Dyadic Adaptation in Business-to-Business Markets - CiteSeerX

“Dyadic Adaptation in Business-to-Business Markets” by D. Ross Brennan Middlesex University Peter W. Turnbull Birmingham Business School David T. Wilson The Pennsylvania State University

ISBM Report 9-2002

Institute for the Study of Business Markets The Pennsylvania State University 402 Business Administration Building University Park, PA 16802-3004 (814) 863-2782 or (814) 863-0413 Fax

Title: Dyadic Adaptation in Business-to-Business Markets

D. Ross Brennan Middlesex University The Burroughs Hendon NW4 4BT United Kingdom Telephone: 0044 20 8362 5861 Fax: 0044 20 8202 1539 Email: [email protected] Peter W. Turnbull Birmingham Business School The University of Birmingham Edgbaston Birmingham B15 2TT Telephone: 0044 121 414 7097 Fax: 0044 121 414 7791 Email: [email protected] David T. Wilson Smeal College of Business Administration Penn State University University Park PA 16802 Pennsylvania Telephone: 814-865-2219 Fax: 814-863-0413 Email: [email protected]

Word Count 8866 (excluding references)

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Information about the authors D. Ross Brennan is a principal lecturer in marketing and chairperson of the marketing group at Middlesex University Business School, London, UK. Prior to entering the academic profession, he obtained industrial marketing experience with British Telecommunications PLC. His research and teaching interests focus on business-to-business marketing, and on the application of academic research to marketing practice. Dr. Brennan's work has appeared in Industrial Marketing Management, the Journal of Marketing Management, and the Journal of Euromarketing. Peter W. Turnbull is a professor of marketing at, and head of, the Birmingham Business School, Birmingham University, UK. His areas of expertise include international marketing and purchasing, the management of customer relationships and portfolios and health care management and marketing. He is a member of a number of professional bodies, has had positions as the editor and associate editor of journals and is on a number of editorial boards. During his career he has acted as a consultant for a number of companies including HSBC Bank. His work has been published widely, including contributions to Industrial Marketing Management, the European Journal of Marketing, and the Journal of Business and Industrial Marketing. David T. Wilson is the Alvin H. Clemens Professor of Entrepreneurial Studies and Managing Director of the Institute for the Study of Business Markets at the Mary Jean and Frank P. Smeal College of Business Administration, Penn State University. Professor Wilson has published widely, in such journals as the Journal of Marketing Research, Journal of Consumer Research, Decisions Sciences, and the Journal of Purchasing, and was business marketing section editor for the Journal of Marketing. He was the founding editor of the Journal of Business-to-Business Marketing.

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Abstract Competitive success in business-to-business markets often depends upon the ability of the firm to adapt specifically to the needs of a single customer organization. Research into buyer-seller relationships in industrial markets has shown that both buying and selling firms implement specific adaptations for a single partner. Adaptation can take place at the level of the product, or more broadly in terms of management processes, information exchange, and even organizational restructuring. The paper develops an improved taxonomy for dyadic adaptation in business-to-business markets, and explores the driving forces behind relationship-specific adaptation. Adaptation by supplier firms is found to be more frequent than adaptation by buyers. Supplier adaptation is driven by relative power, buyer support, and by the managerial preferences of the two firms for a more or less relational form of exchange. Several managerial implications and avenues for further research are discussed. Keywords Business-to-business; interaction; adaptation; telecommunications; automotive

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Dyadic Adaptation in Business-to-Business Markets

INTRODUCTION

According to Sheth (1996), research into organizational buying behavior is shifting from a transaction centered to a relational-centered philosophy. Marketing scholars and practitioners need concepts, and models of behavior, which help them to understand and to manage in a relational world. Wilson (1996) reviewed theory transitions in the field of organizational buying behavior over the period 1972 to 1996. She concluded that the most dramatic shift in research focus had been the movement from studying buyers and sellers in isolation to studying the relationships between firms. Hallen, Johanson and Seyed-Mohamed (1991) investigated lasting exchange relationships in business markets, arguing that exchange could be conceptualized as both an interaction process, and as an adaptation process in which firms alter their normal business practices uniquely for individual partners. They contended that adaptation is a central feature of working business relationships. Adaptations may imply considerable investments by one or both parties to a relationship, often non-transferable investments that create durable economic bonds between companies. Such adaptations can be of critical importance in matching the supplier’s market offering to the customer’s needs. In seeking to explain inter-firm adaptations, Hallen, Johanson and Seyed-Mohamed(1991) examined reciprocal adaptations as a means of trust-building within the relationship, and unilateral adaptation as a response to asymmetric resource dependence. They hypothesized that interfirm adaptations were elements in a social exchange process, involving trustbuilding and power relations. Hallen, Johanson and Seyed-Mohamed (1991) found that buyer and supplier adaptations were correlated with each other, providing evidence that adaptations were elements in a social exchange process, and that adaptations were associated

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with the level of dependence on the other party, indicating that power plays a role in adaptation.

In this paper further evidence is presented to support the hypotheses of Hallen, Johanson and Seyed-Mohamed (1991) that interfirm adaptations are elements in a social exchange process. In addition, the influence of conscious management strategy – “relationship marketing” or “partnership sourcing” - upon adaptation behavior is explored, and the hypothesis that adaptations may vary with the age of the business relationship is tested.

This paper contributes to our understanding of inter-firm buyer-seller relationships by addressing two central questions:

1. How can adaptations in inter-firm, buyer-supplier relationships be defined, classified and measured?

2. What factors predispose partners in a buyer-supplier relationship towards adaptation behavior?

It builds upon previous work by providing further evidence to support propositions made by Hallen, Johanson and Seyed-Mohamed (1991, 1993), Håkansson (1982) and Turnbull and Valla (1986), while extending this work by re-examining and augmenting prior classification schemes and prior definitions of adaptations, and investigating the role of management strategy in influencing adaptation behavior.

We first discuss prior attempts to define, classify, measure and explain adaptations. Then we

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describe a mixed method (qualitative/quantitative) empirical study that was used to gather data to investigate the specified research questions. The results are used to develop a robust classification scheme for adaptations, to identify some important measurement issues in the study of inter-firm adaptations, and to evaluate the antecedents to adaptive behavior. We conclude with the implications of the work for management practice, and for future research.

DEFINITION AND CONCEPTUALIZATION

Defining dyadic adaptations

A European vehicle exhaust systems manufacturer builds a $5 million manufacturing plant next door to the car assembly plant of an American-owned global automobile manufacturer. A British telecommunications company provides office space and facilities on its own premises and at its own expense so that the engineers from a global systems supplier can join the in-house network design and new product development teams.

A small, British

manufacturer of automobile components adopts just-in-time delivery systems so that it can continue to do business with a global automobile manufacturer. These examples, from the field research conducted for this study, illustrate not only what dyadic adaptations are, but how they can represent substantial investments of resources.

In each case, the adaptation

was not a response to the demands of the market place as a whole, but was perceived to be an effective way of maintaining or developing a single, valued business relationship. Should that relationship fail, then much of the investment would be wasted – although the manufacturer of automobile components might be able to exploit its experience of just-intime to build new customer relationships.

