Specificity Investments, Relationship Learning, and Competence Building: the. Supplier s Perspective. Wann-Yih Wu 1. Su-Chao Chang 2.

Transcription

1 Specificity Investments, Relationship Learning, and Competence Building: the Supplier s Perspective Wann-Yih Wu 1 Su-Chao Chang 2 Ya-Jung Wu 3** ** indicates Corresponding author 1 2 Professor, Department of Business Administration, National Cheng Kung University, Taiwan. wanyi@mail.ncku.edu.tw No.1, Ta-Hsueh Road, Tainan 701, Taiwan. TEL:(886) ext FAX: (886) Professor, Department of Business Administration, National Cheng Kung University, Taiwan. No.1, Ta-Hsueh Road, Tainan 701, Taiwan. 3** Assistant Professor, Department of Finance, Kao Yuan University, Taiwan. yajungwu@yahoo.com.tw 1

2 Specificity Investments, Relationship Learning, and Competence Building: the Supplier s Perspective Abstract Traditionally, supplier s specificity investments are always seen as the commitments from the supplier. The effect of supplier s specificity investments on buyer s benefits is evident. However, previous studies regarding the strategic benefits which supplier s specificity investments could bring to supplier are limited and subject to further validation. Thus, our major concern is that could supplier s specificity investments raise the strategic benefits in terms of relationship learning and competence building for the supplier? This paper develops a research model to integrate supplier s specificity investments, relationship learning, as well as competence building, and further test the model using collected data from 148 exporting suppliers in the Taiwan manufacturing industries. The study concludes that (1) supplier s specificity investments can promote relationship learning benefits, in terms of information sharing, joint sense making, as well as integrating into firm s memory; (2) there are significant relationships between relationship learning, and supplier s competence building. While integrating acquired knowledge into supplier firm s memory is positive associated with competence building, making joint sense is negative associated with marketing and coordination competence building; (3) while the direct effect of supplier s specificity investments on competence building is negative, the indirect effect which is mediated by way of relationship learning is positive; (4) the moderating effects of norms, customer s power advantage, and interdependence are also verified. These results highlight the importance of recognizing the facilitating role as well as restraining role of supplier s specificity investments to articulate benefits to suppliers. Keywords: Specificity investments, Relationship learning, Competence building 2

3 RESEARCH BACKGROUND AND RESEARCH MOTIVATIONS Facing a more competitive management environment and a more serious global competition, a consensus has emerged on the importance of interfirm networks as a modern mode of organizing economic activity. Indeed, it can be observed that the most important recent changes in industrial buying behavior are increased cooperation between suppliers and customers (Matthyssens & Van den Bulte, 1994; Sporleder & Moss, 2002; Peterson, 2002; Hyland et al., 2003; Dyer & Nobeoka, 2000). Among many studies of buyer-supplier relationships, researchers have generally focused on examining why customers enter these close relationships with their suppliers (e.g., Helper, 1991; Lyons et al., 1990). There are only few research employing supplier s perspective to explore could suppliers raise strategic benefits drawing from building close relationship with their customers. It is argued that while supplier s specificity investments tend to lower transaction cost for customers, they are unavoidable to bring hold-up risks for suppliers. Under this circumstances, the decision about specificity investments deployment is an important issue from the perspective of suppliers. Further, it can be found that in the environments of global competition, lots of manufacturing firms are forced to embed in global supply chain to play a more active role than ever. The question confronting suppliers is often not whether they should deploying specificity investments but how they can take advantage of these specificity investments and benefit from these investments (Subramani, 2004). Thus, unlike research that uses a transaction cost perspective, supplier s specificity investments could be viewed as an enabler of strategic outcomes, in terms of relationship learning, supplier s competence building, instead of a transaction cost to be minimized. This study builds on previous research on two aspects. First, the study explicitly examines the strategic outcomes of supplier s specific asset investments. In an era of intense global competition, firms realize that the effective use of global sourcing contributes 3

4 significantly to their market performance. For the suppliers who embed in global value chain, pursuing for business opportunities drawing from outsourcing seems to mean highly specific assets involved as well as competence building. Thus, the first concern of this study is that could supplier s specificity investments bring relationship learning, and competence building for the supplier. Second, the context factors existing in buyer-supplier dyad relationship are examining in this study. Previous research has verified that exchange relationships are significantly impacted by sociological elements. However, it seems that there are no best practices in Supply Chain Management universal. While Dyer & Singh (1998) propose that, by moving away from arm s-length exchanges and specializing their relationships through idiosyncratic investments, knowledge exchange, complementary competencies, and more effective governance mechanisms (such as trust), firms can create the potential for earning competitive advantages, Mudambi & Helper (1998) admit that most of buyer-supplier dyad relationship is still belonging to close but adversarial relationship. Thus, relational norms, and dependence structure are conducted as context factors, to examine moderating effects upon the relationship between supplier s specificity investments, and relationship learning. Taken together, in this paper we study partnerships in the context of a buyer-supplier relationship to investigate two research questions: What kinds of impact do such relationships have on the suppliers involved, and which processes account for these effects? Answering these and similar questions is fundamental to differentiating high-performing partnerships from those that perform poorly or fail. LITERATURE REVIEW Drawing from previous studies, it is found that supplier s specificity investments could raise the operational benefits such as more constant sales volume, more repeat business, a decrease in sales expenses, and vastly improved planning and forecasting. However, the 4

