting to the outsourced logistics provider Dynamex) and that carried items

need to be kept in very controlled transport condition in order not to break the

temperature chain.

UK


General 1 1 2

Grocery

1 1


Others

1 1

Total 2 4 6


152

Table 176 - sector vs. coverage same day UK

The situation is opposite in the United Kingdom (which however has of

course a much more limited territory): in fact, two thirds of the retailers are able

to cover the whole country with their same day delivery options. Additionally

three out of these four merchants (Argos, Tesco and Farnell) can offer this service

with their own internal logistics, while just one resorts to outsourced couriers for

the delivery option. The ones instead able only to serve few selected postcodes

(i.e. the general merchant Next and the Informatics company Currys) leaves

distribution activities in the hands of external providers. The setup and the

management of an internal logistics channel surely constitutes an economic

effort and a market risk, but it could allow to offer a more homogeneous and

controlled service within higher distances.

Other European countries

Country Commodity sector Local Coverage National Coverage Total

France Clothing 2

2


1

France Totale 3 3

Germany Cosmetics & Perfumery 1

1


1

Germany Totale 2 2

Italy General

1 1


1

Italy Totale 1 1 2

Spain Clothing 1

1

Publishing 1

1

Spain Totale 2 2

Total 8 1 9 Table 177 - sector vs. channel same day Europe

In the other European countries almost no merchants are able to offer a

national same day service, excepted for one Italian case (D-Mail which operated

in the General sector and offers same day delivery option in Italy overall in

partnership with the express courier BRT). All these services however resort to

outsourced logistics provider and can serve one city only (and its adjacent zones

of course): Milan for Italy (ePrice together with TNT courier); Paris for France (Le

Bon Marchè and Brand Alley) or at most Lyon (C-Discount in partnership with

Colissimo and Chronopost); Barcelona (for Massimo Dutti) or Madrid (for

Casadellibro) in the Spanish country. Different is the service in Germany, in

which it is more spread even if not reaching the national coverage (Berlin,

Hamburg, Cologne, Dusseldorf, Hannover and Ruhr area for Notebooksbilliger


153

served by NBB Courier; many spread postcodes for Douglas retailer served by

DHL).

Asian countries

Country Commodity sector Local Coverage National Coverage Total

China Grocery 1

1


2 2

China Totale 1 2 3

India Clothing 1

1

General 3

3


1

Others 1

1

India Totale 6 6

Japan Clothing 2

2

General

1 1


Japan Totale 4 4 8

South Korea Grocery 2

2

Publishing 1

1

South Korea Totale 3 3

Total 14 6 20 Table 178 - sector vs. coverage same day Asia

Interesting to notice, differently from previous geographies, that in China and

Japan instead the majority or at least one half of same day merchants is able to

cover the whole country with its delivery service. In both countries the sector

with largest coverage is Informatics, with one only case also of Japanese retailer

belonging to the General sector. Among the two Chinese cases, one exploits an

external courier for performing the delivery (Dangdang), while the other uses an

internal logistics (Gome Electrical Appliance). Japanese merchants instead for the

large majority have left the management of logistics activities to outsourced

operators, excepted for one merchant having kept it internally and being anyway

able to cover the whole country (Dospara); the other cases of national coverage

report the exploitation of one preferential courier company (Sagawa Express) and

the recourse to air transportation. India instead has no cases of same day retailers

with national coverage (even if many of them are able to serve a big amount of

cities, e.g. 116 cities served by Firstcry, a ten by Myntra and Flipkart); similarly

South Korean company operating in the Publishing industry covers a big number

of cities, while the two grocers just two or at most three cities.


154

4.2.2.3 Less than 6 hours

Global

Commodity sector Local Coverage Total

General 2 2

Grocery 2 2


Others 1 1

Total 11 11 Table 179 - sector vs. coverage <6h global

For what regards services faster than same day, no merchant in no country is

able to offer a spread geographic coverage. In some cases the served cities can be

numerous (28 US cities for Amazon Prime Now, 8 French cities for Darty, 20

German cities for Conrad merchant, 39 Spanish cities for El Corte Inglès, 6

Chinese cities for Jingdong and many Indian ones for The Mobile Store); two of

these retailers operate in the general sector, but most of them belong to

Informatics. In the other cases instead the service regards one only city or even

just few districts (San Francisco or New York for Apple, Paris for Carrefour,

London for Sainsbury, Chennai for Univercell and Tokyo for Rakuten); three

cases again belong to Informatics industry, while two to Grocery.

4.2.3 Commodity sector – type of logistics service

4.2.3.1 Next day

Global

Commodity sector Internal Outsourcing Total

Clothing

19 19


2 2

General 1 8 9

Grocery 1 1 2


Others 2 4 6

Publishing

1 1

Total 5 45 50 Table 180 - sector vs. logistics next day global

Next day options in the large majority of cases are carried out by professional

logistics operators, able to perform final delivery for a big variety of different

merchants without particular specialization in the services. Few are the cases of

internal logistics appositely developed for this kind of services and they mostly

belong to industries less traditionally developed in the online channel: excepted

for the few cases in the general and informatics sectors, we can find one out of


155

the two grocery merchants and other minor industries corresponding in

particular to Eyewear and Office supplies.