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Adaptation is a concept of central concern in the analysis of buyer-seller relationships. If two "partners" were merely to transact business between each other under standard terms and conditions, at standard prices, buying and selling standard products using standard commercial procedures, then it would hardly be a "partnership". The defining characteristic of a "relationship" or a "partnership", arguably, is that at least one of the partners adapts to the specific needs of the other. This corresponds to the argument of Hallen, Johanson and Seyed-Mohamed (1991) that adaptations are important aspects of interfirm exchange relationships, because most business relationships are based on a process of matching between the operations of two companies.

The concept of inter-firm adaptations has been used extensively in research into inter-firm relationships (e.g. Håkansson 1982; Turnbull and Valla 1986; Hallen, Johanson and SeyedMohamed 1991 and 1993; Håkansson and Snehota 1995; Cannon, Achrol and Gundlach 2000). Nevertheless, there is still no single accepted definition of the concept. The earliest source (Håkansson 1982) provides no clear definition, but a series of examples to illustrate the concept. Hallen, Johanson and Seyed-Mohamed (1991, p29) draw a useful analogy with the natural sciences "Adaptation is a concept with a long history in biology.... Adaptation has also been used in human and cultural ecology" but again provide no succinct definition of inter-firm adaptations. Håkansson (1982) asserted the importance of adaptations:

Another important aspect of the relationship is the adaptations which one or other party may make in either the elements exchanged or the process of exchange. Examples of this are adaptations in product, in financial arrangements, in information routines or social relations. (Håkansson 1982, p18, emphasis in original)

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The unqualified use of the term adaptations in the marketing literature is problematic, since it would not be unreasonable to define marketing itself as the process of adapting an organization to meet the needs of the customer. Take Levitt's (1960, p10) classic statement of what has come to be known as the marketing concept:

Selling focuses on the needs of the seller; marketing on the needs of the buyer. Selling is preoccupied with the seller's need to convert his product into cash; marketing with the idea of satisfying the needs of the customer by means of the product and the whole cluster of things associated with creating, delivering and finally consuming it.

The illustrations in the opening paragraph of this section illustrated that adaptation covers a wide range of actions, which may be carried out both by supplier and customer organizations. We use the following definition in this study. It is wide enough to include changes by both parties, and to incorporate a broad range of managerial activities:

dyadic adaptations are defined as behavioral or organizational modifications at the individual, group or corporate level, carried out by one organization, which are designed to meet specific needs of one other organization.

The expression “dyadic adaptation” is used to focus attention at the level of the suppliercustomer relationship. In standard approaches to strategic marketing the emphases are on the macro-environment, and at the level of the market - what might be referred to as

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"environmental adaptation" and "market adaptation", in contrast to "dyadic adaptation". The strategic marketing management process is often conceptualized as a process of adaptation by the firm to changes in the broad marketing environment, the competitive environment, and consumer preferences (Aaker 1998, Jain 2000).

In business-to-business marketing,

adaptation at the level of the individual customer or supplier – dyadic adaptation – is often equally important. Dyadic adaptation can be either unilateral or mutual. In a unilateral dyadic adaptation the firm implements a specific modification for an exchange partner without any reciprocal modification by that partner. Mutual adaptation sees both parties adapting reciprocally for each other so as to facilitate the exchange process.

Classification and measurement of dyadic adaptations

A number of classification schemes for adaptations have been suggested (Håkansson 1982; Turnbull & Valla 1986; Hallen, Johanson and Seyed-Mohamed 1991; Holmlund and Kock 1995; Cannon, Achrol and Gundlach 2000).

In Håkansson (1982) there is extensive

reference to supplier-customer adaptations, but largely this is at the level of qualitative description, rather than quantification. However, quantitative data on adaptations from the same empirical database were analyzed in the later work by Turnbull and Valla (1986). Subsequently Hallen, Johanson and Seyed-Mohamed (1991, 1993) endeavored to quantify inter-firm adaptations and to establish the key factors influencing parties to a business relationship to adapt for each other. In a study of small Finnish manufacturing firms, to investigate perceptions of quality in business networks, Holmlund and Kock (1995) measured inter-firm adaptations as an element of relationship quality. Cannon, Achrol and Gundlach (2000) investigated the moderating influence of adaptations on relationship performance.

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The classification schemes used in these prior studies of interfirm adaptations are compared in table 1. Our examination of these studies led us to believe that no evidence has emerged from prior work to support the differentiation of customer adaptations from supplier adaptations. During the qualitative fieldwork for this study it emerged that a single classification system could be equally well applied to adaptations implemented by supplier and customer organizations. The most comprehensive of the prior classification schemes (Håkansson 1982) was selected as the basis for the classification used in the quantitative fieldwork. This classification was amended following a close inspection of the evidence presented by Håkansson (1982), which showed that the system employed was not exhaustive of the types of adaptation mentioned in the case study data. Notably, adaptation by provision of unusually detailed or sensitive information, and by changing the organization structure, were added. This amended classification scheme was explored further with interviewees during the qualitative fieldwork, and was subsequently tested in the quantitative study.

(insert table 1 here)

While the above studies focused explicitly on adaptations, a parallel stream of research has focused on the related concepts of transaction-specific assets and switching cost investments (e.g. Heide 1994; Heide and John 1988 & 1992; Nielson 1996; Artz 1999; Joshi and Stump 1999a; Joshi and Stump 1999b). Nielson (1996, p38) argued that: “in empirical studies of marketing interfirm relationships, the switching costs concept has typically been operationalized as a single-item construct”, and set out to explore the dimensionality of the switching cost concept. This objective can be compared to the efforts of other researchers, cited above, to develop good classification schemes for adaptations - the categories employed in a classification scheme for adaptations can be seen as the dimensions of a multi-

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dimensional theoretical construct.

The idea of transaction-specific investments originates from the study of transaction cost economics (Williamson 1975, 1985, 1991a, 1991b).

Williamson (1985, p30) discusses

specific investments in the following terms:

Transaction cost economics further maintains that the most critical dimension for describing transactions is the condition of asset specificity. Parties engaged in a trade that is supported by nontrivial investments in transaction-specific assets are effectively operating in a bilateral trading relation with each other.

Conventional neo-classical economics takes the existence of firms for granted. By contrast, one of the basic issues in transaction cost economics is why firms exist. A closely analogous question is what determines the limits of the firm and, in particular, what limits the extent of vertical integration of a firm. The answer, according to Williamson (1985), is that economic organization is determined by the minimization of the sum of production and transaction costs.

Transaction costs are “the economic equivalent of friction in physical systems”

(Williamson 1985, p19).

Williamson adopted the assumption of bounded rationality, and added to it the assumption that human beings are, at least sometimes, prone to opportunistic behavior. Opportunism is “in plain English … trying to exploit a situation to your own advantage” (Douma & Schreuder 1992, p 105). Were it not for bounded rationality, contracts could be specified completely so ruling out the risk of opportunism. If nobody ever behaved opportunistically, contractual arrangements could be specified in general terms, as neither party would attempt

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to exploit loopholes in the contract.

However, simultaneous conditions of bounded

rationality and opportunism, the norm according to Williamson, render complete contracts infeasible and make a trust-based solution risky.

