The Effect of Logistics Capability, Information Technology ...umkeprints.umk.edu.my/6641/1/The Effect of Logistics Capability.pdf · The Effect of Logistics Capability, Information

The Effect of Logistics Capability, Information

Technology Implementation and Innovation Ability on

Road Transportation Logistics Performance

by

Nur Fadiah Mohd Zawawi

A thesis submitted in fulfilment of the requirements for the degree of

Master of Entrepreneurship

Faculty of Entrepreneurship and Business

UNIVERSITI MALAYSIA KELANTAN

ii

THE EFFECT OF LOGISTICS CAPABILITY,

INFORMATION TECHNOLOGY IMPLEMENTATION

AND INNOVATION ABILITY ON ROAD

TRANSPORTATION LOGISTICS PERFORMANCE

NUR FADIAH MOHD ZAWAWI

MASTER OF ENTREPRENEURSHIP

ii

ACKNOWLEDGEMENTS

Thank you to Allah s.w.t for His opportunity, health, love and blessing, for taking me to

this stage, upon my completion of the study for Master in Entrepreneurship (Management). Shalawat is also sent to Prophet Muhammad ملسو هيلع هللا ىلص who had delivered the

truth to human beings in general and Muslim in particular. During the period of study,

there have been many treasurable people who have motivated and guided me through

the whole work of this research. They are my backbone through thick and thin.

In this valuable chance, I would first like to convey my deepest appreciation and thanks

to my precious family especially my dear husband, Marmizal Mohd Nawi, my beloved

parents, Haji Mohd Zawawi Mohd Daud and Hajah Che Rohainu Che Jafaar and my

beloved siblings for their endless love, pray, understanding and inspiration till the day I

completed this study. You are my forever supporters.

A sincere appreciation and thanks goes to my main supervisor, Prof. Dr. Sazali Abd

Wahab, the Dean of Malaysian Graduate School of Business and Entrepreneurship for

his cheerful encouragement, inspiration, and help in giving me such a positive working

climate. Many thanks to my co-supervisor, Dr. Abdullah Al-Mamun for his patience in

guiding me along the journey of this study.

I also would like to say a lot of thanks to my respected lecturers in Faculty of

Entrepreneurship and Business, Assc. Prof. Dr. Mohd Rafi Yaacob and Mr. Zuraimi

Abd Aziz for spending their time to share knowledge and experience. Your journeys

motivate me to work harder. To my fellow cliques of postgraduate studies, thank you

very much for your never ending support and encouragement. May our humble works

contribute to the nations.

To all my dear friends who have inspired me internally to stay focus in this academic

world, let us together cherish and share the knowledge for the sake of Allah s.w.t.

Thank you.

I hereby express my gratitude to all of them.

