The determinants of relational governance and performance: How to manage business relationships?

Industrial Marketing Management 32 (2003) 703 – 716

The determinants of relational governance and performance: How to manage business relationships? Danny Pimentel Claro*, Geoffrey Hagelaar1, Onno Omta2 Department of Business Administration (Bode 77), School of Social Sciences, Wageningen University, Hollandseweg, 1, 6706 KN, Wageningen, The Netherlands Received 1 January 2003; received in revised form 1 May 2003; accepted 1 June 2003

Abstract It is the aim of this study to assess the influence of the determinants of the transaction, dyadic, and business environment level on relational governance and ultimately performance. We build an integrated framework for relationship management drawing from literature of transaction cost economics, marketing channels, and business networks. Dutch suppliers of potted plant and flower products (N = 174) provided data for the empirical analysis. Our results show that joint planning, one of the constructs of relational governance, is positively influenced by interorganizational trust, information obtained from the network, physical transaction-specific investments (TSIs), and by fixed lines as the exchange mode. Joint problem solving, the other construct of the governance, is solely influenced by the two dimensions of trust. These two constructs of relational governance effect positively our performance measures. Managers should consider carefully each of the determinants of relational governance for the management of a relationship. As shown in our study, the success is dependent on some of the determinants of the three analytical levels of our integrated framework. D 2003 Elsevier Inc. All rights reserved. Keywords: Business relationships; Relational governance; Relationship management

Up to now, the field of business relationship management is rather fragmented. Empirical studies draw from a wide range of perspectives, such as transactions cost economics (e.g., Klein, Frazier, & Roth, 1990), marketing channels (e.g., Stern & El-Ansary, 1996), and business networks (e.g., Anderson, Hakansson, & Johanson, 1994; Powell, 1990). Although there is a wide range of perspectives to relationship management, it is surprising to find few large-scale surveys that test the widely espoused assumptions regarding the influence of determinants of a business relationship on relational governance (Dyer & Singh, 1998). A business relationship can be defined as the exchange of property rights between two firms, which contains elements of the transaction, dyadic, and the business environment. Previous research on business relationship has addressed several determinants of relational governance. Examples are trust (Anderson & Narus, 1990, Zaheer & Venkatraman,

1995), transaction-specific investments (TSIs) (Klein et al., 1990), and networks (Dyer, 1996). The objective of this paper is to propose an integrated framework for relationship management that attempts to elucidate the relation between the determinants at the transaction level, the dyadic level, and the business environment level and relational governance. This integrated framework also attempts to elucidate the choice of relational governance opposed to a transactional orientation and its influence on performance. The empirical setting for the present study is the business relationships between suppliers and merchant/distributors in the Dutch potted plant and flower industry. This is an interesting empirical setting because it provides insight in how firms manage focal business relationships in an industry where an increasing number of firms are replacing market governance (e.g., auction clock 3 transactions) by relational governance (Kalenzi, 2000, Deneux & Luten, 2001). In this article, we will first discuss the relational governance as a mode to coordinate business relationships. The

* Corresponding author. Tel.: +31-317-482410; fax: +31-317-485454. E-mail addresses: [email protected] (D.P. Claro), [email protected] (G. Hagelaar), [email protected] (O. Omta). 1 Tel.: +31-317-482410; fax: +31-317-484846. 2 Tel.: +31-317-482410; fax: +31-317-484035.

3 Flower auctions use the Dutch auction method for price determination. This method uses a clock, with the clock hand starting at a high price determined by the auctioneer and dropping until a buyer stops the clock by pushing a button to bid for a lot at the price determined by the clock hand.

1. Introduction

0019-8501/$ – see front matter D 2003 Elsevier Inc. All rights reserved. doi:10.1016/j.indmarman.2003.06.010

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determinants of relational governance and performance are then discussed on the basis of the three analytical levels and the hypotheses are elaborated. The integrated framework for relationship management is tested in a sample of 174 suppliers. The results are discussed and the conclusions, limitations, and suggestions for further research are drawn. The article ends with the managerial implications of the study.

2. Relational governance While theoretically the choice of governance has been cast in terms of the two polar extremes, market and hierarchy (Williamson, 1991), the intermediary mode—namely relational governance—has increasingly drawn attention from scholars and managers (Rindfleish & Heide, 1997). The relational governance does not solely rely on the market forces or the power of fiat to coordinate the relationship, but rather the governance relies on cooperation. This implies that independent but closely related firms can reduce their range of activities and concentrate on a few core competences (Prahalad & Hamel, 1990). In the decision to cooperate with others, relational governance reflects the degree to which joint actions are established in a business relationship (Bensaou & Venkatraman, 1995; Heide & Miner, 1992). Two joint actions appear to be central to relational governance, joint planning and joint problem solving. While joint planning refers to the extent to which future contingencies and consequential duties and responsibilities in a relationship have been made explicitly ex ante (Heide & John, 1990; Heide & Miner, 1992), joint problem solving refers to the extent to which recent disagreements with a partner have been productively resolved (Heide & Miner, 1992, Lusch & Brown, 1996). There are benefits of joint planning and joint problem solving that make relational governance more efficient than market governance (Dyer & Singh, 1998). Joint planning allows mutual expectations to be previously established and cooperative efforts to be specified at the outset. Moreover, when a party’s actions influence the ability of the other to effectively compete, there is an increasing need for jointly setting goals, long-term plans, responsibilities, and expectations. Through joint problem solving, a mutually satisfactory solution may be reached for every contingency and consequently add to relationship success. There can be differences in the nature of the two joint actions. While joint planning can be mostly proactive, joint problem solving can be also reactive. For instance, a supplier engaged in joint planning is more likely to take action at the outset rather than wait for a problem to occur and then (jointly) act as a result of the problem.

3. Determinants of the relational governance The integrated framework is built on determinants that fall into three analytical levels, which are useful in

managing the complexity of a business relationship. First of all, any firm is involved in a business relationship with the purpose of exploiting the economic gains of the transaction, defined as an exchange of property rights (Williamson, 1996). The transaction composes of an analytical level that focuses on the economical exchange, which includes the exchange mode and the TSIs. Secondly, a transaction does not develop in a vacuum but rather it accounts for the social bonds of trust (Anderson & Narus, 1990) and the ongoing business interaction, which is part of the analytical level called dyadic. Thirdly, apart from the transaction and dyadic level, the business relationship is determined by the environment in which firms are embedded (Granovetter, 1985). This third set of determinants refers to the business environment level, which is composed of the information support obtained from the business network and the environment instability. These three distinct levels form the integrated framework for relationship management of our research. Based on the integrated framework, a business relationship can be defined as an economical exchange of property rights (i.e., transaction) that contains elements of the dyadic and the business environment. Drawing determinants from the three analytical levels, in Table 1, we show the implications for the conceptualization of a business relationship as well as the constructs and their dimensions.