US

Commodity sector Internal Outsourcing Total

Clothing

3 3


2 2

Grocery 1

1


1 1

Others 1 2 3

Total 2 8 10 Table 181 - sector vs. logistics next day US

In the US 80 percent of cases relies on outsourcing and in many of them no

preferential courier is indicated; in other cases instead we can find FedEx (for

HP), UPS (for J Crew) and USPS (for light products distributed by Musicians’

friend). The merchant having an internal logistics instead are one selling Office

supplies (Office Depot) and the other in the Grocery sector (Peapod). All the

cases are also traditional multichannel merchants.

European countries (UK included)

Country Commodity sector Internal Outsourcing Total

France Clothing

3 3

General

2 2

Grocery

1 1


1 1

Publishing

1 1

France Totale 8 8

Germany Clothing

1 1

General 1 3 4


1 1

Germany Totale 1 5 6

Italy Clothing

1 1

Italy Totale 1 1

Spain Clothing

2 2

Spain Totale 2 2

UK Clothing

6 6

General

2 2


Others

2 2

UK Totale 1 13 14

Total 2 29 31 Table 182 - sector vs. logistics next day Europe


156

Also European countries have a big portion of next day merchants relying on

outsourced logistics providers for deliveries, excepted for two cases: the first is

the UK informatics retailer and Dot Com player Misco; the other is the German

Otto Group having setup an internally own logistics spin-off, the sub-company

Hermes, for performing deliveries for itself and also for offering logistics services

to other retailers (e.g. Baur Versand); it is not only the unique German retailer

having specialized its logistics service, but also the only one pure online player.

While most of British companies resorting to outsourcing do not rely on a

preferred operator (10 out of 13, with the exceptions of Clothing companies Marks

& Spencer and The Hut Group and the Informatics Carphone Warehouse, all

resorting to DPD), in France and Germany many retailers exploit a preferred

outsourced operator: in Germany we can find Deutsche Post (for Clothing retailer

Klingel), DHL (for informatics Cyberport) and DPD (for general merchants

Printus and Schneider); in France FedEx Express (for general Rue du Commerce),

TNT (for the again general Oxybull) and mostly Chronopost (four merchants in

very different sectors such as grocer Auchan, Clothing companies

Showrommprivè and Sarenza until informatics LDLC). Italy and Spain do not

present significant cases (just one Italian and two Spanish, both resorting to

outsourcing).

Asian countries


China Informatics & general electronics

1 1

China Totale 1 1

India Others 1

1

India Totale 1 1

Japan Clothing

1 1

General

1 1


3 3

Japan Totale 5 5

South Korea Clothing

2 2

South Korea Totale 2 2

Total 1 8 9 Table 183 - sector vs. logistics next day Asia

In India we can find one case of merchant with internal logistics

infrastructure for expanding its business to the online channel (it is the Eyewear

company Lenskart). On contrary, in the other countries we can observe only

outsourcing practice: in South Korea there are two Dot Com clothing retailers

(Gaenso and Minsshop) exploiting different couriers; in Japan 4 out of 5 cases are

multichannel companies not having a preferred operator (excepted for clothing


157

Point choosing preferably Yamato as its courier), while the only Dot Com

merchant is the informatics NTT-X which partners with Sagawa Express; in China

no particular cases can be highlighted.

4.2.3.2 Same day

Global

Commodity sector Crowd-sourcing Internal Outsourcing Total

Clothing 5 1 6 12


1 1

General

1 6 7

Grocery

6 1 7

Informatics & general electronics 1 4 9 14

Others 4 1 2 7

Publishing

3 3

Total 10 13 28 51 Table 184 - sector vs. logistics same day global

Moving to same day options, the situation changes significantly: indeed, the

percentage of merchants having developed their internal logistics increases a lot

(corresponding to 25 percent) and a good percentage appears (20 percent)

presenting the recourse to crowd-sourcing. The commodity sectors in which we

can find the highest development of internal logistics are Informatics & general

electronics (in the case in which the merchant would like to personalize in a

particular way the delivery service) and especially Grocery (industry in which the

peculiarity of transported items implies the advantage of developing a personal

fleet of refrigerated vans). Crowd-sourcing instead, excepted for some disparate

cases in some sectors, finds large use in the Clothing sector, probably thanks to

the particularly low complexity of the items to be transported and to the

advanced degree of presence in the online market of this industry, fact that

guarantees a widespread diffusion and therefore a certain easiness in “recruiting”

independent individuals for delivery provision.

US


Clothing 5

1 6

Grocery

2 1 3


1

Others 4 1

5

Publishing

1 1

Total 10 3 3 16 Table 185 - sector vs. logistics same day US

In the United States the most largely employed modality is crowd-sourcing: 10

out of 16 merchants in fact rely on a network of independent couriers for


158

performing final deliveries. Most of them (6 out of 10) manages the network

through the Deliv app (whose couriers travel in their own car); in the other 4

cases we can find retailer resorting to couriers by bicycle, mostly through Uber

Rush (for the three clothing merchants) and Etsy ASAP (for the retailer operating

in Other sectors, in particular Home & Furniture). The three players having

instead an internal logistics belong mainly to Grocery sector (Amazon Fresh

and Walmart) and one case of Office supplies. The three left cases resorting to

outsourcing are one grocer (Target that exploits the preferred courier Dynamex),

the publishing Barnes&Nobles (resorting to Google Express for same day

deliveries) and clothing Saks (without preferred courier).