Asset specificity is central to the concept of opportunism in business relationships. In many cases a firm could provide a better product or service to its customers by investing in special equipment, by relocating some of its production (for example, to support a customer’s JIT initiative), or by training some of its employees specifically to meet the needs of an individual customer. The costs incurred in such actions would be recouped over time from the customer concerned. However, if the assets created in this way have little alternative use, then the firm is placing itself at risk of opportunistic behavior. By threatening to remove its business elsewhere, the customer could force the supplier to reduce its price or be left with valueless assets. Williamson (1991a) has proposed that asset specificity can take a number of forms, namely site specificity, physical asset specificity, human asset specificity, brand name capital, dedicated assets, and temporal specificity. The suitable form of organization for economic transactions depends upon the level of asset specificity. Market governance (open market) is appropriate for conditions of low asset specificity, unified governance (vertical integration) is suitable for conditions of high asset specificity, and bilateral governance (buyer/seller partnering) is suitable for conditions of intermediate asset specificity.

Williamson’s approach has been criticized for over-emphasizing the role of opportunism, and correspondingly underestimating the role of trust in business relationships. According to Maitland, Bryson and Van de Ven (1985, p63):

One of Ouchi’s most valuable insights is that trust increases economic efficiency, that is the

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transaction costs associated with an exchange will be much less if the parties trust each other. Thus a high-trust culture may ceteris paribus be more efficient in economic terms.

They cite Ouchi (1980) as providing an alternative solution to the problem of bringing about mutually beneficial co-operation between people with incongruent goals, based on equitable allocation of rewards, rather than on hierarchical authority (unilateral governance) or the exchange of hostages (under bilateral governance).

A further criticism of Williamson's concept of transaction-specific investments is the focus on the transaction as the unit of analysis. Easton and Araujo (1994) proposed the concept of "relationship investments", for which they suggested a fourfold classification.

1. Minimal investment: the bare minimum required to do business at all. 2. Relationship specific investment: a broader category, which includes investments designed to foster trust within the relationship. 3. Relationship development investment: where both parties invest in the development of tangible and intangible relationship resources, so that the relationship itself is being used to create new resources. 4. Secondary investments: occur where the resources created within the relationship are used by one or both parties to develop new business opportunities, for example, where the skills learned within the relationship are deployed to win a third party contract.

Williamson's 'transaction-specific investments' would be allocated to the first of these four categories.

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How can the concept of dyadic adaptations be reconciled with that of transaction-specific investments, and with Easton and Araujo's extended concept of relationship investments? To some extent, this is a question of semantics, since the definitions of both adaptations and relationship investments are broad and fairly elastic. Nevertheless, it seems that 'minimal investment', 'relationship-specific investment' and 'relationship development investment' are wholly contained within the concept of adaptation. There is also degree of overlap with the idea of secondary investments.

For example, where two parties agree to combine the

expertise that they have developed within the dyad, to enter a new market in co-operation, this would appear to encompass both adaptation and secondary investment.

However,

secondary investment goes beyond the concept of adaptation, particularly where one party uses expertise or assets developed within the relationship (for example, quality management skills or a reputation for on-time delivery) to develop new and independent business. As defined here, adaptation is a dyadic phenomenon, whereas secondary investments may extend beyond the dyad.

METHOD

A mixed-method, qualitative and quantitative, approach was adopted. Table 2 shows the stages of the research. The data gathering can be divided into two phases, each of which was sub-divided into a number of stages. During the first phase, qualitative case studies were developed of 13 inter-firm buyer-supplier relationships in the automotive and telecommunications sectors.

In the second phase a mail survey was conducted among

automotive component supply firms. The purposes of the qualitative phase were to explore managerial understanding of dyadic adaptation in order to refine the definition and improve

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the categorization of the concept, to investigate inductively causal factors underlying dyadic adaptations, and to elicit rich descriptions of particular adaptation events in dyadic relationships. During the survey phase quantitative data were gathered on supplier and customer adaptations, and on the variables expected to be associated with adaptations, some of which were identified from the literature, and some of which emerged from the qualitative study. The quantitative data were used to test the robustness of the classification scheme for adaptations, and the hypotheses concerning the causes of dyadic adaptations.

(Insert table 2 here)

Qualitative Study

The case study phase investigated in depth managers’ understanding of the nature and causes of adaptations in buyer-supplier relationships. The results from this phase of the study were compared with prior academic findings.

The measurement items used and the formal

hypotheses tested during the survey phase were based upon the synthesis of ideas emerging from the case studies with prior published work.

Yin (1994, p13) defined a case study as:

an empirical enquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident.

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He advocated a case study strategy for research problems where the emphasis was on "how?" and "why?" questions. This strategy he contrasted with the survey approach, where the emphasis is more on questions of "who? what? where? how many? and how much?". Bonoma (1985) proposed inductive case research in marketing as a complement to the more conventional quantitative/deductive method. Eisenhardt’s “roadmap for building theories from case study research” (Eisenhardt 1989, p532) was used as a template for the case study process. In Yin’s terminology a multi-case embedded design was employed (Yin 1994), meaning that multiple case studies were developed, and that there were multiple units of analysis within each case. The principal unit of analysis was the inter-firm dyad, but analysis was also conducted at the level of the individual firm, and at the industry sector level.

Case studies were developed in the automotive and telecommunications sector. In each sector the process of case study development began with an investigation of the purchasing and supplier management strategies of three major purchasing organizations. Contacts within the purchasing organizations were asked to suggest two supply companies that could be used for the development of dyadic case studies. Respondents in the purchasing and the selling organizations were interviewed regarding the nature of the relationship.

In both the

purchasing and selling organizations respondents were identified who had direct involvement in the management of the focal relationship. Semi-structured interviews were used as the primary method of data collection, with a topic guide indicating the areas to be investigated. While it had been hope to tape-record and transcribe the interviews, it became clear at an early stage that respondents were not prepared to talk frankly about the details of key business partnerships on tape.

This necessitated reliance on field notes, which were

subsequently typed and checked for accuracy with the respondents. It was judged that the detail lost through this approach was compensated by the increased frankness of the

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interviewees.

In all, 36 qualitative interviews were conducted, in three phases, with a total of 37 different managers, representing 16 companies. Three managers were interviewed twice (once at the main stage and again at the follow-up stage), and on four occasions there were two managers present at one interview, where the interviewee invited an informed colleague to attend. A total of 13 dyadic relationships were investigated, between 6 purchasing organizations and 9 supply companies. Interview length varied from 1 hour to 4 hours, with a mean length of 2 hours. In addition to the face-to-face interviews, a variety of methods (fax, mail, phone, email) were used to clarify or expand upon the data gathered. A minimum of two depth interviews were conducted for each case study, with a minimum of one interview with a respondent from the supplier firm and one with a respondent from the customer firm. This corresponds to Wilson’s (1996) recommendation that empirical data should be collected from both sides of the dyad, and can be thought of as a form of ‘within-method triangulation’ (Jick 1979). Rather than simply relying upon the views of one party to the interfirm relationship, the researcher gathers data from key informants in both firms, and is in a position to compare and contrast the views of both parties. In addition, relevant documentary evidence was obtained from respondents – such as the customer firm’s procurement policy guidelines where these existed, and permission could be granted to release them.

With one or two people in the telecommunications sector, electronic mail provided a useful additional vehicle for communication. Electronic mail:

•

was very useful to break the real-time hiatus involved in connecting over the telephone;

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•

was used to arrange, and to confirm meeting dates and times;

•

appeared to avoid some of the "gatekeepers" who are encountered using conventional means of communication;

•

was also used, with one or two interviewees, as a means of establishing a dialogue subsequent to the meeting.

