Electronic version of an article published as International Journal of Innovation Management, Vol. 16, No. 4 (August 2012) 18 pages. DOI: 10.1142/S1363919612003836. © World Scientific Publishing

Company http://www.worldscientific.com/worldscinet/ijim

MANAGING CUSTOMER-DRIVEN BUSINESS MODEL INNOVATION

Mikko Pynnönen*, Jukka Hallikas

and Paavo Ritala Lappeenranta University of Technology

P.O. Box 20, FI-53851 Lappeenranta, Finland *Corresponding author, email: mikko.pynnonen@lut.fi

The Information and Communications Technology (ICT) industry is now reaching saturation point in terms of growth, and constantly increasing demand for services can no longer be taken for granted. Customers have lot of options, and firms have to compete for business ever more intensely. In order to provide evidence of best practices in such environments, this paper reports a case study on customer-driven business model innovation. The resulting four-phase process framework is based on findings from a Pan-Nordic ICT service provider’s recently implemented R&D project. On the theoretical level, the framework builds on the value-network and resource-based approaches, whereas in practice it may be useful to firms intending to innovate and redesign their business model in an attempt to provide superior customer value.

Keywords: Customer value; innovation; business model; ICT; service concept; value network; analytic hierarchy process; quality function deployment.

Introduction In order to build a strategy based on customer needs it is essential to understand the firm’s business as part of a larger system. The business model is a particularly useful conceptual tool for this purpose in that it describes the architecture of the firm’s business system in terms of its product, service and information streams (Timmers, 1999). New technologies and innovations, as well as the changing expectations of end-customers, create constant change in the business models of established firms. The problem in many

cases is that these firms do not necessarily know what the value preferences of their customers are. In order to resolve this issue, firms need to develop customer-driven business models by integrating customers into their R&D and innovation processes (Thomke and von Hippel, 2002). In fact, customers are increasingly seen as valuable participants, in various roles, in the innovation process (Öberg, 2010). From the firm’s perspective, creating customer-driven business models, in other words business-model innovation, requires the capability and the processes to innovate and redesign the firm’s offering (Chung et al., 2004). If it is successful, it may even help the firm to redefine or refine the ‘rules of the game’ in the markets (Tidd and Bessant, 2009).

Current developments in the Information and Communications Technology (ICT) sector vividly illustrate the above-mentioned issues. At worst, a lack of understanding of customer preferences and the value of technologies leads to the creation of services with no users. It is therefore important to know the value of the firm’s offering (Dissel et al., 2009). An example of failing to understand customer preferences is Motorola’s Iridium satellite phone system, which was too expensivefor the target users and had several design limitations in terms of service availabilityand phone size. In addition, some of the current business models in communications services do not work well in situations in which customers value services offering added value and not only low prices. For instance, some telecom operators have adjusted their business plan to allow low prices through cutting down R&D operations and downsizing the staff. However, if

customer preferences drift towards media services, for example, these operators cannot provide them, firstly because of ignorance about the changed situation and secondly because of their inability to offer or deliver new services.

In order to avoid such rigidity, customer value must be included in the firm’s strategy and business model. Indeed, a better approach is to generate loyalty among customers with a superior value proposition (Brodie et al., 2009). This voluntary customer lock-in is typical in Internet business due to the intense competition that is forcing firms to provide free services. The offering must provide better overall value for the customer to be chosen in the first place. The offerings must also evolve with the changing preferences of customers, who stay loyal to a company if they feel it gives the best value for the service they use (Gardner, 2001). Even though the issue of managing the alignment of the business model and customer value is considered important in general, the current literature lacks an empirically validated, practitioner-oriented, holistic approach to managing customer-driven business model innovation.

In order to find best practices in terms of reducing this research gap, the aim in this study is to provide a framework for customer-driven business model innovation, and to offer the tools with which to implement and manage it. This should thus give insights into how customer preferences could be better integrated into the firm’s technology and service offerings — and subsequently its business models.

The implementation of the framework is demonstrated by means of a case study on a Pan-Nordic ICT service provider, which has an essential role in the integration and orchestration of an entire multi-play service offering (multi-play refers to an integrative, channel-independent offering including several communication and entertainment services and the related hardware). We examine the case study in a systematic four-stage process, each of which has its own methods and tools. The stages are as follows: (1) Analysis of how customer-value preferences align with the initial service offering; (2) Business model innovation based on customer needs; (3) A customer-value

survey in order to validate the new business model; (4) Fitting the business model to customer needs.