European countries (UK included) Table 186 - sector vs. logistics same day Europe

In the UK crowd-sourcing category disappears, but the one of internal

logistics has a relevant presence (a 50 percent of the overall cases): the merchants

with internal logistics belong always to Grocery sector (Tesco), but also General

(Argos) and Informatics (Farnell). The other cases of outsourcing present

different sectors but do not report any preferred courier. In the rest of European

countries instead there are only outsourcing cases. In Spain both cases (in

Clothing and Publishing sectors) do not have any preferred courier. In France the

two clothing cases do not resort to a preferred operator, while for Informatics

sector the preferential courier is Colissimo or Chronopost. In Germany each


France Clothing

2 2


1 1

France Totale 3 3

Germany Cosmetics & Perfumery

1 1


1 1

Germany Totale 2 2

Italy General

1 1


1 1

Italy Totale 2 2

Spain Clothing

1 1

Publishing

1 1

Spain Totale 2 2

UK General 1 1 2

Grocery 1

1


Others

1 1

UK Totale 3 3 6

Total 3 12 15


159

merchant has its own partnered courier: NBB Courier for Notebooksbilliger

(informatics), DHL for Douglas (Perfumery); the same thing happens in Italy

with TNT serving the informatics Dot Com ePrice and BRT for general D-Mail.

Asian countries


China Grocery 1

1


China Totale 2 1 3

India Clothing 1

1

General

3 3


1

Others

1 1

India Totale 2 4 6

Japan Clothing

2 2

General

1 1


Japan Totale 1 7 8

South Korea Grocery 2

2

Publishing

1 1

South Korea Totale 2 1 3

Total 7 13 20 Table 187 - sector vs. logistics same day Asia

Also in Asian countries crowd-sourcing is not employed anymore, but the

recourse to internal logistics is more relevant than in European countries. In

China the internal infrastructure has been developed not only for Grocery sector

(Tmall owned by Alibaba with its own logistics branch Cainiao), but also for

Informatics (Gome Electrical Appliance); the third same day merchant however

resorts to outsourcing without having a preferred courier (the informatics

Dangdang). In India two are the cases of internal logistics, one in Clothing

(Myntra) and the other in Informatics (Flipkart with its internal logistics branch

Ekart); the remaining four cases resorting to outsourcing belong to the less

developed sectors for what regards eCommerce of General and Baby Care

products, without the indication of a preferential logistics operator except for the

case of Firstcry (courier XpressBees). In South Korea two out of three cases

belong to Grocery and have an internal logistics (Lotte Mart and E-Mart), while

the third relies on a preferentially outsourced provider (Yes24 resorting to GTX).

Instead in Japan just one retailer exploits its own logistics and it belongs to the

Informatics sector (Dospara), while all the other cases utilize outsourcing with a


160

prevalence of preferred courier’s specification (Yamato or Fast Retailing for

Clothing companies, Sagawa Express for General and Informatics industries).

4.2.3.3 Less than six hours

Global


General

2

2

Grocery

1 1 2 Informatics & general electronics 2 4

6

Others

1

1

Total 2 8 1 11 Table 188 - sector vs. logistics <6h global

In the context of fast services, the presence of outsourced couriers is almost

null, with a large majority of cases of internal logistics and a few merchants

resorting to crowd-sourcing models. The merchants belonging to Grocery and

providing so fast services are really few and they at most present the internal

logistics’ alternative to outsourcing. For the General sector instead there are only

cases of internal logistics, while for the Informatics not only internal but also

crowd-sourcing (despite the peculiarity of products to move, which can be

particularly voluminous and heavy). In the US the internal logistics is employed

in the General sector (Amazon Prime Now and Air), while crowd-sourcing can be

found in the Informatics sector (Apple with couriers riding bikes in San Francisco

and New York). In the UK there is one only case in Grocery with internal logistics

(Sainsbuty with the Chop Chop network of couriers by bike). In the rest of

Europe there are two cases of internal logistics (the German informatics Conrad

with its branch Tiramizoo and the Spanish El Corte Inglès in the General sector);

while in France we can find one outsourcing (LaPoste serving Carrefour grocer

with couriers riding a bike in Paris) and one crowd-sourcing case (the informatics

Darty exploiting Colisweb network). In Asian countries instead we can only find

internal logistics because crowd-sourcing has seen no development up to now;

we only have few merchants operating in the Informatics industry which have

developed their own infrastructure to expand their traditional business into

eCommerce (the Indian Univercell and The Mobile Store) or to start activities as

pure online players (the Japanese Rakuten and the Chinese Jingdong).


161

4.2.4 Commodity sector – used transportation means

4.2.4.1 Next day

Global

Commodity sector Plane Van Refrigerated van Total

Clothing

3

3

General

2

2

Grocery

1 1


3

Others

1

1

Total 2 7 1 10 Table 189 - sector vs. vehicles next day global

For what regards next day, few are the cases of merchants declaring of

resorting to a particular type of transportation means for performing deliveries.