iii

TABLE OF CONTENTS

PAGE

THESIS DECLARATION I

ACKNOWLEDGEMENTS Ii

TABLE OF CONTENTS Iii

LIST OF TABLES Vii

LIST OF FIGURES Ix

ABSTRAK X

ABSTRACT Xii

CHAPTER 1 INTRODUCTION 1

1.1 Background of Study 1

1.1.1 Congestion and Its Impact 6

1.1.2 Empirical Evidences on Congestion’s Impact 8

1.1.3 Discussion 10

1.1.4 Definition of Terms 11

1.2 Problem statement 12

1.3 Research Questions 14

1.4 Research Objectives 15

1.5 Scope of Study 16

1.6 Significance of Study 16

1.7 Limitations of Study 18

CHAPTER 2 LITERATURE REVIEW AND HYPOTHESES

DEVELOPMENT

20

2.1 Introduction 20

2.2 The Concept of Logistics 20

2.3 Logistics and Supply Chain 22

2.4 Resource-Based View (RBV) Theory 23

2.5 East Coast Region of Peninsular Malaysia 25

2.6 Logistics Service Providers (LSPs) 26

2.6.1 LSP’s Descriptions 26

2.6.2 Capability of LSPs and Firm Performance 27

iv

2.7 IT Implementation 30

2.7.1 Definition of IT 30

2.7.2 IT Implementation and Firm Performance 31

2.8 Innovation Capability 35

2.8.1 Revolution of Innovation to Capability 35

2.8.2 Innovation Capability and Firm Performance 36

2.9 Firm Size as a Moderator 39

2.10 Logistics Firm Performance 40

2.11 Discussion 44

2.12 Theoretical Framework 43

2.13 Chapter Conclusion 45

CHAPTER 3 RESEARCH METHODOLOGY 47

3.1 Introduction 47

3.2 Research Design 47

3.3 Target Population 48

3.4 Sample Size 48

3.5 Response Rate 49

3.6 Unit of Analysis 50

3.7 Data Collection Method 51

3.8 Measurement Variables 51

3.9 Pilot Study 53

3.10 Procedure for Data Analysis 54

3.11 Data Cleaning and Transformation 55

3.12 Normality Test 55

3.13 Skewness Test 56

3.14 Multicollinearity Test 56

3.15 Descriptive Statistics 57

3.16 Reliability Test 58

3.17 Validity Test 58

3.18 Scatterplot 59

3.19 Correlation Analysis 60

v

3.20 Regression Analysis 61

3.21 Moderated Multiple Regression 61

3.22 Chapter Conclusion 64

CHAPTER 4 RESULTS AND DISCUSSION 65

4.1 Introduction 65

4.2 Data Analysis 65

4.2.1 Normality Test 65

4.2.2 Skewness Test 66

4.2.3 Frequency Distribution 66

4.2.3.1 Frequency Distribution 66

4.2.3.2 Size of Firm 76

4.2.4 Descriptive Statistics 78

4.2.5 Reliability Test 79

4.2.6 Bivariate Correlation 81

4.2.7 Scatterplot and Correlation Analysis: Hypotheses Testing 82

4.2.7.1 Capability of LSPs and Firm Performance 82

4.2.7.2 IT Implementation and Firm Performance 83

4.2.7.3 Innovation Capability and Firm Performance 85

4.2.8 Multicollinearity Statistics 86

4.2.9 Standard Multiple Regression 87

4.2.10 Moderated Multiple Regression (MMR): Hypotheses Testing 90

4.2.10.1 Moderating Effect of Firm Size on the Relationship of

Capability of LSPs and Firm Performance

90

4.2.10.2 Moderating Effect of Firm Size on the Relationship of

IT Implementation and Firm Performance

94

4.2.10.3 Moderating Effect of Firm Size on the Relationship of

Innovation Capability and Firm Performance

97

4.3 Discussion 100

4.4 Chapter Conclusion 103

vi

CHAPTER 5 CONCLUSION 105

5.1 Introduction 105

5.2 Key Findings 105

5.3 Implications of the Study 106

5.4 Limitations of the Study 109

5.5 Recommendations for Future Research 110

5.6 Overall Conclusion of the Study 111

REFERENCES 113

APPENDIX A 127

APPENDIX B 130

APPENDIX C 136

APPENDIX D 142

APPENDIX E 152

APPENDIX F 153

APPENDIX G 163

APPENDIX H 167

APPENDIX I 169

APPENDIX J 171

APPENDIX K 173

LIST OF TABLES

NO. PAGE

1.1 Costs of transport delays and disruptions 8

1.2 Seven classes of congestion impact and potential business

response

9

2.1 Performance indicators for effective and efficiency 44

3.1 Measurements of this study 52

3.2 Cronbach's Alpha for pilot survey 54

4.1 Demographic of respondents 67

4.2 Demographic of firms 70

4.3 Frequency of measurements 73

4.4 Mean and standard deviation 78

4.5 Value of Cronbach's Alpha for the actual survey 80