5 strategic benefits such as relationship learning, and competence building is hardly referred. It is argued that these strategic benefits are essential both to suppliers attenuating transaction cost caused by specificity investments, as well as to customers exploiting the outsource benefits which exists in supplier s innovation and capabilities. Thus, in this section, the strategic benefits of specificity investments, in terms of relationship learning, as competence building will be defined, and then the relationships among these constructs will also be explored. Competence Building The capability-based theory of competitive advantage suggests that a firm can achieve sustain competitive advantage through distinctive capabilities possessed by the firm (Grant, 1996; Teece, et al., 1997) and that the firm must constantly re-invest to maintain and expand existing capabilities in order to inhibit imitability. According to resource-based theory, the competitive advantages lie in the heterogeneous firm-specific resources possessed by the firm (Rumelt, 1987). Resources include all assets, capabilities, organizational processes, firm attributes, information, knowledge, etc. controlled by a firm that enable the firm to conceive of and implement strategies that improve efficiency and effectiveness (Barney, 1991). Therefore, organizational capabilities are viewed as a resource. However, Mahoney and Pandian (1992) argue that a firm achieves rents not because it has more or better resources, but because the firm s distinctive capabilities allow it to make better use of available resources. Drawing from the stream of global value chain research, it is commonly observed that the rapid growth of the NIEs is following the process of supplier-oriented industrial upgrading. According to Kaplinsky & Morris (2000), four trajectories have been identified which firms can adopt in pursuing the objective of upgrading, namely, process upgrading, product upgrading, functional upgrading, and chain upgrading. In addition, according to the 5

6 study of LaBahn (1999), three investments that component suppliers can make to circumvent their large customers ability to achieve significant power advantages are including: partnering with an alternative key customer, developing products that serve the needs of many customers within a targeted market segment, and building technical capabilities to become more valuable to their key customers. Similar token, by observing the growth of contract manufacturers in the electronics industry in Taiwan, Lee & Chen (2000) indicate that contract manufacturer in its pursuit of sustainable growth is to expand the scope of value creation by creating a self-reinforcing cycle containing conscious learning in product design and development knowledge, both internally and externally, and productive leveraging activities across multiple buyer-supplier engagements. Combining the above discusses, it could be found that the innovation opportunities exist in multi-dimensions, such as the field of technologies (e.g. process upgrading, and product upgrading), of marketing (e.g. finding alternative customers, and others niches), of managerial capabilities improvement (e.g. logistic management, and coordination). The above capabilities are seen as the content of competence which suppliers could learn from the interactions with the specific customers. It is termed competence building in this study. Relationship Learning Learning from the experience of others has been a persistent theme in the organizational learning literature. It is argued that the active participation of others in the process of challenge and support is recognized as a powerful enabling resource at the interpersonal level and was developed into a widely used approach termed action learning (McGill & Warner, 1989). This concept stresses the value of experiential learning and the benefits which can come from gaining different forms of support from others in moving around the learning cycle. Whilst these ideas originated at the interpersonal level there is clearly potential for their application in inter-firm learning (Bessant & Tsekouras, 2001). 6

7 Similarly Cohen & Levinthal (1990) argue that organizations with a high level of absorptive capacity are likely to harness new knowledge from others to help their innovative activities, since absorptive capacity is assumed to increase the ability to recognize knowledge, assimilate knowledge, and commercialize knowledge. In this study, we see absorptive capacity as a supplier s competence rather than as a learning process. In other words, we would focus on the learning processes embedded in relationship learning, rather than the extent of supplier s absorptive capacity. According to Selnes & Sallis (2003), relationship learning is defined as an ongoing joint activity between the customer and the supplier organizations directed at sharing information, making sense of information, and integrating acquired information into a shared relationship-domain-specific memory to improve the range or likelihood of potential relationship domain-specific behavior. They identify four learning processes, including (1) information sharing between the two parties in a customer- supplier relationship is a starting point and a necessary element of relationship learning. (2) dialogue within the relationship constitutes a relationship-specific element of interpretation or sense making (i.e., knowledge development) of the shared information. (3) organizations develop relationship-specific memories into which acquired relationship-specific knowledge is integrated. (4) relationship memories manifest in physical artifacts, such as documents, computer memories, and programming. Following Selnes & Sallis (2003), in this study, relationship learning is defined as an ongoing joint activity between the customer and the supplier organizations directed at sharing diversity information to extend the original cognitive map to a highly advanced organization s schema in dealing with environmental stimuli. The Relationship between Relationship Learning and Competence Building 7