Regarding Grocery sector, the need is the one of having a fleet of refrigerated

vans (due to the perishability of products). In some cases (7 out of 51) merchants

state that they use vans and these are the mostly web developed sectors:

Clothing, Informatics and General. In a couple of cases however the mean used

for delivery is the plane: they are cases in the Informatics sector, in which the

high value density of moved products (i.e. products that may have a small size

but have a high cost) justifies the recourse to such an expensive transportation

modality. In the US one only merchant declares of exploiting vans uniquely and it

relates to Office Depot, a merchant which have expanded from traditional to

online channel and have decided to invest in its own delivery fleet. There is one

only other case of merchant with internal logistics (the grocer Peapod) and it

doesn’t state anything about the vehicles used, but according to the nature of its

business probably it may employ temperature-controlled vehicles. In the UK

some more cases of merchants choosing one preferential business exist: 5 out of

14 declare of utilizing only vans for delivery and they always refer to the more

web advanced sectors; all these cases exploit outsourced couriers and ask them to

use vans exclusively; in three cases it is the same courier (DPD) which only uses

vans. In France there is one only case out of 8 and it is the grocer Auchan

exploiting refrigerated vans. In Germany we can find two more cases: they deal

with Hermes courier, put in place by pure Dot Com player Otto Group in the

moment of development of the online business and become a real logistics

operator to which other merchants could resort (like for instance Baur Versand);

this courier has a fleet of vans for its deliveries. No cases instead in Italy and

Spain. Lastly, for what concerns Asian countries, Japan only presents two cases of

merchants resorting exclusively to air transportation: both of them belong to the

Informatics sector and rely on the same outsourced courier Sagawa.


162

4.2.4.2 Same day

Global

Commodity sector Airplane Car Bike Van Refrigerated

van Bike/

motorbike Total

Clothing

2 1

2 5

General 1

1

2

Grocery

6

6 Informatics & general electronics 2 1

1

4

Others

3

1

1 5

Publishing

1

1

Total 3 7 1 3 6 3 23 Table 190 - sector vs. vehicles same day global

Moving to same day deliveries, merchants declaring of resorting to one or

more specific vehicles increase notably. Again here we can find the recourse to

fleets of refrigerated vans in the Grocery sector (two cases in US, one in the UK,

one in China and two in South Korea) and of traditional vans in more generic

General, Informatics and Office supplies sectors (one in US, one in UK and one in

Japan). There are also three cases of recourse to air transport and as before

especially for the Informatics sector (one in the United Kingdom and one in

Japan). In addition to next day however, we can start to observe the use of more

“individual” vehicles: in some cases indeed bicycles and motorbikes are mostly

employed ( in the US and mainly for Clothing industries, together with a case in

the Others category belonging to Home & Furniture). Interesting also to notice

the case of exclusive utilization of the bicycle: it is still a US merchant operating

in the Clothing industry, in which moved items have no particular criticalities in

terms of size and weight. However the highest number (7 out of 51) is represented

by retailers doing exclusive use of the car: not only in Clothing, but also in

Informatics (for products of small dimensions) and other minor sectors as Drugs,

Flowers and Publishing; again the only country interested by these initiatives are

the United States. All the cases of exclusive utilization of cars and bicycles, which

come from US as already said, refer to merchants resorting to crowd-sourcing

models for the delivery: cars are the preferred vehicle by Deliv and Postmates,

while bicycles are mostly employed by Uber Rush independent couriers, having

however a more limited geographic coverage. Sectors are quite varied, with a

general presence of sectors with little sized products (excepted for one case in the

Informatics sector which involves only small items). Again crowd-sourcing is the

model of the three couriers freely choosing their own vehicle: we refer to

Clothing and Home & Furniture sectors and to Postmates and Uber Rush

operators. In Barnes&Nobles case instead (Publishing sector) logistics is


163

outsourced to Google Express, which provides its employee with car or van.

When involved items allow to do it, the recourse to vehicles allowing to easier

navigate in the urban traffic is pushed. In three cases of internal logistics instead

the mostly employed mean is the van: refrigerated for Amazon Fresh and

Walmart grocers, traditional for Office Depot (non-perishable products). Very

few are the US cases in which no transportation mean is specified and they are all

linked to logistics outsourcing. In the UK and in Asian countries (in the other

European countries no cases of specific means can be found), together with the

disappereance of the crowd-sourcing model, also the recourse to individual

vehicles disappears: indeed, in the UK we have just three cases of merchants

having internal logistics (one grocer using refrigerated vans, one general

merchant exploiting vans and one informatics employing the plane); in Japan one

case of vans’ use for the only internal logistics’ merchant (the informatics

Dospara) and two cases of retailers resorting to air transportation by outsourced

operator Sagawa Express; in China and South Korea three cases overall of grocers

having invested in their own fleet of temperature-controlled vans.

4.2.4.3 Less thansix hours

Global

Commodity sector Bike Drones Van Bike/motorbike Electric

bike Total

General

1

1

Grocery 2

2


1 2 1 4

Total 2 1 1 2 1 7 Table 191 - sector vs. vehicles <6h global

Moving to delivery options performed in few hours, merchants not specifying

any preferential transportation means are even less. Vans and motorbikes remain

in a limited number and exclusively linked to Informatics sector (which involves

the products with the highest volumes and therefore requiring bigger vehicles).