4.6 Bivariate correlations for independents variables 81

4.7 Correlation analysis for capability of LSPs and firm

performance

82

4.8 Correlation analysis for IT implementations and firm

performance

84

4.9 Correlation analysis for innovation capability and firm

performance

85

4.10 Model summary of standard multiple regression 87

4.11 ANOVA table 88

4.12 Coefficient for regression analysis 88

4.13 Model summary of firm performance, capability of LSPs and

firm size

91

4.14 Coefficients for variables involved 91

4.15 Model summary of firm performance, IT implementations and

firm size

94

4.16 Coefficients for the variables involved 95

4.17 Model summary of firm performance, innovation capability and

firm size

97

vii

viii

4.18 Coefficients for variables involved 98

ixi

LIST OF FIGURES

NO. PAGE

1.1 Dependency of seaports, airports and railway stations on road

transportation

5

1.2 Illustrated summarization of how congestion affects business

performance

10

2.1 Theoretical framework for this study 45

4.1 Percentage of highest education own by respondents 67

4.2 Positions of respondents in their organization 68

4.3 Working experience of respondents in current job 69

4.4 Working experience of respondents in current organization 69

4.5 Years of firms’ establishment 71

4.6 Characteristics of firms 72

4.7 Numbers of employees of a firm 78

xi

LIST OF ABBREVIATION

COL Capability of Logistics Service Providers

COL*FS Product Term of Capability of LSPs and Firm Size

EDI Electronic Data Interchange

ERP Enterprise Resource Planning

FP Firm Performance

FMM Federation of Malaysian Manufacturers

FS Firm Size

INNV Innovation Capability

INNV*FS Product Term of Innovation Capability and Firm Size

IT Information Technology

IT*FS Product Term of IT and Firm Size

LSPs Logistics Service Providers

MMR Moderated Multiple Regression

OLS Ordinary Least-squares

RBV Resource-Based View Theory

RFID Radio-frequency Identification

xii

Kesan Keupayaan Logistik, Implimentasi Teknologi Maklumat dan Kebolehan

Inovasi ke atas Prestasi Logistik Pengangkutan Jalan

ABSTRAK

Era globalisasi hari ini membuatkan para usahawan lebih aktif menjalankan aktiviti

perniagaan tanpa mengira sempadan negara. Setiap perniagaan yang dijalankan

memerlukan perkhidmatan logistik sama ada untuk perniagaan di dalam atau di luar

negara. Antara perkhidmatan yang paling penting adalah perkhidmatan logistik

pengangkutan jalan, demi melengkapkan kitaran logistik dan memastikan barangan

sampai ke destinasi yang sepatutnya. Malangnya, perkembangan perniagaan yang

positif ini telah membawa kepada isu kesesakan jalan raya yang kemudiannya memberi

kesan yang tidak baik kepada prestasi syarikat perkhidmatan logistik (LSPs)

terutamanya dari segi masa penghantaran dan peningkatan kos operasi. Dengan itu,

kajian ini telah mengadaptasi satu model untuk mengkaji bagaimana keupayaan LSPs,

pengaplikasian IT and keupayaan inovasi sesuatu syarikat LSPs memberi kesan kepada

prestasi syarikat itu sendiri. Selain itu, kajian ini juga mengkaji kesan saiz syarikat yang

bertindak sebagai perantara dalam model tersebut. Memandangkan kajian-kajian lalu

menunjukkan Pantai Timur Semenanjung Malaysia juga menghadapi masalah

kesesakan jalan raya yang melibatkan perkhidmatan logistik pengangkutan jalan, maka

kajian ini dilaksanakan di kawasan tersebut dengan tujuan menyediakan laporan terbaru

tentang keadaan di sana serta membantu rantau tersebut untuk mengembangkan

potensinya sebagaimana yang dirancangkan oleh Ekonomi Wilayah Pantai Timur.

Berlandaskan kajian kuantitatif, sebanyak 210 set soalan soal selidik telah diedarkan

kepada syarikat-syarikat LSPs di sekitar kawasan kajian. Sebanyak 81 soalan soal

selidik dikembalikan (38.57%) dan data tersebut dianalisa menggunakan SPSS.

