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This article was downloaded by: [University of Strathclyde] On: 10 October 2014, At: 08:45 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Journal of Marketing Management Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/rjmm20 Customer portfolio planning in a business network context Teck-Yong Eng Published online: 01 Feb 2010. To cite this article: Teck-Yong Eng (2008) Customer portfolio planning in a business network context, Journal of Marketing Management, 24:5-6, 567-587, DOI: 10.1362/026725708X325995 To link to this article: http://dx.doi.org/10.1362/026725708X325995 PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms- and-conditions

Customer portfolio planning in a business network context

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This article was downloaded by: [University of Strathclyde]On: 10 October 2014, At: 08:45Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registeredoffice: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK

Journal of Marketing ManagementPublication details, including instructions for authors andsubscription information:http://www.tandfonline.com/loi/rjmm20

Customer portfolio planning in abusiness network contextTeck-Yong EngPublished online: 01 Feb 2010.

To cite this article: Teck-Yong Eng (2008) Customer portfolio planning in a business networkcontext, Journal of Marketing Management, 24:5-6, 567-587, DOI: 10.1362/026725708X325995

To link to this article: http://dx.doi.org/10.1362/026725708X325995

PLEASE SCROLL DOWN FOR ARTICLE

Taylor & Francis makes every effort to ensure the accuracy of all the information (the“Content”) contained in the publications on our platform. However, Taylor & Francis,our agents, and our licensors make no representations or warranties whatsoever as tothe accuracy, completeness, or suitability for any purpose of the Content. Any opinionsand views expressed in this publication are the opinions and views of the authors,and are not the views of or endorsed by Taylor & Francis. The accuracy of the Contentshould not be relied upon and should be independently verified with primary sourcesof information. Taylor and Francis shall not be liable for any losses, actions, claims,proceedings, demands, costs, expenses, damages, and other liabilities whatsoever orhowsoever caused arising directly or indirectly in connection with, in relation to or arisingout of the use of the Content.

This article may be used for research, teaching, and private study purposes. Anysubstantial or systematic reproduction, redistribution, reselling, loan, sub-licensing,systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions

Page 2: Customer portfolio planning in a business network context

INTRODUCTION

In today’s increasingly globalised and competitive business environments, the analysis of a firm’s relationships has moved from a dyad relationship or a focal firm’s portfolio of relationships to a network view of relationships. While a network view of business and relationships has attracted much research attention, current approaches

JOURNAL OF MARKETING MANAGEMENT, 2008, Vol. 24, No. 5-6, pp. 567-587ISSN0267-257X print /ISSN1472-1376 online © Westburn Publishers Ltd. doi: 10.1362/026725708X325995

Customer portfolio planning in a business network context

Teck-Yong Eng, University of London, UK*

Abstract In an increasingly globalised business environment, it is no longer adequate to analyse and develop supplier-customer relationship portfolios without consideration of a firm’s network relationships. While research in business relationships has examined resource allocation and strategy development in the context of a dyadic relationship, portfolios and network relationships, little is known about the network effects of a focal firm’s relationships on its performance particularly from both supplier and customer evaluations. The present study attempts to fill this gap by developing a customer portfolio framework that includes four levels of business relationships, and integrates a resource-based view and industry determinants of competitive advantage. The proposed framework is applied and analysed using data of UK-based food service companies. The main results show that a focal relationship performance is influenced by both industry and resource-based advantages in a business network context. The results also suggest that a focal firm can better enhance its competitive position with the knowledge of network effects and interdependence of strategic actions in a business network context.

Keywords Customer portfolios, Network effects, Focal-firm performance

JOURNAL OF

MARKETINGMANAGEMENT

*Correspondence details and a biography for the author are located at the end of the article.

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to analysing business customers remain under-developed in terms of treating business relationships separately for a single exchange relationship, a dyad relationship, a focal firm’s portfolio of relationships or network relationships. Such approaches fall short of capturing potential changes in the network that would affect a focal firm. In particular, there is little empirical evidence about the extent to which network effects of a focal firm’s relationships affect business performance from both supplier and customer perspectives.

While there is recognition of the importance of business networks in enabling and constraining firm performance (Anderson, Håkansson and Johanson 1994; Håkansson and Snehota 1995), there is lack of theoretical and empirical contribution to the customer portfolio concept as regards the analysis of customer relationships in a business network context. For example, scholars investigating the network phenomenon and interfirm relationships have noted that there is relatively little research that examines multilevel and network effects on a firm’s focal relationships (see Hagedoorn 2006; Lavie 2006). Prior research has mainly focused on theorising and conceptualising types of network relationships and their implications for network members (e.g. Ritter, Wilkinson and Johnston 2004; Lavie 2006). In brief, the focus of previous studies on network characteristics, network structure and network position has left a theoretical and empirical gap between integration of internal resources and external relationships for examining network effects on a focal firm’s business relationships.

