Bouwman, H. (2003). State of the Art Business Models

State Of the Art on Business Models

Copyright © 2002 Telematica Instituut, TU Delft, TNO, KPN research

Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective

works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from or via Telematica

Instituut (http://www.telin.nl).

Colophon

Date : September 04, 2003

Version : Final

Change : Rewrite based on review Pals

Project reference: B4U/D3.2

Freeband reference : B4U/D3.2

Company reference : TI/RS/2003/112

URL :

Access permissions : Public

Status : Final

Editor :

Company :

Author(s) : Harry Bouwman (TUDelft)

Synopsis:

This document offers a state of the art in the domain of business models in

complex value systems, discussing customer value, organisational and

network aspects, technical issues and economical approaches. Objectives

are not only to offer an overview of existing theories, concepts and

measurement approaches, but also a basis for further analysis for case

studies that are executed within the B4U project and to deliver a basis for

design guidelines.

S t a t e o f T h e A r t

B u s i n e s s m o d e l s , v a l u e w e b s , d e s i g n a n d m e t r i c s V

Preface

This document offers a state of the art in the domain of business models in complex value

systems, discussing customer value, organisational and network aspects, technical issues

and economical approaches. Objectives is not only to offer an overview of existing theories,

concepts and measurement approaches, but also a basis for further analysis for case-studies

that are executed within the B4U (Business for Users) project and to deliver a basis for the

design method and game.

As such this document offers more background information that play a role in other work

packages of B4U. The B4U project is part of the Freeband Impulse programme. The

Freeband Impulse programme aims at the generation of public knowledge in advanced

telecommunication (technology and applications). It specifically aims at establishing,

maintaining and reinforcing the Dutch knowledge position at the international forefront of

scientific and technological developments. The Dutch Ministry of Economic Affairs is co-

funding this programme as part of the policy plan "Concurreren met ICT Competenties". The

general intention is to prepare the grounds for the big leap forward towards 4G, in which

seamless integration of fixed, wireless and mobile networks will be the standard and in which

an attractive environment for user centred applications will be the norm.

T e l e m a t i c a I n s t i t u u t

Management Summary

General information 1. Acronym: B4U State of the art Business models in complex value systems

2. Title: Business for Users (B4U)

3. Programme leader: Ferial Moelaert (TI-CO),

Project manager: Edward Faber (TI-CO),

Manager research TI-CO: Edward Faber ,

Manager research TU Delft: Harry Bouwman (TU Delft).

Manager research TNO Telecom: Nico Pals

Manager research TNO STB: Pieter Ballon

4. Date of first submission: 03-06-2003

5. Date of current project proposal:

Synopsis

This document offers a state of the art in the domain of business models in complex value

systems in general and more specifically of mobile business models, discussing customer

value, organisational and network aspects, technical issues and economical approaches.

Objective is not only to offer an overview of existing theories, concepts and measurement

approaches, but also a basis for further analysis for case studies that are executed within the

B4U project and to deliver a basis for design guidelines for mobile services.

Most new mobile services for 3G and beyond are developed by a network of organisations

that have to work together to realise access to infrastructure, middleware (such as location

based technologies), multimedia content, customer data and customers. This network of

organisations and or business units within organisations adds to the value of the service as

perceived by the customer. Although much is written about business models, little is known

about business models used by networked organisations. Furthermore, proper performance

indicators for business models are still under development. Within ongoing research projects,

such as Business Models for Innovative Telematics Applications (BITA) and Business for

Users (B4U) we are developing methods and tools to design and evaluate business models

for mobile services. In this state of the art document we will discuss literature with regard to

business models, networked services and performance and propose a measurement

instrument. Furthermore we offer both descriptive models and causal models that will help to

analyse the data of case collected both in the BITA end B4U projects.

S t a t e o f T h e A r t

B u s i n e s s m o d e l s , v a l u e w e b s , d e s i g n a n d m e t r i c s v i i

Table of Contents

1 Introduction 9

2 Business models in context 11

2.1 Customer value 14

2.2 Organisational issues 15

2.3 Technical arrangements 16

2.4 Financial arrangements 16

2.5 Metrics and performance 17

3 Business models and complex value networks 20

3.1 Customer value and complex value systems 21

3.2 Complex value systems and organisational arrangements 22

3.3 Complex value systems and technical arrangements 24

3.4 Complex value systems and financial arrangements 24

3.5 Complex value systems, performance and metrics 25

4 Mobile business models 26

4.1 Mobile business model and customer value 26

4.2 Mobile business model and organisational arrangements 28

4.3 Mobile business model and technical arrangements 28

4.4 Mobile business model and financial arrangements 29

4.5 Explaining the success of mobile business models 32

4.5.1 Causal model 32

4.5.2 Mobile business model, metrics and performance 34

4.6 Conclusion 35

5 References 37

E r r o r ! R e f e r e n c e s o u r c e n o t f o u n d . 9

1 Introduction

The objective of this state of the art is to offer an overview of literature with regard to business models in

general, and more specifically with regard to business models for mobile services. The overview of mobile

business models starts from the perspective of service providers rather than from the perspective of

mobile network operators. First, we will discuss the literature that discusses business models in general,

subsequently we will shift our focus towards business models that are developed in a complex actor

setting, where multiple actors have to work together to deliver customer value to the end-user and we will

finish this overview with the mobile perspective. Furthermore the concepts as discussed in this state of the

art are relevant for the development of framework for analysis of the case-studies that are part of WP 3 of

the B4U project, and for the design of guidelines for mobile services.

A large portion of the extensive body of literature on business models is devoted to understanding what a

business model is, what its main characteristics are or what typologies are available. In most cases the unit

of analysis is the single firm or organization. A business model can be defined as the description of the

roles and relationships among a firm’s consumers, customers, allies and suppliers that identifies the major

flows of products, information and money, and the major benefits to participants (Weill & Vitale, 2001, p.

34). Although definitions may vary and pay greater or lesser attention to the elements constituting a

business model, in practice we have not seen research whereby the business models of a large number of

firms are evaluated in terms of their performance. Studies with regard to business models and business

models performance are mainly based on case-material and tend to be anecdotic in nature. We fully

realize that most large-scale analyses of competing business models are hindered by the lack of financial

data. Most companies are very reluctant to share this kind of information, and when it is available the data

can seldom be compared.

In this state of the art document we will discuss the problems involved in developing an instrument to

measure the performance of business models across a range of firms. To make it even more complicated

we are not interested in business models of single organisations but of networked enterprises or complex

value systems where a number of firms have to work together to provide a service to the end-customer.

We will focus specifically on the mobile service domain. Research questions are:

• What is a business model? Which elements do constitute a business model? What metrics help to

understand the feasibility and viability of a business model?

With regard to the complex value systems we will discuss the following questions

• How are business models and complex value networks related? How do business models of complex

value systems differ from business models of singular organisations?

With regard to the mobile dimension we will discuss the following questions

1 0 B 4 U / D 3 . 2

• Are business models for 3rd generation mobile services different from more general business models?

Although thus far the questions have mostly been descriptive in nature, we also want to analyse the

performance of business models.

• Can we, based on the reviewed literature develop a model that explains the performance of business

models for 3rd G and beyond and what relevant indicators can be used to measure the concepts in this

model?

In this state of the art document we will therefore discuss a number of definitions of business models, the

concepts used to analyse them, such as the description of the customer value, and of the organizational,

technical and financial aspects. As a first step we will introduce a model of the elements that make up a

business model (for a more extensive discussion of this descriptive model see Faber et al., 2003). Starting

from this descriptive model we will develop a conceptual model that may help us understand which

concepts contribute to the performance of a business model and what the causalities are between the

concepts. Subsequently we will apply the model to the mobile domain.

E r r o r ! R e f e r e n c e s o u r c e n o t f o u n d . 1 1

2 Business models in context

In the 1970’s the concept of business model was used to describe and map business processes and

information and communication patterns within a company for the purpose of building an IT-system

(Stähler, 2001). More recently, business models have been related to market structures and the place of

individual companies within those structures. Sometimes the concept is used to describe co-ordination

mechanism in economic processes i.e. markets or hierarchies, or to discuss intermediation or dis-

intermediation trends. In other studies the implementation of a specific market model, for example the

English auction, is discussed in terms of business models. Very often only one economical or technical

aspect of a business model is emphasized, for example the B2C-model for the retail sector. The concept of

business model is also used as a synonym for business modelling: the modelling of organizational

processes with the use of Unified Modelling Language (UML), an object-oriented modelling language. It is

clear that the concept business model is widely used but hardly ever clearly defined. In the introduction we

referred to Weill & Vitale's definition of a business model, which is most probably not the best definition for

the purpose of our research, because in our view the authors fail to pay sufficient explicit attention to

technology. Alternative definitions, for instance the one proposed by Timmer (1998) stress the architectural

and technology elements. A business model is an architecture for the product, service, information flows,

including a description of various business actors and their roles, a description of potential benefits for the

various actors, and a description of the sources of revenue. We therefore prefer this definition above the

definition given by Weill & Vitale. Kiezen we nu de definitie van Timmers?