The paper continues with a discussion on the theoretical background of customer value creation and the role of business models in it. After that we describe our research design and process, and then present the case study and the results. Finally, we draw our conclusions and suggest some implications for managers. Theoretical Background The resource-based view of the firm and customer value The issue of producing customer value has its roots in the Resource-Based View (RBV) of the firm, according to which the firm is a bundle of resources, and these resources may vary between firms (Barney, 1991; Wernerfelt, 1984). An important aspect of the RBV is the creation of value for customers (Bowman and Ambrosini, 2000). Wernerfelt (1984) argues that the firm’s resource profile is related to its optimal product-market activities. This means that it uses its resources to generate value for its customers, and that identifying the link between a specific resource and a specific product could optimise the value for both the firm and the customer (Clulow et al., 2007).

According to Barney (1999), a firm without the resources it needs to be successful has three options: It can cooperate with another firm, it can develop the resources by itself, or it can acquire a firm that already possesses them. The two latter options are costly to implement, however. Even quite critical resources may be outsourced in value networks, and this gives a certain amount of negotiation power to the suppliers concerned. Barney (1999) argues that the governance structure is non-hierarchical in many technology-intensive industries because the costs of creating and acquiring capabilities are greater than the costs caused by an increased threat of opportunism. This also applies to ICT value networks. In short, the value network is a source of complementary and substitutive resources for a firm (Kothandaraman and Wilson, 2001). The transaction cost economics perspective, again, identifies the optimal

structure of the network through make-or buy decisions (Barney, 1999).

The RBV considers the value of resources, barriers to imitation, and appropriability mainly from the internal perspective (Priem and Butler, 2001). For example, Barney (1991) emphasises the fact that resources are valuable when they enable a firm to conceive or implement strategies that improve its efficiency and effectiveness. This criticism of the RBV framework for ignoring external resources and the external environment (e.g., changes in demand) limits its direct applicability in the value network. There is a distinct need to study how changing customer needs affect the value of resources in the firm’s business model.

Furthermore, it is necessary to extend the RBV to cover environments in which the product or service embodies resources obtained from several actors. From the RBV perspective, our study focuses on identifying how customer value is related to the value of resources, and on the implications this might have as far as the business model is concerned. Business models and value networks The concrete operational implementation of a firm’s high-level strategy takes place in the form of business models. The difference between the business strategy and the business model is that the former defines the relationship between the firm and its environment and the latter is more of an implementation tool for the strategy (Mansfield and Fourie, 2004). The ultimate goal of the business model is to provide the firm with the competitive means for providing value for its customers.

In order to keep the business model adjusted to customer value the firm should therefore have a strategy supporting repeatable innovation processes that provide these innovations (Brown, 2010). As Gardner (2001) states, a perfectly satisfied customer may shift to a competing offering if it provides significantly greater value. Customer satisfaction does not create real (voluntary) customer lock-in (Hamel, 2002); it is the overall value of an offering that does so (Gardner, 2001).

There are many different organizational structures containing varying numbers of business relationships in the modern ICT business world, and all the firms involved are somehow part of a value network (Kothandaraman and Wilson, 2001). One reason for is that producing value for customers with quickly changing needs requires flexibility and quick responses that business networks can provide (Hameri and Paatela, 2005). A value network could be compared to a firm that has a number of different strategic processes. As far as the network is concerned it is important to have the capabilities to connect assets and resources. Furthermore, companies form strategic alliances with partners in order to gain access to the external resources they need in their business (Yasuda, 2005), and focal firms often seek to ‘orchestrate’ the value network in the desired direction (Dhanaraj and Parkhe, 2006; Ritala et al., 2009). The creation of customer value Creating customer value is one way of integrating the customer into the firm’s processes (Anderson and Narus, 1998; Harmsen and Jensen, 2004). Customer value refers to what the customer wants, given certain limitations such as time and money resources. The aim of customer-value analysis is to integrate the customer into the firm’s R&D process (Ulaga and Chacour, 2001; Pynnönen et al., 2011), and it can also be used for segmentation purposes (Ulaga and Chacour, 2001). The value profiles tend to be similar within certain groups of customers (Pynnönen and Hallikas, 2008). The identification of similar profiles and of other factors that explain the similarities facilitates the segmentation of customers based on their value perceptions. Although the idea of customer integration originally arose in a business-to-business environment, it is easily transferable, in essence, to consumer markets (Thomke and von Hippel, 2002). We concentrate on the desired value, which is the bundle of desired product attributes and the resulting consequences, both positive and negative, and both monetary and non-monetary. Change in customer-desired value is caused by trigger events (new opportunities or

supplier problems, for example) that stimulate customers to change their opinions (Flint et al., 1997).