4. Hypotheses regarding the determinants of relational governance 4.1. Transaction level 4.1.1. Exchange mode In general, two distinct operational sales modes can be identified in manufacturer sectors, namely daily trade and fixed lines (Stern & El-Ansary, 1996). Daily trades are daily orders, which resemble market governance, while fixed lines are transactions with close and direct interaction between the parties. The fixed lines rely on self-enforcing mechanism, whereas the daily trade relies on the influence of a third party (Williamson, 1985), such as a mediator or a broker. In the fixed line mode of exchange, the transactional parties make every decision in order to increase the gains. This fixed line then allows for joint planning and joint problem solving as forms of collaboration. We expect that the more a supplier does business with a specific buyer via fixed line, the more the supplier will plan and solve problems together with the buyer. Thus, we formulate the following hypothesis: H1: The higher the level of fixed line exchange mode, the higher the levels of the two dimensions of relational governance; (a) joint planning and (b) joint problem solving.

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Table 1 Determinants of relational governance Determinants

Business relationship

Construct

Dimensions

Operations of economical exchange

Exchange mode

Exchange mode to a specific buyer

Investments increasing coordination

Transaction specific investment (TSI)

Human and physical TSI

Ongoing business relationship: reputation and future expectation

Long-term business interaction

Length of the business interaction with a specific buyer

Confidence and belief in the counterpart

Trust

Inter-personal trust and interorganizational trust

Business environment level Business networks

Informational support

Network intensity

Market volatility and diversity

Concerns with opportunism and information asymmetry

Environmental uncertainty

Information obtained from the business network Environmental instability

Transaction level Execution

Assets

Dyadic level The time orientation of the dyadic Social bond

TSI is an important and distinctive construct in transaction cost economics (Williamson, 1996). TSI refers to the degree to which an asset cannot be redeployed to alternative uses and by alternative users without sacrifice of productive value (Williamson, 1991). Williamson (1991) distinguishes two types of TSIs. First, physical TSI refers to transaction-specific capital investments (e.g., customized machinery, tools, and dies) that tailor processes to particular exchange partners. Physical investments can stimulate relational governance. Consider a supplier that has invested in a machine to pack products specifically for a buyer; joint problem solving and joint planning are likely to be stimulated because of the counterpart’s familiarity with the machine and the packing operation. The other kind of TSI is the human TSI that refers to transaction-specific know-how gained to deal with a specific partner (e.g., dedicated supplier salesperson who learns the systems, procedures, and the idiosyncrasies of a buyer). Over time, human specialization increases as transactional partners develop experience in joint problem solving and joint planning. Considering variations in degrees of TSI, suppliers select a governance mode that minimizes transaction costs. If assets are not specific, then there is no need for a complex mode of governance so market governance may suffice to minimize the transaction costs. If the assets are to a certain extent specific, relational forms of governance are appropriate. We then expect that a higher degree of TSI, either physical or human specificity, may affect relational governance positively. Thus, we formulate the following hypotheses: H2: The higher the level of human TSIs, the higher the level of the two dimensions of relational governance; (a) joint planning and (b) joint problem solving.

H3: The higher the level of physical TSIs, the higher the level of the two dimensions of relational governance; (a) joint planning and (b) joint problem solving. 4.2. Dyadic level Long-term business interaction captures the long-term orientation of the partners in a business relationship, through the integration of activities and the outcomes that are expected to benefit both parties over a series of transactions. Suppliers with a short-term orientation are concerned solely with the options and outcomes of the current period and merely rely on the market forces to generate gains. Furthermore, past interaction enables a supplier to monitor the reputation of a buyer and vice versa. The reputation provides information about the firm and shapes the responses of the counterpart (Weigelt & Camerer, 1988). The effect of a long-term business interaction includes not only the benefits of reputation and long-term orientation, but also the desire of firms towards future interaction (Ganesan, 1994). A supplier that interacts with the same buyer for a long period of time is likely to be oriented towards gains and benefits of the continuity and create expectation for future interaction. This length of business interaction captures the longevity of the joint actions in the business relationship (Noodewier, John, & Nevin, 1990). We then expect that the longer the length of the business interaction with a specific buyer is, the more relational governance will be found. Thus, we formulate the following hypothesis: H4: The longer the length of business interaction with a specific buyer, the higher the levels of the two dimensions of relational governance; (a) joint planning and (b) joint problem solving.

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4.2.1. Trust The presence of trust in relational governance is a basic concept (Zaheer & Venkatraman, 1995). Defining in a broad sense, trust reflects the extent to which negotiations are (expected to be) fair and commitments are sustained (Anderson & Narus, 1990) and a party’s belief that its requirements will be fulfilled through future actions undertaken by the other party (Anderson & Weitz, 1989; Barney & Hansen, 1994). Trust counterbalances the need for a costly safeguard mechanism against opportunism because of the expectancy held by a supplier that the buyer’s word or written statement can be relied on (Rotter, 1980). Since trust is an important determinant of the dyadic level of analysis, two dimensions of trust are examined, interpersonal and interorganizational trust. While interorganizational trust reflects the extent to which a member of an organization has a collectively held trust orientation toward the partner firm, interpersonal trust reflects the extent to which a boundary-spanning agent trusts his specific counterpart of the partner organization (Zaheer, McEvily, & Perrone, 1998). In considering the role of trust in relational governance, we highlight the personal structure, processes, and routines that create a context within which interpersonal trust can develop and persist (Rotter, 1980). Under high level of interorganizational trust conditions, firms are less inclined to rely on elaborated safeguards for specifying, monitoring, and enforcing agreements (Ganesan, 1994). Using this foundation, we expect that the existence of both interpersonal and interorganizational trust motivates joint planning and joint problem solving. Thus, we formulate the following hypotheses: H5: The higher the level of interpersonal trust, the higher the level of the two dimensions of relational governance; (a) joint planning and (b) joint problem solving. H6: The higher the level of interorganizational trust, the higher the level of the two dimensions of relational governance; (a) joint planning and (b) joint problem solving. 4.3. Business environment 4.3.1. Network intensity In the business environment, the business network is an important source of information for firms. The network intensity can be defined as the amount of valuable information obtained from the network of connected relationships that supports a focal business relationship. The focal business relationship can be seen as part of this network of connected relationships, but our intention is to evaluate the impact of the network on the relational governance of this focal relationship. For instance, suppliers may obtain from the network valuable information about the buyer’s resources and capabilities and the confidence in the buyer’s