The premise of this study is that a firm’s business relationships are part of networks of relationships, which can be influenced by network effects. Network effects can be described as changes that occurred beyond a company’s focal and portfolio relationships. The changes in question are strategic such as strategic moves related to pricing, new product development, technology, new entrants to a business network and service quality. They have implications for a firm’s focal relationship performance as well as strategy development. Network effects are characterised by dynamic changes through ongoing business development in relationships, and competitive actions and cooperation between firms. But the existing works on buyer-seller relationship analysis do not examine the network effects on business performance (e.g. Shapiro and Varian 1999; Ford and McDowell 1999). As Lavie (2006) points out interfirm relationships have either been examined at the dyadic or network level but never across interconnected network relationships and/or across customer portfolios.

Thus, the present study attempts to examine the influence of network effects in business relationships on business performance. Specifically, a new framework of business relationship analysis is developed to extend the customer portfolio concept to a business network context, and to accommodate the main assumptions of a business network such as blurring of organisational boundaries and multilateral coordination in strategy development. The proposed framework accounts for network effects by analysing business relationships on four interdependent relationship levels, and integrating the resource-based theory to capture dynamic aspects of relationship development. This framework is operationalised and tested using actual data of both supplier and customer relationships. To accomplish these, the article first reviews the literature to examine customer portfolio planning in a business network context and specify a framework for the research. This is followed by description of the procedure used for implementing and analysing the framework. The results are then analysed and discussed in terms of implications for theory and practice.

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LITERATURE REVIEW

Background theories and defi nitions

The study of business networks and interorganisational networks has been examined through many research traditions. In particular, social exchange theory, relational view and social network theories have provided insights to the International Marketing and Purchasing (IMP) group research on business networks. Drawing on social exchange theory, a business network can be defined as a set of two or more connected business relationships (Emerson 1981), and connected refers to the extent to which exchange in one relation is contingent upon exchange (or non-exchange) in the other relation (Cook and Emerson 1978). In this sense, a company’s portfolio of relationships is not isolated from network relationships outside its portfolio, which can be both directly and indirectly connected with other relationships that have some bearing on the company, as part of a network context. The relational view (Dyer and Singh 1998) recognises that critical resources may span firm boundaries, and joint development of resources through business relationships can give rise to competitive advantage. Social network theories examine interfirm relationship structures, and the impact of network-level cooperation, communication and learning on strategies and performance on the basis that interorganisational relationships are interdependent entities (e.g. Di-Maggio and Powell 1983; Grandori and Soda 1995; Nohria 1992).

Table 1 provides a summary of terms and/or concepts from the business network literature for understanding network features. A network context is part of a firm’s environment that is socially constructed and shared through interactions between firms. It differs from the concept of environment in that the boundary of a firm in a network context is much more diffuse than the environment (Anderson et al. 1994). Network horizons recognise that a business network context extends without limits through connected relationships, and an actor’s (firm) view of the network depends on bounded knowledge and experience of the actor (Emerson 1981; Håkansson and Johanson 1993). This has implications for defining a firm’s boundaries for determining structural advantages in strategy development. Since a firm’s business relationships extend beyond two parties of a focal relationship and portfolio of relationships, strategic action in networks can affect business relationship performance. Network position influences structural position (competitive position) from the firm’s past, present and future activities (also see Mattsson 1987). Thus, both network position and network horizons have implications for present and future performance of relationships, and competitive position.

The concept of network horizon has been defined in the literature for the purpose of conceptualising and analysing network effects on relationship performance. For example, Anderson et al. (1994) divide relationships into primary and secondary functions. The former are directly connected to each other in a focal dyadic relationship whereas secondary functions are the effects of relationships connected directly or indirectly to other relationships that can be as important as the primary ones. For example, the primary functions comprise of two parties in a buyer-seller relationship leveraging and learning about each other’s resources to increase the benefits that each receives. The secondary functions are connections of relationships between the two parties in the primary functions such as several other parties or third parties may support the activities of the primary functions in a focal relationship (Anderson et al. 1994). Möller and Halinen (1999) propose a network management framework that comprises: exchange relationships, portfolio relationships, firms

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in network and industries. Similarly, Ritter et al. (2004) suggest five levels of relationship: the individual actor, the single dyad, the portfolio of relationships, the connected relationships, and the complete set of relationships on the network level. These classifications illustrate that a buyer-seller relationship in business markets is connected to a network of relationships but no research has yet examined the network effects of different levels of business relationships on a focal relationship performance.

Network effects and levels of customer analysis

Although it is possible to conceptualise business relationships at different levels to account for network effects, the multiple effects from network relationships do

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TABLE 1 A summary of main constructs and concepts for analysis

Definition ExampleA customer portfolio refers to a mixture of different supplier-customer relationships of a company.

A firm analyses the interplay of its customers for effective resource allocation and strategy development.

Network effects are changes related to a company’s relationships beyond two parties or portfolio relationships.

A firm’s focal relationship performance is influenced by changes in network relationships such as quality of raw materials and entry or exit of business partners in a network.

Network horizons recognise that the network extends without limits through connected relationships and thus a business network boundary depends on how extended an actor’s (e.g. firm) view of the network is.

Each firm not only has different network relationships but its network boundaries for consideration are also different depending on its knowledge of network relationships.

Network position is a consequence of the earlier activities between firms in the network. It influences the competitive position of a firm, as the past activities enable or constrain present and future strategies.

A firm’s choice of relationships and future performance can be influenced by its past and current relationships as regards use of resources in and through relationships.