8 As discussed above, relationship learning refers to the extent and degree of information sharing, joint sense making, as well as integrating knowledge into firm s memory. This interfirm learning process is similar to what action learning suggests. Applying action learning into the context of buyer-suppliers relationship, suppliers in partnerships acquire knowledge and skills through a process of knowledge management and creation. Through their involvement in the operation of the cooperation, firms can learn from their customers and raise new knowledge. Then, this knowledge has the potential to be shared and distributed within the organization, and through processes of amplification and interpretation, the knowledge is given shared organizational meaning (Nonaka, 1994). The translation of new knowledge into organizational action is the basis for creating new skills that underpin a firm s competitive advantage. Studies of learning behavior in supply chains suggest that superior competencies emerge from superior learning (Sturgeon & Lee, 2001; Selnes & Sallis, 2003; Roy, et al., 2004). The most notable example is the case of how Toyota facilitates network learning. Toyota relies on three interorganizational processes--supplier associations, consulting groups and learning teams to facilitate the transfer of knowledge within is supplier network (Dyer and Hatch, 2004). In addition, in an empirical case study of Taiwanese firms, Wu & Hsu (2001) find that under OEM sub-contracting, knowledge transfer takes place in a systematic fashion. The variety and quantity of knowledge exchanged contribute to the subject firms continuous improvement of their innovative capabilities. Thus, it is proposed that the greater relationship learning is achieved through information gathering, communication, decision-making conflict resolution, and overall-governance of the collaborative process, the greater supplier s competence building will be. Hypothesis 1: The higher extent of relationship learning, the better will be the supplier competence building for a supplier. 8

9 Supplier s Specificity Investments A small but growing body of literature on transaction value is emphasizing the influence of governance on the value-creation initiatives of alliance partners (Zajac & Olsen, 1993; Mohr & Nevin, 1990; Dyer & Singh, 1998). Among these studies, governance is referred as a key role in the creation of relational rents because it influences transaction costs, as well as the willingness of alliance partners to engage in value-creation initiatives. As one of important governance mechanisms in global value chain, in this section, supplier s specificity investments are defined firstly, then how supplier s specificity investments promote relationship learning and competence building will be explored. The Definition of Supplier s Specificity Investments The extent to which one partner s assets are specialized to the other is viewed as key in determining exchange cost. The distinguishing feature of transaction specific assets is that their value would be largely lost if the focal relationship were terminated (Williamson, 1985). Specific asset investments may take a variety of forms. Some examples of idiosyncratic investments in buyer-supplier relationships are training or dedicating personnel to servicing a specific customer s products, adopting a common order processing system, building specialized facilities to handle a specific customer s product line. In this study, we focus on two types of asset specificity that are particularly relevant in the OEM-supplier context: human, and physical specificity. Following the definition of Heide & John (1992), human asset specificity addresses areas such as supplier s technical knowledge specialized to a particular customer s product, or the time and effort that goes into learning about a customer s specific requirements. Physical asset specificity refers to items such as specialized production equipment, computer technology and related interorganizational systems that link customer and supplier production and scheduling activities. 9

10 The Relationship between Supplier s Specificity Investments and Relationship Learning Since specificity investments have value only within the relationship, such transaction-specific investments create a need to safeguard against opportunism. Especially, for Taiwanese exporting manufacturers, they are often embedded in such a vertical interorganizational relationships characterized by considerable power asymmetries, in which supply firms are vulnerable to the exercise of power by more powerful firms. From the perspective of the supplier, how to safeguard relationship specificity investments is essential. Heide & John (1990) suggest developing longer-lasting relationships. Collaboration in the form of joint learning activities thus functions as a safeguard against opportunism and offers a direct check of the other party (Selnes & Sallis, 2003; Subramani & Venkatraman, 2003). Similar tone, drawing upon their empirical results, Celly et al. (1999) find that buyers reciprocate by sharing information with suppliers that make relationship-specific investments. This result provides a support to their arguments concerning overseas suppliers may proactively manage uncertainty by making customized investments to serve their buyers. Thus, it is argued that through relationship learning, the supplier would have the opportunities to turn the asymmetric interorganizational relationship into a mutual reliance relation, thus, to reduce the transaction costs caused by the hostages. As a consequence, it is expected that relationship learning is an important governance strategy adopted by suppliers to safeguard their specificity investments. Hypotheses 2: In a buyer-supplier relationship, supplier s specific asset investments have a positive effect on supplier s relationship learning. The Relationship between Supplier s Specificity Investments and Competence Building In general, it is proposed that no or only a weak connection among actors hampers system performance in terms of innovation as interaction and learning do not sufficiently take 10