mutual assessments. Therefore, business networks reduce information asymmetries by increasing the privileged information that is available to a selected number of firms that form the network (Thorelli, 1986). Moreover, given the ambiguities and uncertainties of the business environment, access to valuable information can alleviate some of the risks of opportunism, making firms more likely to be engaged in an ongoing business relationship (Gulati, 1998). The information provided by the members of a business network may facilitate a wide range of activities such as monitoring and control (Burt, 1997; Williamson, 1996), coordination of the production processes (Hakanson & Snehota, 1995), coordination of logistic operations (Gadde & Snehota, 2000), product development (Hakansson, Havila, & Pedersen, 1999), and setting sales strategy (Wathne, Biong, & Heide, 2001). A supplier that intensively accesses its business network is likely to possess valuable information about its buyers. Thus, we expect that the information obtained from the business network positively affects relational governance with a specific buyer of a business relationship on which we base our following hypothesis: H7: The higher the intensity of information obtained from the business network, the higher the level of the two dimensions of relational governance; (a) joint planning and (b) joint problem solving. 4.3.2. Environmental uncertainty High environmental instability may preclude the effective use of mechanisms to safeguard and enforce a business relationship (Anderson & Weitz, 1989). This environmental instability increases information asymmetry and encourages buyers to behave opportunistically. Relational governance may absorb the environmental instability through joint planning and problem solving. Supplier and buyer may employ relational governance in order to manage an environment that is more turbulent than each can cope with alone and additionally because integrative outcomes satisfy the needs and concerns of both firms (Mohr & Speckman, 1994). The environmental instability is derived from the construct of environmental uncertainty that refers to the volatility and diversity of the market (Ganesan, 1994; Klein et al., 1990). While market volatility represents the rapid changes in the environment that can catch firms by surprise, the market diversity represents the multiple sources of uncertainty in the environment. Consider, for example, a market where there are rapid changes in product and delivery characteristics demanded by consumers, it is expected that a supplier will contact the buyer and jointly plan future demands in order to cope with the volatile market. Furthermore, the market diversity would be associated with joint activities between suppliers and buyers. For example, a supplier facing a variety of market segments would have difficulty to obtain information and formulate an effective strategic program for each

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segment of the market. Thus, we expect that high environmental instability is positively associated with relational governance. The following hypothesis is formulated: H8: The higher the level of environmental instability, the higher the level of the following dimensions of relational governance; (a) joint planning and (b) joint problem solving.

5. Hypotheses regarding relational governance and performance Research on performance of business relationships has generally focused on two kinds of indicators, objective and affective ones (Bensaou & Venkatraman, 1995; Mohr & Speckman, 1994; Zaheer et al., 1998). In our integrated framework for relationship management, we use both kinds of indicators. As the objective indicator, we use sales growth; while as the affective indicator, we use the satisfaction of one party with the other, which is based on the notion that performance is determined in part by how well the business relationship achieves the performance expectations. The reasoning underlying the expected positive influence of relational governance on performance is based on the reduction of transaction costs (i.e., sales growth rate) and achievement of mutual expectations (i.e., perceived satisfaction). Joint planning reduces the risk of unexpected problems, which in turn reduce the need for a sophisticated monitoring apparatus. Joint problem solving allows for creative forms of dealing with disagreements and other contingencies of the business relationships, which reduce transaction costs and consequently improves performance. In this regard, the joint actions allow a supplier to draw attention to their core business because there is little

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distraction to individually solve problems or revise a strategic plan that did not consider the contingencies of the buyer. Therefore, the time and energy so often spent on trying to plan and work out problems without consulting the buyer is gained. We expect that a high degree of joint planning and joint problem solving lead to a high level of perceived satisfaction and sales growth. Thus, we formulate the following hypotheses: H9: The higher the level of joint planning, the higher the levels of the two performance measures; (a) sales growth and (b) perceived satisfaction. H10: The higher the level of joint problem solving, the higher the levels of the following performance measures; (a) sales growth and (b) perceived satisfaction.

6. Control variables Previous research suggested that relational governance and performance might vary by the supplier size, the buyer size, the type of buyer’s client (Stern & El-Ansary, 1996), and the number of auction clock transactions (Deneux & Luten, 2001). No hypotheses are developed for the control variables, but the variables were added to the framework. The integrated framework for relationship management is shown in Fig. 1.

7. Research design Data on the business relationship of supplier (i.e., potted plant and potted flower production units) and

Fig. 1. The integrated framework for relationship management.

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merchant distributor in the Netherlands were gathered in order to test the hypotheses developed above. We selected this industry because of the significant number of suppliers and buyers that are replacing market governance by relational governance and because it provides a sampling frame of adequate size. 7.1. Data collection We developed a questionnaire on the basis of literature search and previous case studies (Claro, Hagelaar, & Omta, 2002; Claro, Hagelaar, & Zylbersztajn, 2002). In order to test for content validity of the scales in the questionnaire, a panel with four experts was conducted. We then carried out a pretest at five suppliers in which managers and/or owners were asked to fill out the questionnaire and raise questions as problems and ambiguities arose. This information was used to further improve the questions and scales. Attempting to minimize response bias, we sought to identify the knowledgeable informant in the supplier company. As a great number of suppliers are owner managed, we chose the owner as our informant (Zaheer & Venkatraman, 1995). When responding all questions about the business relationship, informants were asked to consider their relationship with a specific partner with whom the informant has done business regularly over the previous year. The sample of 598 companies was based on a list of potted plant and potted flower growers, which are active on the mediation department of the Dutch flower auction cooperatives. In the beginning of 2002, each company received by mail a package containing an introduction letter, a questionnaire, and a return paid envelope. After one month a follow-up package was mailed to those companies that had not yet responded. The package contained a questionnaire and a new introduction letter to remind the relevance of the study. Of the 174 usable responses, 124 were received in the first wave. An effective response rate of 31% compares favorably with those obtained in prior research in this field. Nonresponse bias was tested according to the extrapolation method, which is based on the assumption that companies who respond late are comparable to the nonrespondents (Armstrong & Overton, 1977). A comparison of early respondents versus late respondents yielded no significant differences. 7.2. Measures The scales and the Cronbach alpha of the different constructs are reported in Table 2. We tested the unidimensionality of each construct by conducting an exploratory factor analysis (EFA). The result of the factor analysis indicated that the items underlying a single construct loaded at the same factor and no significant correlation was found between items measuring different constructs. Performance was assessed through two measures. First, sales growth rate consists of an objective measurement of

performance, which refers to the development of sales volume in the last three years (Mohr & Speckman, 1994). Second, the perceived satisfaction measurement refers to the rating of the respondent’s perceived satisfaction of the selected buyer. This six-item measurement instrument was adapted from previous studies (Bensaou & Venkatraman, 1995; Zaheer et al., 1998). Two dimensions construct relational governance: joint planning and joint problem solving. Joint planning is meant to measure the extent to which future contingencies and consequential duties and responsibilities in a relationship have been made explicitly ex ante (Heide & John, 1988, 1990); four items measured this construct. Joint problem solving refers to the behavior to the relationships that captures the degree of joint solutions to problems a supplier demonstrates toward the selected buyer (Heide & Miner, 1992; Lusch & Brown, 1996); four items measured this construct. Exchange mode was measured based on an open-ended question, which asks the percentage of sales via daily trade and fixed lines. On one hand, daily trades are daily orders or offers handled by the mediation department, which resembles market governance. On the other hand, fixed lines are transactions with close interaction between the parties that last long. Respondents who are members of the Dutch auction cooperatives easily recognize the sales modes. According to a membership contract with the cooperative, respondents must report every sale to the responsible department of the cooperative. The length of the business interaction was measured through an open-ended question about the time that the respondent is doing business with the selected buyer. TSIs refer to the supplier’s perception of the extent to which an investment was made specifically for the transaction with the selected buyer. First, the measurement of physical TSIs refers to investments such as equipment, machineries, special docks, and special wagons. Second, the measurement of human TSIs refers to HRM investments, such as training of staff in term of knowledge about the buyer, methods to deal with the buyer, and other business practices specifically to operate with the selected buyer. This construct was measured with a seven-point Likert scale adapted from previous studies (Bensaou & Venkatraman, 1995; Heide & John, 1988). Network intensity was measured by five items. These items were created based on the concept of network subgroups (Burt, 1980). The subgroups investigated in this research are suppliers of raw material, other buyers, other suppliers of potted plant products, buyer’s customers, and agents of the mediation department of the auction cooperatives. As such, each subgroup is a set of organizations holding the same function in the market. This measurement instrument was based on previous research (Blankenburg, Eriksson, & Johanson, 1999). The measurement of environmental instability captures the respondent’s perception with regard to market volatility and diversity. Five items assessed this measurement. This measurement instrument was based on previous research (Klein et al., 1990). Trust is a construct measured by two dimensions. First, interpersonal trust refers