What business models are available? In various taxonomies a large number of business models are

mentioned (Timmers, 1998, 1999; Rayport, 1999; Madehevan, 2000; Rappa, 2000; Turban, Lee, King &

Chung, 2000; Afuah & Tucci, 2001; Deitel, Deitel & Steinbuhler, 2001; Deitel, Deitel & Nieto, 2001;

Raessens, 2001; Rayport & Jaworksi, 2001). The basis for these classifications varies. Some

classifications are based on developments in the area of technology, others on marketing concepts or

product types. In some classifications elements like value creation or strategy play a role. However most

classifications tend to be based on new opportunities offered by the Internet (Afuah & Tucci, 2001). Some

classifications pop up in a number of places, sometimes in slightly modified or more detailed versions. The

business models as discussed in these taxonomies basically are versions of what Weill & Vitale (2001) call

Atomic business models, to wit Content Provider, Direct to Customer, Full Service Provider, Intermediary,

Shared Infrastructure, Value Net Integrator, Virtual Community and Whole-of-Enterprise/Government

models. In our view most taxonomies can be traced back to these eight basic models.

What are the basic elements of a business model? Alt & Zimmerman (2001) suggest that there are a few

common elements that turn up in definitions of business models:

• Mission: determining the overall vision, strategic objectives and value proposition, but also the basic

features of a product or service.

1 2 B 4 U / D 3 . 2

• Structure: this has to do with the actors and the role they play within a specific business environment (a

value chain or web), the specific market segments, customers and products.

• Process: the concrete translation of the mission and the structure of the business model into more

operational terms.

• Revenues: the investments needed in the medium and long term, cost structures and the revenues that

are generated.

As in the definition of Weill & Vitale the role of technology and architectural elements is negelected.

Afuah & Tucci (2001) see business models as a system of components (value, revenue sources, price,

related activities, implementation, capabilities and sustainability), relationships and interrelated technology.

Mahadevan (2000) emphasizes value creation, revenues and logistics. As far as the buyer is concerned

value creation means a reduction in searching and transaction costs. The seller can reduce costs

associated with tracing customers, promotion and transaction costs, and benefit from a shorter turnover

rate. The introduction of all sorts of intermediary parties on the Internet is assumed to increase the value

stream for both the supply and the demand side. According to Mahadevan this will lead to a virtuous cycle,

which will finally materialize in Virtual Communities. These communities offer benefits to all parties

concerned: companies, customers, market makers and portals. Osterwalder (2002, also Osterwalder &

Pigneur, 2002) is far more systematic in his approach to the concept of business models. Based on the

questions what a company has to offer, who it targets, how this can be realized and how much can be

earned, he discusses four basic elements, i.e.:

• product innovation and the implicit value proposition,

• customer management, including the description of the target customer, channels, customer relations,

• infrastructure management, the capabilities and resources, value configuration, web or network,

partnerships

• financial aspects, the revenue models, cost structure, and profit.

In our approach we will focus on customer value, and the organisational, technical and financial

arrangements needed to provide a service that offers customer value (see Figure 2.1). In our opinion the

starting point is the customer value of a product or service that an individual company has to offer.

Strategies, which in the organisation domain are leading, are increasingly being translated into business

models. Nowadays, many business ventures have a limited interest in formulating strategies; instead they

formulate business models (Hedman & Kalling, 2002; 2003). Strategies, and consequently business

models, to a large extent determine the processes that lie at the basis of the business case: the concrete

implementation of the business model in operational terms. To achieve this a company has to make

resources and capabilities available within the organisation and organise relevant (information) processes


that will ensure the delivery of the product or services. This is enabled by technologies, in the case of

mobile services most importantly by information and communication technology.

Information and communication technology, i.e. Internet is playing an increasingly important role not only in

the organisational processes but also in delivering valuable products and services to the end customer as

well. It is clear that in addition to these elements financial aspects play a significant role too. In our view

business models are defined by these four elements: customer value, and organisational, technological

and financial arrangements. We will discuss these four elements in greater detail in the next sections.

Figure 2.1 Business model components

On a process level we see that technological innovations or combinations of existing technologies make it

possible to develop services that are assumed to deliver customer value. However to realize this new

services specific organisations have to collaborate within other department within an organisation of across

the borders of an organisation, for instance for a service that requires location specific information

collaboration with GIS-providers is necessary. So in the development of a services matching of service

requirements with technologies and therefore the establishment of collaboration with a number of

organisations is an important phase in the development of a business model. This process becomes most

explicit in the phase of the development of the services where negotiations on investments, revenue

models and revenue sharing take place. Most of the time this will lead to a redefinition of the business

Customer ValueOf services

Technicalarchitecture

Organisational arrangements

Financialarrangements

Enables(T0)

Defines(T1) Based on (T1)

Generate costs (T1)

Division of costs& revenues

(T3)

Delivers (T4)

Redefines(T2)

1 4 B 4 U / D 3 . 2

model and an adjustment of the initial service concept. As a result the customer value as initially foreseen

will be different from the actual customer value offered.

2.1 Customer value

There is a long tradition of literature on customer value, and basically it discusses what Ansoff’s (1987)

matrix, based on the dimensions of market and product newness, illustrates. Newness is quite a

troublesome concept, whether it concerns products that are new to the world (Booz et al , 1982), or major

(Lovelock, 1984) or disruptive (Christensen, 1997) innovations. ffering has to have added value for its

customers. In general, we will make the distinction between new-to-the-world products or services and new

versions of existing products or services (see also the concepts of versioning as used by Shapiro & Varian,

1999). Value is seen as part of an equation in which customers in target markets compare the perceived

benefits and total costs (or sacrifice) of (obtaining) a product or service (Chen & Dubinsky, 2003). The

value proposition of a firm must be considered better, and deliver the desired satisfaction more effectively

and efficiently than competitors. Customer experience is the key (Bouwman, Staal & Steinfield, 2001).

With the increasing importance of electronic networks, i.e. the Internet or mobile Internet, the channels that

play a role in offering a product or service also become more important. Rayport & Sviokla (1994) therefore

draw a distinction between

- content: what companies are offering,

- context: how companies are offering it, and

- infrastructure: what enables the transaction to take place.

All three factors can play a role in defining the newness of the product or service. Both the product or

service and the context can be new. For instance location-based mobile services represent a new product,

whereas it may also be the mobile channel that constitutes the new element. Increasing connectivity is

crucial. Furthermore, the intangible nature of the product or service as well as the increased role that

customers play (McNaughton, Osborne & Imire, 2002) is becoming more and more important and reflects

the service character of transactions through electronic networks. Customers contribute to and consume

value.

In most cases, due to all kinds of organizational, technical and operational problems, customer value, as

defined in strategic plans, is not the value that will be ultimately delivered to the customer, and even if it is,

it is not the value that will be perceived by the customer. In many cases the customer value as perceived


by the end-user has little to do with the customer value that is envisaged in initial business models and

greatly depends on the user’s personal or consumption context (Chen & Dubinsky, 2003).

In general, research into (perceived) customer value is associated with customer satisfaction and

evaluation. Until now there is no generally accepted theoretical conceptualisation for customer value in e-

services (Van Riel, Liljander & Jurriens, 2001). The SERVQUAL model is used in many research projects

but seldom in relation to services delivered over the (Mobile) Internet (Parasuraman, Zeithaml & Berry,

1988). It is, however, doubtful that the five dimensions of SERVQUAL: tangibility, responsiveness,

reliability, assurance and empathy, actually capture customer value and perceptions of e-service quality.

The SERVQUAL approach is backward looking: discussing customer value from the point of view of

existing customers and customer satisfaction. An alternative, forward–looking, approach, in literature

mentioned as policy capturing, vignette studies or conjoint measurement, discusses the perceptions and

perspectives of end users and decision makers on an unknown product or service. This approach is

handicapped by the absence of physical prototypes and the difficulty of reproducing market conditions.

This causes problems when conducting research into predominantly intangible products or services.

Alternative research methods, i.e. policy capturing (Wijngaert 1996; Bouwman & Wijngaert, 2002, 2003)

might present a more realistic alternative, not only because customer value can be manipulated, but also

because the context and infrastructure can be taken into account.

2.2 Organisational issues

In general, organisational issues revolve around the resources and capabilities that have to be made

available to the organisation. In their analysis of business models Hedman & Kalling (2002) conclude that

the bottom line is that economic value is determined by a firm’s ability to trade and absorb ICT-resources,

to align (and embed) them with other resources, to diffuse them in activities and manage the activities in a

way that creates a proposition at uniquely low costs or with unique qualities in relation to the industry in

which the company is operating. Collaboration, in-sourcing and network formation are possible strategies

to obtain the necessary resources if an organisation doesn't control the resources. Both the resource

based (Barney, 1991) and resource dependency (Pfeffer & Salancik, 1978) theory are relevant in this

respect.

Hedman & Kalling (2002, 2003) rightfully point out that the relevant literature on business models is

dominated by descriptions of 'specific' empirically identified business models and that little attention is paid

to the theoretical sub-constructs of these models. Starting from strategy theory, more specifically theories

on Industrial Organisation (Porter 1985; Porter & Millar, 1985), the strategy process perspective

(Mintzberg, 1983; Scott Morton, 1990; Henderson & Venkatraman, 1993) and the resource-based theory

(Barney, 1991) they conclude that strategy has to deal with industry, industry position, customer segment,

1 6 B 4 U / D 3 . 2

geographical markets, product range, structure, culture, position in value chain, resource bases,

knowledge bases and technologies.

2.3 Technical arrangements

Although technological innovations enable new services offering, not every new technology will lead to new

services. Business requirements as defined in corporate strategies and business models determine the

process and information infrastructure. Both specify the internal technical architecture, but also the

technologies necessary to offer a specific new service. This way, new service offerings and business

processes can be embedded in web-services, which contain both IT-functionality and data. As we have

discussed before there is an interaction between technological innovations that make a new service

offering possible at one hand and the technological embedding of the service at the other hand. In this

section we will not look into technology as a driver and enabler of technology but look at the internal

technological embedding of a services.