Network capabilities are combined or joint capabilities embedded in network relationships through interaction of activities and resources.

A joint product development requires resource inputs and coordination of activities among different interfirm relationships.

Resource differentials refer to differences in terms of possession of resources through various means (e.g. access, joint development) that confer competitive advantage.

A firm can gain access to technology and knowledge through its business relationships.

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not necessarily affect focal and network relationships in a linear fashion. Network research has noted that it is important to take into account cross-functional relations and their impact on a focal relationship (e.g. Brandenburgers and Nalebuff 1997; Eng 2005a). This suggests that customer portfolio planning needs to account for the influence of network effects at multiple levels, which could have both linear and non-linear effects. In contrast to the linear effects, the non-linear effects are indirect consequences occurring in a network such as an increased in the cost of raw materials having an indirect impact on market demand. Prior customer portfolio models (e.g. Turnbull 1990; Turnbull and Zolkiewski 1995; Eng 2004a) have focused on refining and/or introducing new variables for analysis without analysing perceived strategic advantages or potential constraints based on resources or industry positions of different levels of relationship in a network context. The current network literature has mainly focused on conceptualisation of concepts for analysing different levels of network relationships (e.g. Lavie 2006; Hagedoorn 2006). Also, such research can be considered as exploratory due to the limitation of linear statistical methods for analysing multiple network effects. Thus, there is not yet empirical research on multiple levels of network effects on a focal relationship.

Conceptually, it is possible to analyse network effects from the perspective of the focal firm based on the levels of relationship. Figure 1 (overleaf) presents a visual representation of customer portfolio planning from the perspective of a focal firm, which includes different levels of relationship conceptualised in the literature (Möller and Halinen 1999; Ritter et al. 2004), and provides support for the importance of considering network members in focal firms’ business performance (Brass and Burkhardt 1993). Clearly, the ways to break down network relationships for the purpose of analysis can vary (e.g. see Anderson et al. 1994) but they essentially show both direct and indirectly connected relationships. This is consistent with the concept of network horizon (Anderson et al. 1994), where it can be interpreted that a focal firm has bounded knowledge of network effects on its relationship performance. Literature on interfirm partnership formation has conceptualised that a firm’s relationships are connected to many separate levels of interaction characterised by interdependence of positive and negative effects (Chung et al. 2000; Gargiulo and Benassi 2000; Hagedoorn 2006). In brief, a firm’s knowledge of network effects can be examined on different relationship levels (see Figure 1) to improve its competitive advantage and network position.

Network effects and customer portfolio analysis

Since the concept of customer portfolio planning has been used for analysing relationship performance and strategy development, the inclusion of network effects on a focal relationship raises important questions as regards control of both strategy and network resources, and the extent to which a focal relationship performance is influenced by different relationship levels. Within a network context, strategic action of any single firm in the network can have different degrees of influence on a focal firm’s strategy. This is because ongoing strategy and changes in the network may impact on the focal firm or activities beyond the control of the focal firm (see Ford and Saren 1996; Eng 2005a). Recent development in the network literature has noted that strategy development in a network context cannot be fully explained using structural characteristics (e.g. Bengtsson and Kock 2000; Eng 2005a) and internal control of resources by a firm (e.g. Eng 2005a & b; Lavie 2006). In addition, recent studies on customer portfolio analysis have noted the importance of network

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relationships for a focal relationship performance (Johnson and Selnes 2004; Eng 2004a) compared to customer portfolio models developed in the 1980s (e.g. Fiocca 1982; Campbell and Cunningham 1983). But no research has yet examined the implications of network effects on multiple levels of relationship for performance from both supplier and customer perspectives.

Advances in the strategy and network literature have pointed out that it is necessary to analyse interfirm relationships beyond industry or firm structural differences. Customer portfolio planning in a network context draws on theories of strategy analysis for resource allocation and strategy development. For example, relationships and knowledge of network resources are considered strategic assets. This network perspective is compatible with the resource-based view theory in terms of resource accumulation over time. In other words, business relationship development is dynamic whereby it is characterised by an iterative process of the interaction of actors-activities-resources (Håkansson and Snehota 1995). In the context of strategy analysis and development, the resource-based view provides insight into the importance of tangible and intangible resources for developing a sustainable competitive advantage (Wernerfelt 1984; Barney 1991). Also, the resource-based view moderates the deterministic approach of structural analysis (Eng 2005b), and considers access, development and acquisition of resources through business relationships (Eng 2004a). Thus, this study integrates the resource-based view with the analysis of structural differences for customer portfolio planning in a network context.

While the resource-based view examines a firm’s resource capabilities for developing competitive advantage, it assumes ownership or at least complete control of critical resources by the firm (Amit and Schoemaker 1993; Barney 1991). In a business network, the control of resources may require several partners to coordinate in a multilateral ownership rather than in a single ownership. Lavie’s (2006) theoretical assessment of the resource-based view and network resources suggests that the focus on resources controlled by the firm undermines the essential contribution of the resources of network members. Evidence from alliance partnership and interfirm studies have indicated that resources of counterpart firms can be accessed, utilised and shared by alliance partners (e.g. Saxton 1997; Afuah 2000; Lee, Lee and Pennings 2001). In brief, network resources can contribute to the focal firm’s performance (Conner 1991) particularly in a cooperative type of interaction (Lavie 2006). Prior research provides support for the need to examine different levels of network effects in business relationship and their impact on relationship performance. By extending the customer portfolio concept to consider network effects, a reformulated resource-based view would integrate the relational view (Dyer and Singh 1998) and the concept of actors-activities-resources (Håkansson and Snehota 1995).