D.P. Claro et al. / Industrial Marketing Management 32 (2003) 703–716 Table 2 Multiitem scales and single items used in the questionnaire Performance Sales growth rate (single item) 1. What are the current sales of the potted plants and flowers in euros? What were the sales in the year 1998? Perceived satisfaction a=.86 (seven-point Likert scale, ‘‘very unsatisfied’’ to ‘‘very satisfied’’) 1. The order frequency over the year. 2. Prices paid by the selected buyer for our products. 3. Communication quality with people of the selected buyer. 4. Prices paid by the selected buyer for our products. 5. Quality of their purchasing department. 6. The way in which problems are solved. Relational governance Joint planning a=.70 (seven-point Likert scale, ‘‘not at all’’ to ‘‘very much’’) 1. Our company plans volume demands for the next seasons together with this buyer. 2. Our company plans the new products and varieties demands for the next seasons together with this buyer. 3. This buyer provides us with sale forecasts for the products our company sells to them. 4. Our company shares long-term plans of our products with this buyer. Joint problem solving a=.87 (seven-point Likert scale, ‘‘not at all’’ to ‘‘very much’’) 1. This buyer and our company deal with problems that arise in the course of the relationship together. 2. This buyer and our company do not mind owing each other favors. 3. In most aspects of the relationship with this buyer, the responsibility for getting things done is shared. 4. This buyer and our company are committed to improvements that may benefit the relationship as a whole. Exchange mode (single item) 1. Considering the total amount of potted plants and flower product sales (in cash) to the specific buyer over the last year, please write down the percentage traded via ‘‘fixed lines’’ and ‘‘daily trade.’’ Physical TSI a=.79 (seven-point Likert scale, ‘‘not true at all’’ to ‘‘totally true’’) 1. In our company, we have made significant investments to deliver products to the selected buyer. 2. We have made significant investments to handle internally the products that are ordered by the selected buyer.

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Table 2 (continued ) Inter personal trust a=.75 (seven-point Likert scale, ‘‘not true at all’’ to ‘‘totally true’’) 2. In our company, we have faith in the contact person to look out for our interests even when it is costly to do so. 3. Our company’s contact person is trustworthy. 4. In our company, we have faith in the contact person to look out for our interests even when it is costly to do so. 5. In our company, we would feel a sense of betrayal if the contact person’s performance would be below my expectations. Inter organizational trust a=.83 (seven-point Likert scale, ‘‘not true at all’’ to ‘‘totally true’’) 1. We expect this buyer to be working with us for a long time. 2. The selected buyer has always been evenhanded in his or her negotiations with us. 3. The selected buyer may use opportunities that arise to profit at our expense (item dropped after EFA). 4. Based on experience, we can with complete confidence rely on the selected buyer to keep promises made to us. 5. We are hesitant to transact with the selected buyer when the order specifications are vague (item dropped after EFA). 6. The selected buyer is trustworthy. Network intensity a=.89 (seven-point Likert scale, ‘‘not at all’’ to ‘‘very much’’) 1. I get valuable information from other buyers, which supports my business relationship with the selected buyer. 2. I get valuable information from other suppliers, which supports my business relationship with the selected buyer. 3. I get valuable information from buyer’s customers, which supports my business relationship with the selected buyer. 4. I get valuable information from other buyers, which supports my business relationship with the selected buyer. 5. I get valuable information from agents of the cooperative, which supports my business relationship with the selected buyer. Environmental instability a=.60 (seven-point Likert scale, ‘‘not true at all’’ to ‘‘totally true’’) 1. We are often surprised by the high volatility of prices of our products in the market. 2. There are many potted plant growers for similar products in the market. 3. We are often surprised by the instability of volume purchased by ‘‘all’’ of our buyers. 4. There are many suppliers for similar products in the market. 5. Our buyers say that there are few immediate customers in the market for our products.

Human TSI a=.68 (seven-point Likert scale, ‘‘not true at all’’ to ‘‘totally true’’) 1. We have invested time and efforts to learn about the business practices of the selected buyer. 2. If we switch to another buyer, we would lose a lot of investments that we have made to sell to the selected buyer. 3. If we decided to stop working with this buyer, we would be wasting a lot of knowledge regarding the buyer’s method of operation. Length of business interaction (single item) 1. How long have you been doing business with the selected buyer? (years) Inter personal trust a=.75 (seven-point Likert scale, ‘‘not true at all’’ to ‘‘totally true’’) 1. Our company’s contact person (purchasing agent) has always been evenhanded in negotiations with us.

to the trust placed by the respondent in the purchasing agent of the selected buyer. Five items with Likert scales assessed interpersonal trust. This measurement instrument was based on the study of Zaheer et al. (1998). Second, interorganizational trust refers to the trust placed in the organization of the selected buyer. Six items assessed this dimension. Five measures were used to evaluate the variance of the control variables. First, the variable firm size was measured based on the respondent’s annual sales in the year 2001, which was assessed by a categorical scale with a five-interval class (1 = very small; 2 = small; 3 = medium; 4 = large; and 5 = very large). Second, buyer size was also measured by

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a categorical scale with three intervals referring to the sales volume of the selected buyer (1 = small; 2 = medium; and 3 = large size). Third, the measure for auction clock transactions reflects the percentage of sales that goes via the auction clock of the Dutch cooperatives. Finally, the variables type of buyers was measured according to the type of buyer’s customers where buyer business to business (B2B) refers to sales aiming at firms, and buyer business to consumers (B2C) refers to sales aiming at end consumers. Because the original nominal scale of the question is not a mutually exclusive variable, we decided to add one dummy variable for each of the types of buyer. The data analysis was carried out in SPSS and focused on Pearson correlation coefficients and ordinary least squares (OLS) regression models. The hypotheses were tested by estimating ordinary least square models, which refers to the estimation of the linear relationship between a dependent variable and the independent variables. According to the review of Malhorta, Peterson, and Kleiser (1999), the use of OLS to test hypotheses is a common practice among marketing researchers because the method maximizes the overall predictive power of the independent variables as represented in the variate. Moreover, regression analysis is mostly concerned with the degree, nature, and optimization of the causal relation between variables (Churchill, 1999). In the estimation procedure, we entered all the variables in a single step—‘‘enter’’ entry mode.