Hasilnya, keputusan kajian mendapati keupayaan LSPs dan keupayaan inovasi

mempunyai hubungan signifikan yang positif terhadap prestasi syarikat LSPs itu

sendiri. Bagi pengaplikasian IT, keputusan menujukkan fenomena “productivity

paradox”, sebagaimana dapatan kajian-kajian yang terdahulu. Manakala, untuk kesan

pengantaraan, keputusan menunjukkan saiz syarikat mempengaruhi hubungan antara

keupayaan LSPs dan prestasi syarikat. Syarikat yang kecil memberi impak yang besar

kepada hubungan antara keupayaan LSPs dan prestasi syarikat. Dapatan-dapatan kajian

ini dilihat menampung kekurangan literatur dalam bidang logistik di Malaysia,

terutamanya dalam konteks Pantai Timur Semenanjung Malaysia. Lebih dari itu, kajian

ini adalah model pertama yang menggunakan saiz syarikat sebagai pembolehubah

perantaraan dalam kajian-kajian logistik. Dengan itu, dapatan ini memberi sumbangan

penting kepada ilmu pengetahuan yang sedia ada. Selain itu, kajian ini juga bertindak

sebagai informasi terkini buat bakal pelabur sama ada dari dalam atau luar negara untuk

membuat pelaburan di rantau tersebut. Tidak lupa juga, dapatan kajian ini berfaedah

untuk pihak kerajaan menambahbaik polisi yang sedia ada bagi memastikan prestasi

logistik di Malaysia setanding dengan negara-negara sedang membangun yang lain.

xiii

The Effect of Logistics Capability, Information Technology Implementation and

Innovation Ability on Road Transportation Logistics Performance

ABSTRACT

The globalization era makes business people today hustle and bustle doing their trade

boundlessly. Every trade needs logistics services to cater their activities either for local

or international business. Among the services, road transportation logistics service is

seem very vital in supporting other types of logistics transportations in order to

complete the logistics cycle. Hence, this phenomenon has created severe congestions

which then affect business performance of logistics service provider (LSP) firms

especially in terms of delivery delay and increment in operating cost. Due to these

issues, this study has adapted a model, investigating how capability of LSPs, IT

implementation and innovation capability relate with performance of road logistics

transportation. Additionally, this study also measured the moderating effect of firm size

on the examined relationships. Since previous literature found that the East Coast region

of Peninsular Malaysia faced with the congestions as a result of busy trade, this research

is tempted to investigate the region with the intention to provide latest report about the

situation there, thus helping the East Coast region to expand their potential, as planned

by the East Coast Region Development Council. Since this research is using

quantitative method, 210 questionnaires were distributed to LSP firms in the desired

research areas. With the final of 81 usable questionnaires (38.57%), the data was

analysed by using SPSS. The results found that the capability of LSPs and innovation

capability have positive significant relationships with firm performance. IT

implementation however produce “productivity paradox” phenomenon, parallel with

previous findings. Meanwhile, in terms of moderating effect of firm size, the results

found that firm size moderates the relationship of capability of LSPs and firm

performance. The relationship is found stronger in small firms compared to large firms.

Nevertheless, there is no moderating effect found for the relationships of IT

implementations and innovation capability with firm performance. The results of this

study bridge the gaps of previous literature which lack of logistics literature in

Malaysian context, especially in East Coast region. Moreover, this study is the first

model using firm size as a moderator variable in the logistics research. Therefore, the

results fill this gap and contribute importantly to the body of knowledge. Going further,

the study also gives latest information on logistics performance of the East Coast

region. This is very important to the potential investors, as their guidelines to invest in

the region, either local or foreign. Last but not least, the study might be beneficial for

our government to consider new improved policy if needed in order to enhance the

logistics performance in Malaysia, thus could stand steadily with other developing

countries in the world.

1

CHAPTER 1

INTRODUCTION

1.1 Background of Study

The concept of logistics outsourcing was traced quite far in history. It

started in the 1950s‘ and 1960s‘ with transportation and warehousing services.

In 1970s‘, the logistics services were upgraded to improve productivity and cost

reduction, while in 1980s‘, they concentrated on value-added services like

packaging, labeling and system support. Up to the 1990s‘, the logistics services

expended into numbers of services including import/export management, freight

forwarding, distribution, freight consolidation and reverse logistics (Mitra,

2008). This situation shows that logistics market has always been evolving in

order to cope with economic changes.