A framework for examining network effects

Figure 2 provides a summary of the variables used for customer portfolio analysis in a network context. While the focus of current portfolio models is limited to structural analysis of market attractiveness (e.g. market share, degree of industry concentration, industry profitability), this approach is able to capture performance at a point in time and provide guidance for strategic planning (Eng 2004a). Structural analysis of industry and firm-level differences delineates structure and strategic action to identify advantages such as market power and market share. There is a reciprocal relation between structure and action as individuals create structure through action and that at the same time they are restricted in their actions by that structure (Giddens

573Eng Customer portfolio planning in a business network context

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1984). For example, intensity of competition between firms in their industry sectors affects profitability of individual firms connected to the network of industry sectors. In this instance, structural differences such as intense competition can be a central driving element in pressuring and stimulating firms to innovate and upgrade their competitive advantage (Porter 1990).

Since a firm’s performance in its industry can include relational rents governed by cooperative interaction and coordinated strategic action, the proposed framework integrates a reformulated resource-based view in a network context. This moderates the static assumptions (e.g. predetermined industry boundaries, stable equilibrium model) of structural analysis, and recognises the potential for developing sustainable competitive advantage through network resource capabilities. Valuable resource capabilities are non-tradable and cannot be acquired in strategic factor markets (Dierickx and Cool 1989; Barney 1989) but their market value can be determined by network relationships (Koh and Venkatraman 1991; Reuer and Koza 2000). This is because network resource capabilities are not fully reducible to any single firms. Empirical research showed that firms in network relationships achieved higher performance through leveraging complementary resources (Rothaermel 2001), cooperation (Stuart 2000) and sharing of network resources (Lee, Lee and Pennings 2001). The concept of network capabilities underscores the complexity and ambiguity of network effects that are not clearly identifiable and yet able to contribute to the overall performance of the network. The types of resource capabilities can be examined by Hall’s (1993) strategic analysis of tangible and intangible resources, namely product attributes and four types of differential capabilities: functional, positional, regulatory and cultural. A functional differential relates to the ability to do specific things; it results from the knowledge, skill and experience of employees and others involved in the business such as suppliers, franchisors, distributors, stockbrokers, lawyers and advertising agencies. A positional differential is a consequence of past actions such as reputation, networks and location of facilities. A regulatory differential results from the possession of legal entities such as intellectual property rights, contracts and

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FIGURE 2 Strategy analysis of business relationships in a business network context

External environmentalvariables of structuraldifferences, e.g. marketshare, profitability, growth, degree of competition, bargaining power

Internal resource differentialsbased on product attributes, functional, regulatory and cultural capabilities

Interaction between firmsinfluenced by both short andlong-term relationship dynamics, e.g., power dependence, co-evolution, control

Network effectson four levels of businessrelationships

Relationshipperformance:• Supplier evaluations• Customer evaluations

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licenses. A cultural differential includes the habits, attitudes, beliefs and values, which permeate the individuals and groups which comprise the organisation (for details of these capabilities see Hall 1992, 1993). They include network resources that can help the network to reach its goals quickly, efficiently and effectively (Christie and Levary 1998).

METHODOLOGY

Research strategy

It is worth noting that theory development and empirical research on multilevel analysis involving different levels of relationship and cross relations are still at an exploratory stage (Lavie 2006; Hagedoorn 2006). This study attempts to build on existing research and extend the customer portfolio concept using theoretical insights from the strategy and network literature for network effects on a focal firm relationship performance. The choice of the case study method was influenced by: (1) the complexity of network relationships; (2) the need to operationalise the proposed framework; and (3) the need to gain insights into potential network effects of four levels of relationship. The research method needs to be open, flexible, and produce valid and robust interpretations of the proposed framework and practice. The case study method provided the opportunity to establish rapport with respondents through interviews or conversations, which was necessary for obtaining insights about network effects. Sampling procedure is not applicable to case studies but rather each case company is analogous to replication logic of experiments. Also, a large scale quantitative research would not be suitable for applying and testing the application of the proposed framework on different levels of relationship.

Company selection and interviews

A total of 15 large (employing more than 500 personnel) UK-based companies operating in the food service sector agreed to participate on the condition that their identity will be kept anonymous. Large companies were selected because they tend to develop complex networks of relationships (e.g. Holm and Eriksson 1999; Dyer and Nobeoka 2000) as well as relationship management is important in the food service business. For example, food service companies develop good supplier relationships to achieve high quality produce and timely delivery of perishable goods. Interviews were conducted first with Chief Executive Officers (CEOs) in each company, and they provided an introduction to the operations of the company, its core business and markets, competitive position and its business relationships with other firms. In order to examine network effects on different levels of relationship, the CEOs were asked to identify business relationships (supplier or customer relationships) on four levels of relationship that are considered important to their company. The choice was primarily influenced by the size of sales turnover, the strategic importance of the relationship or the deteriorating state of the relationship. On the basis of the chosen relationship, a reliability check was carried out by mapping all the relationships connected either directly or indirectly to identify relationship connection according to the four levels of relationship defined earlier. The total number of business relationships and/or networks examined was: n = 218 for level one; n = 306 for level two; n = 82 for level three; and n = 78 for level four. Senior managers responsible

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for managing these relationships were approached for further interviews through the CEOs’ cooperation. Multiple personal interviews were carried out with the senior managers over an 18-month period to analyse the strategic implications of network relationships.