8. Results Table 3 shows the mean, standard deviation, and correlation coefficient for each construct of the framework for relationship management. In our sample, the focal relationship on average accounts for 29% of the total sales (ranging from 16% to 80%). We call attention to the mean and standard deviation of sales growth rate of the companies in the present study. The mean shows that companies are growing about 10% a year, and the standard deviation indicates that some companies present a negative growth while others present a growth rate of about 50% annually. Checking the mean of the two dimensions of relational governance, joint problem solving present a higher mean compared to joint planning. This shows that business relationships have been just initiated by the proactive action of joint planning, which might be strong among the suppliers that set the trend towards relational governance. In addition, the network intensity presented a low mean and standard deviation, which suggest that initiatives are somewhat modest. Although joint planning and network intensity can provide the firms a competitive edge, the mean demonstrated that suppliers appear to begin to concern about these two determinants of relational governance. The individual correlations between the constructs do not suggest obvious problems of pairwise collinearity that would preclude the use of all independent variables in a

regression model (Hair, Anderson, Tatham, & Black, 1998). The significant association of the constructs can be seen in the highlighted correlation coefficients. We found significant correlations between the determinants and the dependent constructs, as expected. The two dimensions of relational governance are correlated with growth rate and perceived satisfaction. The constructs of the transaction level (exchange mode and human and physical TSI), the two dimensions of trust, and network intensity are correlated with joint planning. Furthermore, the two dimensions of trust, interpersonal and interorganizational, are associated with joint problem solving. Surprisingly, length of the business interaction was only associated with sales growth and with a negative sign. This might be related to the long length of the business relationships (on average 8.4 years) and its relatively high standard deviation (5.6 years). Regarding the construct of environmental instability, there is a positive correlation with exchange mode and a negative correlation with length of business interaction. This suggests that environmental instability is associated with the use of fixed lines and not so long business interactions. Table 4 summarizes the results of ordinary least square regression analyses of H1 – H8 of the integrated framework in Fig. 1. While relational governance was the dependent variable, the constructs—exchange mode, TSIs, length of the business interaction, trust, network, and environmental instability—derived from the three analytical levels of the determinants were the independent variables. The joint planning (R2=.360) and joint problem solving (R2=.364) regression models both achieved good levels of predictive accuracy. Furthermore, the two equations were statistically significant below the .01 level. 8.1. Transaction level The transaction level of analysis includes the effects of operations of the economic exchange (i.e., exchange mode) and the TSIs on relational governance. The exchange mode has a significant positive effect on joint planning (b=.19, P < .01), whereas no significant effect on joint problem solving was identified. The hypotheses (H1a and b) that exchange mode influences relational governance positively are partially supported, which might be related to the different nature of the joint actions. As the fixed line mode allows for self-enforcing mechanisms, the joint planning is preferable rather than joint problem solving because of the close contact between parties and the proactive nature of joint planning. The human TSIs do not significantly influence relational governance. It was expected that sales personnel of a supplier that learns how to deal with the buyer’s purchasing system would motivate suppliers to be engaged in joint actions (H2a and b). This nonsignificant coefficient might be due to a standardized approach to purchases, which means that the buyer’s purchasing system does not differ across buyers and consequently no HRM investments are

Table 3 Descriptive statistics Mean S.D.

SG

9.21 15.22 165 5.28 1.00 0.14

Relational governance Joint planning (JP) Joint problem solving (JPS)

2.86 5.64

Transaction level Exchange mode (EM) Human TSI (HTSI) Physical TSI (PTSI) Dyadic level Length business interaction (LBI) Interpersonal trust (IPT) Interorganizational trust (IOT) Business environment level Network intensity (NI) Environmental instability (EI) Control variables Supplier size (SS) Buyer size (BS) Auction clock transactions (ACT) Buyer type B2B (B2B) Buyer type B2C (B2C)

1.38 1.37

42.32 38.27 3.34 1.35 3.47 1.85

PS

JP

JPS

EM

HTSI

PTSI

171 0.55 * 171

LBI

IPT

IOT

NI

EI

SS

BS

ACT

0.16 * 0.19 *

0.23 * 173 0.47 * 0.29 * 173

0.14 0.04 0.01

0.04 0.24 * 0.15

0.36 * 0.42 * 0.31 *

0.04 0.26 0.18

169 0.28 0.13

5.63

0.18 *

0.12

0.06

0.14

0.21

0.04

0.11

4.69 5.32

1.13 1.16

0.03 0.18 *

0.41 * 0.68 *

0.30 * 0.35 *

0.52 * 0.57 *

0.10 0.10

0.20 * 0.36 *

0.23 * 0.18 *

0.13 0.14

2.76 3.57

0.95 1.10

0.06 0.02

0.01 0.14

0.39 * 0.04

0.13 0.12

0.14 0.15 *

0.30 * 0.02

0.27 * 0.09

0.08 0.19 *

0.11 0.03

0.07 0.13

4.10 1.20 1.32 0.70 34.27 22.17

0.08 0.05 0.05

0.17 * 0.10 0.37 *

0.25 * 0.02 0.16 *

0.29 * 0.03 0.31 *

0.20 * 0.00 0.07

0.29 * 0.12 0.12

0.25 * 0.08 0.11

0.12 0.01 0.19 *

0.14 0.10 0.25 *

0.22 * 0.02 0.28 *

0.09 0.04 0.14

0.12 174 0.02 0.02 171 0.18 * 0.14 0.13 173

.06 0.03

.01 0.01

.23 * 0.28 *

.01 0.02

.25 * 0.27 *

.19 * 0.15 *

.09 0.02

.23 * 0.26 *

.08 0.04

.02 0.05

.10 0.04

.08 0.01

.48 0.50

B2C

173

8.40

.65 0.47

B2B

174 169 0.61 * 172

170 0.09 174

.03 0.00

.04 0.00

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Performance Sales growth (SG) Perceived satisfaction (PS)

.03 174 0.02 0.74 * 174

Figures on the diagonal represent number of observation. * Correlation is significant at the .05 level (two-tailed test).

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Table 4 Results of the regression analysis of relational governance and the hypothesized determinants Determinant

Joint planning

Hypothesis supported?

Joint problem solving

Hypothesis supported?