Miles and Huberman (1994a; 1994b) advocate both data triangulation and gaining feedback from respondents as means of enhancing reliability in qualitative studies. In addition to the informal feedback process with informants, conducted through electronic mail, all interviewees were sent a summary report based on the qualitative phase of the study with an invitation to comment. While only a few comments were received, these were constructive, and supportive of the initial conclusions from the qualitative study.

There were four stages in the process of qualitative data analysis. At the first stage narrative accounts of each business relationship were produced, focusing upon adaptations described by the respondents. At stage two these narrative accounts were used to compare adaptations in relationships between several supplier firms and a key purchasing organization – investigating how different suppliers adapt for a single customer, and how that customer adapts for its suppliers.

At stage three, comparisons were made between purchasing

organizations within an industry sector – exploring similarities and differences between the patterns of adaptations involving different major buyers in the automotive industry, and in the telecommunications industry.

While the first three stages of analysis were predominantly

inductive, the final stage of analysis involved comparing the findings from the first three stages of analysis with the results from prior empirical studies

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The qualitative data analysis software Q.S.R. NUD.IST was used to facilitate the qualitative data analysis process (Richards and Richards 1994, Weitzman and Miles 1995, Gahan and Hannibal 1998).

NUD.IST was the focal point for the development of the conceptual

framework encompassing inter-firm adaptations and related processes.

The protocols

advocated by Miles and Huberman (1994) for coding qualitative data were used, namely the creation of a start list of codes based on prior knowledge of the topic, and the amendment and augmentation of this list on the basis of inspection of the data.

The coding process within

NUD.IST comprises the tagging of components of the online documents (text documents imported into NUD.IST), so that these components can be logically allocated to one or more nodes within the NUD.IST indexing tree. Sample interview data were independently coded by a researcher from outside the authorial team, achieving acceptably high levels of coding consistency (83% inter-rater reliability).

The indexing tree is a graphical depiction of the logical inter-connections between concepts within the research project. It can be used to index straightforward factual information, or to index complex behavioral phenomena. The tree is a hierarchical system, with higher level concepts near the top, which are then disaggregated into lower level concepts lower down.

The higher level concepts in the NUD.IST indexing tree for this project are illustrated in table 3. Table 3 indicates that, in addition to the focal concept, adaptations, a number of other recurring themes emerged from the interviews. These included concerns about staff turnover within purchasing departments, the increasing prevalence of modular or systems buying, suppliers aiming to diversify a narrow customer base, and the professional status of marketing and purchasing managers.

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(Insert table 3 here)

Analysis of the qualitative data confirmed the findings of Hallen et al (1991) that power and reciprocity are important factors in inter-firm adaptation behavior. For example, mediumsized automobile components suppliers feel compelled to adapt their business to meet the requirements of automobile OEMs, owing to their dependency on these customers. Yet such suppliers admitted that they were considerably more likely freely to share confidential information with OEMs that offered them substantial support (i.e. reciprocity), for example by assisting them in setting up quality systems and in troubleshooting engineering problems. However, it became clear from the qualitative data that the managerial orientation of the parties to the business relationship could substantially affect the level of adaptation within it. For example, a telecommunications systems operator actively sought close supplier partnerships with two major supply firms. The first supplier adopted a relational approach to marketing, and a very close business relationship was quickly established. Major orders were placed and resources committed without formal paperwork, supplier personnel were located on customer premises and gained access to confidential data. The second supplier had a marked preference for maintaining arm’s length customer relationships, and the systems operator never succeeded in developing a close partnership. Adaptation by both parties was much less in this relationship. Such findings suggested that managerial orientation, that is, the preference within a firm for close partnerships or arm’s length business relationships, was a factor affecting adaptations. Consequently, managerial orientation was included in the quantitative study as two constructs, the preference of supply firms for relational marketing, and the preference of customer firms for partnership sourcing.

The classification scheme for adaptations described above was explored during the

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qualitative fieldwork. Instances where suppliers had altered their organization structure specifically to reinforce the relationship with a single customer were identified, and greater information exchange with selected partner firms (both customers and suppliers) was a recurring theme in the interviews. It was concluded, therefore, that the decision taken at the literature review stage, to augment the Hakansson (1982) classification scheme for adaptations with “organization structure” and “information exchange” was valid. These categories were retained for the quantitative study. In addition, throughout the qualitative fieldwork the use of a single classification scheme for both supplier and customer adaptations proved to be satisfactory.

Although different categories were mentioned more or less

frequently by supplier and customers, there was no persuasive evidence to use different classifications for suppliers and customers.

Quantitative Study

A mail survey was designed to investigate how, how much, and why firms adapt for each other within buyer-seller relationships. The hypotheses specified for the survey phase of the project were related to the original research questions and research hypotheses, but amended to take account of the findings from the interviews. In particular, new variables that emerged from the qualitative analysis seemed to be important in the adaptation process - these were the managerial orientations of the two firms towards buyer, or seller relationship management. The following hypotheses were specified for the survey stage.

Hypothesis 1: Adaptations are positively associated with the degree of dependence on the other party to the relationship

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Hypothesis 2: Adaptations are positively associated with the closeness of the relationship

Hypothesis 3: Supplier and customer adaptations are positively associated

Hypothesis 4: Adaptations are positively associated with management strategies designed to promote buyer-supplier partnerships

Hypothesis 5: Adaptations are positively associated with relationship age

Hypothesis 6: Adaptations by suppliers are greater than adaptations by customers.

The hypotheses emerged from the review of prior literature, augmented by the findings of the qualitative study. Hypotheses 1, 2 and 3 are derived from prior research into adaptations as elements of a social exchange process (Hallen, Johanson & Seyed-Mohamed 1991). The qualitative case studies provided further evidence to support this proposition, bringing to light instances of adaptation in response to power imbalance, and specific examples of reciprocal adaptation.

Hypothesis 4 emerged from the qualitative phase of research. Relationships were observed in which substantial mutual adaptation was achieved with surprising speed. Other relationships, comparable in other respects (notably power balance), were observed in which much more limited mutual adaptation took place. The explicit preference of the firms for a relational or transactional approach to business (relationship marketing or partnership sourcing) was consistent with these observations.

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Hypotheses 5 and 6 are designed to test propositions from prior studies of inter-firm adaptation. Hypothesis 5 is directed at the suggestion by Hallen et al (1991) that adaptations may vary with the life-cycle stage of a relationship. Relationship age, that is the length of time during which business has been transacted, is used as a proxy for life-cycle stage. Hypothesis 6 is complementary to hypothesis 3. While social exchange theory expects that supplier and customer adaptations will be positively associated, it is a fundamental principle of marketing (the ‘marketing concept’) that suppliers should be highly responsive to customers. It would be surprising if adaptation by customer firms was typically as great as adaptation by supplier firms, yet Turnbull and Valla (1986) presented limited evidence suggesting broad equivalence between supplier and customer adaptations. This is tested in hypothesis 6.

The survey was conducted in the UK automotive components industry, a sector that had already been investigated during the qualitative research. The automotive component sector contains a relatively large number of firms of a wide variety of sizes, which were known from the qualitative phase to vary greatly in their dependence on individual customers, and in their degree of adaptation to customers.