Analytical procedure

The analysis was based on the variables in Figure 2, and ratings on the variables were anchored accordingly, for example, on a five point Likert scale (1= ‘very low’, 5 = ‘very high’). The use of ratings allowed comparison of network effects on different levels of relationship. In order to reduce selection bias and increase reliability, both tangible and intangible resources were examined in the analysis. The variables analysed can be discussed following the perspective of the resource-based view and the industry analysis. The present study used a process-driven method (Eisenhardt 1989) to describe the content of the different levels of relationship and the network effects on a focal relationship (Srivastava, Fahey and Christensen 2001). In addition, the variables of external analysis of industry differences and resource differentials were noted in terms of the extent to which the variables have been analysed on different levels of relationship.

Resource-based analysis

The concept of resource differentials (Coyne 1986; Hall 1993) provided insights for the analysis of resource-based advantages. The analysis of resources can be divided into three categories: resource analysis, channel analysis and capability analysis. Resource analysis accounts for competitive advantage based on technology, product attributes (e.g. brand, image), database, skills, knowledge and experience. Channel analysis is based on access to resources through relationships (e.g. sharing resources), network relationships, and network membership and strength. Capability analysis refers to capability differential relative to other networks based on functional, regulatory and cultural capabilities (see Hall 1992, 1993).

In the context of network relationships, differential capabilities are valuable resources. They were analysed in terms of provision, use, access, development and complementarities (Håkansson and Snehota 1995), which exist on different relationship levels. The provision of resources was analysed to determine the extent to which firms in networks provide resources for the focal relationship. The use of resources was examined by comparing the use of resources on different levels of relationship. The question of access was examined in terms of the opportunity available on different levels of relationship, in order to gain access to valuable resources. Also, resources were analysed in terms of whether valuable resources require joint development with other actors in networks. Resource complementarities were examined in terms of the extent to which firms are interdependent over the use of valuable resources. These valuable resources in and through different levels of relationship were first assessed before they were compared and contrasted with the industry-based advantages.

Industry differences

The second part of the analysis was derived from the existing customer portfolio models (see Eng 2005a) for developing strategy based on positioning for structural

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advantages. In the first instance, perceived positional advantages based on structural determinants (see Figure 2) were analysed by comparing the relative performance of the business relationship on different relationship levels. The variables based on industry analysis were divided into three categories according to their function: market, structure and competition. Market analysis includes market share, segmentation, sales territory, growth rate, demand, customers and products. Structural variables include size and scale, capital investment, profitability, bargaining power and switching costs. Competitive analysis focuses on positioning strategies such as cost leadership, differentiation, and focus or niche.

The significance of the perceived positional and resource-based advantages was further analysed in terms of the degree of control and dependence. The degree of control over the advantages was assessed as regards the extent to which firms have possession over the resources (Pfeffer and Salancik 1978). The degree of dependence examined the extent to which the firm is dependent on its network counterparts (cf. Kelly and Thibaut 1978). This recognises that control of network resources could reside with several firms (Lavie 2006) and the path dependency of business relationships (Håkansson and Waluszewski 2002; Uzzi and Spiro 2004). Furthermore, there is no presumption that control over critical resources by one party would necessarily render dependence to the other party. For example, control may be perceived as complementary or the resources may not be required in certain markets.

Evaluation of the study

Since the strength of the sources of competitive advantage may vary on different levels of relationship, an evaluation of the extent to which companies control and depend on the industry determinants and resource capabilities can enhance the study’s reliability. A ten-point scale with anchors ranging from 1 (highly uncontrollable/independent) to 10 (highly controllable/independent) was applied to examine the relationship between control and dependence. The total scores obtained from both the degree of control and dependence was first multiplied by the number of companies noted in the analysis and then divided by the number of companies in the study to obtain average scores for four levels of relationships.

The key issues concerning the validity of the constructs must be interpreted with an understanding of the limitations inherent in a qualitative study. The underlying strategic variables used for analysing the industry-based advantages and resource capabilities should provide sufficient support for content validity. Theoretically, the strategic variables were drawn from previous empirical studies. The strategic variables reflect some of the common indicators (e.g. market share, profitability) used by managers to assess the marketplace. Consistent with the literature, a firm’s resource capability is concerned with its ability to use, develop, access and combine and complement resources with other firms in networks to take advantage of both valuable resources and structural differences for developing competitive advantage (Håkansson and Snehota 1995; Kaleka 2002). These provide support for convergent validity as the internal analysis of resources and the external analysis of positional advantages are based on contrasting theories for strategy analysis.