Interesting to notice instead the increasing interest towards the bicycle, not only

for small sized informatics items but especially in the Grocery sector for small

expenses which involve a limited amount of products. Additionally new vehicles

can be found, among which the electric bikes according to the recent trend of

environmental concern and drones in order to make deliveries even more

efficient and effective by eliminating the courier’s need. In the US we can find

two merchants: the general retailer Amazon using drones and being able to serve

28 cities in half an hour after having received the order; the informatics Apple

resorting to Postmated crowd-sourcing model, with couriers utilizing their own

bike or motorbike at their choice. In the UK instead we can find one of the two

cases of grocer delivering through bicycles and it is Sainsbury, that to expand its


164

business online has developed an internally controlled network of employed

couriers managed through an application called Chop Chop and delivering

ordered items by bicycle in London. The other grocer with bike delivery is the

French Carrefour, relying in outsourcing to LaPoste operator for deliveries in

Paris in one hour; still in France we can find the informatics Darty resorting to

crowd-sourcing operator Colisweb, which leaves couriers free to preferably

choose among bike and motorbike in 8 cities. In Germany instead van service for

the internal logistics of the informatics merchant Conrad. No cases in Italy and

Spain. In the end, for what concerns Asia, only China reports an interesting case:

it is the informatics retailer Jingdong, born as Dot Com player with its own

internal logistics of couriers which can use the traditional van or, as an

alternative, the electric bicycles for deliveries in six cities. Interesting to notice

how China addresses the topic of environmental sustainability proposing this

more “green” technology for delivery. The other merchants in India and Japan do

not specify any transportation means.

4.2.5 Conclusions ans insights from second empirical classifications

Moving then to double-variable classifications, we can get the following

insights:

Commodity sector versus business’ nature: summing up the analysis of the

commodity sector versus the business nature of merchants, we can state

that almost all the sectors are interested by online initiatives when next

day and same day delivery options are involved, while the number of

present industries reduces itself when moving to faster services and

especially Clothing industry disappears; knowing for how much time

Clothing companies have been operating online sales and how many of

them have gained a strong position in the market. This lack of fast services

mustn’t be a matter of backwardness of the sector with respect to others;

the most probable reason for this is that merchants have experienced the

fact that the effort for setting up this kind of options is not worth as it

won’t bring to a significant service improvement from customers’

perspective. In addition the most present sectors in the next day context

are only Clothing, Informatics & general electronics and General (in

decreasing order of amount of initiatives) and all the others have a

significant numerical distance; differently from this, for what regards same

day environment also Grocery sector gains a relevant position, tied with


165

General industry. Going into detail of pure Dot Com players, we can

observe that for next day options almost only Clothing and Informatics

have few Dot Com players, while in the same day context other sectors

come up (e.g. General, Grocery, Publishing and Others), to return in the

end to few industries in the fast cases but different from the next day

situation: indeed, while Informatics keeps its presence, Clothing is

replaced by General and Other minor sectors. United States account for

no Dot Com players in the next day environment and few in the other

faster contexts, but in not traditionally developed sectors (Grocery and

Others). Europe overall (including also United Kingdom) reports instead a

relevant number of Dot Com players operating next day services, few

performing same day and zero for fast options. Asia instead has pure

online players in all the time contexts, especially for what regards same

day options in India and linked to Informatics, General and Grocery

sectors. Therefore Dot Come players are more present in countries of

more recent development in the eCommerce (typically Asian ones) and,

excepted for Informatics which has a relevant presence, in industries of

recent online invasion (mostly General and Grocery).

Commodity sector versus geographic coverage: by increasing the speed of

the service, the distances covered shorten themselves. Clothing merchants

are the ones with a particularly local spread (i.e. they represent the only

next day local and most of same day local options). The other industries

have different developments according to the country: Grocery is quite

local worldwide, but has a larger national coverage in the United

Kingdom; Informatics instead is very much nationally developed in the

Asian countries (especially in China and Japan). Lastly, US situation is the

most critical one from a point of national coverage due to the vastness of

its territory.

Commodity sector versus logistics type: outsourcing is the most utilized

practice in the next day options (90 percent of cases), with few internal

logistics cases as only alternative; it loses relevance in the same day

context, leaving the ground to both internal and crowd-sourcing practices

and almost completely disappears in case of fast deliveries. For the next

day context, the sectors mostly interested by outsourcing practices are

Grocery in the US, while General and Informatics in the European

countries; moving instead to same day and fast deliveries, internal logistics

mainly regards Informatics sector and Grocery and especially UK and

Asian countries. Crowd-sourcing instead can be found almost exclusively

in the United States and specifically for Clothing sector.

Commodity sector versus transportation means: to conclude, we can

observe that the number of merchants specifying the type of


166

transportation means utilized increases by speeding up the service

timings. In addition, for next day options we can only find cases of use of

vans (mostly for Clothing, General and Informatics sectors and mainly in

the UK), refrigerated vans (for Grocery in France) and planes for

Informatics industry (in Japan). By decreasing the time available for the

service provision, increases the presence of more individual vehicles and

this is strongly related to the presence of crowd-sourcing logistics: in fact,

for what concerns next day, individual means (bicycles, motorbikes and

cars) are employed only in the US and by independent couriers “recruited”

via crowd-sourcing models, but still mostly for traditional industries such

as Clothing, Informatics and General. Coming to the fastest services, the

share of individual vehicles increases but it specifies in the Informatics

sector only; in the meantime, other innovative technologies are employed

in other less developed sectors (e.g. electric bikes in Grocery, drones in

General) while Clothing industry finds no place at all in this classification.