In general organisations have a choice in the degree to which they want to embed processes in IT-

functionalities. The most detailed level at which business processes can be embedded is the CRUD-matrix

level (Create, Read, Update and Delete). At a higher level objects are defined. Objects are related to the

business and information processes. A complex organisation can use object-models with thousands of

objects with a limited scope. At still higher-level components are used. Components are applications that

can be used by multiple users. One level above that web-services are being discussed (Koushik & Joodi,

2000). Functions and objects are combined together with business processes in a service application that

can be used by "business messages". Web-services have the highest level of granularity. Web-services

are business functions exposed to the web through a well-defined interface and use standard web

protocols, such as UDDI, SOAP and WSDL (Lankhorst, Van der Stappen & Jansen, 2001). Most web-

services are based on a 3-tier infrastructure defining external client interfaces, middleware and application

services and back end data services. We will not discuss technology in detail, it is clear that technology at

one hand enables new services offering, and at the other new service offerings require new technologies.

At a governance level web-services can be provided by third parties and do not depend on the IT-

resources of an individual firm. Furthermore, we have to realise that, to provide services over the Internet

and mobile networks, organisation legacy IT-systems or web-services are not sufficient.

2.4 Financial arrangements

With regard to financial arrangements there are basically three main issues: investment decisions, revenue

models and pricing. We will not discuss pricing in general terms, because pricing issues are directly related

to a specific service offering. We will only deal with investment decisions and revenue models in general

terms. When it comes to investment decisions there are a large number of surveys available (Demkes,


1999; Renkema, 1996; Oirsouw, 1993). The authors of these surveys describe a large number of methods

predominantly based on financial criteria. They discuss general financial methods as well as multi-criteria,

ratio and portfolio approaches (Renkema, 1996). Financial methods are aimed at average cost-

effectiveness, net cash worth, and internal return. Multi-criteria methods are those found in Information

Economic, Kobler Unit Framework and the Siesta-method, which is partly based on the Strategic

Alignment model. The ratio-methods are those found in Return-on-management and IT-assessment.

Portfolio-methods are found in Bedell, investment portfolio and investment mapping (see Renkema, 1996,

and Demkes, 1999). Some methods go beyond the merely financial considerations, for example the

balanced score cards (Kaplan & Norton, 1992; 1996) and the option theory, a more detailed elaboration on

the net cash worth concept (Renkema, 1996; Demkes, 1999). Demkes (1999, p. 91) does point out that

decision-makers hardly ever use these kinds of investments methods. Decision making on new

investments is most of the time ad hoc and intuitive. Nevertheless if decisions are made it is important to

evaluate these decisions on a continuous basis and therefore it is important to develop performance

measures. Generally speaking the cost side of investments are reasonably well charted. As far as the

revenue side is concerned, which from our point of view not only includes realizing cost reductions but also

long term advantages that stem from intangibles, literature is less uniform.

Revenue models indicate what methods of payment are used, what is being paid for, and thus in what way

income is generated. The thinking about models for income generation is less articulated than that with

regard to business models. Furthermore, the distinction between the two is often vague. Mahadevan

(2000), when talking about revenue models for the Internet, distinguishes, for example, subscriptions,

shopping mall operations, advertisements, computer services, general services, time usage and

sponsoring (or free services). Weill & Vitale (2001) distinguish between (1) payments for transactions, (2)

payments for information and advice, (3) payments for services and commissions and (4) advertisement-

generated income and payments for referrals. Holland, Bouwman, & Smidts(2001) discuss the following

revenue models for Internet services: advertisement based, transaction based, models based on the float,

subscription-based, licensed based and models based on utility, i.e. pay for-models.

2.5 Metrics and performance

Performance indicators for organizations have long ago ceased being determined solely on the basis of

solid economic assets. In 1981, the book value of a company was equal to its market value. In the year

2000 the market value was 4.2 times the book value. In other words, the value of a company is determined

not only by its tangible assets, but by its intangible assets, such as goodwill, as well (Boulton, Elliott, Libert

& Samek, 2001), which include, for example, marketing costs for branding, patents, etc. There have been

various attempts to quantify these assets by means of performance scales and indices, such as the Value

Creation Index, Value on InvestmentTM, Performance Measurement Matrix, Smart Pyramid, Macro Process

1 8 B 4 U / D 3 . 2

Model, the Balanced Score Card, the Performance Dashboard, and the Customer Value Index (this list

was partly based on Marr & Neely, 2001).

In the Value on Investment TM (VOI) approach a relationship is established between strategy, business

models and modelling on the one hand, and implementation and innovation on the other hand (Davies,

2001). The approach is based on the balanced score card (Kaplan & Norton, 1992, 1996). In addition to

the financial performance, which is usually referred to in terms of Return on Investment (ROI), other ways

to measure success are elaborated on the basis of internal work processes, performance of systems and

infrastructure, productivity of employees and customer satisfaction.

Based on the Balanced Score Card approach, Dubosson-Torbay, Osterwalder & Pigneur (2001) propose,

product measures that assess

• the originality of the value proposition,

• customer measures that evaluate the relationship of the organisation with its customer (retention,

acquisition, satisfaction, profitability) and the appreciation of the value proposition,

• infrastructure measures, identifying internal and outsourced activities, and

• financial measures, such as revenue growth, cost management, asset utilization and market

capitalisation.

The balanced score card approach has a number of limitations. According to Rayport & Jaworski (p. 263)

the balanced score card cannot be used to evaluate business models. They argue that in the BSC

methodology there is no clear definition of strategy (or business models), no clear location of

organizational capabilities or resources and no clear identification of strategic partners. Rayport & Jaworski

have developed an alternative method. This method, the so-called performance dashboard, is equipped

with a set of concrete indicators. They are:

• measures for market opportunities, including market size and competitive environment,

• business model measures, the unique value proposition, capabilities and resources, exclusive

partnerships, investment in technology

• measures for branding and implementation, brand awareness, but also indicators for system uptime,

number of IT staff and the percentage of inaccurate orders.

• measures for customer acquisition, customer share, purchases, service requests.

• financial measures, such as revenues, profits, earnings per share and debt to equity ratio.

Auer (2003) relates the Balanced Score Card method, in combination with other approaches to eServices.

In his approach he makes a distinction between three main phases, the customer process integration, the

eService scorecard and investment simulation and controlling. In the first phase the objectives are analysis

of the customer processes, estimation of the value and costs for the user and the development of key-

indicators. In the second phase the objectives are estimation of the value and costs for the eService


provider and again the development of key-indicators. In the third phase target values for cost and

performance indicators are estimated, various utilisation and cost scenarios considered, and target values

controlled and adjusted. In the services score card several intangibles elements are taken into account,

while differentiating from the original BSC approach a fifth dimension is added, discussing trust issues,

including security and safety, brand and image, product and process information, assuring trust building

signals, improving trustworthiness and mechanisms for control. The basic question is how the factor trust

be can translated into a competitive advantage.

Thus far we have mainly been concerned with individual organisations. However, in reality most services

are developed in value networks.

2 0 B 4 U / D 3 . 2

3 Business models and complex value networks

Traditionally business models are related to single organisations in a value chain. Value chain analyses

gained popularity through the writings of Porter (1985) and have since evolved to include a wide variety of

models. Although the original purpose of a value chain was to identify the fundamental value-creating

processes involved in producing a product or service within a firm, the concept has since been broadened

and is often used to describe an entire industry. An industry-level value chain serves as a model of the

industry whereby processes are considered independent of the firms that may or may not engage in them.

This separation enables analyses of the positions of various firms in the overall industry as well as

instances of vertical integration or cooperative agreements (alliances, joint ventures, etc.). Despite these

strengths, critics (e.g Tapscott, Ticoll & Lowy, 2000) note that the chain metaphor masks the importance of

horizontal aspects of a firm’s processes, particularly their relationships with other firms. Furthermore,

dynamic forces in the course of production are ignored and the model implies that product and service

development is necessarily a sequential process. Such criticisms have led to the development of

alternative conceptualisations such as stakeholder value chains, business webs and value nets (see

respectively Tapscott, Ticoll & Lowy, 2000; Kothandaraman & Wilson, 2001). There is a shift towards

providing information, products and services by networks consisting of collaborating sub-units of

organizations and/or cooperating organizations (e.g. Stähler, 2001). The borders of organizations are

becoming more transparent and organizations, enabled by ICT, cooperate in changing constellations.

Information, services, and products can be offered by sub-units of organizations, by single organizations or

by collaborations between companies, so-called value networks.

The broadening of the value chain concept to that of a value net or web coincides with the general trend

towards greater attention to network concepts in the strategic management literature (Gulati, Nohria &

Zaheer, 2000). By definition, plural organizations with various roles and functions create an organizational

network by pursuing a collective set of objectives (Demkes, 1999). Inter-organizational networks, relations

between firms that extend beyond the dyad or triad, come in many forms, such as business groups

(Granovetter, 1994), cooperative and governance networks (Wigand, Picot & Reichswald, 1997),

constellations (Jones, Hesterley et al. 1998), network enterprises (Castells, 1996), trade associations

(Oliver, 1990), and strategic networks (Gulati, et al. 2000). These various forms can be differentiated

based on the patterns of interaction in exchanges among the members, as well as the flows of resources

between them (Jones, Hesterley et al. 1997). A more dynamic approach specifically directed towards the

evolution of networks, seen as complex systems, is discussed by Monge & Contractor (2003). They see

complex (adaptive) systems as systems where actors (agents) in a network follow rules that explicitly and

sometimes consciously seek to improve their fitness in terms of performance, adaptability, or survival.


3.1 Customer value and complex value systems

For complex value systems, the generation and delivery of value to the users becomes a mutual interest.