Ineffectiveness provides a motive for developing business models (Chung et al., 2004). Moreover, if the model is to take change into account, it has to be more than a descriptive framework. As Morris et al. (2005) state, if the business model framework is not specified properly and in detail, it does not allow comprehensive analysis. Timmers (1999) provides one general definition: A business model is the architecture for product, service and information streams. It also includes descriptions of the various business actors and their roles, their potential benefits, and the sources of revenue (Timmers, 1999).

If a firm is to provide value and remain competitive in the eyes of the customer, it faces the major strategic challenge of managing the fit between its competences and customer value (Gardner, 2001; Normann and Ramirez, 1993). However, the extant literature does not identify the linkages between business models and customer preferences. Despite the many good attempts to define business models, there are a limited number of frameworks that are capable of taking customer-driven change into account. Indeed, Magretta (2002) argues that business models fail because they are based on wrong assumptions about customer behaviour. Thus, the model has to be aligned with customers’ value preferences, and in order to be able to reconfigure its business model the firm has to have innovation capabilities (Chung et al., 2004). It is also essential to have a mechanism that connects the customer value to the business model (Thomke and von Hippel, 2002). Research design and process In the competitive world of ICT services, it is essential to know customers’ value preferences in order to create appropriate services. Thus, the starting point in this study is that changing value preferences among customers also

change the perceived value of firms’ offerings. It is, therefore, essential to have the firm-level capability to align the business model accordingly in order to keep the customers satisfied and to provide superior value over competitors’ offerings.

Our chosen method was an explorative case study, given our aim to find insights into a previously underexplored field (Eisenhardt, 1989; Yin, 2003). Furthermore, in the data collection we followed the principle of data triangulation in order to find the relevant evidence that would serve the research aim. The study is based on a rich set of various types of qualitative and quantitative data on a Pan- Nordic ICT service provider’s R&D project concerning a new customer-driven business models in the ICT industry. The study was implemented during the years 2007 and 2008. The aim of the development was to create a multi-play service offering for end customers, including a range of communication and entertainment services and related hardware. We used a panel comprising long-term customers, data on the case firm’s segmentation model, R&D workshops conducted in the case firm (between five and ten product managers in several workshops), a panel of five ICT experts from different ICT companies, and finally a survey of potential end-user customers of the multi-play service.

We used the service provider’s existing segmentation in the survey, and selected the five most attractive segments representing about 50% of its total market. The initial sample size was 12,000 customers, representing about 50% of the total consumer market in Finland. A total of 2,507 customers responded to the survey. These different sources and types of data were collected in order to give us a holistic and practically applicable view on how customer-driven business-model innovation takes place in the case firm. Figure 1 depicts the process implemented by the ICT service provider in managing such innovation, which is based on the case study.

(1) The issue of customers’ value preferences is dealt with in the first phase. If the changes in preference are rapid, the process of monitoring has to be simple enough to be agile. The traditional customer-survey approach used in marketing is not simple enough, and often does not force respondents to give consistent answers (Gardner, 2001). A solution to this problem is to devise a Customer Value Model (CVM) by means of Analytic Hierarchy Process (AHP) (Saaty, 1999) in order to analyse the values that drive and explain the changes in the business model and on the level of the entire value network. Defining the single attributes of the value elements, which may be of a technical, economic, service or social nature, facilitates access to and analysis of the CVM (Anderson and Narus, 1998).

(2) The second phase involves refining the business model through innovation to fit customer needs and the business strategy. If customers have needs that the current offering cannot meet, the model has to be redesigned. The Business Mapping

Framework (BMF) presented in this paper is based on the idea of systematically mapping the value-stream structure of a value network (Pynnönen et al., 2008). The value network is depicted as a collection of actors with value streams flowing between them, associated with the requisite resources to produce and consume the streams. This phase can be implemented in Group Decision Support System (GDSS)-based workshops, for example.