11 place. When there is substantial connectivity among actors, fruitful opportunities for learning and innovation would arise. Since the supplier s investment in relation-specific assets signals its assurance of commitment (Celly et al., 1999), the buyer would in turn be more willing to share knowledge with the investing firm. Thus supplier s specificity investments could provide a great opportunity for the supplier to upgrade resource configuration. Similarly, according to Petroni (2000), as a compensation for the greater involvement of subcontractors in the entire design/manufacturing process, customers may often be induced to stimulate their suppliers for further competence building. It is often to find that suppliers are required to take charge of either the development of new products or improving their manufacturing process. In this way supplier s specificity investments may be accompanied by the supporting drawing from customer s consultancy and training services in order to develop the required capabilities. Drawing upon an empirical survey of Taiwanese manufacturers in information industries, Wang et al. (2001) verifies that process specificity devoted by suppliers is positively associated with a supplier s competence building. Thus, it is expected that the higher level of supplier s specificity investments enhance supplier competence building. Hypotheses 3: In a buyer-supplier relationship, supplier s specific asset investments have a positive effect on supplier competence building. Relationship Factor: Norms and Dependence Structure Transaction cost theory has achieved a prominent role in the analysis of governance mechanisms for exchange relationships. However, the assumption of opportunism that underpins this perspective has been challenged. Specifically, in the marketing literature, Heide & John (1992) argue that norms play a central role in structuring relationships between firms and have produced empirical evidence to support this contention. In addition, Stern & El-Ansary (1992) argue that dependence structure is the major means available to achieve 11

12 coordination and cooperation among channel members. Thus, norms and dependence structure are seen as critical moderating factors influencing the relationship between supplier s specific asset investments and relationship learning. The Moderating Effect of Norms on The Relationship between Supplier s Specificity Investments and Relationship Leaning Pfeffer & Salancik (1978) mention that norms are commonly of or widely shared sets of behavioral expectations. In other words, a norm is a belief shared to some extent by members of a social unit as to what conduct ought to be in particular situations or circumstances. Similarly, Dwyer et al. (1987) in their discussion of the development of expectations between trade parties focused on the concept of trust as one major issue deserving priority, since relational exchange dominates over discrete transactions. According to Kaufman & Stern (1988), three factors play a most important role in developing attitudinal ties between partners, namely solidarity, role integrity, and mutuality. Departing from this multi-dimension definition of norms, Sako (1992) have proposed a model to explain customer-supplier relations, including the arm s-length contractual relations (ACR) and obligational contractual relations (OCR). This model is constructed around two ideal types, situated at either end of a continuum (ACR-OCR), which captures complex variations in customer-supplier relationship and on to which an organization can be placed. At one extreme, organizations rely on arm s-length contractual relation (ACR) if they want to retain control over their destiny. This type of company would disclose the minimum information about costs and future plans to existing and potential buyers and suppliers. In contrast, OCR depends on high trust cooperativeness with a commitment to long-term trade. Similarly, with regard to the automobile industry, Helper (1991) states that in an exit relationship, a customer that has a problem with a supplier finds a new supplier. In a voice relationship, the customer works with the original supplier to resolve the problem. The 12

13 voice strategy requires extensive communication systems, the exchange of proprietary information, and the sharing of production secrets for the purpose of improving each other s efficiency. Thus, it often be accompanied by high levels of loyalty and commitment. Since it is hard to find an uniform definition of norms, further, with the above multi-dimension definition of norms is more difficult to explore its moderating effect on the relationship between supplier s specificity investments and relationship learning. In this study it is proposed that when suppliers involving in an exit relationship, in which a customer that has a problem with a supplier finds a new supplier, the level of norms should be lower than of a voice relationship, in which the customer works with the original supplier to resolve the problem (Helper, 1991). Due to bounded rationality and uncertainty, the TCA framework admits that interfirm exchanges fraught with unforeseen contingencies cannot be governed with complete contracts. The parties can resort to incomplete contracts that enable them to adapt better changing circumstances by aligning supportive governance arrangement (Williamson, 1991). Drawing on relationship perspective, previous research has seen norms as one such supportive mechanism. It is found that in an embedded network, the exchange partners often use relational norms and expectations of continuity to regulate opportunism (Lusch & Brown, 1996). Further, it is found that in high relational norm relationships exchange parties are more committed (Gundlach et al, 1995) and demonstrate a long-term orientation (Ganesan, 1994), because they are confident that their actions will not be opportunistically abused (Heide & John, 1992). By providing a generalized safeguard against partner opportunism, relational norms make parties more willing to engage in actions that result in relationship continuity. Thus, it is expected that the greater norms between the buyer and supplier, interactions will be more informal, and knowledge creation and transfer will be at the tacit level. In addition, norms will also facilitate the sharing of information that is proprietary and yet critical to the 13