Respondents were asked to complete the

questionnaire with respect to their firm’s relationship with its most important customer. Further details of the questionnaire are included in the appendix.

The sample

A simple random sample of 500 firms from a selected range of standard industrial classification headings (see table 4) was taken from a sampling frame purchased on computer disk from a commercial list broker. It would have been quite straightforward to stratify the

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sample in a number of ways. However, since there was no convincing theoretical reason, nor any compelling reason arising from the qualitative stage to do this, a simple random sample was used.

(Insert table 4 here)

For the administration of the survey, many of the guidelines suggested by Diamantopoulos and Schlegelmilch (1996) and by Bourque and Fielder (1995) were implemented. The cover letter was personalized and signed; generally simple, short, pre-coded questions were used; assurances of confidentiality were provided; and, respondents were promised a summary of the study’s results. A follow-up request was sent to non-respondents four weeks after the first mailing. Of the 129 responses received overall, 79 (61.2%) were received in response to the first mailing, and 50 (38.8%) in response to the second mailing (overall response rate 25.8%). Non-response bias was assessed by comparing early to late respondents (Armstrong and Overton 1977). Univariate tests of significance were conducted, and no significant difference was found between the two waves of respondents on any variable. Therefore, nonresponse bias is considered not to be a serious limitation.

The first draft of the survey questionnaire was developed from the topic guides used during the qualitative interviews, with some further questions to measure additional variables (notably the managerial orientation of the parties towards relationship marketing and partnership sourcing). This draft was refined first by obtaining the expert opinions of four researchers (from outside the authorial team) skilled in questionnaire design, second, by discussing the draft face-to-face with two respondents from the qualitative stage, and, third, by sending an early version to 10 automotive components firms selected at random. Table 5

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shows the variables, and measurement items, that were included in the final questionnaire.

The dependent variables were measured using the seven categories of adaptation identified from the literature search and the qualitative phase, with each category measured dichotomously. Additionally, respondents answered a single question on a seven point scale regarding their perception of the overall extent of supplier adaptation in the relationship, and a further question regarding their overall perception of customer adaptation.

Relationship age was measured by the number of years that the supplier had done business with the customer. Closeness was a single item asking for the respondent’s perception of this variable. The managerial orientation variables, which had emerged from the qualitative research, were each measured using two items. Analysis of the case study data suggested that managerial orientation comprised an intentions dimension and an action dimension. The former is the stated policy of the firms (a preference for relational or transactional business), and the latter is the practical implementation of this policy through customer relationship building, or active supplier support. The variables measuring buyer and supplier power were based on the resource dependence model (Pfeffer and Salancik 1978), in which resource dependence refers to the availability of alternative sources for the resource and the possibilities of switching to other sources. This is the “comparison level for alternatives”, or CLalt (Anderson & Narus 1984 and 1990).

Logistic regression analysis

Logistic regression analysis was used to investigate the relationships between adaptation and the independent variables (Jobber 1994). The dependent variables are non-metric, so that

26

ordinary least squares methods are dubious (Hair et al 1995), although OLS models were also developed, yielding similar results to the logistic regression models reported here. Discriminant analysis was considered and rejected as an alternative technique, on the grounds that several of the independent variables are non-metric, and the assumption of multivariate normality necessary for discriminant analysis would not be met (Sharma 1996).

Respondents were grouped together into high and low adapter categories, for customer and supplier adaptation separately, and two bivariate logistic regression models were calculated using SPSS version 9.0 for Windows. In order to achieve a high degree of reliability in classifying cases into the high and low adapter categories the following procedure was followed:

•

the cases were divided into above and below the median groups for the sum of dichotomous adaptation types recorded (i.e. many types of adaptation recorded implies a "high adapter")

•

the cases were divided into above and below the median groups for the overall extent of adaptation recorded (i.e. high overall adaptation implies a "high adapter")

•

those cases that were above the median in each of these classification exercises were deemed to be "unambiguous high adapters", and those cases that were below the median in each classification exercise were deemed to be "unambiguous low adapters".

While this approach had the merit of reliably identifying high and low adapters, it meant that those cases that were ambiguously classified were not included further in the logistic regression analysis.

27

(Insert table 5 here)

FINDINGS and DISCUSSION

Defining, classifying and measuring adaptations

Of prior classification schemes used to categorize adaptations (Håkansson 1982; Turnbull & Valla 1986; Hallen, Johanson and Seyed-Mohamed 1991, Cannon, Achrol and Gundlach 2000), the most complete was that of Håkansson (1982), which contained the following categories:

•

product specification

•

product design

•

manufacturing processes

•

planning

•

delivery procedure

•

stockholding

•

administrative procedures

•

financial procedures.

Detailed analysis of the case studies reported by Håkansson (1982) suggested that two further categories should be added to this classification, namely information provision and organization structure. Table 6 shows the frequency with which different categories of

28

adaptation had been implemented by supply firms and their key customers.

(Insert table 6 here)

The very low number of respondents using the "other changes" category indicates that the classification of adaptations used in the questionnaire was, more or less, collectively exhaustive of adaptation types. It seems that the additional categories (information provision and organizational structure) that were added to the classification derived from Håkansson (1982) have improved the classification of adaptation outcomes. Information exchange ranks as the second most frequently cited category of customer adaptation, and supplier adaptation of organization structure was cited by 30% of respondents, indicating that these are meaningful additional categories.

Earlier studies of inter-firm adaptation behavior (Hakansson 1982; Turnbull and Valla 1986; Hallen, Johanson and Seyed-Mohamed 1991, 1993; Holmlund and Kock 1985; Cannon, Achrol & Gundlach 2000) have relied upon single-end research, thus ignoring differences of perception that might exist between the buying and selling organization. It is clear from the case studies conducted for this study that such differences do exist.

However, for the

quantitative phase of this study, as for prior empirical studies, it was necessary to rely on data from only one end of the relationship. The challenge of gathering quantitative data from both ends of a large sample of supplier-customer relationships remains to be solved, and is considered further below. The reliance on single-end data gathering is a limitation of this study, and of prior empirical studies of the same phenomenon.

In general, respondents tended to emphasize adaptations made by their organization, and

29

place less emphasis on adaptations made by the counterpart. Self-adaptation tends to be more visible than partner-adaptation. There is a tendency to classify what the other party does as "no more than should be expected" (not an adaptation), and what one's own company does as "over and above normal expectations" (an adaptation). Where a large customer interacts with a small supplier, the customer tends to under-estimate the effort required within the supplier organization to respond to "routine requests". For example, the large automobile OEMs expect their suppliers to adopt the current fashion in quality standards (e.g. BS5750, ISO9000, QS9000 and customer-specific systems), and appear not to realize the administrative burden that this places on a small firm. The scale of an adaptation is often judged against the resources available to your own organization.

It follows that the measurement of adaptation is affected by the perspective of the respondent. Therefore, straightforward measurement techniques based on the reporting of the frequency and magnitude of adaptations by a respondent from one or other party to a relationship are problematic. Ideally, data would be gathered from both ends of the relationship and from more than one respondent in each organization, so that the degree of inter-respondent consistency can be observed both within the partner firms, and between the partner firms. In the qualitative phase of this study, multiple respondents were interviewed from several, but the results cannot be investigated in the manner suggested here because the respondents were selected to represent different customer or supplier relationships.