Transaction level Exchange mode Human TSI Physical TSI

0.19 (2.67)*** 0.11 (1.25) 0.13 (1.61) *

H1a: Yes H2a: No H3a: Yes

0.06 (0.88) 0.08 (0.89) 0.04 (0.54)

H1b: No H2b: No H3b: No

Dyadic level Length of business interaction Interpersonal trust Interorganizational trust

0.02 (0.21) 0.09 (1.06) 0.17 (1.98) **

H4a: No H5a: No H6a: Yes

0.01 (0.06) 0.24 (2.95)*** 0.31 (3.61)***

H4b: No H5b: Yes H6b: Yes

Business environment Network intensity Environmental instability

0.25 (3.59)*** 0.04 (0.61)

H7a: Yes H8a: No

0.04 (0.61) 0.04 (0.57)

H7b: No H8b: No

Control variables Supplier size Buyer size Auction clock transactions Buyer B2B Buyer B2C Adjusted R2

0.02 (0.25) 0.07 (1.07) 0.06 (0.87) 0.01 (0.08) 0.20 (1.91) ** .360***

0.22 (3.14)*** 0.08 (1.17) 0.11 (1.57) * 0.10 (0.99) 0.16 (1.51) * .364***

Regression coefficients are standardized coefficients (b) and | t test| within parentheses. * P < .10 (one-tailed test). ** P < .05 (one-tailed test). *** P < .01 (one-tailed test).

specifically done for a particular buyer. Contrary to the result of human specificity, physical specificity does influence the joint planning (b=.13, P < .10), as it was predicted in our hypothesis (H3a). Machinery and equipment, which are tailored to the selected buyer, may foster suppliers to develop a plan together with the buyer. The results of the effect of TSIs on relational governance highlight the importance of evaluating two dimensions of TSIs. It shows that the joint planning can function as a mechanism to safeguard the physical specific investments.

cope with problems that occur. As H6a and b suggest, high levels of interorganizational trust is positively related to the occurrence of relational governance, joint planning (b=.17, P < .05), and joint problem solving (b=.31, P < .01). This confirms the relevance of trust in business relationships as previous research also underlined (Bhattacharya & Devinney, 1998; Doney & Cannon, 1997; Zaheer & Venkatraman, 1995). Except for H5a, the other hypotheses were supported implying that trust enables relational governance to be undertaken by parties involved in a business relationship.

8.2. Dyadic level

8.3. Business environment

Complementing the operations and investments of the transaction analytical level, the dyadic level involves the effects of ongoing business relationships and the social bonds of trust on relational governance. The results of the regression analysis show no significant effect of the length of the business interaction on relational governance, contrary to what was hypothesized (H4a and b) and previous research (Ganesan, 1994). This suggests that no matter the length of the business interaction, partners will or will not engage in joint activities. The influence of trust on relational governance was evaluated based on two different dimensions of trust, interpersonal and interorganizational. Interpersonal trust does not significantly influence joint planning whereas it does influence positively the joint problem solving (H5b). This result suggests that interpersonal trust enables parties to

The third analytical level consists of the business environment, which focuses on the effect of business networks and the environmental instability on relational governance. In accordance with H7a, the information obtained from the business network affects joint planning positively (b=.25, P < .01). For the suppliers of our sample, this result suggests that information from the network reduces information asymmetries and motivates suppliers to plan together with the buyer. Although the information from the network affects joint planning, the results show no significant effect of the information on joint problem solving (H7b). This suggests that suppliers attempt to solve problems in a bilateral effort concentrating on the buyer or perhaps on the problem itself, and the information from other firms is not relevant to the joint problem solving. Environmental instability does not significantly affect the two determinants

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of relational governance (H8a and b). The results of the regression analysis confirmed what was found in the analysis of the individual correlations. It is likely that the environmental instability is absorbed by the joint action the parties of a business relationship undertake. Contrary to our findings, other studies found significant effect of environmental instability on issues related to the governance of a business relationship (Klein et al., 1990). The effects of the control variables provide some interesting results. Large suppliers are likely to engage in joint problem solving (b=.22, P < .01), whereas there is no significant effect of the supplier size on joint planning. The buyer size and buyers B2B (e.g., wholesalers and exporters) do not affect significantly the two dimensions of relational governance. However, the results suggest that business relationship with buyers B2C (e.g., garden centers and cash-and-carries), which sell directly to consumers, affects joint planning negatively (b = .20, P < .05) and joint problem solving positively (b=.16, P < .10). Noteworthy, the sales concept of buyers B2C is similar to that of supermarkets where consumers in the shop choose products based on the shelf availability and in-advance ordering is rather unusual. So, suppliers managing business relationships with buyers B2C prefer to engage in joint problem solving that might be supported by consumers’ perceptions of product conditions in the buyer’s shelves. In addition, the joint planning is perhaps unfeasible because there are so many customers of these B2C buyers, which might not offer a payoff for the planning with suppliers.

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rate. The level of predictive accuracy of the perceived satisfaction regression model was acceptable according to previous research (R2=.23); the equation was statistically significant below the .01 level. The sales growth rate model however achieved a low level of predictive accuracy (R2=.04), and the significance level of the equation was .05. Previous research also faced low level of predictive accuracy (Mohr & Speckman, 1994). Although the model of the rate of sales growth presents a low level of explanatory power, we decided to examine it because of the importance of having not only an affective measure for performance, but also an objective one. Relational governance affects positively sales growth and perceived satisfaction, as predicted in H9 and H10. Joint planning has a significant positive effect on sales growth (b=.11, P < .10) but has no significant link to perceived satisfaction, while joint problem solving correlates positively with perceived satisfaction (b=.36, P < .01) and sales growth (b=.21, P < .01). Therefore, the results show the importance of joint planning and joint problem solving as means to reduce waste of time and resources in managing a business relationship. The control variables were not significantly related to performance, except auction clock transactions. The transaction through the auction clock are negatively related to perceived satisfaction (b = .22, P < .01) and positively related to sales growth (b=.15, P < .05). This result reveals that although joint actions are important, the auction clock transactions still play a significant role in the performance of suppliers.

8.4. Relational governance and performance 9. Discussion and conclusions H9 and H10 were also tested through a regression analysis of relational governance and performance (see Table 5). The two models test the effect of relational governance, in terms of joint planning and joint problem solving, on the perceived satisfaction and the sales growth

9.1. Integrated framework for relationship management Fig. 2 shows the integrated framework for relationship management highlighting the significant results of the

Table 5 Results of the regression analysis of performance and relational governance Predictor Relational governance Joint planning Joint problem solving Control variables Supplier size Buyer size Auction clock transactions Buyer B2B Buyer B2C Adjusted R2

Sales growth

0.11 (1.35) * 0.21 (2.42)***

0.01 0.08 0.15 0.09 0.01 .04 **

Hypothesis supported? H9a: Yes H10a: Yes

(0.08) (0.99) (1.81) ** (0.75) (0.10)

Regression coefficients are standardized coefficients (b) and | t test| within parentheses. * P < .10 (one-tailed test). ** P < .05 (one-tailed test). *** P < .01 (one-tailed test).