14 generation of innovation (Roy, et al., 2004). It is proposed that to the extent of norms between two firms can moderate both the relationship between specificity investments with relationship learning, and the relationship between specificity investments and competence building respectively by two ways. Firstly, according to Uzzi (1997), trust is developed over time and there must be a certain level of trust before any deeper learning can take place. As relationship with voice type of norms is viewed as a facilitator of trust building, relationship with exit type of norms is seen as an inhibitor of trust building. It is expected that the former relationship form will be more easily to reap learning benefits by allowing customers and suppliers to communicate and interpret tacit information in a relatively holistic way than the latter relationship form. Secondly, the relationship with voice norms which refers to customers is more inclined to devote to joint problem-solving arrangements than relationship with exit norms. Through these arrangements, which typically consist of routines of negotiation and mutual adjustment, it is claimed that the suppliers could promote relationship learning and build their own competence by working though problems. Accordingly, it is proposed that, Hypothesis 4: In a buyer-supplier relationship, the positive relationship between supplier s specificity investments and relationship learning will be enhanced with increasing levels of norms. The Moderating Effect of Dependence Structure on the Relationship between Supplier s Specificity Investments and Relationship Learning According to the social exchange and resource dependence ideas of Pfeffer and Salancik (1978), Provan et al., (1980), and others, dependence is critical for understanding interorganizational relationships. Gundlach and Cadotte (1994) define a dependence structure as consisting of two dimensions: the degree of interdependence between parties and the relative balance of power within the relationship. The term, asymmetric dependence, is used 14

15 to indicate that the dependencies of the two parties are such that one party holds a power advantage over the other. In contrast, equilibrium can exist at any level of interdependence, but the relative balance of power must be equal for an equilibrium state to exist. Following this concept, the variables of central interest in this study are the two dimensions of the transacting parties dependence structure: interdependence and power asymmetry. The Moderating Effect of Customer s Power Advantage Dahl (1957) defined power as the ability of one individual or group to get another unit to do something. El-Ansary & Stern (1972) applied this concept to distribution channels by defining power as the ability of a channel member to control the decision variables in the marketing strategy of another member at a different level in the channel of distribution. In this study, customer s power advantage refers to the degree of power asymmetry as represented by the extent to which the supplier s dependence on its OEM customer exceeds the customer s dependence on this supplier. This bargaining power stems from the suppliers and customers relative concentration in their respective industries, the distribution of market shares among suppliers, and the switching costs, that is, the costs that the customers face to change their suppliers. Both transaction cost analysis and resource-dependence theory suggest that uneven rewards from exchange relationships will result if either party has an advantage over the other party. Drawing on resource-dependence theorist have proposed that dependence of actor A on actor B will lead to poor outcomes for A if A s dependence exceeds actor B s dependence on actor A. The reason is that the advantaged firm is able to use its power to achieve its own objectives at the expense of the weaker party as has been discovered in bargaining situations (Pfeffer & Salancik, 1978) In the context of buyer-supplier relationship, Hakansson (1982) observes that powerful OEMs are able to leverage their position to demand adjustments to agreements without offering compensation. Kalwani & Narayandas (1995) study of suppliers in the 15

16 industries where they are usually the weaker party reports that firms in long-term relationships face lower gross margins over time. The reason is that a customer with a power advantage can demand price concessions and shorter production runs with success because alternative suppliers are available and the disadvantaged supplier has few options other than adjusting. Such demands can severely affect the performance of component suppliers since a single OEM s business often accounts for a sizable share of a supplier s revenue. Thus, as customers with power advantages are expected to be able to make costly demands on their weaker suppliers and receive compliance to these demands. Under this circumstance, it is hard to expect that a true partnership could be built through unilaterally deploying supplier s specificity investments. It is argued that when the ability to use power and influence is balanced (low relative influence) conflict is discouraged because both parties know the other can inflict meaningful damage to their own interests. Such balance encourages cooperation by focusing the attention of the parties on their joint interests. Each party has a vested interest in sharing information and being flexible, which when reciprocated, supports further cooperation and strong relational behavior (Dwyer et al., 1987) In contrast, power imbalance in an exchange relationship will lead the more powerful party to use coercion to increase their share of relationship outcomes at the other s expense. In unbalanced relationships, the motivation to maximize individual and not joint outcomes creates instability in relationships (Anderson & Weitz, 1989). Further, especially under the situation of this study, suppliers have made asymmetry in input commitment, in which the customer with lower stakes will tend to care less and interactions will be less effective in generating relationship learning (Roy, et al., 2004). Accordingly, it is hypothesized that: Hypothesis 5: In a buyer-supplier relationship, the positive relationship between supplier s specificity investments and relationship learning will be hindered with increasing levels of 16