Based on their internal resources and capabilities, they adjust their functional contribution in the

development of customer value. Their operation in this framework is based on the exchange of information,

products, services and financial assets. Hence, organizations become dependent on each other

strategically, functionally and financially. Continuous and repetitive interactions lead to the emergence of

relationships between firms, which might become institutionalised through legal agreements and contracts.

The interrelationships between the actors can exist at various levels, e.g. communications, information

flows and revenue flows (Maitland, Van de Kar, When de Montalvo, & Bouwman, 2003).

Complex value systems, value networks or value webs (we will use these concepts as synonyms) have to

strive for supporting customer processes to the maximum possible extent when thinking of improving

customer value (based on Grönroos, 1994). On the other hand each service is associated with costs.

Companies can choose whether they support the entire customer process or only one or a few steps in the

entire process. This choice depends on a company’s core competencies (based on their resources and

capabilities) (Petrovic and Kittl, 2002). Since we assume many services are provides by value networks,

this choice forms the basis for the configuration of a value web. Each company in the web will choose

which value (and ultimately which part of the end-user value) it will offer or in other words which part(s) of

the customer process it will support. So, the values and cost are formed by various organizations

performing roles that contribute to the value being offered to the customer through the e-service.

The following five characteristics distinguish a value net and give it the edge over a traditional business:

• Customer-aligned. Customer choices trigger sourcing, building, and delivery activities in the net.

Distinct customer segments receive customized solutions with customized service “wraps.” The

customer commands the value net; he or she is not a passive recipient of supply chain output.

• Collaborative and systemic. Companies engage suppliers, customers, and even competitors in a

unique network of value-creating relationships. Each activity is assigned to the partner best able to

perform it. Significant portions of operational activities are delegated to specialist providers, and the

entire network functions flawlessly thanks to collaborative, system-wide communication and information

management.

• Agile and scalable. Responsiveness to changes in demand, new product launches, rapid growth, or re-

design of the supplier network are all assured through a flexible production, distribution, and

information flow design. Constraints imposed by bricks and mortar are reduced or eliminated. Working

capital shrinks. Process time and steps are reduced, sometimes eliminating entire echelons of the

traditional supply chain. Everything in the value net, physical or virtual, is scalable.

2 2 B 4 U / D 3 . 2

• Fast flow. Order-to-delivery cycles are fast and compressed. Rapid delivery goes hand in hand with

reliable and convenient delivery. That means on-time, complete orders delivered to the customer’s

plant, office, or home. Time is measured in hours or days, not weeks or months. At the same time, it

means drastically lower inventories for the company.

• Digital. E-commerce is a key enabler. But beyond the Internet, it is the information flow design and its

intelligent use that lie at the heart of the value net. New digital information pathways link and coordinate

the activities of the company, its customers, and its providers. Rule-based, event-driven tools take over

many operational decisions. Distilled real-time analysis enables rapid executive decision-making.

The value web model appropriates various concepts of economic and information systems theory.

Markets, hierarchies, networks and information technology are woven into an intricate web of relations to

make this possible (Selz, 1999). According to Selz the main characteristics of the model are cherry picking

from existing value systems, a value web broker that acts as central coordinator, an endeavour to gain

proximity to the final consumer, and an integration of upstream activities. This integration is either

coordinated with market platforms or with hierarchical mechanisms. Coordination mechanism (Powell,

1990) may differ from network types to traditional market mechanisms.

3.2 Complex value systems and organisational arrangements

Of more interest are relationships between what we might call ‘structural’ participants in the value

networks. The balance of theory suggests that there are many motivations for firms to assume such

structural roles – ranging from simple opportunism to requirements for new technological and market

knowledge – but that the solidity of the relationship will depend largely upon social and institutional

antecedents. Depending upon which actor(s) contribute key assets in the creation of value and the

operating risks involved (Kothandaraman & Wilson, 2001), a different configuration of actors is likely to

result, some taking structural, integrative roles in the alliance and others taking supporting, facilitating

roles. In deciding how to describe such a network is important to decide on the focal point of the value web

and starting from there what the network looks like. It is clear that the description of the network or value

web is dependent on the perception of the researcher and it is problematic to delineate a network or value

web and to decide which actor belong to the core or periphery of the network.

Although in reality, the lines between some of them may blur, we can identify at least three basic types of

participants in any new value network:

• Structural or tier-1 partners provide essential and non-substitutable tangible and/or intangible assets to

the value web on an equity or non-equity basis. They play a direct and core role in making the

customer value assumption and in creating the business model.


• Contributing or tier-2 partners provide goods and/or services to meet requirements that are specific to

the value web, but otherwise they play no direct role in making the customer value assumption and in

creating the business model. If the assets they provide are substituted, the value assumption and the

business model could still stand.

• Support or tier-3partners provide generic goods and services to the value web, without which the value

web would not be viable, but which otherwise could be used in connection with a wide variety of value

assumptions and business models.

Structural partners make up the core of the network while contributing and support partners are loosely

linked to the network. As firms create products and services and engage customers in value exchanges,

partners are playing an important role and require careful management (Galbreath, 2002).

A remaining consideration in this scheme is the nature and longevity of these relationships. In principle, the

assets and roles of contributing and supporting partners could be obtained in the wider market, through

long or short-term contracts, depending on circumstances. Many of such partners may only be required at

specific points in time. Most structural partners would be in it for the long haul. Almost by definition, for the

business model to survive, a structural partner leaving the alliance would have to be replaced by another

partner bringing the same type of assets to the enterprise and fulfilling the same role. A variation may

occur when a structural partner’s role is highly temporary – i.e. required to create and float the business

model, but not essential to its subsequent operation. In such cases, it is likely that the assets contributed

by this partner would be retained through a formal permission or license.

In literature little attention is paid to what kind of resources should be shared in value webs and how they

are organised. Although there are several resource typologies (Grant, 1991: tangible-intangible resources;

Barney, 1991: physical, human and organisational capital resources; Das & Teng, 1998: financial,

technological, physical and managerial, Miller & Shamise, 1996: property-based and knowledge-based)

these typologies are too general for our research project. In our view access to critical resources is the key

element in deciding which actors to incorporate. Critical resources for value webs that use the Internet are:

access to the Internet and/or mobile infrastructure, to content, to content developers, aggregators and

hosting providers, to software and application platforms, to customers, customer data, billing, customer

support and management, based on the type of service providers of specific technology-related services,

for instance mobile, location or positioning applications. Some of the resources may be found within a

single organisation, whereas for others more than one organisation may be needed. Some resources may

only be provided by one organisation (structural partners), for other multiple alternatives (support partners)

are available.

2 4 B 4 U / D 3 . 2

3.3 Complex value systems and technical arrangements

Value webs are supported by ICT. In the B2B domain there has been a shift from integrated applications

and workflow management towards systems that support customer-oriented business processes, which in

some cases will require complete business integration. These systems make use of the Internet and the

TCP/IP protocol. Consequently, in addition to internal ICT-systems, web–services, etc., other relevant

factors are fixed network technology, both traditional (mobile and wireless) telecommunication and data-

networks like the (Mobile) Internet, object-oriented (.net, cobra, java and java beans) and mobile (Wap, I-

mode, SIM, Camel, etc.) middleware services and Internet (HTTP, XML) and web server architecture

technologies. With regard to services payments, trust, business oriented (CRM, SCM, ERP) and

collaborative (CSCW, workflow) services are relevant as well. However, discussing these technologies in

detail falls beyond the scope of this state of the art (Lankhorst et al., 2001).

3.4 Complex value systems and financial arrangements

An important question is how investments are arranged within complex value networks. Important

stakeholders in complex value systems are next to the core or structural actors, actors that invest, i.e.

banks, or make investments possible, i.e. venture capitalists. Investment decisions weigh the interests of

the actors involved and take the mutual benefits of multiple organizations into account. Organizations that

are connected through intended relationships and interdependencies consider risk sharing, solving

common problems, and acquiring access to complementary knowledge to be major motivators for

collective investments. To facilitate inter-organizational investments, organizations go through a collective

decision–making process. Compared to internal processes, these joint processes have the following

implications (Demkes, 1999):

• They require a lengthy decision-making process

• They demand multiple rounds of negotiations

• There are conflicting interests to be sorted out (not always resulting in a win-win situation for all parties

concerned)

• There are large costs and possible subsequent disputes

Inter-organizational investments require explicit articulation and collective agreement on the terms of

investment and timing (Miller & Lessard, 2000). The share of each participant and the corresponding

partnership ratio must be defined. It will be determined what each member will contribute in terms of

financial and technical expertise. The success of these arrangements hinge on whether or not the role of

each member within the terms of institutional framework is clearly defined (ibid.)


3.5 Complex value systems, performance and metrics

Vesalainen (2003) has developed a measurement instrument for measuring the (economic) performance

and impact of virtual or networked organisations, starting from the central organisation (the point of

gravity in a network, the organisation that holds control over access to the customer and has most roles

combined within their own organisation). In a sense each organisation is unique, being the centre of its

own network. The measurement starts at the organisation and its most important (buyer and seller)

relationships, measured as dyads. The decision to start here to a greater or lesser extent less limits the

network to cases where clear economical (input-output) relationships, often based on an exchange of

services and product, exist, which means that less formalised networks are not taken into account.

Nevertheless, Vesalainen’s approach offers a number of interesting indicators. He distinguishes between

structural and social links (organizational integration) on the one hand and commercial exchange and

strategic integration (business integration) on the other. In his view, whenever there is a low level of

organisational and business integration, the inter-organisational relationship is typically market-oriented.