Intelligence (2013) reported that nowadays, the logistics market is once

again evolving to support the new trends of world trade. For instance, instead of

manufacturers‘ production in China, the geographic spread of logistics hubs is

changing and new ones are developed closer to greater customer‘s

concentrations. Thus, the industry is going through a shift in trade paths towards

developing markets such as to Brazil, Russia, South Africa and the Middle East

as well as South East Asia. As such, logistics providers are evolving service

offerings and expanding into these new geographic markets. As forecasted and

analyzed by Datamonitor (2010), the global logistics size will reach $4 trillion in

2

2013. The bigger the logistics size, the bigger the demand of logistics services

and vice versa.

This expansion of world‘s logistics industry is parallel with its growth in

Malaysia. Historically, in the 1950s and 1960s, agro-based sector like rubber,

palm oil, pepper and timber conquered Malaysian economy. In 1970,

agricultural sector contributed 30.9% to the Gross Domestic Product (GDP)

compared to only 14.8% from manufacturing sector. However, this percentage

increased after the announcement of Investment Incentives Act in 1968 and free

trade zones (FTZ) in 1971 where they enticed numbers of multinational

companies to launch export oriented operations with well infrastructures

facilities, competitive pay, as well as politically and economically stable region.

In the early 80‘s, Malaysian Government took initiatives to develop strength in

manufacturing sector through heavy industries such as automobile,

petrochemicals, cement and steel.

In the 1990s, Malaysia started to look forward in being a country with an

innovation-led economy (Hasnan, Noordin, & Osman, 2014). As reported by

Bank Negara Malaysia (2003), this effort was seen successful when the

manufacturing‘s sector in GDP rose to 33.1% in 1995 and it continued to

steadily arise and stabilized (Salina, 2004). The latest news from Bank Negara

(2013), GDP of manufacturing sector in Malaysia stabilized at 24% from 2009

to 2012 while MITI (2010) reported that exports of manufactured goods

increased by 11.6% to MYR461 billion from MYR413 billion in 2009 and

imports manufactured goods increased 19.9% to MYR430.5 billion from

MYR359 billion in 2009 (MITI, 2010).

3

Due to good expansion of manufacturing industry, logistics sector plays

a key role in supporting the industry as mentioned in the Third Industrial Master

Plan (IMP3) as an engine of growth with the target to increase GDP from 50.5%

in 2005 to 59.7% by 2020 (MITI, 2009). Not only IMP3, the logistics services is

also one of Malaysia‘s most important investments, together with other

components of service sector like Information and Technology Services,

Environmental Management Services, Medical and Healthcare Services etc.

(MIDA, 2012). The service sector is also supported by the National Key

Economic Areas (NKEAs) and contributed 55% to GDP in 2008 (MIDA, 2012).

Recently, MITI (2013) updated that service sector contributed 58% of GDP in

2011 and is targeted to reach 65% in 2020. Malaysia‘s Minister Industrial Trade

and Industry added, the service sector will contribute 60% to GDP by 2020,

making it a major contributor to Malaysia‘s economy in a very near ahead

(MITI, 2014b).

The Ministry of Science Technology and Innovation (MOSTI, 2010)

testified that Malaysia was fruitfully ranked at 24th tier in the Innovation

Competitiveness and was also successfully placed at 26th rank in the Global

Competitiveness Index for 2010-2011 session as a consequence from a favorable

achievement of the service sector (Hasnan et al., 2014). Walking through the

years, the logistics industry in Malaysia keeps growing and becomes one of the

most important sectors that supported the development of Malaysia as a whole

and is considered as one of the catalysts for the industrial development to link

with the international trade In IMP3, export trade is expected to increase to

MYR1.4 trillion in the year 2020 and total trade to increase to MYR2.8 trillion

4

(MITI, 2012). It is agreed by Banomyong and Supatn (2011) who said that

freight logistics activities are significant to support export activities.

In logistics sector, transportation is a very significant element of supply

chain (Tracey, 2004) and somehow it is considered as a backbone of logistics.