Perceived satisfaction 0.06 (0.78) 0.36 (4.79)***

0.01 0.08 0.22 0.02 0.01 .23***

(0.01) (1.10) (3.04)*** (0.215) (0.09)

Hypothesis supported? H9b: No H10b: Yes

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Fig. 2. The tested integrated framework for relationship management.

empirical evidence. Our integrated framework aimed at the combination of constructs on the transaction, dyadic, and business environment level for testing their influence on relational governance and performance. The dimensions of relational governance positively affect both measures of performance, sales growth, and perceived satisfaction, except that joint planning is not related to perceived satisfaction. This result highlights the importance of a collaborative approach to achieve success in a business relationship. Noteworthy, the determinants at the three analytical levels show distinct relations with the two dimensions of relational governance, namely joint planning and joint problem solving. The combination of fixed line exchange mode, physical TSI, network intensity, and interorganizational trust comprise the determinants of joint planning, which is a proactive action by nature. For mutual expectations and cooperative efforts to be established at the outset, the business relationship is influenced by the determinants of the three analytical levels. Transactions must be based on a self-enforcing agreement (Dyer & Singh, 1998) and physical TSI (Williamson, 1985), the dyadic relies on interorganizational trust (Zaheer et al., 1998), and finally the business environment affects joint planning by the information obtained from the network (Burt, 1997). The constructs of the three analytical levels provide suppliers with the ability to effectively plan together with the selected buyer. The other dimension of relational governance, joint problem solving, is notably affected by both dimensions of trust, interorganizational and interpersonal. For jointly solving a problem, trust is essential because it involves an arduous process of elaborating a solution and making the necessary adaptations that satisfies both parties. Interestingly, interorganizational trust is the most encompassing determinant affecting joint planning and joint problem solving. Researchers (Anderson & Narus, 1990; Anderson & Weitz, 1989) have treated trust as a unidimensional construct. However, our research shows that trust is a multidimension-

al construct and affects in different ways the dimensions of relational governance. Such a multidimensional approach provided a strong diagnostic power with respect to the effect of trust on business relationships. Trust acts as a lubricant (Bradach & Eccles, 1989) of relational governance of business relationships, which fosters a mutual understanding and fluid contact between partners. Therefore, not only fixed line exchange mode, physical TSI, and network intensity are important for relational governance, but also interorganizational and interpersonal trust. 9.2. General conclusions This article highlights the importance of the determinants of relational governance and the impact of relational governance on performance. Building on transaction cost economics (Williamson, 1985), marketing channel theory (Stern & El-Ansary, 1996), and business network theory (Gulati, 1998; Hakanson & Snehota, 1995; Powell, 1990; Thorelli, 1986), we proposed an integrated framework for relationship management. This integrated framework was tested and presented some partially supported hypotheses. For relationship management, the significant determinants might form the final integrated framework that presents the determinants derived from the three analytical levels for the study of a specific business relationship. The presence of interpersonal and interorganizational trust as strong determinants of relational governance in our integrated framework leads us to the conclusion that a social bond surrounds the transaction as Granovetter (1985) suggests. The economic exchange is not made by anonymous actors acting in an opportunistic way but rather by organizations and individuals within these organizations that trust each other. Trust allows organizations to transact without the need for a complex safeguard mechanism. We found evidence that the information provided by the business network plays an important role in the choice of

D.P. Claro et al. / Industrial Marketing Management 32 (2003) 703–716

relational governance. Relational governance is a complex organizational arrangement that can require multiple levels of internal approval, search issues in identifying partners, and detailed negotiations (Dyer & Singh, 1998). The information provided by the network appears to support the relational governance of the suppliers in our sample. Our results and the studies that highlight the role of embeddedness (e.g., Uzzi, 1997) do not contradict the economic motivations for a business relationship. Firms do not form this relationship as symbolic social affirmations of their network but rather base relationships on concrete jointly developed long-term plans. At the transaction level, the fixed line exchange mode and physical TSI appear to affect relational governance positively. For joint planning a buyer, suppliers prefer self-enforcing mechanisms rather than relying on a third party and specific physical investments rather than no coordination of the transaction. We found that the conditions of mutual economic advantage are necessary but not sufficient for relational governance. According to our study, there is a need for trust and information provided by the network and moreover the use of fixed lines as an exchange mode and physical TSI.

10. Limitations and further research The implications of this study should be evaluated in the light of the following limitations. First, although tests of the models yield several results that are consistent with the hypotheses, the used cross-sectional design limits the ability to rule out alternative causal inferences. It is also conceivable that the causality is (also) reverse to that what we suggested. Our framework is predicated on the assumption that trust and length of the business interaction affect relational governance and performance. Although studies have conceptualized trust as a determinant rather than a consequence of relationship nature (e.g., Anderson & Narus, 1990; Anderson & Weitz, 1989; Doney & Cannon, 1997), performance might influence the relational governance and trust. For instance, firms that benefit from very good performance (e.g., perceived satisfaction or sales growth rate) are likely to become willing to invest in the relational governance and trust, taking some risks for granted. The proof of the causality of this relationship requires a longitudinal research design, and further research along this line is therefore encouraged. Second, while some variables in our study were bilateral (e.g., relational governance, and trust), the data were obtained from only one party of the relationship. We then recognize that further research on business relationship should aim at the analysis of both the supplier and the buyer side. Finally, the sample of Dutch companies may limit the variation of some of the dimensions and may reflect market particularities of this sector. For instance, our control variables showed that large suppliers are likely to be engaged in joint problem solving and that the market

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transactions (auction clock) remains the dominant exchange mode among the suppliers that participated in our research. Thus, further research is encouraged to replicate the present study in other research settings.

11. Managerial implications Understanding why and how some business relationships succeed while others fail are perhaps among the central questions for firms. From the managerial perspective, it is then important to know how to improve overall performance. Based on our study of business relationship and considering the context in which our respondents are embedded, it is possible to state that performance is directly affected by the two joint actions of relational governance, joint planning and joint problem solving. The joint actions should then be considered explicitly in the management of a relationship. By setting up these joint actions, managers can exploit the benefits of safeguarding and coordinating a business relationship with buyers. The joint planning safeguards the physical specific investments of suppliers and further support the self-enforcing agreements of fixed lines exchange mode. Managers should also consider the business network as an essential source of information that can offer valuable information to the relationship with buyers. The information of the connected relationships of a firm’s network can encourage firms to be engaged in joint planning. Managers may use our study to assess the adequacy of their business network in terms of its functional advantages of the information. Furthermore, we discuss the relational governance from the perspective of designing interfirm collaboration that allows for creative joint problem solving. Managers should also be engaged in trust-enhancing activities because it can foster joint problem solving.

Acknowledgements The authors are grateful for the research grant from CAPES (Project BEX 1257/98-6). The authors appreciate the comments from the anonymous reviewers and suggestions from the editor of the special issue.

References Anderson, E., & Weitz, B. (1989). Determinants of continuity in conventional industrial channel dyads. Marketing Science, 8, 310 – 323. Anderson, J. C., Hakansson, H., & Johanson, J. (1994). Dyadic business relationship within a business network context. Journal of Marketing, 58, 22 – 38. Anderson, J. C., & Narus, J. A. (1990). A model of distributor firm and manufacturer firm working partnerships. Journal of Marketing, 54, 42 – 58. Armstrong, J. S., & Overton, T. S. (1977, August). Estimating nonresponse bias in mail survey. Journal of Marketing Research, 14, 396 – 402.