167

5. Final conclusions

The previous research has been developed with the objective of filling the

gaps arisen from the literature review; for sake of clarity, the questions

representing the objective of the thesis were:

1) Which are the most relevant real examples of merchants operating in the

eCommerce at a worldwide level?


going beyond the next day from order reception? And how many among

them offer even faster options?

3) Which commonalities and/or differences exist among initiatives belonging

to different geographical areas?






services?

The collection of data from rankings and then from single websites, together

with their multiple classifications and in-depth analyses, have provided answers

which canbe summarized as follows:

1) The most relevant cases of actual merchants operating in the eCommerce

nowadays belong to United States, immediately followed by United

Kingdom and then, some steps away, by France and Germany. The rest of

the European continent and the Asian countries represent a still too

under-developed context with respect to the first players (especially in

comparison with the United States). The worldwide market is still in

general strongly characterized by traditional retailers having added

eCommerce as their secondary or even third business, in an attempt of

implementing a multichannel strategy in order to increase their often

already stable market share; however, most of them have already

understood the potential of mobile devices’ diffusion and have developed

applications to increase the degree of pervasiveness into the market. Most

relevant actors in the actual context still belong to already strongly web

developed sectors of Clothing and Informatics, but other more recent

industries such as General and Grocery sectors are moving forward.

2) The portion of merchants performing deliveries in which the e-fulfillment

process lasts less than twenty-four hours at worldwide level corresponds

to an almost 46 percent of all the eCommerce merchants; of course this

value changes depending on the geography: it is a bit higher in the US


168

continent (52 percent), balanced a lower value in the Asian continent (38

percent). The European context, if United Kingdom is excluded, reports an

amount of cases not far from the one of oriental countries (37 percent),

but if adding the British merchants (which provide fast services in the 88

percent of national cases) the overall situation of Europe moves close to

the worldwide average value (reaching a 48 percent). Again United

Kingdom and United States provide the highest quantity of cases of

interest. However splitting these cases into more precise time windows

needed for delivery service provision, we find out that most of really fast

initiatives (i.e. the ones taking less than six hours) do not have a precise

country of belonging as they mainly are few sporadic cases or pilot

projects spread in almost all the global territory; instead interesting to

notice is the fact that while most of initiatives in American and European

countries relate to next day options, the most developed trend in the

Asian geographies is the one of same day deliveries.

3) Some of the insights got in order to answer to this question have been

already reported below. We can add that while for next day deliveries no

significant differences among countries can be found (excepted for the fact

that Dot Com next day players are in limited number in Asia and in the

US, while they constitute a more significant portion of the European

market), same day deliveries differentiate themselves according to the

country of development: indeed, while United States and Europe see a

limited diffusion of these delivery options, Asian countries led by India

report a huge development of same day services. In addition, while almost

all cases of interest can reach only a local coverage, in the United Kingdom

and in some Asian countries (mainly China and Japan) some merchants

are able to offer also more spread options that reach a more national

coverage.

4) The main sectors interested by fast initiatives in general are Clothing and

Informatics, but we can observe some dedicated trends according to the

country and the delivery timing. In fact, for what regards same day

deliveries, while in the US and Europe overall we can mainly find projects

in commodity sectors of recent development (such as Grocery and Others)

Asia provides a higher amount of examples belonging to sectors such as

Informatics and General, that in the other countries have experienced a

precedent development but then have often remained stuck to the next

day delivery timings. Additionally, some sectors comprehend merchants

that are able to cover higher distances with their fast delivery services

(maybe due also to the peculiarity of items transported), which are

Grocery sector in the UK context and Informatics industry in the Asian

continent.


169

5) The most delivery services increase their speed, the most we can observe

that retailer leave the recourse to outsourced logistics operators in favor of

internal infrastructures properly developed for providing a more

personalized and controlled service; another interesting trend which

ensures a certain speed of the overall e-fulfillment process avoiding big

investments is represented by the crowd-sourcing model application, but

it remains quite under-developed, with a relevant presence only in the

United States. For what concerns vehicles utilized in transportation, vans

(or refrigerated vans in the case of grocers) are leaving the ground to

lighter and faster means such as bicycles and/or motorbikes, especially

individually owned ones for the crowd-sourcing cases. Few cases of major

interest can be found (one of use of electric bicycles and the other project

with drones), but they only represent an almost irrelevant amount of pilot

and testing projects under development.


170

BIBLIOGRAPHY

- Lee H.L., Whang S. (2001). Winning the Last Mile of E-Commerce. MIT

Sloane Management Review. USA.

- Punakivi M., Yrjola H., Holmstrom J. (2001). Solving the last mile issue:

Reception box or delivery box? International Journal of Physical

Distribution and Logistics Management. Finland.

- Kamarainen V., Saranen J., Holmstrom J. (2001). The reception box

impact on home delivery efficiency in the e-grocery business. International

Journal of Physical Distribution and Logistics Management.

Finland.

- de Koster, R. (2002). Distribution structures for food home shopping.

International Journal of Physical Distribution and Logistics

Management. Netherlands.

- Delaney-Klinger K., Boyer K.K., Frohlich M. (2003). The return of

online grocery shopping: A comparative analysis of Webvan and Tesco's

operational methods. TQM Magazine. USA.