On those fortuitous

occasions on which it was possible to interview two or more people within a single firm on adaptations within a given relationship, differences of perspective were noticed.

30

Antecedents of adaptation in buyer-seller relationships

Each of the response variables (supplier adaptation and customer adaptation) was regressed on the explanatory variables.

Additionally, customer adaptation was included as an

explanatory variable for supplier adaptation, and supplier adaptation as an explanatory variable for customer adaptation.

Hallen, Johanson and Seyed-Mohamed (1991)

demonstrated that there is a substantial degree of reciprocity in adaptation behavior. The results from the regression modeling are given in table 7.

(Insert table 7 here)

Table 7 shows the logistic regression coefficients for the supplier adaptation model and the customer adaptation model, with their associated significance levels. We subsequently calculated the proportion of cases that would have been correctly allocated to the 'low adapter' and 'high adapter' categories using the models shown in table 7. Overall 83.1% of cases are correctly classified by the supplier adaptation model, and 77.8% by the customer adaptation model (further details are provided in the appendix).

We now discuss the meaning of these results for the hypotheses stated earlier in the paper.

Hypothesis 1: Adaptations are positively associated with the degree of dependence on the other party to the relationship

The evidence suggests that supplier adaptations are influenced by buyer power, but that customer adaptations are not influenced by supplier power.

31

Hypothesis 2: Adaptations are positively associated with relationship closeness

This hypothesis is not supported by the data. However, the significance level of the closeness coefficient in the supplier adaptation model suggests that further research may be justified.

Hypothesis 3: Supplier adaptations and customer adaptations are positively associated

This hypothesis is supported by the data.

Hypothesis 4: Adaptations are positively associated with management strategies designed to promote buyer-supplier partnerships

This hypothesis is supported.

Both supplier and customer adaptation are positively

associated with a relational approach to marketing and purchasing.

Hypothesis 5: Adaptations are positively associated with relationship age

There is no evidence to support this hypothesis.

Hypothesis 6: Adaptations by suppliers are greater than adaptations by customers

The evidence presented in table 6 provides strong support for this hypothesis.

32

The evidence from this study is that specific dyadic adaptation by suppliers in industrial markets occurs frequently, and that specific adaptation by customer organizations, although less frequent, is not at all unusual. Supplier adaptation has been explained more satisfactorily than customer adaptation in the quantitative study. This may be for methodological reasons, since the questionnaire was administered to senior managers in supply firms, and it is their perceptions of business relationships that have been measured. Reservations about singleended research into essentially dyadic phenomena have been noted above. On the other hand, it may well be that the data are valid, that customers typically adapt less than suppliers, so that the effective explanation of customer adaptation would require a larger sample size than was achieved in this survey.

Supplier adaptation in dyadic relationships is strongly associated with buyer power, with customer adaptation, with supplier managerial orientation, and with customer managerial orientation. Supply firms adapt more for more powerful customers and for customers who offer reciprocal adaptation.

Those firms that have a preference for building customer

relationships adapt more than firms that prefer to sell on the open market. This provides evidence that a “relationship marketing” stance in industrial markets is more than rhetorical, and is associated with really doing more for the customer, i.e. adapting specifically to the customer’s needs. There is evidence that a partnership sourcing approach by the customer might lead to increased specific adaptation by the supplier.

Customer adaptations are rather less well explained by the data. It seems very likely that customer firms typically adapt less then their suppliers. However, they adapt more for suppliers that adapt for them, and they adapt more for suppliers that pursue a policy of active relationship development.

There is some evidence here that relationship marketing in

33

industrial markets can provide a pay-off in terms of encouraging reciprocal adaptation by the customer.

CONCLUSION

In this paper we set out to contribute to the understanding of adaptations in inter-firm, supplier-customer relationships. The study of organizational buying behavior is increasingly concerned with the development and conduct of long-term exchange relationships (Sheth 1996, Wilson 1996).

Adaptations, and the related concept of transaction-specific

investments, are an important element of long-term exchange relationships (Hallen, Johanson and Seyed-Mohamed 1991; Cannon, Achrol and Gundlach

2000). Hallen, Johanson and

Seyed-Mohamed (1991) explained adaptations in inter-firm relationships using a social exchange framework. Both the qualitative and quantitative phases of the present study have provided further evidence in support of the social exchange framework, emphasizing mutual adaptations as a component of the trust-building process, and unilateral adaptations as a response to power imbalances within the relationship. However, managerial orientation towards partnering, a factor previously neglected in adaptations research, emerged from the qualitative research as influencing adaptation in supplier-customer relationships.

The

evidence from the survey confirmed that the supplier’s managerial orientation – a preference for relational or transactional marketing – does influence adaptation behavior. Similarly, customer adaptations were influenced by the customer’s managerial orientation (whether transactional purchasing or partnership sourcing). A suggestion made by Hallen, Johanson and Seyed-Mohamed (1991) that adaptations might be related to the life-cycle stage of a relationship was not supported by the evidence of this study.

34

Regarding the statistical association between adaptations and managerial orientation, identified in the quantitative study, some further comment is necessary on the presumed direction of causality. We have implied in the preceding paragraph that causality runs from managerial orientation to adaptation. Clearly the mere existence of a statistical association proves no such thing. For example, it would be plausible to argue for reverse causality - that the process of adapting for a customer (or supplier) involves considerable interaction, which in turn induces a favorable managerial orientation towards that organization. We would not disagree with this proposition, indeed it seems likely that causality is to some extent bidirectional. However, during the qualitative phase of the study very clear evidence was gathered that indicated a causal link from managerial orientation to adaptation behaviour, leading us to postulate hypothesis 4. The quantitative data support this hypothesis.

A comprehensive classification scheme for adaptations has been proposed in the paper, based originally on a review of the prior literature (Håkansson 1982; Turnbull and Valla 1986; Hallen, Johanson and Seyed-Mohamed 1991,1993; Holmlund and Kock 1995, Cannon, Achrol and Gundlach 2000), and tested during the quantitative phase of the study. It is concluded that the addition of two new categories - adaptation through the provision of additional or sensitive information, and changes to organization structure - improves upon prior classifications of adaptations. The managerial and research implications of the study are now addressed.

Managerial implications

To a degree, managers understand implicitly the concept and the importance of adaptations in inter-firm relationships. Managers at one case study firm had already invested in a dedicated

35

manufacturing plant for an automobile OEM, and were considering doing so for another, without any contractual commitment from the customer. At another automotive supplier it was acknowledged that doing business with one (American) OEM was simply harder work than doing business with another (Japanese). The supplier often had to make connections between people within the American OEM, had experienced a steep learning curve trying to understand their way of doing business, and did not receive any real engineering support. Managers at one telecommunications operator had wanted to develop a genuine partnership with a key supplier but had failed to do so because it ran counter to the (transactional) marketing strategy of the supplier, and supplier personnel were unable to adapt to the customer’s preferences. This same operator had developed such a close working partnership with another systems supplier, which pursued a relationship marketing strategy, that both parties had agreed that they needed to bring about a managed reduction in business intimacy.

Adaptations, then, play an important role in interfirm relationship management. A key question is whether managers put sufficient explicit effort into understanding and managing inter-firm adaptations. The case studies provided evidence that the gradual accumulation of small adaptations can lead, unintentionally and unnoticed, to a position in which one firm is heavily dependent on another.