716

D.P. Claro et al. / Industrial Marketing Management 32 (2003) 703–716

Barney, J. B., & Hansen, M. H. (1994). Trustworthiness as a source of competitive advantage. Strategic Management Journal, 15, 175 – 190. Bensaou, M., & Venkatraman, N. (1995). Configurations of interorganizational relationships: A comparison between U.S. and Japanese automakers. Management Science, 41, 1471 – 1492. Bhattacharya, R., & Devinney, T. M. (1998). A formal model of trust based on outcomes. Academy of Management Review, 23(3), 459 – 472. Blankenburg, D., Eriksson, K., & Johanson, J. (1999). Creating value through mutual commitment to business network relationships. Strategic Management Journal, 20, 467 – 486. Bradach, J. L., & Eccles, R. G. (1989). Price, authority and trust. Annual Review of Sociology, 15, 97 – 118. Burt, R. S. (1980). Models of network structure. Annual Review of Sociology, 6, 79 – 141. Burt, R. S. (1997). The contingent value of the social capital. Administrative Science Quarterly, 42, 339 – 365. Churchill, G. A. (1999). Marketing research: Methodological foundations. Claro, D. P., Hagelaar, G., & Omta, S. W. F. (2002). Selection of suppliers embedded in networks: Empirical results on supplier – buyer relationships in the flower supply chain. In J. H. Trienekens, & Omta S. W. F. (Eds.), Proceedings of 5th International Conference on Chain and Network Management in Agribusiness and the Food Industry ( pp. 615 – 626). Wageningen Press. Claro, D. P., Hagelaar, G., & Zylbersztajn, D. (2002). Relationships with suppliers and strategic network effects: A case of an exporter of the supply chain of flowers. In S. K. Kundu (Ed.), Midwest review of international business research ( pp. 152 – 166), Chicago. Deneux, S. D. C., & Luten, J. H. (2001). A closed-chain concept for application in the floristry sector, Project code 64343-01-30. Doney, P. M., & Cannon, J. P. (1997, April). An examination of the nature of trust in buyer – seller relationships. Journal of Marketing, 61, 35 – 51. Dyer, J. H. (1996). Specialized supplier networks as a source of competitive advantage: Evidence from the auto industry. Strategic Management Journal, 17, 271 – 291. Dyer, J. H., & Singh, H. (1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23, 660 – 679. Gadde, L. E., & Snehota, I. (2000). Making the most of supplier relationships. Industrial Marketing Management, 29, 305 – 316. Ganesan, S. (1994). Determinants of long-term orientation in buyer – seller relationships. Journal of Marketing, 58, 1 – 19. Granovetter, M. (1985). Economic action and social structure. American Journal of Sociology, 91, 481 – 510. Gulati, R. (1998). Alliances and networks. Strategic Management Journal, 19, 293 – 317. Hair, J. F., Anderson, R., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis. Upper Saddle River: Prentice-Hall. Hakansson, H., Havila, V., & Pedersen, A. C. (1999). Learning in networks. Industrial Marketing Management, 28, 443 – 452. Hakanson, H., & Snehota, I. (1995). Developing relationships in business network. New York: Routledge. Heide, J. B., & John, G. (1988). The role of dependence balancing in safeguarding transaction-specific assets in conventional channels. Journal of Marketing, 52, 20 – 35. Heide, J. B., & John, G. (1990, February). Alliances in industrial purchasing: The determinants of joint action in buyer supplier relationships. Journal of Marketing Research, 27, 24 – 36. Heide, J. B., & Miner, A. S. (1992). The shadow of the future: Effects of anticipated and frequency of contract on buyer – seller cooperation. Academy of Management Journal, 35, 265 – 291. Kalenzi, E. (2000). Marketing channel performance in the flower industry: A case on Kenya-Netherlands flower business. MBA dissertation, Wageningen University. Klein, S., Frazier, G. L., & Roth, V. J. (1990). A transaction cost analysis model of channel integration in international markets. Journal of Marketing, 196 – 208.

Lusch, R. F., & Brown, J. R. (1996, October). Interdependency, contracting, and relational behavior in market channels. Journal of Marketing, 60, 19 – 38. Malhotra, N. K., Peterson, M., & Kleiser, S. B. (1999). Marketing research: A state-of-the-art review and directions for the twenty-first century. Journal of the Academy of Marketing Science, 27(2), 160 – 183. Mohr, J. J., & Speckman, R. (1994). Characteristics of partnership success: Partnership attributes, communication behavior, and conflict resolution techniques. Strategic Management Journal, 15(2), 135 – 152. Noordewier, T. G., John, G., & Nevin, J. R. (1990, October). Performance outcomes of purchasing arrangements in industrial buyer – vendor relationship. Journal of Marketing, 54, 80 – 94. Powell, W. W. (1990). Neither market nor hierarchy: Network forms of organization. Research in Organizational Behavior, 12, 295 – 336. Prahalad, C. K., & Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, 68(3), 79 – 91. Rindfleish, A., & Heide, J. B. (1997). Transaction cost analysis: Past, present and future applications. Journal of Marketing, 61, 30 – 54. Rotter, J. B. (1980). Interpersonal trust, trustworthiness and gullibility. American Psychologist, 35, 1 – 7. Stern, L. W., & El-Ansary, A. (1996). Marketing channels. Upper Saddle River, NJ: Prentice-Hall. Thorelli, H. B. (1986). Networks: Between markets and hierarchies. Strategic Management Journal, 7, 37 – 51. Uzzi, B. (1997). Social structure and competition in interfirm networks: The paradox of embeddedness. Administrative Science Quarterly, 42, 35 – 67. Wathne, K., Biong, H., & Heide, J. B. (2001). Choice of supplier in embedded markets: Relationship and marketing program effects. Journal of Marketing, 65, 54 – 66. Weigelt, K., & Camerer, C. (1988). Reputation and corporate strategy. Strategic Management Journal, 9, 443 – 454. Williamson, O. E. (1985). The economic institutions of capitalism. New York: Free Press. Williamson, O. E. (1991, June). Comparative economic organization: The analysis of discrete structural alternatives. Administrative Science Quarterly, 36, 269 – 296. Williamson, O. E. (1996). The mechanism of governance. New York: Oxford University Press. Zaheer, A., McEvily, B., & Perrone, V. (1998). Does trust matter? Exploring the effects of interorganizational and interpersonal trust on performance. Organization Science, 9, 141 – 159. Zaheer, A., & Venkatraman, N. (1995). Relational governance as an interorganizational strategy: An empirical test of the role of trust in economic exchange. Strategic Management Journal, 16, 373 – 392. Danny Pimentel Claro Research assistant and PhD Candidate in the Department of Business Administration at the Wageningen University. He is also a part-time researcher in the Dutch Research Institute of Agricultural Economics - LEI. His research interests are Relationship Management, Marketing Channels, Supply Chain Management and Network Management. His fields of research are Agri and Food Industries. Geoffrey Hagelaar Associate Professor in the Department of Business Administration at Wageningen University. He received his PhD from University of Twente. His research interests are Supply Chain Management, Environmental Management and Network Management. His fields of research are Agri and Food Industries. S.W.F (Onno) Omta Professor of Business Administration at Wageningen University. His research interests are Supply Chain Management, Innovation and Network Management. His fields of research are Pharmaceutical and Agri and Food Industries.