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RESULTS AND DISCUSSION

Infl uence of industry analysis on different levels of relationship

Table 2 shows the variables for industry analysis feature strongly on the level one and two relationships of the 15 focal companies. Market share (81%) and industry profitability (78%) are most often used in strategy analysis of relationships. These variables indicate short-term firm performance and they are less notable as the companies’ focal relationships extend further into networks. In this instance, both market share (31%) and profitability analysis (23%) have been considered on the level four but less significant for the variables of growth (18%) and degree of competition (14%). The relationships close to the focal firm have been examined closely due to the importance of rapid market turnover and cash flow in the food service business.

The strong emphasis on market power through the analysis of industry differences has been shown to confer performance advantages (Scherer 1980). Prior research has found that structural differences account for about 15 percent, at best, variance in firm performance (Gale 1972; Rumelt 1991; Roquebert, Philips and Westfall 1996; McGahan and Porter 1997). But much of the extant research examines industry attractiveness in manufacturing and production industries. Also, little is known about network effects on different levels of relationship and their influence on relationship performance.

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Percent Using (Rate of Usage 1 = not very important; 5 = very important)

Strategy perspective Level 1n=218

Level 2n=306

Level 3n=82

Level 4n=78

Industrial OrganisationMarket share 81(3.12) 75(2.25) 41(1.46) 31(1.35)Industry profitability 78(2.76) 64(1.60) 37(1.52) 23(1.17)Growth rate 76(3.71) 72(2.59) 52(1.17) 18(2.01)Degree of competition 73(2.71) 62(1.17) 62(1.22) 14(1.10)Substitute 48(1.43) 36(1.12) 26(1.20) 21(1.21)Entry barriers 41(2.19) 39(1.73) 24(1.42) 16(1.32)Bargaining power 36(1.60) 31(1.35) 19(1.27) 15(1.28)

Resource-based ViewProduct attributes 68(2.49) 61(2.01) 38(1.12) 18(1.19)Skills/knowledge 53(2.28) 59(1.69) 25(1.38) 17(1.12)Experience 58(2.98) 54(2.49) 31(1.49) 15(1.20)Legal protection 57(1.85) 51(1.85) 28(1.12) 13(1.15)

Organisational culture 31(1.36) 25(1.41) 13(1.17) 11(1.12)

TABLE 2 Structural determinants versus resource-based advantages ranked on degree of usage

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Infl uence of resource-based analysis on different levels of relationship

The variables of resource-based analysis received considerably less attention compared to external analysis, with product attributes (68%), and skills and knowledge (59%) as most popular variables for strategic analysis of relationship. The companies were more concerned with analyses related to product attributes (e.g. brand name, service quality), and skills and knowledge rather than with cultural capabilities (e.g. teamwork, management styles). More than 57 percent at the focal relationship noted the importance of regulatory differential for their business activities, namely copyright, registered trademark and intellectual property rights. The food service business is characterised by innovation of ready meals, branding and meal solutions. Interestingly, there is little consideration of the use of regulatory and cultural differentials for strategy analysis on level four of network relationships. As shown in Table 2, product attributes, and skills and experience play a weak role for most of the level four relationships. But it is important to analyse skills and knowledge (25%) of business relationships in the level three relationships. The competitive pressure of the food service sector provides some explanation for the companies’ focus on sales growth and profitability target.

Network resources and different levels of relationship

The results indicate that the companies use, provide, acquire, combine and/or develop resources with their business partners on different levels of relationship. Although resources are exchanged and developed most intensely in focal relationships or relationship portfolios, they have implications for existing and future commitments in a business network. The focal level of relationship provides direct access to a partner’s resources. This is important because food service companies often rely on partners and retailers for new product development and speed to market. In addition, the level of technological compatibility between firms has been noted to influence commitment and choice of relationships. For example, an efficient flow of information through compatible information technology is crucial for inventory management, and food service companies are often locked into supply chain activities of their membership to a particular exchange platform (see Eng 2004b).

Further research is needed to examine focal relationships such as whether developing a strong relationship with key network partners would enhance relationship commitment and performance in the presence of physical distance with network relationships. Ganesan, Malter and Rindfleisch (2005) suggest that for efficient exchange and sharing of knowledge a firm must first develop strong relationships with key knowledge providers to gain access to knowledge regardless of whether these organisations are near or far. This is because close interaction provides enhanced communication for exchange and sharing of resources. The implications for customer portfolio planning in a network context are twofold. The first is that a focal firm’s knowledge of network relations could enhance network horizons and present new business opportunity such as innovation through complementary resources. The second is related to the first that physical distance or perceived distance of the level four relationships is not necessarily an obstacle for developing strong relationships and accessing network resources.

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Perceived network effects and focal relationship performance

Since the companies may not follow any explicit and systematic approach to analysing business relationships, the study examines perceived network effects of strategic actions on different levels of relationship. The analysis focused on performance outcomes based on three composite dimensions of strategy analysis (see Table 3). The perceived network effects of strategic actions based on environmental analysis were derived from companies’ perception about the extent of changes to strategic variables initiated by the companies themselves, or by their exchange partners on the four levels of relationship in terms of perceived advantages. The changes could affect the food service companies, as they are dependent on different industries to manufacture and distribute their products.