17 customer s power advantage. The Moderating Effect of Interdependence Interdependence refers to the level of mutual supplier and customer dependence in the relationship. As evident by this definition, the dependence structure of an exchange relationship is derived fundamentally from each firm s level of dependence on the relationship. For suppliers and customers, a firm s own dependence is determined by the availability of substitutes and the firm s need for the resources derived from exchanges with the other company. In contrast to asymmetric dependence, interdependence is expected to have positive consequences for exchange relationships. Firstly, according to bilateral deterrence theory (Bacharach and Lawler, 1981) and social exchange theory s norm of reciprocation contend that, all else being equal, greater interdependence leads to lower conflict, greater cooperation, and greater trust as retaliation poses an ever-greater threat for both partners (Kumar et al., 1995). It is expected that interdependence serves to raise the costs of acting unilaterally and using coercive influence and provides an effective deterrent to self-serving behavior (Anderson and Weitz, 1992), since dyadic relationships are often embedded in a broader network of supplier-buyer relations, a view strongly expressed by Granovetter (1985) who mentions that such social embeddedness provides a powerful incentive to limit opportunistic acts. In addition, as argued by Provan (1993) and in consistence with Axelrod s (1984) ideas on cooperation, when outcome interdependence is high, interdependent firms will not necessarily seek short-term goals, but rather look for long-term strategic advantage. The reason is that interdependence discourages OEMs from using their power to demand exchange concessions because such requests will meet resistance and may produce conflict, supply interruptions and product quality lapses. Further, interdependence also provides a mutual incentive for suppliers and OEMs to cooperate. Such cooperation is essential since 17

18 many aspects of the final product s performance do not fall exclusively within a single member s domain but rather involve complex systems that draw upon both partners unique competencies. Many of the recent trends in original equipment manufacturing are motivated by the potential to increase final product performance through such systematic cooperation (e.g., Just-in-Time, supplier involvement in product development, etc.). Under this close partnership, the customer has a strong incentive to maintain the relationship and avoid disruptive disagreements over pricing and other sensitive issues. In other words, goal incongruence does not exist in this close partnership. Hence, when outcome interdependence is high, as in well-established networks, member firms can be expected to make some short-term sacrifices that do not necessarily serve their immediate interests in return for expected long-term strategic advantage. Thus, it is expected that the greater interdependence between the buyer and supplier, interactions will be more effective to the generation of relationship learning. Accordingly, it is proposed that, Hypothesis 6: In a buyer-supplier relationship, the positive relationship between the supplier s specificity investments and relationship learning will be enhanced with increasing levels of the interdependence. RESEARCH DESIGN AND METHODOLOGY The Conceptual Model In this research, we are anxious to investigate the interrelationships between supplier s specific asset investments, relationship learning and supplier competence building, as well as the moderating effects of norms, customer s power advantage, and interdependence on the relationship between supplier s specificity investments and relationship learning. In addition, other contextual factors, in terms of environment dynamics, learning intend, and internal learning are also included as control variables. For the purpose of this study, we developed the following conceptual model, as shown in Figure

19 CONTROL VARIABLES ENVIRONMENT Dynamism INTERNAL LEARNING LEARNING INTENT SUPPLIER SPECIFICITY INVESTMENTS Interdependence H5 H6 H2 H4 RELATIONSHIP LEARNING * INFORMATION SHARING * JOINT SENSE MAKING * INTEGRATING INTO FIRM S MEMORY H3 H1 SUPPLIER COMPETENC BUILDING *TECHNOLOGY COMPETENCE *SCM COMPETENCE *MARKETING COMPETENCE *COORDINATION COMPETENCE CUSTOMER S POWER ADVANTAGE NORMS Figure 3.1 The Conceptual Model of this Research Construct Measurement For the purposes of this study, the following major constructs are operationalized in this study: (1) supplier s specificity investments, (2) relationship learning, (3) competence building, (4) relationship factors, and (5) control variables. To measure the supplier s specificity investments, we adopted a total of five questionnaire items, based upon the studies of Wang, et al. (2001). Regarding the relationship learning, it is composed of three distinct elements: information sharing (7 items), joint sense making (4 items), and integrating knowledge into firm s memory (6 items). Not a single element can it interpret the whole picture of an organization s relationship learning. Thus, we adopted most of the questionnaire items developed by Selnes & Sallis (2003). When concerning the supplier s competence building, namely technology, SCM, marketing, and coordination competence, we adopted 23 items from Danneels (2002), and Ritter & Gemunden (2004). Regarding the relationship factors, dependence structure is composed of the supplier s dependence on the buyer, the buyer s dependence on its supplier, and relative dependence. Then, the level of interdependence and customer s power advantage can be computed drawing upon the study of LaBahn (1999). In addition, norms are measured by the strategy which the 19

20 customer adopts when the supplier meets problems, in terms of exit or voice strategy as described by Helper (1991) and Humphrey & Ashforth (2000). Finally, there are three control variables included in our conceptual model, which are environment dynamism (3 items), internal learning (4 items), and learning intent (2 items) respectively. We adopted most of the questionnaire items of control variables developed from previous literature (Bensaou & Anderson, 1999; Schroeder et al., 2002; Johnson & Sohi, 2003). For the above constructs except for measurement of norms, respondents are asked to indicate whether they agree with each of the statements on a seven-point rating scale, from 1 represents strongly disagree to 7 represents strongly agree. Regarding the measurement of norms, respondents are required to indicate the recognized interaction experience with their buyers. Semantic Differential scales were developed to measure the opinion of the respondents. The questionnaire is pre-tested through a pilot study. Questionnaire items are revised based on the results of the pilot study and interviews before being put into the final form. Sampling Plan A sampling plan was developed to ensure that certain types of firms were included in this study. We restrict our interest to relationships between Taiwan exporting oriented manufacturers and their major foreign customers. Following previous research (Kalwani & Narayandas, 1995), the suppliers coming from computer and allied equipment manufacturers, machine tool equipment manufacturers, electronics and other electrical equipment manufacturers, automotive product manufacturers, and manufacturers of scientific instruments are the focus of this study. The reason for focusing on these industries is that customer firms in these industries have faced intense competitive pressures at the international level. There is documented evidence that to improve their competitiveness in the ever changing global marketplace, on the one hand, manufacturing firms in these industries 20