Tseng, Yue, and Taylor (2005) mentioned that transportation occupies one-third

of the amount in the logistics costs, therefore transportation system influences

the performance of logistics system vastly. The operation of transportation

determines the efficiency of moving products. The evolution in skills and

management principles enhances the moving load, service quality, delivery

speed, the usage of facilities, operation costs and energy saving. It can be

considered that transportation takes a decisive part in the manipulation of

logistics.

Furthermore, Rosena, Harlina and Sabariah (2008) and Sum, Teo, and

Ng (2001) confirmed that the vivid expansion in the external trade countries

such as Singapore, Malaysia, Indonesia and Thailand recently has resulted in an

increment of demand for more efficient and effective logistics services

especially logistics transportation service. This is crucial because the

performance of the industry will have an impact on the progress of the nation‘s

industrialization and its competitiveness in international trade.

Regarding to MITI (2009), Malaysia has four main modes of logistics

transportation which are land, sea, air and rail. Other than these four modes,

Malaysia also now involves in pipeline projects for the fifth mode of logistics

transportation. The Prime Minister previously has contributed an amount of

allocation for the pipeline projects (MITI, 2010), but the pipeline is not yet

5

considered as a main mode of transportation in Malaysia since it is still in the

development stages.

Meanwhile according to Penang Economic Monthly (2008) in Rosena et

al. (2008), logistics transportation services are including transport operators of

air, sea, road and rail; terminal operators and multimodal operators. Each of

these transportation modes; air, sea, road and rail are actually dependent on each

other. Air, sea and rail transportations are depending on road transportation like

trailers and trucks for haulage process from airports, seaports and railway

stations to the end point (consumers, factories, shop lots or warehouses).

Therefore, road transportation is very significant to complete the logistics

process holistically, as mentioned by Coyle (1996):

“Logistics is the process of planning, implementing and controlling the efficient,

effective flow and storage of raw materials, in-process inventory, finished goods,

services and related information from point of origin to point of consumption

(including inbound, outbound, internal, and external movements) for the

purpose of conforming to customer requirements”.

Figure 1.1: Dependency of seaports, airports and railway stations on road

transportation

Source: Own proposed concept

6

This research proposes a model that shows the dependency of seaports

(sea transportation), airports (air transportation) and rail stations (rail

transportation) with the road transportation, as shown in Figure 1.1. They need

trucks and trailers to haulage or distribute their products or goods to the end

users. Road transportation has the highest reliability to deliver goods from door

to door or warehouse to warehouse, depends to the types of road transportation.

For example, according to the National Bureau of Statistics (2011) in Mahpula,

Yang, Kurban, and Witlox (2013), out of 27,806.3 million tons total freight

traffic of the four major transportation modes in 2009 in Beijing, more than 76%

of cargo travels by road, 11.9% by rail and 11.4% travel by water.

According to David J. Bloomberg (2002), ―road transportations are

including cars, motorcycles, trucks and trailers‖. All of them are using roads as

their medium of travel. In logistics, trailers and trucks, which are also called as

motor carriers, have been used as transport for the delivery process. Therefore,

the combination of public users like cars and motorcycles with the logistics

motor carriers, it might cause road congestion.

1.1.1 Congestion and Its Impacts

Generally, congestion affects businesses negatively on deliveries,

business schedule, workers, customers and meeting with clients (Hartgen, 2007).

Hartgen (2007) did a survey on Charlotte businesses and he found that 78% of

businesses there consider congestion as a greater than average problem for their

business. For them, the traffic congestion interrupts business performance by

7

introducing time delays that can be hardly managed and avoided. Other than

Charlotte, this issue has been widely discussed especially in big countries like

Japan (Taniguchi, Noritake, Yamada, & Izumitani, 1999), UK (Trunick, 2004)

and China (Gui-yan, Zu-tuo, Zu, Jia-qi, & Lei-lei, 2007). McKinnon, Edwards,

Piecyk, and Palmer (2009) claimed that traffic congestion can spoil the

efficiency and quality of logistics operations.