(3) The third phase includes an analysis of the fit between the customer value and the firm’s business model. A weighted cross-fit evaluation matrix (Mikkonen et al., 2008) is used to weight the elements of the business model according to customers’ value preferences. The resulting analysis reveals the value generating elements of the firm’s business. Customer opinion is critical in this phase, and therefore several customer segments should be included. CVM could be used in the implementation here, too, but in order to ensure wider generalisation of the results we used a customer survey.

Fig. 1. The process of developing and managing a customer-driven business model.

(4) The fourth phase is to re-design the

innovative service concept. Customisation of the concept is based on an evaluation of the fit between the targeted customers’ value preferences and the service elements, which includes identifying the high and low value-adding elements.

It is important to introduce the changes into the firm’s business model after executing each of the four phases. There are significant differences in the roles of the innovation phases, however. Incremental changes can be handled within the first two phases in that the new service elements, actors, and other related issues are mapped into the original model. If the changes are radical and require major alteration to the original model, it may be wise to re-design it and move on to phases three and four. Hence the business-model system better supports the innovated new logic. The process here is iterative and should be repeated regularly.

Each step is described in more detail in the following, based on the empirical evidence, and examples are given. Building a customer-driven business model It is essential for a firm to build its business model on customer needs in order to be able to recognise customer value and create a business model that will capture it. The framework outlined here is based on the case study examined in this paper, as well as on empirical evidence from several existing studies on ICT business models (Pynnönen and Hallikas, 2008; Mikkonen et al., 2008; Pynnönen et al., 2008). In the following we explain the entire process, using the case study on the Pan-Nordic ICT service provider’s multi-play offering as an example. The multiplay offering combines a set of telecommunications and multimedia content products and services into a new kind of convenient, innovative whole (see Mikkonen et al., 2008, for further discussion on typical multi-play offerings). Analysing the current customers’ value preferences

The starting point of the study was to map initial customer needs and prioritise them. The first step in this process was to obtain a basic understanding of the current services, the business model and the industry from lists of

services, for example, and by organising a workshop with company experts. In this case we mapped the initial business model in cooperation with the firm’s executives and ICT industry experts, and then used CVM to map the service-specific attributes.

We used the AHP decision model for the assessment and prioritisation of the initial CVM attributes. We also convened a customer panel in which 15 advanced customers formed judgments about their relative attribute preferences, comparing each quality attribute pair-wise with another in order to find the relative orders of importance. We finalised the CVM criteria in accordance with the results of the panel discussion. CVM here consists of eight value elements: Performance, Features, Reliability, Usability, Conformance fit, Appearance, Costs, and Socioeconomic aspects, defined in terms of attributes that link them to the case service system. A panel comprising five advanced customers then assessed these criteria.

The results are presented in Fig. 2.We asked the panelists to compare the relative importance of each attribute with respect to the case services, and then used the AHP model to calculate the weighted preferences for each cluster of service attributes and for the single items. The results shown here are the consensus answers of the group. The highest-ranking attributes are compatibility, terminal design, bundled fee, response time and convenience, all of which an integrated and well-designed service will cope with. This, however, would require much more service development and a new kind of business model into which the different access networks and their end-user devices would be integrated. The wireless and fixed-access networks have traditionally operated in different business units in the case firm, and there was no end-user integration. The firm’s managers had been sensing these signals of new kind of demand. The results of this pre-study were the trigger for conducting a larger study on developing an advanced multi-play business model that would offer the customer a solution. The innovation process continued with the help of the firm’s R&D specialists.

Business-model innovation The R&D specialists in the case firm took part in a series of workshops based on the results of the customer panels, the aim being to map potential new services that might be attractive to customers and relevant to the multi-play business model. We used these service proposals as the basis of the new business-model mapping, and applied the BMF tool in mapping the service design of the multi-play offering (see Fig. 3). The value streams are based on the products and services, and

describe what is being transferred, where the transaction originates from and to whom it goes. The product or service stream often includes indirect and complementary value streams, revealed in analyses of the actors and customers. The analysis also reveals new actors, customers and value streams that are not visible until the process is underway. We categorised the value streams as follows: Products, Services, € Product transaction, € Service transaction and Information.

The business of the multi-play operator consists of offerings produced for customers (consumers and advertisers) and

Fig. 2. The assessment and prioritisation of CVM attributes in a mobile communications system.

resource providers (a media-content provider, an incumbent operator, and a network-equipment and device manufacturer).