The results provide support that choice of strategy variables have implications for determining competitive position. For example, a relatively high network effect of market analysis (47%) has been observed for the level four relationships. Third parties or industry and network relations can affect potential sales growth through demand in the consumer markets, availability of substitutes and competition. As expected, the strength of network effects is most evident in focal relationships for both external environment analysis (67% for market analysis) and internal resource analysis (72% for resource analysis). This is partly due to the companies’ knowledge of immediate or directly connected relations.

Whilst the strategic changes that occurred in the focal relationship level have a strong impact on the companies, strategic actions that affect other levels of relationship could initiate changes at the focal level. Table 2 shows both structural analysis and resource-based view have been frequently noted in focal relationships. The results of the network effects of the resource-based variables (72%) are slightly more significant than the industry-based variables (67%). The focal relationships are highly susceptible to changes of strategic actions related to channel and capability resources of the level three network relationships. The food service companies noted speed to market, responsiveness and coordinated strategies for their success in the marketplace. They require efficient logistics to retain quality and freshness of perishable products. For example, a focal relationship needs to work with other companies to adapt and respond to demand, and achieve quality use of resources in the industry such as innovative meal solutions.

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TABLE 3 Perceived network effects on four relationship levels

Percent times selectedStrategy perspective Level 1

n=218Level 2n=306

Level 3n=82

Level 4n=78

External environmentMarket analysis 67.3 65.7 58.4 47.3Structural analysis 59.7 53.6 42.8 37.8Competitive analysis 56.8 61.5 34.1 27.4

Internal resourcesResource analysis 71.8 63.6 58.4 33.7Channel analysis 66.2 61.8 40.8 21.6Capability analysis 63.4 55.4 32.7 18.3

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The results suggest that competitive advantages based on structural differences (e.g. differentiated markets, cost leaderships) are supported by superior resource capabilities (e.g. joint development, access to resources in the networks). This implies that different firms in a business network provide different relationship specific advantages. Dyer and Hatch (2006) note that companies’ relationship specific resources such as network resources and knowledge transfer between firms are not easily transferable to other settings. In addition, companies in a business network may achieve differential benefits though their membership in a business network or industry structure in terms of distance from a focal firm (Dyer and Singh 1998).

Perceived control and dependence for focal relationship performance

Although not all the companies’ strategic actions show a high network effect on the level three and four relationships, the results suggest the vulnerability of focal companies in terms of threats from their network members. For example, the focal companies could face threats of control and over-dependence on certain relationships for product technology and product distribution. One way to assess whether the presence of network effects has a weak or strong impact on the focal companies’ choice of strategies is to examine the perceived degree of control and dependence (see Table 4). As shown in Figure 3, the companies’ degree of control over the sources of industry and resource-based advantages decreases as the focal relationships extend into networks. For example, the control over structural advantages at the focal relationship is high (7.2) compared to network relationships (3.17). The results of control over factors related to competitive position at the focal relationships (6.38) are higher than the network level of relationships (3.08). Table 4 shows that companies with a low level of control over channel resources (2.17) on the level four network relationships also have a low level of dependence (3.39). This could be because the perception of dependence is examined against relationships at the focal level.

The results of perceived dependence are consistent with the observe power resulting from control. For example, companies have a higher degree of control or lower dependence on the level one focal relationships compared to the level four network

TABLE 4 Perceived degree of control versus dependence on four relationship levels

Control = C; Dependence = Da

Strategy perspective Level 1n=218

Level 2n=306

Level 3n=82

Level 4n=78

External analysisMarket analysis C(7.83) D(5.63) C(5.78) D(4.18) C(3.73) D(4.83) C(3.12) D(2.11)Structural analysis C(7.21) D(6.17) C(5.61) D(5.46) C(4.11) D(5.73) C(3.17) D(2.42)Competitive analysis C(6.38) D(6.19) C(5.47) D(4.94) C(5.27) D(5.87) C(3.24) D(1.18)

Internal resourcesResource analysis C(8.64) D(6.12) C(5.87) D(4.49) C(4.74) D(5.31) C(2.37) D(2.28)Channel analysis C(7.79) D(6.45) C(5.85) D(4.21) C(5.68) D(6.85) C(2.17) D(3.39)Capability analysis C(7.31) D(6.38) C(5.14) D(4.63) C(4.85) D(5.93) C(3.17) D(2.18)

a Note: Ranked on a ten-point scale: 1=highly uncontrollable/dependent and 10=highly controllable/independent

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relationships. The results indicate that the dependence on resource capabilities increases as the focal relationships extend further into the network relationships. This suggests that the companies with a low level of control are also susceptible to the interaction of network relationships on the level three and four relationships.

The nature of multilateral control in business relationships highlights potential opportunities as well as threats from networks. In customer portfolio planning, the performance of focal relationships is not only influenced by network capabilities (Foss 1999) but also by network resources of the focal firm’s relationships (Dyer and Hatch 2006). The network resources could provide strategic opportunities and affect firm behaviour and value (Lavie 2006). Firm performance has been shown to have a direct relationship with its relative bargaining power to alliance partners (Khanna, Gulati and Nohria 1998). This is because the industry differences are fixed in the short-run whereas firms’ processes of resource accumulation are path dependent and a resource capability can be developed over time through learning. Thus, consideration of power and dependence needs to include network relationships especially relative bargaining power can be accumulated over time through learning skills (Hamel 1991; Inkpen and Beamish 1997).