Furthermore, Taniguchi et al. (1999) added, the congestion is pretty

worse in urban areas, partly due to increase of truck traffic, which led to increase

of transportation cost. This situation happened because of the fact that frequent

transportation of small capacity of goods decrease the cost of inventory as well

as satisfying consumer needs. It is true that such way can decrease inventory

cost, but when volume of traffics increase and network of the road are nearly in

full capacity, the vehicle movement becomes unbalanced and more risky to

incidents such as road works, breakdowns, accidents and bad weather, thus

giving bad impact on transit time, transportation cost and delivery reliability.

Most of the unfavourable effects of road congestion on performance of

logistics are usually related with this unreliability. In Malaysia for example, the

increase in commercial vehicle drivers has increased road accidents too. The

increment of accidents which involving lorry drivers (logistics transportation)

from 44,683 cases in 2008 to 65,944 cases in 2009 has made road accident as

one of the main major factors of death in Malaysia (Royal Malaysian Police

Force Record, 2010) in Daud, Mohamad, Hassan, and Yahya (2013). On the

other hand, Sankaran, Gore, and Coldwell (2005) suggested that congestion is

always being a catalyst of delays and rising costs, which might affect business

8

growth and increase service level. Furthermore, Systematics (2008) as well as

Short, Trego, and White (2010) said that from most previous transportation

literature, they found congestion as a cost factor, composed of operation

expansion and time delay. Badly, the delays were clearly lead to severe damage

of companies‘ image, customer relationships as well as their reputation (Zhang

& Figliozzi, 2010).

1.1.2 Empirical Evidences of Congestion‘s Impacts

Again, according to Hartgen (2007), congestion virtually affects all

angles of business like deliveries and shipping, business activities and workers-

customers relationship. It is proven that due to congestion, delivering and

receiving goods and merchandise cost of Charlotte business community lost

about 20.3% of delivery time. In short, that study claimed that traffic congestion

weakens business control and lengthen delivery time. Since the delay lead to

increase in operation cost, Zhang and Figliozzi (2010) did a study on importers

and exporters in China to observe the effect of the delay on their operating costs,

and the results are shown in Table 1.1.

Table 1.1: Costs of transport delays and disruptions

Transport Disruption Related Cost Importers Exporters

Increase administration workload and costs 42.9% 28.6%

Increase transport costs 28.6% 37.1%

Affect sales and promotion plans 35.7% 20.0%

Inventory costs 28.6% 2.9%

Account receivable and cash flow 0.0% 12.2%

Custom-port costs (inspection, storage, clearance, etc.)

7.1% 2.9%

Source: Zhang and Figliozzi (2010)

9

From Table 1.1, it is shown that the transportation delays of delivery

increased importers‘ and exporters‘ operating costs, especially in terms of

administration costs and transportation costs. The results simultaneously showed

the increment of operating costs charged by Logistics Service Providers (LSPs)

to their clients, due to the delays. Other than the delay and cost effects,

Weisbrod and Fitzroy (2011) from Economic Development Research

Incorporation, USA discussed the impact of congestion in a broader view of

economic and as a result, they divided the effects of congestion into seven

classes as well as their effects on LSPs‘ business and economy, as shown in

Table 1.2.

Table 1.2: Seven classes of congestion impact and potential business response

Class of Congestion Impact Implication for Business and Economy

Market and

Fleet Size

delivery area, market scale, fleet size/type,

delivery & reliability cost, assignment flexi

Business & Delivery

Schedules

delivery time shifts, truck dispatch, backhaul

operations, relief drivers, operating schedules

Intermodal Connections access to truck/rail/air/sea interchange terminals

Business Inventory and

Operations Management

inventory requirements, stocking costs, inventory

management/control, cross-docking opportunities

Worker Travel worker time/expense; worker schedule reliability,

service delivery cost

Business Relocation distribution from smaller, more dispersed locations, consolidation of production sites

Externalities: Interactions

with Other Activities

land use & development shifts, costs passed on to

workers and customers

Source: Weisbrod and Fitzroy (2011)

All in all, due to bad effects of congestion to logistics players as well as

the economy, LSPs‘ firms must improve their logistics systems, technology,

practices and ability to suit with the recent congestion problem. Thus, if there

10

are shortcomings in road transportation services like in terms of their service

capability and technologies embedded, it will affect other parties and logistics

performance as a whole. Due to the interest on these effects, we determine this

research to focus on road transportation with the intention to strengthen the road

logistics transportation services performance holistically.