The findings of this study have practical implications in terms of identifying the factors which drive adaptations, differentiating between genuine partnering and "rhetorical partnering", and understanding the different perceptions of the parties concerning adaptations.

Perhaps the commonest managerial response to the concept of inter-firm adaptations is to suppose that it must all be a matter of relative power. Power is an important motivator of

36

adaptations. However, the case studies revealed that adaptations that are purely brought about by the exploitation of a power advantage are likely to be relatively superficial, grudgingly conceded, and cannot be taken to signal commitment or trust within the relationship. Furthermore, bringing about adaptations by exercising coercive power creates exactly the wrong conditions for subsequent adaptation.

In particular, the flow of

information between the parties is likely to be adversely affected by explicit "power plays" within the relationship.

There is evidence here that a professed orientation to a more relational approach to marketing, and purchasing, is genuinely associated with adaptive behavior towards the other party. While managers would be well-advised to remain cautious about the claims by other firms to adapt specifically for them, there is an association between management policy (the relationship “rhetoric”) and adaptive behavior (relationship “reality”).

To summarize, managers are advised not to rely extensively on power plays as a means of brining about desirable partner adaptations, because this will deter longer-term relationship investment. They are advised to look for clear-cut evidence of specific adaptation by the counterpart organization as evidence in support of any "partnering initiative", and to consider adaptations from the perspective of the other party as well as their own, in trying to understand the message conveyed by adaptation behavior. This latter point is arguably of particular importance in inter-firm relationships between businesses of markedly different size. For example, a small supplier may believe that offering to dedicate a man-year to a product enhancement specific to a single major customer is a potentially substantial adaptation which signals considerable commitment to the relationship. The customer, if a global corporation, may perceive this to be a relatively minor adaptation.

37

Implications for further research

There is a growing body of evidence concerning adaptations within dyads in the manufacturing sector. This study has contributed further to that body of evidence, while also undertaking qualitative research in the telecommunications sector, and Halinen (1994) has provided some evidence in professional services. If the concept of adaptation is to be generalized, then it will be necessary to investigate it in a range of industry contexts. In particular, there is a great deal still to be learned about adaptations in "pure" service industries. The classification scheme appropriate to a manufacturing industry is likely to need amendment for a service industry. Whether this will be relatively cosmetic ("service" and "service delivery process" for "product" and "production process"), or more substantial is a matter for future research.

Broadly, the likely research paths diverge from this study. On the one hand, it is desirable to focus intensively on adaptations within single dyads to explore adaptation processes in depth. On the other hand, clearly the opportunity is there to conduct additional quantitative research, by this means to extend the research into additional industry sectors, and to increase the sophistication of the survey methodology by devising a means of gathering data at both ends of the dyad.

The qualitative approach employed in this study could be extended in a number of ways. In order to investigate processes of adaptation in depth, at a minimum, multiple, depth interviews with responsible managers at both ends of the dyad would be necessary. This would enable a retrospective analysis of past adaptations to be constructed - using the same

38

processes employed in this study, but in greater depth, and demanding greater access and cooperation from a small number of buyer-seller dyads. One interesting augmentation to the interview strategy employed in this study would be to use the co-interview technique in which both parties are interviewed simultaneously. This approach would create the opportunity to address directly the divergent views that the exchange partners may hold about the nature and significance of adaptations within the business relationship. It is difficult to know whether it would be possible to persuade key informants to participate in such a study, but the potential insights would be considerable. If a longitudinal study were possible, then it would be possible simultaneously to investigate past adaptations, and to follow current adaptations as they emerged.

It is likely that the investigation of currently occurring

adaptations through a genuinely longitudinal method would result in more reliable data.

If a conventional survey approach is to be adopted, then the problem of single-ended data gathering on an intrinsically dyadic phenomenon arises (Wilson 1996). The question remains whether it is possible to generate useful quantitative data from both ends of the relationship. Three possibilities suggest themselves:

•

to conduct the study in collaboration with a major buying or selling organization, to use its customers or suppliers as a sampling frame, and to match questionnaire returns with questionnaires completed by members of the collaborating firm (sales executives, or buyers);

•

by some means (perhaps by collaborating with an industry association) to identify "matched pairs" of buyer and seller within an industry, and then to collect matched pairs of questionnaire returns;

•

simply to conduct two random and independent sample surveys among the

39

"buying" and the "selling" organizations, and to construct a "buying" and a "selling" data set.

Option 1 would yield matched questionnaire returns, but suffers from a strongly non-random sample and an excessive burden on a few people in the collaborating firm. Option 2 also yields matched returns. The problem is how to ensure a sample of sufficient size, given likely response rates at both ends of the dyad (a response rate of 30% from each end would generate, on the basis of probabilities, a "matched pair" response rate of 9%). Option 3 is the most pragmatic. The data would not be collected in matched pairs, so restricting the analysis. Nevertheless, this method would yield interesting observations on the differences in mean adaptation scores between buying and supplying firms, and in their perceptions of the factors underlying adaptation behavior.

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APPENDIX Independent variables: questions asked and mean responses On average, what percentage of your annual sales do you make to this customer? For approximately how long have you been doing business with this customer? How difficult would it be to find alternative business if this customer switched to another supplier? This is a very close relationship … this is an arm’s length relationship They offer a high degree of supplier support … they offer no supplier support Our products are important inputs to the customer … our products are not important inputs They would have difficulty finding another supplier … there are lots of good suppliers around They like to develop close partnerships with suppliers … they like to keep their distance from suppliers We actively work to maintain and develop the relationship … We treat this customer the same as any other Our priority is to develop and maintain close relationships with a few key customers … Our priority is to avoid being too reliant on a few customers and to win contracts from multiple sources

Scale Metric

Mean 27%

Metric

11.3 years

4 point 1 = very difficult 7 point 1 = very close 7 point 1 = high support 7 point 1 = important 7 point 1 = difficult 7 point 1 = close 7 point 1 = actively work 3 point 1 = relationships

2.0 2.7 3.5 2.5 3.6 3.0 2.3 2.0

Dependent variables: questions asked and distribution of responses The product itself has been specially tailored There have been adaptations to the production process There have been adaptations to the production planning and scheduling process Changes have been made to financial or contractual terms and conditions Changes have been made to stockholding and delivery procedures The organization structure has been altered There is greater exchange of information with this company than with others Other changes, please specify

By own company 52% 45% 58%

By customer 16% 10% 19%

44%

38%

52%

23%

30% 46%

9% 29%

5%

2%

Classification Table for Supplier Adaptation Predicted 0 23 4

% Correct

1 0 8 74.2 1 36 90.0 Overall % correctly classified 83.1 Table shows the number and percentage of suppliers that were correctly classified as high and low adapters using the logistic regression model in table 7. Observed

45

Classification Table for Customer Adaptation

Observed

0 1 Overall % correctly classified

Predicted 0 27 7

% Correct 1 9 29

75.0 80.6 77.8

Table shows the number and percentage of customers that were correctly classified as high and low adapters using the logistic regression model in table 7.