- Tarn J.M., Razi M.A., Wen H.J., Perez Jr A.A. (2003). E‐fulfillment: the

strategy and operational requirements. Logistics Information

Management. USA.

- de Koster, R. (2003). Distribution strategies for online retailers. IEEE

Transactions on Engineering Management . Netherlands.

- Mitrovic-Minic S., Laporte G. (2004). Waiting strategies for the dynamic

pickup and delivery problem with time windows. Transportation Research

Part B: Methodologies. Canada.

- Lasserre F. (2004). Logistics and the Internet: Transportation and location

issues are crucial in the logistics chain. Journal of Transport Geography.

Canada.

- Boyer K.K., Hult G.T.M. (2005). Extending the supply chain: Integrating

operations and marketing in the online grocery industry. Journal of

Operations Management. USA

- Lunce S.E., Lunce L.M., Kawai Y., Maniam B. (2006). Success and

failure of pure-play organizations: Webvan versus Peapod, a comparative

analysis. Industrial Management and Data System. USA.

- Scott J.E., Scott C.H. (2008). Online grocery order fulfillment tradeoffs.

Proceedings of the Annual Hawaii International Conference on

System Sciences. USA.

- Gagliardi, J.P., Ruiz A., Renaud J. (2008). Space allocation and stock

replenishment synchronization in a distribution center. International

Journal of Production Economics. Canada.


171

- Cho J.J.-K., Ozment J., Sink H. (2008). Logistics capability, logistics

outsourcing and firm performance in an e‐commerce market.

International Journal of Physical Distribution and Logistics

Management. USA.

- Gong Y., De Koster R. (2008). A polling-based dynamic order picking

system for online retailers. IIE Transactions. Netherlands.

- Song R., Cherrett T., Mc Leod F., Guan W. (2009). Addressing the last

mile problem: Transport impacts of collection and delivery points.

Transportation Research Method. UK

- Ghiani G., Manni E., Quaranta A., Triki C. (2009). Anticipatory

algorithms for same-day courier dispatching. Transportation Research

Part E: Logistics and Transportation Review. Italy

- Hu K.-Y., Chang T.-S. (2009). An innovative logistics model for multi-

channel retailing. Journal of the Chinese Institute of Industrial

Engineers. China

- Hu K.-Y., Chang T.-S. (2010). An innovative automated storage and

retrieval system for B2C e-commerce logistics. International Journal of

Advanced Manufacturing Technology. China

- Agatz N., Campbell A., Fleischmann N., Savelsbergh M. (2011). Time

slot management in attended home delivery. Transportation Science .

Netherlands

- Runciman B. (2011). Do IT yourself? ITNOW: Oxford Journals. UK

- Durand B., Gonzalez-Feliu J. (2012). Urban Logistics and E-Grocery:

Have Proximity Delivery Services a Positive Impact on Shopping Trips?

Procedia - Social and Behavioral Sciences (Seventh International

Conference on City Logistics, Mallorca, Spain) . France

- Xiao H., Qian J., Tang X. (2013). B2C e-commerce vehicle delivery model

and simulation. Information Technology Journal. China

- Vanelslander T., Deketele L., van Hove D. (2013). Commonly used e-

commerce supply chains for fast moving consumer goods: comparison and

suggestions for improvement.. International Journal of Logistics

Research and Applications. Belgium

- Sareen H. (2013). Once refined, same-day delivery will be commonplace.

Wired. USA

- Morganti E., Seidel S., Blanquart C., Dablanc L., Lenz B. (2014). The

Impact of E-commerce on Final Deliveries: Alternative

Parcel Delivery Services in France and Germany. Transportation research

Procedia. France

- Morganti E., Dablanc L., Fortin F. (2014). Final deliveries for online

shopping: The deployment of pickup point networks in urban and suburban

areas. Research in Transportation Business and Management. France


172

- Wang X., Zhan L., Ruan J., Zhang J. (2014). How to choose "last mile"

delivery modes for E-fulfillment. Mathematical Problems in

Engineering. China

- Gruber J., Kihm A., Lenz B. (2014). A new vehicle for urban freight? An

ex-ante evaluation of electric cargo bikes in courier services. Research in

Transportation Business and Management. Germany

- Cleophas C., Ehmke J.F. (2014). When Are Deliveries Profitable?:

Considering Order Value and Transport Capacity in Demand Fulfillment for

Last-Mile Deliveries in Metropolitan Areas. Business and Information

Systems Engineering. Germany

- Ehmke J.F., Campbell A.M. (2014). Customer acceptance mechanisms for

home deliveries in metropolitan areas. European Journal of Operational

research . USA

- Visser J., Nemoto T., Browne M. (2014). Home Delivery and the Impacts

on Urban Freight Transport: A Review. Procedia - Social and Behavioral

Sciences (Eight International Conference on City Logistics, Bali,

Indonesia). Netherlands

- Ducret R. (2014). Parcel deliveries and urban logistics: Changes and

challenges in the courier express and parcel sector in Europe — The French

case. Research in Transportation Business and Management. France

- Hausmann L., Herrmann N.-A., Krause J., Netzer T. (2014). Same-day

delivery: The next evolutionary step in parcel logistics.