High organisational and business integration reflects deep inter-organisational relationships. The four

dimensions are measured using a number of measurable concepts (67 questions, answer categories 1 -

reflecting a thin, market-based relationship - to 5 - reflecting a deep partnership -):

• Structural links via interface structure (people of two companies work together), systems integration (in

the ICT-domain, but also quality management systems) and core process integration (typically a

process that would normally be the responsibility of a single company, i.e. order delivery);

• Social structure through trust (reciprocity, loyalty, commitment), reciprocal relationships (personal

contacts), collective learning (from each others, from mistakes, innovative learning) and shared goals

and values;

• Physical exchange (products delivered), value-adding services (R&D, logistics), exchange

centralization (focusing of buyer and seller behaviour);

• Strategic integration through strategic dependence (mutual dependence, result of asset specificity,

exchange volume and depth of relationship), shared partnership strategy (a common vision, strategy

formation and network development), common risk taking and win/win (considering both cost based

win/win, but also growth in business volume).

2 6 B 4 U / D 3 . 2

4 Mobile business models

3rd generation mobile business will be the combination of two value chains, the mobile telecommunication

value chain and the electronic business value chain (Harmer & Friel, 2001; Barnes, 2002; Sabat 2002). It is

expected that this combination will lead to a wide variety of new possibilities. There are various conceptual

illustrations of this model. Actors within the 3G value network are in the infrastructure domain: network

operators, service providers, mobile virtual network operators; in the content or end-services domain:

content and portal providers/organisers, hosting and access providers, application providers, transaction or

payment processing providers, while attention should also be paid to system security providers.

The absence of third-generation mobile services prevents us from describing the exact business models.

Organizations mix their assets at different proportions and introduce new value propositions and business

models (Boulton, 2000). As a combination of mobile telecommunication and electronic business value

chains, business models of third generation shall inherit elements from the business models from both

these markets. The business models are extrapolated by considering the models present in e-business

with respect to the variations, and the models being used in 2G and 2.5G mobile markets (Li & Whalley,

2002). Panis, Morphis, Felt, Reufenheuser, Bohm, Nitz & Saarlo (---) discuss the business models for

location-based services, micro-payments, gambling and intelligent advertising, MacInnes, Moneta,

Carbarato & Sami (2002) for mobile games.

Ballon, Helmus & Pas (2001) lists some of the variations found in models with respect to the focus or range

of customer group, the function or goal in the value chain, the description of the roles of the actors involved

in value creation, and the type of services they use. They also point out the evident variations resulting

from differentiation in the mobile business market landscape, namely the functionality of mobile devices

and the quality of service provided by the network operators. Maitland, Van de Kar, When de Montalvo, &

Bouwman (2003) base their distinction on the types of mobile services being offered and classify the

models according to their value web complexity and level of intermediation. The models on which they

focus offer mobile information and entertainment services, and location-based mobile services, except

productivity-centred services.

4.1 Mobile business model and customer value

To a large extent, the customer value of 3G mobile services is stated in terms of anyplace, anytime.

However, this is very general description of customer value. Future mobile and wireless technologies

enable applications and services that are situation and context aware, augmented and virtual, and use

speech recognition, multi-modal interaction and human supervised computing. Crisler, Anneroth, Aftelak

and Pulil (2003) assume that research into user behaviour, across classes of applications (e.g. context

aware), broad user groups (segmented by age, culture, geographic region, special accessibility needs)


and in specific application domains (healthcare, emergency, extended enterprise logistics, education

learning, entertainment) may help to define applications that offer value to end-users.

Table 4.1 Actors in the mobile value web Roles Definitions

Functionality related roles

Service provider Provides billable service to the end consumer

Network operator Operates the mobile telecommunications network over which the data (service) is transmitted

Platform provider Provides the software that defines the general platform on which a variety of services are run

Application provider Provides the software that makes a service possible and that sits on top of the platform

Web hosting/

presence provider

Operates and maintains the server that hosts a website that is an integral part of the service, particularly relevant to the further development of content

Content supply chain roles

Raw content supplier Supplies content in a format unusable for the mobile service & terminal

Content developer Transforms raw content into content appropriate for the service as well as the mobile terminal

Content provider Provides ‘appropriate’/transformed content to the service provider Content aggregator Serves as an intermediary between the service provider and the content

providers

Hardware roles

Equipment provider Provides the hardware (physical components of network)

Handset supplier Supplies platform or service-specific handsets

Customer relation roles

Billing provider Provides billing services to collect revenues from end consumers

Marketing provider Markets the service

Customer support provider Point of contact for customer queries regarding the service; responds to customer queries

Content quality manager Monitors and improves content quality

LBS roles

Content geo-coding provider Adds x/y coordinates to the content

User positioning Provides the position information of the mobile device

Positioning technology vendor

Supplies user positioning equipment

GIS provider Provides geographical information (and GIS services) necessary to indicate location information of relevant content

2 8 B 4 U / D 3 . 2

Camponovo & Pigneur (2003) describe the value each actor within the mobile business domain is going to

deliver, which ultimately will add up to the final customer value. Table 4.1 gives an overview of the most

important actors (Maitland et al, 2003).

4.2 Mobile business model and organisational arrangements

Camponovo & Pigneur (2002) highlight the increasing importance that the organizations in the mobile

business market attach to building partnerships. Participants of 3rd generation mobile business markets

need to work together in a large number of areas. Even separate mobile network operators, who are

congenital competitors, resort to sharing their network infrastructures due to a discreet mutual interest in

speeding up investments and roll-out (Maitland, Bauer & Westerveld, 2002). Members of value webs

cooperate in the development of enabling technologies, the integration of corporate information systems

and the development of middleware solutions, open platforms and standards (Camponovo & Pigneur,

2002). In addition to the technical cooperation, they develop their billing and pricing schemes (ibid.).

Organizations in the 3G mobile business market have a number of assets they can use to create a

competitive advantage in the market. These assets will be discussed below.

It is believed that the cooperation of network providers and content providers from fixed communication,

Internet and mobile services of 2G will generate the highest quality of service (Maitland, Bauer &

Westerveld, 2002). The tendency of network providers to develop mobile content in-house is diminished

due to a shortage of adequate expertise and capital (knowledge and finance). There are three main

scenarios for network operators entering into partnership with third-party service providers, namely the

open, walled garden and closed approach. The open approach means that there are no limitations for

external parties, whereas the closed approach excludes content provider from taking part in the value

chain. In the walled garden approach particular content providers are allowed to take part on the basis of

pricing and content reserving privileges. Though in e-business building alliances is one the most important

ways of creating value, it seems that for content and network providers it is just one of the strategic ways to

enter the market, and to increase their competitive position (Camponovo & Pigneur, 2003). The access to

key functions of billing and information sharing appears to be of great importance in the competition and

creation of viable business models for the organizations. Each member will utilize its market position,

negotiating power and access to the critical resources to get a bigger piece of the pie.

4.3 Mobile business model and technical arrangements

3rd generation mobile data services will follow an evolutionary route. The assumption with regard to the

evolutionary route is that the GSM technology is subject of further development. Services offered by UMTS

are made possible by upgrading GSM. As the core of the network, GSM offers several commercial

benefits. Firstly, the investments of the existing GSM providers are protected. Secondly, there is already a


large number of customers that can immediately make use of these services. At the moment, GSM offers

the possibility of transmitting data at a speed of 9.6 Kbps. Although this is adequate for transmitting

messages of up to 160 characters, as is the case with the short message service (SMS), voicemail, e-mail

and a limited number of information services, it is inadequate for most data communication services.

Nevertheless, developments in the field of General Packet Radio Service (GPRS), High-Speed Circuit-

Switched Data (HSCSD) and Enhanced Data rates for GSM Evolution (EDGE) make an evolutionary

development to higher data rates possible, which means that it is possible that the so-called 2.5 G may just

be good enough for most 3 G applications (see for an extensive discussion of -regional- standards in the

mobile and wireless domain, Steinbock, 2003). 3G and beyond are assumed to carry video and sound

clips. Wireless technologies based on the WLAN- standards family (802.11a, b, f) and public hotspots are

increasingly seen as a competitive technology for 3G and beyond. The same goes for Bluetooth. However

we also see trends towards service platforms that will enable seamless hand-over of services between the

different mobile and wireless technologies.

Future outlooks are directed towards the personal area and wearable networks, with the so-called I-centric

services adapting to individual requirements (Popescu-Zeletin, Abranowski, Fikouras, Gasbaronne, Gebler,

Henning, Van Kranenenburg, Postschy, Postmann & Raatikainen, 2003). I-centric communication starts

from the human behaviour to which the activities of IP-based and wireless (mobile) communication

systems adapt. Context awareness, personalisation and adaptation are important requirements. They

define service composition, control, creation, environment monitoring, service deployment and services

management (see for an extensive overview of developments with regard to I-centric computing or the

Multi-level sphere concept, Mohr, 2003)

4.4 Mobile business model and financial arrangements

Three topics should be paid attention to when discussing financial arrangements with regard to 3rdG

Business models, i.e. investments decisions, revenue models and pricing. With regard to investment

decisions we advocate that attention should be paid to investment portfolios taking the life-cycle of a

service into account. From an investment appraisal perspective, a business model can be expressed in

terms of a portfolio comprising particular rewards at a price of threatening risks (Renkema, 1999). The

main purpose is justifying the allocation of organizational resources and scarce funds for a particular

project in the mobile domain. Thus, to justify a selected business initiative it is necessary to investigate if

that particular investment portfolio offers more value for price compared to other competing investment

alternatives. The business value following the realization of business initiative is the collection of the

efforts, earnings and uncertainties making up the reward-risk portfolio. Earnings and necessary efforts

have to be dismantled into a set of business impacts. Disaggregating the earnings and efforts into specific

business impacts using structural analysis techniques facilitates identification, measurement and

management of the effects; thus providing insight and means of intervention on the dynamics shaping the

3 0 B 4 U / D 3 . 2

consequences. Accordingly, structural identification and analysis of the business impacts are the

cornerstone of valuing options. Our argument is that structural analysis methodology should be used in the

mobile business domain in order to identify what kind of potential impacts can materialize and the value of

the initiative can be assessed. However we are not aware of such a methodology being applied specifically

for investments in 3G mobile services domain.