46

Table 1: Classifications of Adaptations Used in Prior Studies Study Håkansson 1982

Turnbull and Valla 1986

Hallen, Johanson and SeyedMohamed 1991 and 1993

Holmlund and Kock 1995

Cannon, Achrol and Gundlach 2000

Present study

Classification of adaptations Supplier & customer adaptation of Product specification Product design Manufacturing processes Planning Delivery procedures Stockholding Administrative procedures Financial procedures Customer adaptation of Product Manufacturing process Payment terms Production planning Delivery Stocks Supplier adaptation of Product Manufacturing process Payment system Stocks & deliveries Customer adaptation of Product Production process Production planning Supplier adaptation of Product Production process Stocks Supplier adaptation of End product Information routines Payment routines Inventory Production process Production planning Administrative routines Customer adaptation of Product features Personnel Inventory & distribution Marketing Capital equipment & tools Supplier & customer adaptation of Production planning & scheduling Stockholding & delivery Product Information exchange Production process Financial or contractual terms & conditions Organization structure Other

47

Table 2: Outline of Study Methodology Research Stage Case Study Phase Pilot Stage Case Study Phase Main Fieldwork

Data Gathered 4 depth interviews conducted with 4 managers in 2 organizations, 1 in the automotive sector, 1 in the telecommunications sector

Research Purposes • To refine qualitative instruments

27 depth interviews conducted with 31 managers in 16 organizations, 9 in the automotive sector, 6 in the telecommunications sector, 1 in the aggregates sector

•

• •

Case Study Phase Follow-up Stage

7 case studies of inter-firm relationships in the automotive sector developed 6 case studies of inter-firm relationships in the telecommunications sector developed

5 depth interviews conducted with 5 managers in 4 organizations, 2 in the automotive sector, 2 in the telecommunications sector •

Survey Phase

•

Pilot Stage

•

Survey Phase

•

Main Fieldwork

• • •

further development of 2 automotive case studies and 2 telecommunications case studies face-to-face testing of the questionnaire with 2 managers in case study firms mail pilot to 10 firms randomly selected from the automotive components sector mail questionnaire to 500 randomly selected firms in the UK automotive component sector 129 completed and usable responses received 79 from the first mailing 50 from the follow-up mailing

• • • •

To investigate managerial perceptions of interfirm adaptations To explore classification scheme for adaptations To facilitate development of survey instrument To investigate inductively causes of interfirm adaptation To explore further specific instances of adaptation in selected cases

•

To pre-test the survey instrument

• •

To quantify adaptations To test the classification scheme for adaptations To test deductively for causes of interfirm adaptations

•

48

Table 3: Higher levels of the NUD.IST indexing tree Telecommunications industry ADAPTATIONS PURCHASING MANAGEMENT By customers Staff turnover By suppliers

Modular/systems buying

MARKETING MANAGEMENT Relational marketing Transactional marketing

Influence of power on adaptations

Status within the organisation

Status within the organisation

INTER-FIRM RELATIONSHIPS Influence of power on relationships Influence of the business environment Relationship characteristics e.g. age, trust

Automotive industry ADAPTATIONS PURCHASING MARKETING MANAGEMENT MANAGEMENT By customers Staff turnover Relational marketing By suppliers Modular/system Transactional s buying marketing Influence of power on adaptations

Status within the organisation

Status within the organisation

49

INTER-FIRM RELATIONSHIPS Influence of power on relationships Influence of the business environment Relationship characteristics e.g. age, trust

Table 4: Sampling frame US 4-digit SIC category Description 3011 Tire & inner tube manufacturers 3465 Automotive stampings 3519 Miscellaneous internal combustion engine manufacturers 3566 Speed changer and gear manufacturers 3592 Piston, carburetor & valve manufacturers 3647 Vehicular lighting equipment manufacturers 3694 Combustion engine electrical equipment manufacturers 3713 Truck and bus body manufacturers 3714 Vehicle parts and accessory manufacturers

50

Table 5: Variables Measured in the Survey Variable Measurement items Dependent Variables

Scale

Supplier adaptation of product Supplier adaptation of production process Supplier adaptation of production planning or scheduling Supplier adaptation of financial or contractual terms and conditions Supplier adaptation of stockholding and delivery procedures Supplier adaptation of organization structure Supplier adaptation of information exchange Overall supplier adaptation

Dichotomous Dichotomous Dichotomous

Customer adaptation of product Customer adaptation of production process Customer adaptation of production planning or scheduling Customer adaptation of financial or contractual terms and conditions Customer adaptation of stockholding and delivery Customer adaptation of organization structure Customer adaptation of information exchange Overall customer adaptation

Dichotomous Dichotomous Dichotomous

Percentage of annual sales made to most important customer Difficulty of replacing this customer’s business

Percentage

Supplier power

Importance of this input to the customer Availability of alternative suppliers

7 point scale 7 point scale

Buyer’s managerial orientation

Degree of supplier support offered Preference for close supplier partnerships

7 point scale 7 point scale

Supplier’s managerial orientation

Degree of customer business development effort Supplier preference for relational marketing

7 point scale 4 point scale

Relationship age

Number of years business has been transacted

Years

Relationship closeness

Supplier’s perception of closeness

7 point scale

Supplier adaptations

Customer adaptations

Dichotomous Dichotomous Dichotomous Dichotomous 7 point scale

Dichotomous Dichotomous Dichotomous Dichotomous 7 point scale

Independent Variables Buyer power

4 point scale

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Table 6: Respondents reporting different categories of adaptation Nature of the supplier/customer adaptation Changes have been made in the production planning and scheduling process

% by Suppliers 58

% by Customers 19

Chi-squared 8.74 (0.003)

Changes have been made to stockholding and delivery procedures

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23

7.17 (0.007)

The product itself has been specially tailored

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16

3.82 (0.051)

There is greater exchange of information with this company than with others

46

29

30.26 (0.000)

There have been adaptations to the production process

45

10

3.44 (0.064)

Changes have been made to financial or contractual terms and conditions

44

38

5.38 (0.020)

The organization structure has been altered

30

9

4.95 (0.026)

Other changes

5

2

22.45 (0.000)

Column 1 identifies the nature of the adaptation. Column 2 shows the percentage of suppliers implementing that category of adaptation. Column 3 shows the percentage of customers implementing that category of adaptation. Column 4 shows the chi-squared value (significance level in brackets) for a test of the null hypothesis that there is no difference between the number of suppliers and the number of customers in each adaptation category.

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Table 7: Logistic Regression of Adaptation Variables on Independent Variables Dependent Variables Supplier adaptation Customer adaptation Independent Variables Constant

5.33 (10.32) 0.001

5.28 (5.96) 0.015

Buyer power

1.96 (9.47) 0.002

0.21 (0.21) 0.649

Supplier power

0.24 (0.80) 0.371

0.08 (0.15) 0.699

Buyer’s managerial orientation

0.74 (5.35) 0.021

0.61 (5.16) 0.023

Supplier’s managerial orientation

0.75 (4.17) 0.041

1.93 (7.35) 0.007

Supplier adaptation

not applicable

1.28 (3.37) 0.066

Customer adaptation

1.51 (4.03) 0.045

not applicable

Duration

0.01 (0.02) 0.898

0.061 (2.47) 0.116

Closeness

0.49 (2.92) 0.088

0.34 (1.84) 0.175

Cox & Snell R-squared Nagelkerke R-squared

0.406 0.544

0.307 0.410

Data shown in table are B coefficients, with Wald values in brackets, and exact significance levels of the coefficients in italics

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