McKinsey&Company. Germany

- Xu R., Liu X., Xie Y., Wang F., Zhang C., Yang Y. (2014). Logistics

scheduling based on cloud business workflows. Proceedings of the 2014

IEEE 18th International Conference on Computer Supported

Cooperative Work in Design, CSCWD 2014. China

- Kumagai J. (2014). A day in the life of digi-key. IEEE Spectrum. USA

- Wang J.J., Xiao Z. (2015). Co-evolution between etailing and parcel express

industry and its geographical imprints: The case of China. Journal of

Transport Geography. China

- Koster F., Ulmer M.W., Mattfeld D.C. (2015). Cooperative traffic control

management for city logistic routing. Transportation research Procedia.

Germany

- Li Y., Deng D., Demiryurek D., Shahabi C., Ravada S. (2015).

Towards fast and accurate solutions to vehicle routing in a large-scale and

dynamic environment. Lecture Notes in Computer Science. China

- Zu Q., Sun B. (2015). Optimization of order picking work flow at the e-

commerce logistics centers. Lecture Notes in Computer Science. China


173

- Tsamis N., Giannikas V., McFarlane D., Lu W., Strachan J. (2015).

Adaptive storage location assignment for warehouses using intelligent

products. Studies in Computational Intelligence. UK

- Wang Y., Zhang D., Liu Q., Shen F., Lee L.H. (2016). Towards enhancing

the last-mile delivery: An effective crowd-tasking model with scalable

solutions. Transportation Research Part E: Logistics and

Transportation Review. China

- Sun Y., Wei K., Qiao Z., Wen J., Jiang T. (2016). A personalized service

for scheduling express delivery using courier trajectories. Proceedings -

2016 IEEE International Conference on Web Services, ICWS 2016.

China

- Savelsbergh M., Van Woensel T. (2016). City logistics: Challenges and

opportunities. Transportation Science. USA

- Schrotenboer A.H., Wruck S., Roodbergen K.J., Veenstra M., Dijkstra

A.S. (2016). Order picker routing with product returns and interaction

delays. International Journal of Production Research. Netherlands

- Liu L., Li K., Liu Z. (2016). A capacitated vehicle routing problem

with order available time in e-commerce industry. Engineering

Optimization. China

- Harrington T.S., Singhai J., Kumar M., Wohlrab J. (2016). Identifying

design criteria for urban system last-mile solutions -A multi-stakeholder

perspective. Production Planning and Control. UK

- Saskia S., Marei N., Blanquart C. (2016). Innovations in e-grocery and

Logistics Solutions for Cities. Transportation research Procedia.

Germany

- van Duin J.H.R., de Goffau W., Wiegmans B., Tavasszy L.A., Saes M.

(2016). Improving Home Delivery Efficiency by Using Principles of Address

Intelligence for B2C Deliveries. Transportation research Procedia.

Netherlands

- Yu Y., Wang X., Zhong R.J., Huang G.Q. (2016). E-commerce Logistics in

Supply Chain Management: Practice Perspective. Procedia CIRP. China

- Lee H.L., Chen Y., Gillai B., Rammohan S. (2016). Technological

disruption and innovation in last-mile delivery. Stanford Business School.

USA

- Li J., Huang R., Dai J.B. (2017). Joint optimisation of order batching and

picker routing in the online retailer’s warehouse in China. International

Journal of Production Research. China

-


174

SITOGRAPHY

- http://www.nxtbook.com/nxtbooks/verticalweb/asia500_2013

- http://www.nxtbook.com/nxtbooks/verticalweb/europe500_2013

- http://www.nxtbook.com/nxtbooks/verticalweb/top500_2013

- http://www.geekwire.com

- http://www.retaildive.com

- https://techcrunch.com

- http://www.macrumors.com

- http://onemileatatime.boardingarea.com

- https://www.internetretailer.com

- http://www.twincities.com

- http://money.cnn.com

- https://www.retailmenot.com

- http://fortune.com

- http://uk.businessinsider.com

- http://luxurylaunches.com

- https://www.timeout.com

- http://chb44.com

- https://www.retail-week.com

- http://www.lineaires.com

- http://retailanalysis.igd.com

- http://postandparcel.info

- https://www.wizishop.fr

- http://locationinsider.de

- https://www.deutsche-startups.de

- https://www.modaes.es

- http://www.telegraph.co.uk

- http://internetretailing.net

- http://www.postaltechnologyinternational.com

- https://www.theguardian.com

- http://gadgets.ndtv.com

- http://www.thehindu.com

- https://yourstory.com

- https://www.shoppirate.in

- http://www.medianama.com

- http://www.gadgetsnow.com

- http://www.business-standard.com

- http://thebridge.jp

- http://www.newsonjapan.com

- http://www.enterpriseinnovation.net


175

- http://www.chainstoreage.com

- http://www.alizila.com

- http://www.prnewswire.com

- http://www.innovativechina.com

- http://blog.a1express.com

- http://mengnews.joins.com

- http://www.kejorahq.com

- https://www.logisticaefficiente.it

- http://koreabizwire.com

- http://english.hankyung.com

- http://koreajoongangdaily.joins.com

Additionally, all the single websites of the retailers present in the rankings

have been browsed and deeply investigated.

FAST LOGISTICS IN THE B2C eCOMMERCE: A GLOBAL OVERVIEW FORTIN… · fast logistics in the b2c ecommerce: a global overview 1 politecnico di milano school of industrial and information

Documents