However the individual value activities of actors in the value web can be broken down. Figure 4.1 offers

such an overview.

Existing analyses are mainly directed to revenue models or pricing schemes. Olla & Patel (2002) for

instance present an overview of the revenue models that are used by what they describe as portal type

actors within a value web for 3G services (see table 4.2). Their overview is more or less a specification of

more general revenue models for the mobile (portal) domain.

TABLE 4.2 REVENUE MODELS FOR MOBILE PORTALS

Portal type Data revenue model Revenue source

Mobile intranet/extranet Mobile internet access with unlimited,

premium or basic content subscription

Customer

Revenue share content providers

Customer infotainment Volume-based charging or Advertising-

based models

Customer, reduced rate + revenue

from ads 3rd parties

Multimedia messaging Flat rate per content type Customer corporate

Mobile Internet Session-based charging/ Mobile

Internet Access at basis content

subscription/ Flat rate per content type

Customer

Location-based services Mobile Internet access/ Premium

content subscription

Customer

Revenue share content providers

Simple voice Per message models/ Mobile Internet

Access at basic content subscription

Customer

Rich voice Per message models/ Mobile Internet

Access at basic content subscription/

Flat rate per content type

Customer

Source: Olla & Patel, 2002, p. 562


Figure 4.1 Value streams in the mobile domain

(Source, Elisa, 2003)

s

r

MOBILE NETWORK TECHNOLOGYCUSTOMER SERVICE

MANAGEMENT

The delivered object of resource (excluding cost) :a = wholesale airtimeb = service to aggregate and to distribute the mobile service across different network operatorsc = aggregated contents in the appropriate format for the mobile serviced = contents in the appropriate format for the mobile servicee = platform (software) on which a variety of services are runf = software applicationg = information on the development of software application for mobileh = server that hosts a website that is an integral part of the mobile servicei = the transformed content into the appropriate content for the mobile servicej = content in a format unusable for the mobile service

MOBILE APPLICATION TECHNOLOGY

HARDWARE SUPPLY CHAIN

MOBILE USERINFRASTRUCTURE

MOBILE NETWORKINFRASTRUCTURE

MOBILE NETWORK FUNCTION

h

CONTENT SUPPLY CHAIN

MOBILE APPLICATION ENABLER FUNCTION

k

Network EquipmentProvider

Handset Supplier

Mobile ServiceProvider

Mobile NetworkOperator

Application Provider

Platform Provider

WebhostingProvider

Mobile ServiceAggregator

Raw ContentSupplier

Content Developer

Content Aggregator

Content Provider

CUSTOMER(MOBILE

USER)

i

j

h

g

e

a

b

c

n

ml

o

p

d f

d

Functions in The SupplyChain of Mobile Service

Technical Functions

Roles of Actor

Billing Provider

Marketer

Customer Service

d

q

t

l

Internet ServiceProvider

u

k = distributed mobile service for mobile users accross network operatorl = billable mobile service, distributed mobile handsetm = collected revenue from mobile usersn = bill of the mobile serviceo = advertised information of the mobile service (promotion of the mobile service)p = after sales serviceq = mobile handset with general (common) specificationr = mobile handset with specific function or specifications = information of the development technology in mobile handsett = physical component of mobile networku = access to the internet as the integral part of mobile service

3 2 B 4 U / D 3 . 2

Revenue models are based on pricing schemes. Pricing is a difficult topic within the 3G-services domain.

Pricing new mobile services too high will result in a low take-up of the service, whereas pricing too low

could result in low and unsatisfactory revenues. Although pricing theory is extensive, pricing of innovative

services is under-researched and problematic (Jonason & Holma, 2002). Traditional pricing theory is

mainly directed towards optimising the price-level, pricing is seldom considered as a part of innovations

themselves. Jonason & Holma try to define pricing parameters and to lay a basis for a proper pricing

optimisation method. Based on questions like how valuable an application will be for an end-user, how

many times a week the respondent expects to use a service and what an acceptable price would be for the

use of wireless services like music and video download, e-mail messaging, browsing, wireless photo’s,

banking, micro-payments, interactive games and positioning, tracking services, remote control and

emergency alarm, they conclude that every application has an individual price-demand relation. Private

entertainment related services show a low, but relatively stable price elasticity, whereas consumers were

more price sensitive when it comes to their willingness to pay for business-related services, such as

wireless email. In general the conclusion is that the pricing of applications needs to be taken at a service-

specific level to generate satisfactory profits in 3G.

4.5 Explaining the success of mobile business models

Although there is a large body of knowledge with regard to business models and complex value systems

and with regard to business models for 3G and beyond, case-related empirical analysis is scarce and there

are no cross-sectional data. One of the main problems is the fact that, although there are a great number

of more or less descriptive models, models that explain the viability and feasibility of business models are

still lacking. This is due partly to the complexity of the subject, and partly to its dynamic character (basically

it is a moving target) and partly to a lack of proper data. Nevertheless, we would like to present an initial

causal diagram that may help us understand the underlying causalities. We will give some indications

about how we would expect these concepts to be measured.

4.5.1 Causal model

In the causal model we relate organisational, technical and financial arrangements with a common strategy

or clearly defined business model and customer value that at the end will be decisive with regard to the

viability of a business model of a specific mobile service. Degree of complexity refers to network

characteristics: the number of involved actors and the number of roles they have to fulfil. Degree of

control/co-ordination refers to the governance of the network of actors that deliver the service.

Complementarity’s of resources and capabilities discus the specific roles that have to be fulfilled, more


specifically within a network that has to bring a service forward some resources or capabilities are

essential. In a certain way these resources and capabilities can be defined in access to critical resources

such as capital, both financial as social, but also more mundane access issues access to the Internet

and/or mobile infrastructure, to content, to content developers, aggregators and hosting providers, to

software and application platforms, to customers, customer data, billing, customer support and

management, based on the type of service providers of specific technology-related services, for instance

mobile, location or positioning applications. Financial arrangements have two sides: the input and the

output side. At the input side distribution of costs and risks is essential, while at the output side the division

of revenues is essential. If involved actors don’t get a fair share of the revenues they are most likely to drop

out of the network and hamper the viability of the business models; defined as the fit between customer

value as intended to be delivered and the customer value as experienced.

Intended/delivered Customer value

(value proposition)

Expected/Perceived Customer Value

(acceptation of value proposition)

Supply Side

Demand SideFIT

(market)Viable Service

Degree of complexityValue System

Common strategy (CVS)(new business model)

Degree of control/ co-ordination

Complementarity ofAssets (resources/

capabilities)

Division of costs, risks Division of revenues

Figure 4.2 Causal diagram explaining viability of a mobile business model

Within the model there are multiple feedback loops possible, we only did draw a feedback loop between

viability of the services and the common strategy. It will be clear that the common strategy as materialized

in the business model will be redefined in the case that the service is not successful at the targeted market.

Intended/delivered Customer value

(value proposition)

Expected/Perceived Customer Value

(acceptation of value proposition)

Supply Side

Demand SideFIT

(market)Viable Service





capabilities)

Division of costs, risks Division of revenues

3 4 B 4 U / D 3 . 2

If this will also have consequences for the network arrangements we will leave outside our scope. The

model is intended to be dynamic and be tested therefore we need indicators for the concepts in our model.

4.5.2 Mobile business model, metrics and performance

We make a distinction in our causal model between supply and demand side. The unit of analysis at both

sides are different. The customer value as intended and delivered can only be tested by empirical research

with consumers as unit of analysis. We opt for policy capturing as research method that can be useful to

assess the potential success of a service that is not yet on the market. We will not discuss the demand

side in more detail (see Bouwman & Van de Wijngaert, 2003).

Figure 4.3 Causal diagram of a viable mobile business model and metrics

At the supply side the network of collaborating organisations is the unit of analysis. Network related

metrics, both on the network level as on the level of an individual company, play an important role in

determining the complexity of the network. Degree of control and co-ordination has several dimensions

that have to do with the co-ordination mechanisms in place, and that can be qualified as markets,

hierarchies or networks (see Powell, 1990, Wigand et al, 1997). Financial metrics play a role both at the

Viable Service





capabilities)

Division of costs, risks

Access issues

Network levelSizeInclusivenessConnectivityDensityCentralizationSymmetryTransitivityIndividual levela.o. degree, range et ceteraRoles, i.e. Star, Liaison

Network content related issuesType of co-ordination- M, H, NOut- or co-sourcingSLA’s

Network level

Investment-Assets-Cost- Risk assessment

Stakeholder Dimensions- Investors- Employee-Internal processes- Network learning

OrganisationallevelInvestment- Assets- Cost- Risk assessment

Stakeholder Dimensions- Investors- Employee- Internal processes- Organisation learning

Financial ValuationNetwork/organisational LevelRevenue modelTangible-Benefits-- Tangible (revenu model)-- Intangible (trust, et cetera) Market size (critical mass), positionGrowth, ScalabilityChurn rate, SustainabilityIntangibleBrandCustomer Satisfaction

Metrics


input and the output side. At the input side costs and risks are central both on the network level and the

level of the individual organisation. The performance of the services is indicated by the viability of the

services. Financial output metrics, both tangible and intangible benefits, play an important role again both

on the network level and the level of the individual organisation. We make use of metrics as being

suggested both by Kaplan & Norton (1996) and Neely et al (2002). The last are more attractive because

they distinguish in many cases to input and output metrics. However the metrics still have to have a lower

degree of granularity. Furthermore based on earlier experience (Holland et al, 2000; 2001) we expect that

availability of data is and will be problematic.