The offering comprises the value streams to the customers, which deliver a certain proportion of its total value. We focus here on the analysis of the customer offering, which is basically a ‘Multiplay control centre’ that allows the integration of the services into different devices at home. The offering includes a set-top box that connects to a TV, a PC and a mobile phone. The services are also accessible via mobile devices over the Internet. These are integrated into the ‘Multi-play service’ package, which is a single-fee-based service covering all the communication needs of the household. The monthly fee also covers several communication and media services: The only one that is not covered and is billed according to consumption is the ‘Video on demand’ service.

The following section reviews the results of a customer-value survey, which are

then used in prioritising the value streams of the offering. At this stage the business model represents all possible ideas generated in the R&D workshops based on the initial customer-value analysis and the multi-play concept. It is not necessarily the optimal solution for the customer or for the firm, and further customer opinions are needed in order to streamline the concept. A customer survey aimed at incorporating customer value into the business model. We conducted a large customer survey in order to identify the innovated services and features the customers considered most important. The purpose was to align the offering in the business model with its value to the customer, which requires the customer information to be connected to the firm offering. In the case of larger customer groups the results can also be used for segmentation purposes. The profiles form similar patterns in

Fig. 3. The BMF used as a tool for mapping the initial business model of the case service.

similar users, and by adding the background information on the customers to the analysis the data can reveal what aspects should be emphasised in offerings for different user groups. Our survey produced different value profiles among the respondents, but throughout the data there was a significant demand for convenient and easy-to-use communication services.

Opinions were divided on the integration of services, and especially of hardware, into the same offering, but there was a large group (84.8% of respondents) interested in buying the integrated offering.

We used the weighted cross-fit evaluation matrix based on Quality Function Deployment (QFD) principles to connect the customer-value preferences to the value streams of the business model. The purpose of this was to make sure that the elements of the offering actually contributed to the customers’ desired value. QFD is an analytical tool that is designed to convert high-level business objectives (‘what’ the business stakeholders want) into processes (‘how’ the business delivers the ‘whats’) (Clegg and Tan, 2007). It is also a method for converting customer demands into quality characteristics, and developing product design by systematically deploying the relationships between these demands and the product characteristics (Lee and Ko, 2000). The weighted value attributes of the customer survey are connected to the value streams of the business model through the application of the QFD process (see Fig. 4).

The firm’s offering comprises value streams from the main actor to the customer (e.g., voice communications and client and content search: see Fig. 3). The result of this analysis gives the relative priorities for the customers’ value streams in the business model. The importance of a value stream is calculated by multiplying the correlation value in a single column in the matrix by the importance rate of the value attribute, and the relative importance is the sum of the column of preference-weighted correlations. The QFD analysis also reveals the mostsensitive value attributes in contrast to the elements of the offerings. The sensitivity is calculated by multiplying the sum of a row and the weight of the value attribute. Figure 5 shows the customer-value-weighted value streams of the initial business model.

In this case the most important elements of a multi-play offering are related to the devices and content services in that many of the preferred value elements ease of use and high-quality content. How can this information be used in order to optimise the offering and the business model? This is discussed in the following section. Adjusting the business model

It is not wise to add every new innovation into the design if the aim is to implement the new business model in an efficient and value-providing way. Thus, at this stage the customer-survey results were used in order to adjust the multi-play service offering.

The first thing that catches the eye in

Fig. 5 is that 50% of the cumulative customer Fig. 4. The use of a QFD-based tool to connect customers’ value preferences to the firm’s offering.

value derives from value streams that are typical of normal ICT bundles (elements 2–18). The value streams related to the advanced multi-play offering (elements 19–26) create 50% of the added customer value, of which the enablers and the core elements are the fully integrated hardware products (elements 24–26).

Secondly, non-value-adding services can be excluded from the offering. In this case these are mainly the services that are provided, without charge, by other providers. If these value streams (2–7) were removed the total customer value would decrease by only 10% (see Fig. 5). One exception was made in the

case of element number 3 ‘Multi-play control centre’. A straightforward analysis suggested that it did not add value for the customer, but it is a necessary part of the multi-play system and was therefore moved to the non-core-elements category. It is costly to provide well functioning, easy-to-use and integrated services like these, and it would therefore be reasonable to focus on those that add more value.

Thirdly, the remaining service elements (8–18) are the supportive non-core elements that are needed to implement the offering, but do not provide extra value for the customer.