1.1.3 Discussion

In order to make things clear, the literature mentioned above is

summarized into an illustration, as shown by Figure 1.2.

Figure 1.2: Illustrated summarization of how congestion affects business

performance

Source: Trunick (2004), (Sankaran et al., 2005), Systematics (2008),

(Short et al., 2010) and Weisbrod and Fitzroy (2011).

Therefore, from Figure 1.2 above, it is concluded that the issue of traffic

congestion has weaken the business performance of LSPs and other firms due to

delivery delay and rising of operation costs. At this stage, LSPs need to handle

the situation in the best manner to satisfy their customers as well as to sustain its

growth in the industry.

xii

1.1.4 Definition of Terms

Generally, firm performance and business performance carry a little bit

of difference in definitions but they are aimed to the same goals somehow.

Firm‘s ability normally is based on its performance (Bonn, 2000) and the level

of accomplished goal usually defines a firm‘s performance (Achrol & Etzel,

2003). This is why performance mirrored a firm. Different firms adopt different

methods in order to measure their performance based on their goals of business,

as mentioned by Collins & Porras (2000) in Mohamad and Sidek (2013).

According to many scholars, firm performance is measured by financial and

non-financial measures (Bagorogoza & de Waal, 2010; Bakar & Ahmad, 2010;

Darroch, 2005), or in other specific words they are cost and operational service

level (Kunadhamraks & Hanaoka, 2008).

Meanwhile, business performance is the result of operations, comprising the internal or external

achievement of the firm‘s objectives (C.-H. Lin, Peng, & Kao, 2008). Swanson (1999) defined performance as ―the valued productive output of a system in the form of goods or services‖. He

added that performance is also fulfillment and accomplishment. Rubio and Aragón (2009) resisted

that business performance can be categorized into four elements; rational goal (measured by financial indicators), internal process (measured by increased in quality of product and improved

organization), human relations (measured by increased in motivation of employees and reduced in

employees‘ absenteeism) and open system (measured by increased in customer satisfaction, company

The common aims between the firm performance and business

performance is about the achievement, accomplishment and fulfilment of a

firm‘s goals. Moreover, it can be concluded that both of them are measured by

financial and non-financial elements. Therefore, this study is using both terms

simultaneously without doubt, but will focus more on the non-financial

performance of a firm.

xii

1.2 Problem Statement

The expansion of manufacturing sector nowadays has boosted up the

demand of logistics services all over the world. Traffic volume of each mode of

transportations has increased dramatically year by year, including road

transportation which is rated higher than other modes, except airline (David J.

Bloomberg, 2002). The increment of traffic volumes has led to congestion, as

faced by China (Speece & Kawahara, 1995), New York (Trunick, 2004) and

UK, resulting to delivery time delay, cost increment, customer dissatisfaction

and risk of accident (McKinnon et al., 2009). Year by year passed, Yunus (2012)

reported that Malaysian logistics industry is forecasted to reach MYR203.71

billion by 2016 with the growth of 11.6% annually. This is in line with the

vision of MITI to increase trade between Malaysia and China to US$160 billion

by 2017 (MITI, 2014a).

Regardless the growth of logistics industry and demand in Malaysia,

some studies have found similar issues of congestion in East Coast region

especially in Kemaman and Kuantan (Zuraimi, Mohd Rafi, Mohamed Dahlan, &

Nur Fadiah, 2012) as well as other metropolitan areas in Malaysia (Almselati, Rahmat,

& Jaafar, 2011). Therefore, the LSP firms which operated in the region need to improve

their service capabilities especially in terms of their flexibility in handling expected or

unexpected events caused by the congestion. Empirical study done by Zhang and

Figliozzi (2010) also showed that the congestion has caused delivery delay and

operating costs increased by more than 70%.