The model and metrics are still open to debate, but will be used to analyse business models based on a

set of case studies as available within the BITA and B4U project, that discuss mobile information and

entertainment services, location based services, micro-payments, mobile tracking and tracing services,

communication and community services and services that deliver access to the back office. Case studies

have to be used to further develop the causal model and to assess the reliability and validity of our metrics.

4.6 Conclusion

Based on extensive literature research in which we reviewed literature on business models for individual

firms, complex value systems and 3G and beyond mobile services we developed a descriptive and causal

model for the description and explanation of the viability of business models in the domain of 3G mobile

services. Both models are static while business models appear to be volatile in nature and change quickly

over time. Trying to predict viability of not yet existing 3G services is problematic in itself. Although we can

based on policy capturing (Wijngaert 1996; Bouwman & Wijngaert, 2002, 2003) draw some conclusions on

potential customer value of services data on the services it self is still missing. 2.5G services offer an

interesting alternative as forerunners of the 3G services.

Another complicating factor is that it is hard to account for difference between new to the world business

models and business models that are versions of earlier more or less successful business models that

originally were applied in different settings, i.e. Internet models that are used in 3G services.

Also the financial issues related to business models are difficult to pin down. First of all there is the

distinction between investments and exploitation that plays an important role. Furthermore traditional

investment methods do not take the intangible nature of services into account. Other complicating factors

are the availability of financial data and the lack of comparability of these data.

It is clear that developing a model to explain the viability of business models can help to understand the

performance of business models and support the design of future services as discussed in the Faber et al

paper (2003) and Shubar & Lechner (2003, for an assessment tool of business models for WLAN in a

3 6 B 4 U / D 3 . 2

design phase). Design models have to take the results of the empirical testing of our causal model into

account.


5 References Afuah, A. & C. Tucci (2001). Internet Business Models and Strategies. Boston: McGraw-Hill, Irwin.

Alt, R. & H-D. Zimmerman (2001). Introduction to Special Section: Business Models. Electronic Markets Vol. 11 (1) 3-9.

Ansoff, I. (1987). Corporate Strategy. Middlesex: Penguin.

Auer, C. (2003). EMasurement: An integrated Concept for Measuring the Performance of services. Proceedings 4th World Congress on the Management of Electronic Commerce (January 15-17), http://worldcongress.mcmaster,ca, Hamilton, Canada

Ballon, P., S. Helmus & R. Pas (2001). Business Models for Next Generation Wireless Services. GigaMobile 2001.

Ballon, P. and S. Abranowski (2002) “Business models in the future wireless world”, WWRF WG2 White Paper. Final Draft Version.

Barney, J. R. (1991). Firm Resources and Structural Competitive Advantage. Journal of Management. Vol 17 ( ): 99-120.

Barnes, J.S. (2002). The Mobile Commerce Value Chain: analysis and Future Developments. International Journal of Information Management. (22)

Booz, Allen & Hamilton (1982). New Product Management for the 1980s. New York: Booz, Allen & Hamilton

Boulton, R., T. Elliott, B. Libert & S. Samek (2000). A business Model for the New Economy. Journal of Business Strategy. July-August 2000, p. 29-35.

Bouwman, H. & E. van de Kar (2001). Business models for 3rd generation mobile communication, Opportunities for current and new players in the telecommunications and Internet industry. Paper presented to the 11

th

European Regional Conference of the International Telecommunication Society September 9-11, 2000, Lausanne, SwitzerlandBouwman, H., M. Staal & C. Steinfield (2001). Klantenervaring en Internet concepten. Management & Informatie, Vol 9 (6) pp.52-60.

Bouwman, H.& Wijngaert, L. van de (2002). Content and Context: A new research approach to the basic characteristics of information needs. New Media & Society. Vol 4 (3) pp. 329-353

Bouwman, H.& Wijngaert, L. van de (2003). E-commerce B2C research in context: policy capturing, channel choice and customer value. Paper presented to 16th Bled eCommerce Conference, eTransformation, Bled, Slovenia, June 9 - 11, 2003

Bouwman, H. & E. van den Ham (2003). Business models and eMetrics, a state of the art. In: B. Preissl, H. Bouwman & C. Steinfield (eds). Elife after the Dot.com bust. Berlin; Springer Verlag.

Camponovo, G. & Y. Pigneur (2002). Analysing the M-business landscape. Annals of Telecommunication (2002)

Camponovo, G. & Y. Pigneur (2003). Business Models analysis applied to Mobile Business. ICEIS 2003. pp. 11

Castells, M. (1996). The Rise of the Network Society. Oxford, Blackwell Publishers.

Castells, M. (2001). The Internet Galaxy. Reflections on the Internet, Business and Society. Oxford: Oxford University Press.

Chen, Z. & A. Dubinsky (2003). A conceptual model of Perceived Customer Value in E-commerce: A Preliminary Investigation. Psychology & Marketing, Vol. 20 (4): 323-347.

Christensen, C.M. (1997). The Innovator's Dilemma. When New Technologies Cause Great Firms to Fail. Boston: Harvard Business School.

Crisler, K., M. Anneroth, A. Aftelak & P. Pulil (2003). The human perspective of the wireless world. Computer Communications, Vol 26, pp. 11-18.

Das, T.G. B.S. Teng (1998). Resources and Risk Management in the Strategic Alliance Making Process. Journal of Management 24 (1) 21-42

3 8 B 4 U / D 3 . 2

Davies, T. (2001). E-Gov planning and the value of investment. Presentatie Booz Allen & Hamilton. Egov 2001, 9 July 2001.

Deitel, H. M., P.J. Deitel & K. Steinbuhler (2001). E-Business & e-Commerce for Managers. Upper Saddle River: Prentic Hall

Deitel, H. M., P.J. Deitel & T. Nieto (2001). E-Business & e-commerce. How to program. Upper Saddle River: Prentic Hall

Demkes, R. (1999). COMET: A comprehensive methodology for supporting telematics investment decisions. Enschede: Telematica Instituut.

Dubosson-Torbay, M., A. Osterwalder & Y. Pigneur (2001). EBusiness Model Design, Classification and Measurements. Retrieved from Internet Thunderbird

Elisa (2003). The Determination of Organizational Fit that Supports the Business and Technology Alignment for Mobile Information and Entertainment Services. Delft MSC Thesis

Faber, E., P. Ballon, H. Bouwman, T. Haaker, O. Rietkerk, & M. Steen (2003) Designing business models for ICT services. Paper presented to 16th Bled eCommerce Conference, eTransformation, Workshop on concepts, metrics & visualisation, Bled, Slovenia, June 9 - 11, 2003

Galbreath, J. (2002). Twenty-first century management rules: the management of relationships as intangible assets. Management Decision. (40) 2, pp. 116-126.

Grant, R.M. (1991). The resource based theory of competitive advantage. Implications for strategy formulation. California Management Review Vol 33 (3) 114-135.

Granovetter, M. (1973) “The strength of weak ties”, American Journal of Sociology 78 (6), 1360-1380.

Granovetter, M. (1985) “Economic action and social structure: the problem of embedded ness”, American Journal of Sociology 91 (3), 481-510.

Granovetter, M. (1994). Business Groups. The Handbook of Economic Sociology. N. J. Smelser and R. Swedberg. Princeton, N.J., Princeton University Press: 453-475.

Grönroos, C. (1994). From marketing mix to relationship marketing: Towards a paradigm shift in marketing. Management Decision, 32(2), 4-20.

Gulati, R. and M. Gargiulo (1999). "Where do interorganizational networks come from?" American Journal of Sociology 104(5): 1439-1493.

Gulati, R., Nohria, N., & Zaheer, A. (2000). Strategic networks. Strategic Management Journal, 21, 203-216.

Harmer, J.A. & C.D. Friel (2001). 3G-Products -w hat will the technology enable?. BT Technology Journal Vol 19 (1), pp. 24-31.

Hedman, J. & T. Kalling (2002). The Business model: A means to comprehend the Management and Business Context of Information and Communication Technology. ECIS Proceedings, 2002, June 6-8, Gdansk, Poland, pp. 148-162.

Hedman, J. & T. Kalling (2003). The business model concept: theoretical underpinnings and empirical illustrations. European Journal of Information Systems 12, 49-59.

Henderson, J.C. & N. Venkatraman (1993). Strategic Alignment: Leveraging Information Technology for Transforming Organisations. IBM Systems Journal 32 (1), 4-16.

Holland Chr., H Bouwman, M. Smidts (2000). Back to the Bottom Line. Onderzoek naar succesvolle e-Businessmodellen. Leidschendam: ECP NL.

Holland Chr., H Bouwman, M. Smidts (2001). Return to the Bottom Line. Leidschendam: ECP NL.

Jansen, W. & P. van der Stappen (2000). State of the art in e-business services and components. Enschede: Telematica Instituut, GIGA-TS.

Jonason, A, & B. Holma (2002). Pricing for Profits on the Mobile Internet. Paper presented at IEEE IEMC, 2002, pp. 73- 78.