Fig. 5. The relative importance of value streams in terms of customer value.

Fig. 6. The refined business model involving service elements categorised according to customer

Figure 6 shows the adjusted business model, describing an advanced multi-play offering. In terms of a conscious firm-level strategy, the model now includes only the core value-creating-and-adding elements and the necessary supporting elements, and consciously discards the non-core elements. The core elements are the key for integrating the services. They also constitute the gateway to convenient user experience in that they are used with the devices.

The added-value elements of the offering form the basis of the services that distinguish it from normal communication offerings and bundles. The non-core elements consist of elements of typical bundles and separate services that are not essential in terms of customer value but are potentially good to keep in the offering. The excluded elements are services that are freely available in the markets into which customers have already locked. Conclusions and Implications Customer-driven business model innovation — as presented in this paper — helps firms and their managers to continuously develop technology and business in alignment with current and emerging customer needs. This is not a one-time task, but is more like an iterative process that goes on whenever customer preferences, enabling technologies, and infrastructures change. Involving customers in the continuous innovation of the firm’s business model provides a complementary viewpoint on traditional technology management, which all too often puts technology before customer value (Thomke and von Hippel, 2002). With a view to enhancing knowledge of the aforementioned issues this paper presents a systematic four-stage process framework and the related tools required for customer-driven business model innovation. In doing so, it further refines existing value-stream mapping techniques (Timmers, 1999; Pynnönen et al., 2008, 2011; Allee, 2000) in adding and connecting customers’ value preferences to the business model.

The results of the study have important implications for technology and innovation managers. If businesses are to

function well on a long-term basis, customer information has to be continuously monitored. For example, the creation of customer communities aligned with social-media platforms could provide essential real-time information about changing customer preferences and new service requirements. For example, Microsoft and Apple have successfully developed their community programs to allow their customers to share their ideas about improving the products and services. The notable customer indications in our study included a preference toward service bundles instead of fragmented service offerings, which is indicative of how the case service should be re-designed. When indications of the changes are apparent, the new preference profiles could be analysed within the frameworks described in this paper in order to see whether or not they change the importance of the elements of the offering. If the order of importance of the elements in the business model changes only incrementally, a new kind of marketing message or an adjustment to a minor technical feature, for example, will remedy the situation. However, if customers prefer elements that the business model does not have, or their preferences change radically, the model has to be redirected. The presented framework is potentially useful not only in aligning the current business model with customer needs, but also in the development of new technology and new business. When it is a question of designing new business areas and offerings, it is fruitful to have the customer’s voice in the process from the very beginning.

It should be remembered that the context of this study is the turbulent and evolving ICT industry. Nevertheless, the framework should apply in other kinds of industries as well, although the relative emphasis of the phases might vary.

Moreover, we focused only on customer-demand-based change in this paper. Other external change drivers such as competition were ruled out in order to keep the framework simple. There are thus several potential points of departure for future research. For instance, models taking environmental-contingency factors into account could be particularly useful in that there are several factors, such as regulation

and competition, which potentially affect the dynamics of business models and technologies. Finally, a greater emphasis on the underlying resources would improve the framework presented here, and this could be addressed in further studies. References Allee, V (2000). Reconfiguring the value

network. Journal of Business Strategy, 21(4), 36–39.

Anderson, JC and JA Narus (1998). Business marketing: Understand what customers value. Harvard Business Review, 76(6), 53–65.

Barney, J (1999). How a firm’s capabilities affect boundary decisions. Sloan Management Review, 40(3), 137–145.

Barney, J (1991). Special theory forum the resource-based model of the firm: Origins, implications, and prospects. Journal of Management, 17(1), 99–120.

Bowman, C and V Ambrosini (2000). Value creation versus value capture: Towards a coherent definition of value in strategy. British Journal of Management, 11(1), 1–15.

Brodie, RJ, JRM Whittome and GJ Brush (2009). Investigating the service brand: A customer value perspective. Journal of Business Research, 62, 345–355.

Brown, B (2010). Why innovation matters. Research-Technology Management, 53(6), 18–23.

Chung, WWC, AYK Yam and MFS Chan (2004). Networked enterprise: A new business model for global sourcing. International Journal of Production Economics, 87(3), 267–280.

Clegg, B and B Tan (2007). Using QFD for e-business planning and analysis in a microsized enterprise. International Journal of Quality & Reliability Management, 24(8), 813–828.