21 have been slashing their vendor lists and getting into long-term relationships with a few suppliers. On the other hand, supplying firms are requested to deploy high level of specificity investments to retain the relationship with focal firms (Kerrin, 2002; Celly et al., 1999). Thus, it is expected that these industries are quite suitable for our focus of this study. The sampling frame is mainly obtained from Taiwan Exporters (2004), published by Taiwan External Trade Development Council. Totally, 900 questionnaires were sent to the head of marketing department of sample firms who were supposed to well understand the constructs of this study. RESEARCH ANALYSIS AND RESULTS Data Collection The data were gathered near two months period beginning in middle August of 2004, and ending in end September of 2004, including one pilot test and one final survey. For the final survey, a total of 900 survey questionnaires were mailed to the sample firms. Out of 900 sample firms, with follow-up telephone calls, 155 completed and returned the answers. A total of 148 questionnaires were usable, producing a response rate about percent. Since the response rate is lower than expected, to test for non-response bias, we split the data using the first half respondents as one group and the second half respondents as second group, then we compared the total sales volume, number of employees, type of industry, and the important variables included in this study between those who responded early with those who responded late. The Chi square tests and the t tests were performed. The null hypothesis of this analysis is that an early respondent has the same characteristics as a late respondent (Armstrong & Ovcrton, 1977). The observed significant level p for all variables is much higher than This implies that in this research the extent of non-response bias is insignificant, and the results are generalizable to the sampling frame. 21

22 Factor Analysis and Reliability Tests To verify the dimensionality and reliability of constructs of this study, purification processes, including factor analysis, correlation analysis, and coefficient alpha analysis were conducted in this study. Factor analysis examined the basic structure of the data. Correlation analysis assessed the degree of multicollinearity among variables. Coefficient (Cronbach s) alpha measures the internal consistency of each identified dimension. Table 4.1 presents the results of factor analysis as well as reliability tests for measurements of supplier s specificity investments, relationship learning, competence building, norms, customer s power advantage, as well as the control variables included in this study, namely environment dynamism, internal learning, and learning intent. It is shown that all variables within a factor tend to have a high coefficient of item-to-total correlation. This suggests a high degree of internal consistency for each dimension. In addition, the high coefficient of Cronbach s on each factor further confirms the reliability of the measurement items. Table 4.1 Results of Factor Analysis and Reliability Tests Factors No. of Items Factor Loading Item-to-total Correlation Cronbach s α Specificity Investments Relationship Learning 1: Information Sharing Relationship Learning 2: Joint Sense Making Relationship Learning 3: Relationship Specific Memory Competence Building 1: Technical Competence Competence Building 2: SCM Competence Competence Building 3: Marketing Competence Competence Building 4: Coordination Competence Relationship Factor 1: Norms Relationship Factor 2: Customer s Power Advantage Relationship Factor 3: Interdependence Control Variable 1: Environment Dynamism Control Variable 2: Internal Learning Control Variable 3: Learning Intent

23 Interrelationships among Specificity Investments, Relationship Learning, and Competence Building In this section, structure equation model is employed to test the interrelationship of all the variables in the entire model. The proposed structural equation model is shown in Figure 4.1. RL1 RL2 RL3 RL4 Technology Competence UC5 UC7 AS 2 Information Sharing SCM Competence UC11 UC12 AS 3 AS 5 Specificity Investments Joint Sense Making RL8 RL9 RL10 Marketing Competence UC15 UC16 RL12 Integrating into Memory RL13 RL14 RL15 RL17 Coordination Competence UC20 UC23 Figure 4.1 Structural Equation Model of Specificity Investments, Relationship Learning, and Competence Building Table 4.2 estimates the fit indices of the model. It is shown that the chi-square value of with 155 degrees of freedom ( probability level=0.826 ) is acceptable at the 0.05 significance level. In addition, GFI is 0.928, AGFI is These fit indices indicate a good fit of this model. As the overall goodness of fit is promising, it is encouraged to further identify the magnitudes and significance of the path structural coefficients of the model. Specificity Investments have a significant impact on information sharing, joint sense making, as well as integrating knowledge into memory respectively ( 1 =0.247; 2 =0.455; 3 =0.552). In addition, specificity investments have a significant negative impact on technology competence, SCM competence, as well as marketing competence ( 4 =-0.258; 5 =-0.233; 6 =-0.193). Concerning the impacts of relationship learning on competence building, it is shown that, joint sense making has significant negative effects on marketing and coordination competence ( 14 =-0.507; 15 =-0.577). Further, integrating knowledge into memory has significant effects on all the dimensions of competence building, in terms of technology, SCM, marketing, and coordination ( 16 =1.027; 17 =0.743; 18 =1.173; 19 =1.103). 23