Jones, C., W. S. Hesterly, et al. (1997). "A general theory of network governance: Exchange conditions and social mechanisms." The Academy of Management Review 22(4): 911-945.

Kaplan, R. & D. Norton (1992). The balanced scorecard : measures that drive performance. Harvard Business Review, January-February, p. 71-79.

Kaplan, R. & D. Norton (1996). Using the balanced scorecard as a strategic management system. Harvard Business Review, January-February, p. 75-85.

Kothandaraman, P. & D. Wilson (2001). The Future of Competition. Value Creating Networks. Industrial Marketing Management. Vol 30, pp. 379-389.

Koushik, S. & P. Joodi (2000). E-business Architecture Design Issues. IT Pro May/June pp. 38-43.

Lankhorst, M., P. v.d. Stappen, & W. Jansen (2001). State of the Art in E business Services and Components. Enschede: Telematica Instituut.

Li, F. & J. Whalley (2002). Deconstruction of the Telecommunication Industry: from Value Chains to Value Networks. Telecommunications Policy (26). 451-472.

Lovelock, C.H. (1984). Developing and implementing new services. In: George, W.R. & Marshall, C.E. (eds.). Developing New Services (44-64). Chicago: American Marketing Association.

Maitland C., J.M. Bauer, J.R. Westerveld (2002). The European market for mobile data: evolving value chains and industry structures. Telecommunication Policy, Vol: 26, 9/10p. 485-504.

Maitland, C, E. van de Kar, U. When de Montalvo, & H. Bouwman (2003). Mobile Information and Entertainment Services: Business models and Service Networks. Paper to be presented at M-Business 2003, 23/24 June 2003, Vienna.

Mahadevan, B. (2000). Business models for internet- Based E-commerce. California Management Review. Vol. 42, No.4, pp. 55-69

MacInnes, I., J. Moneta, J. Carbarato & D. Sami (2002). Business Models and the Mobile Games Value Chain. Paper presented at BITA/B4U symposium. Business Models for Innovative Mobile Services. Delft November 16, 2002.

McNaughton, R, P. Osborne& B. Imrie (2002). Market-oriented value creation in service firms. European Journal of Marketing 36 (9/10) pp. 990-1002.

Marr, B. & A. Neely (2001). Measuring E-business Performance. Papers presented to the 12th Annual Conference of the Production and Operations Management Society, POM-2001, March 30-April 2, 2001 Orlando Fl.

Miller, D. & J. Shamise (1996). The resource based view of the firm in two environments. The Hollywood firm studios from 1836 to 1964. Academy of Management Journal Vol 39. 519-543.

Miller, R. & D. Lessard (2000). The Strategic Management of Large Engineering Projects. Shaping Institutions, Risks and Governance. Boston: MIT Press.

Mintzberg, H. (1983). Structure in Fives: Designing Effective Organizations. Englewood Cliffs NJ: Prentice Hall

Mohr, W. (2003). The Wireless World Research Forum (WWRF). Computer Communications, Vol 26, pp. 2-10.

Monge, P., & N. Contractor (2003). Theories of Communication Networks. Oxford: Oxford University Press.

Neely A., C. Adams & M. Kennerley (2002). The Performance Prism. The Scorecard for Measuring and Managing Business Success. London: Prentic Hall/Financial Times See also: Http://www.cranfield.ac.uk/som/cbp/prism.htm

Oirsouw, R. van, J. Spaanderman, H de Vries (1993). Informatie-economie. Investeringsstrategie voor de informatievoorziening. Schoonhoven: Academic Service Telecommunications Policy (26), 551-571.

Olla, P. & N.Patel (2002). A value chain model for mobile data service providers.

Oliver, C. (1990). "Determinants of Interorganizational Relationships: Integration and Future Directions." Academy of Management Review 15(2), 241-265.

4 0 B 4 U / D 3 . 2

Osterwalder, A. (2002) Business Models and their Elements. Position Paper presented to the International BITA B4U workshop, Business Models for Innovative Mobile Services. Delft, The Netherlands, 15-16 November, 2002.

Osterwalder, A. & Y. Pigneur (2002). An e-business Model Ontology for modelling e-business. In: Loebbecke, C., R. Wigand, J. Gricar, A. Puchicar & G. Lenart (Eds.). Ereality: constructing the eEconomy. Proceedings 15th Bled Electronic Commerce Conference. Bled Slovenia June 17-19, 2002.

Panis, S., N. Morphis, E. Felt, B. Reufenheuser, A. Bohm, J. Nitz & P. Saarlo (---) Mobile Commerce Service Scenarios and Related Business Models. Eurescom project P1102

Parasuraman, A, V. Zeithaml, L. Berry (1988). SERVQUAL: a multiple item scale for measuring consumer perceptions of service quality. Journal of Retailing. Vol 64. No 1, pp. 168-174

Petrovic, O & C. Kittl (2003). Capturing the value proposition of a product or service. Position paper for the international workshop on business models. Lausanne Switzerland, October, 2003.

Pfeffer, J. & G. Salancik (1978). The external control of Organizations. A resource Dependence Perspective. New York: Harper & Row, Publishers.

Popescu-Zeletin, R., S. Abranowski, I. Fikouras, G. Gasbaronne, M. Gebler, S. Henning, H. Van Kranenenburg, H. Postschy, E. Postmann & K. Raatikainen (2003). Service architecture for the Wireless World. Computer Communications. (26) 19-25.

Porter, M. E. (1985). Competitive Advantage: Creating and Sustaining Superior Performance. New York:

Porter, M. E. (2001). Strategy and the Internet. Harvard Business Review, 79, 62-79.

Porter, M.E. & V.E. Millar (1985). How Information gives you competitive advantage. Harvard Business Review. 63 (4) pp. 149-160.

Powell, M. W. (1990) “Neither market nor hierarchy: network forms of organisation”, Research in Organisational Behaviour 12, 295 336.

Raessens, B. (2001). E-business Your Business. Over de effectiviteit van E-commerce. Utrecht: Lemma

Rappa, M. (1999) Business Models on the Web available online from: http://digitalenterprise.org/models/models.html, last accessed May 2003.

Rayport, F.J. & B.J. Jaworski (2001). e-Commerce. Boston: McGraw Hill/Irwin

Rayport, F.J. (1999). The truth about Business Internet Business Models. Harvard Business Reviews Briefs.

Rayport, J. F. & Sviokla, J. J. (1994). Managing in the market space. Harvard Business Review, 72, 141-153.

Renkema, T. (1996). Investeren in de informatie-infrastructuur. Richtlijnen voor besluitvorming in organisaties. Deventer: Kluwer Bedrijfsinformatie.

Riel, A. van, V. Liljander, & P Jurriens (2001). Exploring consumer evaluations of e-services: a portal site. International Journal of Service Industry Management. 12 (4) pp. 359-377.

Sabat, H. K. (2002). The evolving mobile wireless value chain and market structure. Telecommunication Policy (26) 505-535.

Scott Morton, M. (ed.) (1990). The Corporation of the 1990s: Information Technology and Organisational Transformation. NEW York: Oxford University Press.

Selz, D. (1999). Value Webs. Emerging forms of fluid and flexible organisations. Thinking, organising, communicating and delivering value on the Internet. Dissertation St. Gallen

Slywotzky, A.J. (1996). Value Migration. How to think several moves ahead of the competition. Boston: Harvard Business Press.

Shapiro, C. & H. Varian (1999). Information Rules. A Strategic Guide to the Networked Economy. Boston Ma: Harvard Business School Press.

Shubar, A. & U. Lechner (2002). Business Systems for Public WLAN Network Operators. Paper presented to Ninth Symposium on Emerging Electronic Markets, pp. 175- 195.


Stabell, C. B. and Ø. D. Fjeldstad (1998) “Configuring value for competitive advantage: on chains, shops, and networks.” Strategic Management Journal 19 (5), 413-437.

Stähler, P. (2001). Geschäftsmodellle in der digitalen Ökonomie. Merkmale, Strategien und Asuwirkungen. Köln: Josef Eul Verlag

Stabell, C. B. & Fjeldstad, Ø. D. (1998). Configuring value for competitive advantage: On chains, shops and networks. Strategic Management Journal, 19, 413-437.

Steinbock, D. (2003). Globalisation of wireless value system: from geographic to strategic advantage. Telecommunications Policy Vol 27 pp. 207-235.

Tapscott, D., Ticoll, D. & Lowy, A. (2000). Digital Capital: Harnessing the Power of Business Webs. Boston (Ma): Harvard Business School.

Timmers, P. (1998). Business models for E-commerce. Electronic Markets, 8 (2) 3-7. (wwww.electronicmarkets.org)

Timmers, P. (1999). Electronic Commerce Strategies and models for business-to-business trading. Chichester: John Willey publisher.

Turban, E., J. Lee, D. King & H. M. Chung (2000). Electronic Commerce A managerial perspective. Upper Saddle River: Prentic Hall

Vesalainen, J (2003). Making Virtual Measurable. Paper presented to NESIS Workshop.

Weill, P. & M.R. Vitale (2001). Place to Space. Migrating to e-business Models. Boston: Harvard Business School Press.

Wigand, R., A. Picot, Reichswald (1997). Information, Organization and Management. New York, John Wiley & Sons

Wijngaert, L. van de (1996). A users' perspective on information services. In: Information services & use, Vol. 16 (Issue 2), pp. 103-122.

4 2 B 4 U / D 3 . 2

Bouwman, H. (2003). State of the Art Business Models

Documents

upper saddle

balanced score

harvard business

harvard business

oxford university

van de kar

innovative

mobile business