Clulow, V, C Barry and J Gerstman (2007). The resource-based view and value: The customer- based view of the firm. Journal of European Industrial Training, 31(1), 19–35.

Dhanaraj, C and A Parkhe (2006). Orchestrating innovation networks.

Academy of Management Review, 31(3), 659–669.

Dissel, MC, R Phaal, CJ Farrukh and DR Probert (2009). Value roadmapping. Research- Technology Management, 52(6), 45–53.

Eisenhardt, KM (1989). Building theories from case study research. Academy of Management Review, 14(4), 532–550.

Flint, DJ, RB Woodruff and SF Gardial (1997). Customer value change in industrial marketing relationships. Industrial Marketing Management, 26(2), 163–175.

Gardner, B (2001). What do customers value? Quality Progress, 34(11), 41–48.

Hamel, G (2002). Leading the Revolution. Boston: Harvard Business School Press.

Hameri, A and A Paatela (2005). Supply network dynamics as a source of new business. International Journal of Production Economics, 98(1), 41–55.

Harmsen, H and B Jensen (2004). Identifying the determinants of value creation in the market — A competence-based approach. Journal of Business Research, 57, 533–547.

Kothandaraman, P and DT Wilson (2001). The future of competition — Value-creating networks. Industrial Marketing Management, 30(4), 379–389.

Lee, SF and ASO Ko (2000). Building balanced scorecard with SWOT analysis, and implementing “Sun Tzu’s The Art of Business Management Strategies” on QFD methodology. Managerial Auditing Journal, 15(1), 68–76.

Magretta, J (2002). Why business models matter? Harvard Business Review, 80(5), 86–92.

Mansfield, GM and LCH Fourie (2004). Strategy and business models — Strange bedfellows? A case for convergence and its evolution into strategic architecture. South African Journal of Business Management, 35(1), 35–44.

Mikkonen, K, J Hallikas and M Pynnönen (2008). Connecting customer requirements into the multi-play business model. Journal of Telecommunications Management, 1(2), 177–188.

Morris, M, M Schindehutte and J Allen (2005). The entrepreneur’s business

model: Toward a unified perspective. Journal of Business Research, 58, 726–735.

Normann, R and R Ramirez (1993). From value chain to value constellation. Harvard Business Review, 71, 65–77.

Öberg, C (2010). Customer roles in innovations. International Journal of Innovation Management, 14(6), 989–1011.

Priem, RL and JE Butler (2001). Is the resource-based “view” a useful perspective for strategic management research? Academy of Management Review, 26(1), 20–40.

Pynnönen, M and J Hallikas (2008). Applying a customer value model in mobile communication business. To appear International Journal of Electronic Business.

Pynnönen, M, J Hallikas and P Savolainen (2008). Mapping business: Value stream based analysis of business models and resources in ICT service business. International Journal of Business and Systems Research, 2(3), 305–323.

Pynnönen, M, P Ritala and J Hallikas (2011). The new meaning of customer value: A systemic perspective. Journal of Business Strategy, 32(1), 51–57.

Ritala, P, P Armila and K Blomqvist (2009). Innovation orchestration capability — Defining the organizational and individual level determinants. International Journal of Innovation Management, 13(4), 569–591.

Saaty, T (1999). Decision Making for Leaders: The Analytic Hierarchy Process for Decisions in a Complex World. Pittsburgh: RWS Publications.

Thomke, S and E von Hippel (2002). Customers as innovators: A new way to create value. Harvard Business Review, 80(4), 74–81.

Tidd, J and J Bessant (2009). Managing Innovation, 4th ed. Chichester: John Wiley & Sons.

Timmers, P (1999). Electronic Commerce — Strategies and Models for Business-to- Business Trading. London: John Wiley & Sons Ltd.

Ulaga, W and S Chacour (2001). Measuring customer-perceived value in business markets. Industrial Marketing Management, 30, 525–540.

Wernerfelt, B (1984). A resource-based view of the firm. Strategic Management Journal, 5(3), 171–180.

Yasuda, H (2005). Formation of strategic alliances in high-technology industries: Comparative study of the resource-based theory and the transaction-cost theory. Technovation, 25(7), 763–770.

Yin, RK (2003). Case Study Research: Design and Methods, 3rd ed. Thousand Oaks, CA: Sage.