24 Table 4.2 The Results of Structure Equation Model of Specificity Investments, Relationship Learning, and Competence Building Relations Standardized Coefficients C. R. SI 2 invested in production equipment.866 * Specificity SI 3 committed a lot of time and specific resources.897 * Investments SI 5 adjusted ordering effectuation.726 * A RL 1 information on experiences.763 * A Information RL 2 information related to changes in needs.855 * Sharing RL 3 information related to changes in market.704 * RL 4 information related to changes in technology.792 * RL 8 solve operational problems.688 * A Joint Sense RL 9 analyze and discuss strategic issues.837 * Making RL 10 stimulates productive discussion.846 * RL 12 adjust our understanding of needs.686 * A Varables RL 13 adjust our understanding of technology.806 * Integrating RL 14 adjust our routines in order-delivery.681 * into memory RL 15 update the formal contracts.688 * RL 17 update information about the relationship.693 * Technology UC 5 Enhancing production capabilities.888 * A Competence UC 7 Improving engineering skills.902 * SCM UC 11 managing overseas selling facilities.951 * A Competence UC 12 managing overseas warehouse.801 * Marketing UC 15 Understanding market changes.861 * A Competence UC 16 Understanding market channel.937 * Coordination UC 20 Contacting with customers.887 * A Paths Fit index Competence UC 23 Managing conflict with customers.721 * : Specificity Investments Information Sharing * : Specificity Investments Joint Sense Making * : Specificity Investments Integrating into Memory * : Specificity Investments Technology Competence * : Specificity Investments SCM Competence * : Specificity Investments Marketing Competence : Specificity Investments Coordination Competence : Information Sharing Technology Competence : Information Sharing SCM Competence : Information Sharing Marketing Competence : Information Sharing Coordination Competence : Joint Sense Making Technology Competence : Joint Sense Making SCM Competence : Joint Sense Making Marketing Competence * : Joint Sense Making Coordination Competence * : Integrating into Memory Technology Competence * : Integrating into Memory SCM Competence * : Integrating into Memory Marketing Competence * : Integrating into Memory Coordination Competence * Chi-Square Degree of freedom (d. f.) 155 Probability Level GFI AGFI RMR Note: 1. *: C. R.>1.96; using a significance level of 0.05, critical ratios that exceed 1.96 would be called significant. 2. +: C. R.>1.64; using a significance level of 0.10, critical ratios that exceed 1.64 would be called significant. 3. a: the parameter compared by others is set as 1, therefore there is no C. R.. It is determined as significant. 4. the coefficients are standardized value. 24

25 As a summary, with an acceptable goodness of fit of the model, it seems to suggest that different dimensions of relationship learning have different impacts on competence building. The results indicate that if firms would like to enhance competence building, integrating into memory seems to be the most effective, while joint sense making even block marketing and coordination competence building. Further, the results also indicate that, when ignoring the indirect effects (mediated by relationship learning), the higher level of specificity investments company with lower level of technology, SCM, as well as marketing competence building. It is suggested that only firms with higher relationship learning, especially by way of integrating into memory, specificity investments could achieve higher competence building based on this relationship. Others, without relationship learning, specificity investments maybe constrain the effectiveness of suppliers competence building based on this relationship. Moderating Effects of Norms, and Dependence Structure on the Relationships between Specificity Investments and Relationship Learning The hypotheses were tested by estimating the following equations using ordinary least squares regression: IS = β 11 + β 12 * ED + β 13 * IL + β 14 * LI + β 15 * SI + β 16 * NM + β 17 * CPA + β 18 * ID + β 19 * SI * NM + β 110 * SI * CPA + β 111 * SI * ID (1) JSM = β 21 + β 22 * ED + β 23 * IL + β 24 * LI + β 25 * SI + β 26 * NM + β 27 * CPA + β 28 * ID + β 29 * SI * NM + β 210 * SI * CPA + β 211 * SI * ID (2) RSM = β 31 + β 32 * ED + β 33 * IL + β 34 * LI + β 35 * SI + β 36 * NM + β 37 * CPA + β 38 * ID + β 39 * SI * NM + β 310 * SI * CPA + β 311 * SI * ID (3) Note: ED= Environment dynamics; IL=Internal learning; LI=Learing intent; IS=Information sharing; JSM=Joint sense making; RSM=Relationship specific memory; SI=Specificity investments; NM=Norms; CPA=Customer s power advantage; ID=Interdepedence. Among these equations, information sharing, joint sense making, and integrating knowledge into memory are the dependent variables in each equation respectively. Environment dynamics, Internal learning, and Learning intent are the control variables. In addition, Specificity investment, Norms, Customer s power advantage, and Interdependence 25