MANAGERIAL IMPLICATIONS

In recent years, scholars in the field of strategy and marketing have pointed out that companies are moving away from vertical integration to horizontal interfirm relationships (e.g. Achrol and Kotler 1996; Srivastava et al. 2001). This reinforces the need to recognise both competitive and cooperative nature of business relationships in a networked economy, and to account for performance implications through a multi-level understanding of network effects on a focal firm’s relationships. The implications for management can be discussed with respect to a strategic choice of

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FIGURE 3 Perceived control and dependence on four relationship levels

100

90

80

70

60

50

40

30

20

10

0

L1 L2 L3 L4

Control

Dependence

Level 1-4 relationships

Con

trol

& d

epen

denc

e (%

)

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relationships, performance leverage and management skills in the network context of customer portfolio planning.

Although business relationships are often selected through an analysis of directly connected relationships or through focal partners, this study has shown that relationships beyond a focal partner can have both positive and negative strategic implications for the focal firm performance. It is possible for managers to exert indirect control over network effects, as their interaction at the focal level as well as with other parties in a particular business network has been shown to affect focal firm performance. As such, a manager’s choice of certain relationships and investment decisions can influence network relationships and subsequent strategic outcomes. The basis of relationship choice may not be either competitive or cooperative; but could include rival partners in the industry characterised by both cooperation and competition, i.e., coopetition (Bengtsoon and Kock 2000; Luo, Slotegraaf and Pan 2006). This requires managers to examine customer relationships using an alternative perspective of the resource-based view that considers both tangible and intangible assets in customer portfolio management such as relational assets, knowledge, skills and experience.

The results indicate that network resources at the level four relationships can affect focal firm performance, and they can be sources of competitive advantage. Managers can identify valuable resources beyond focal relationships such as suppliers of high quality ingredients in the food service business. This long-term perspective of asset accumulation in and through relationships can help firms strategically choose and develop successful relationships (resources) in customer portfolio planning. For example, a firm may choose to develop relationships with network relations connected through its focal relations for the purposes of acquiring skills and developing technological knowledge. The presence of network resources provides the opportunity for firms to develop relationship specific assets, which are embedded in a business network and are sources of a sustainable competitive advantage. Thus, managers need to consider the network effects on the choice of business relationships and the interaction of structural differences with resource capabilities on different levels of relationships in a customer portfolio analysis.

In addition, managers also need to manage business relationships in the context of a business network, where there are difficulties associated with control, change and stability, and management competence in integrating network resources with industry based advantages. This study offers guidelines for the analysis of network effects on focal relationship performance. Although the extent to which a focal relationship extends to network relations is arbitrary and context specific, managers can enhance their skills and knowledge of network relationships through a customer portfolio planning that accounts for both different relationship-levels and network effects. In brief, managers must develop skills and knowledge of their business networks, combine both tangible and intangible resources, and integrate resources and processes with structural advantages according to specific relationships to enhance performance.

CONCLUSION

In conclusion, this study indicates that the analysis of network effects on different levels of business relationships provides more insight into a company’s competitive position than the conventional analysis limited to focal and/or portfolio relationships. A network perspective to customer portfolio planning can better inform firms

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of strategic and network relationships that enable or constrain their strategy development. Both industry determinants and resource-based advantages have been shown to influence different levels of a focal firm’s relationships and its performance. Whilst the analysis of industry determinants received much more attention in focal relationships than network relationships, the resource-based analysis provided insights into the long-term process of resource accumulation that underpins a competitive position. Altogether, the network effects through different levels of relationship, and the complementary perspective of strategy analyses need to be considered in customer portfolio planning.

Specifically, the study contributes to theory development of customer portfolio planning in a network context. It is the first study examining business relationships on different levels in a network context, and applying an extended resource-based perspective drawing on the relational view, where network resources require knowledge beyond firm boundaries and analysing their effects on focal-relationship performance. The present study indicates that network relationships can have a strong effect on focal relationship performance in terms of control of critical resources that influence a focal firm’s performance. By using the proposed framework of customer portfolio analysis, it is possible to analyse, develop and harness network capabilities – which could provide sources for developing a sustainable competitive advantage. Finally, this study suggests a systematic approach to analysing business relationships on four levels in order to account for network relations. Both information advantages and uncertainty reductions from greater understanding and experience of a firm’s network relationships such as through customer portfolio planning in a network context can give rise to a superior firm performance (Macher and Boerner 2006).

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ABOUT THE AUTHOR AND CORRESPONDENCE

Teck-Yong Eng is a senior lecturer in marketing at King’s College London, University of London, UK. He gained a PhD in Business-to-business Marketing from The University of Manchester. His teaching and research interests include business marketing strategy, business networks and supply chain management.

Teck-Yong Eng, Ph.D., Senior Lecturer in Marketing, King’s College London, University of London, School of Social Science & Public Policy Management Department, 150 Stamford Street, London SE1 9NH, UKT +44 (0)207 848 4211E [email protected]

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