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The Impacts of Supplier's Specificity Investments on Relationship Learning And .... tion, human asset specificity addresses areas such as a supplier's specialized ...
The Impacts of Supplier’s Specificity Investments on Relationship Learning And Competence Upgrading Wann-Yih Wu Department of Business Administration, National Cheng Kung University, Taiwan Email: [email protected] Teresa L. Ju Department of Information Management, Shu-Te University, Taiwan Email: [email protected] Ya-Jung Wu Department of Finance, Kao Yuan Institute of Technology, Taiwan Email: [email protected]

Abstract: This paper develops a research model to integrate suppliers’ specificity investments, relationship learning, and competence upgrading, and further tests the model using collected data from 148 exporting suppliers in Taiwan manufacturing industries. The study contributes to the literature by providing evidence that (1) a supplier’s specificity investments can promote relationship-learning benefits in terms of information sharing, and joint sense making, as well as integrate these into a firm’s memory; (2) a high level of relationship learning can bring potential benefits of competence upgrading in terms of exploration as well as exploitation; (3) benefits of competence upgrading, namely exploration as well as exploitation drawing on a supplier’s specificity investments are mediated by the supplier’s relationship learning.

RESEARCH BACKGROUND AND RESEARCH MOTIVATIONS Over the past two decades, we have witnessed a surge in the formation of strategic alliances that foster cooperation among suppliers and customers. Indeed, it can be observed that the most important recent changes in industrial buying behavior are increased cooperation between suppliers and customers (Sporleder and Moss, 2002; Peterson, 2002; Hyland et al., 2003; Dyer and Nobeoka, 2000). Studies of buyer-supplier relationships have generally focused on examining why manufacturers enter these close relationships with their suppliers (e.g., Helper, 1991; Lyons et al., 1990; Artz, 1999; Dyer, 1996; Dyer and Singh, 1998); however, except for research by Kalwani and Narayandas (1995), Subramani (2004), Wang et al. (2001), and Donada (2002), little attention has been paid to the supplier’s benefits derived from their specificity investments and the mechanisms that enable suppliers to realize such benefits. Therefore, in this study, our major research question is ‘can a supplier’s specificity investments bring relationship learning, and competence upgrading?’ This study builds on two aspects of previous research. First, a transaction value perspective (Zajac and Olsen, 1993) is taken in examining the strategic outcomes of suppliers’ specificity investments. Traditionally, transaction cost analysis is employed to detect under which exchange conditions specificity investments would cause intolerable transaction costs (e.g., Williamson, 1985). However, in a globally competitive environment, many manufacturing firms are forced to play a more active role than ever before by embedding themselves in a global supply chain. The question confronting suppliers is often not whether they should deploying specificity investments but how they can take advantage of these specificity investments (Subramani, 2004). Thus, unlike research that uses a transaction cost perspective, suppliers’ specificity investments are viewed as an enabler of strategic outcomes in terms of relationship learning and suppliers’ competence upgrading. Second, most global value chain research suggests that if suppliers coming from developing countries could seize the opportunities to become involved in a global value chain, it brings about a great opportunity for these suppliers to upgrade (Humphrey and Schmitz, 2002; Schmitz and Knorringa, 2000; Gereffi, 1999). However, opinions on whether suppliers’ competence upgrading is smooth or not differ in the literature. Gereffi (1999) examines how East Asian newly industrializing economies (NIEs) have successfully enhanced their capabilities and reached OBM (own brand manufacturer) status through integration into global value chains by becoming an OEM (original equipment manufacturer). Some scholars, however, have questioned this optimistic view that OEM leads progressively to ODM (own design manufacturer) and OBM; local producers face obstacles in upgrading because such upgrading encroaches on their buyers’ core competence. In other words, from the viewpoint of suppliers, it seems that building a close relationship with customers may promote exploitation benefits, but also inhibit exploration benefits (Schmitz and Knorringa, 2000; Humphrey and Schmitz, 2002). Thus, in this study we would like to investigate whether or not a supplier’s specificity investments could bring about more interactions between the supplier and customer, and what kind of competence upgrading, in terms of exploration and exploitation, would be raised.

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LITERATURE REVIEW Previous studies have found that suppliers’ specificity investments could raise operational benefits such as more stable sales volume, more repeat business, a decrease in sales expenses, and vastly improved planning and forecasting. However, strategic benefits such as relationship learning and competence upgrading are hardly referred to. It is argued that these strategic benefits are essential both to suppliers attenuating the transaction costs due to specificity investments, and to customers exploiting the outsource benefits which exist in a supplier’s innovation and capabilities.

Competence Upgrading Drawing upon organizational learning theories, two capabilities have received broad attention and provide the theoretical foundation for this article. The first capability is exploration -- the pursuit of new possibilities. It is the class of activities whose goal is to learn about the environment and discover novel ways of creating value or solving old problems. In contrast, exploitation capability is the extension or elaboration of old certainties. It is the class of actions whose goal is to improve operational efficiencies. Consequently, exploration and exploitation describe different capabilities for organizational knowledge production (Ozsomer and Gencturk, 2003). They affect how much and what kind of knowledge is produced. Exploration generates new, unsettled knowledge with potentially high but uncertain returns. Exploitation generates incremental knowledge with moderate but certain, immediate returns. Consistent with this view, exploitation capability and exploration capability are conceptualized as two complementary patterns of appropriation of supply chain technologies which suppliers learn from their interactions with partners.

Relationship Learning According to Selnes and 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. Following Selnes and 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.

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). Specificity investments may take a variety of forms. Some examples of idiosyncratic investments in buyer-supplier relationships are training personnel or dedicating them to servicing a specific manufacturer’s products, adopting a common order processing system, or building specialized facilities to handle a specific manufacturer’s product line. Following Heide and John’s (1992) definition, human asset specificity addresses areas such as a supplier’s specialized technical knowledge of 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.

The Relationship between Relationship Learning and Competence Upgrading Innovation generation has increasingly been recognized as an outcome of interaction between a firm and various outside entities. According to this view, supplier involvement and alliances are routes to innovation generation. Despite this recognition, there is a dearth of research, conceptual and empirical, focusing on innovation generation in buyer-seller relationships in the supply chain. In an attempt to fill this void, this study will focus on how relationship-learning processes could be employed to build competence upgrading in terms of exploration and exploitation. Drawing upon the concept of socio-cognitive conflict as a vehicle for organizational learning, the needs for cognitive diversity, as well as for appropriate social relations are both assumed to be a necessary condition for learning (Bogenrieder, 2002). It is suggested that well structured relationship learning could both facilitate development of the supplier’s cognitive diversity to raise the potential for exploitation, as well as build the needed social relations to promote the potential for exploration. On the one hand, in supply chain contexts, relationship learning involves more information sharing, joint sense making, and integrating knowledge into a firm’s memory; therefore, it may be that more knowledge exchange, routine and culture assimilation between collaborative partners would occur 662

more easily. In this learning process, suppliers may not only learn market demand trends, key specifications for newly defined products, but more importantly they may learn the buyer’s managerial orientation, working culture, and problem solving methods. In other words, relationship learning enables the suppliers to acquire more knowledge associated with buyers’ capabilities. Such knowledge can then be incorporated into the suppliers’ own corporate system and become “internalized” (Wang et al., 2001). Consequently, it is proposed that the greater the extent of a supplier’s relationship learning, the greater will be the potential for generating exploitation opportunities in supply chain relationships. On the other hand, more and more evidence shows that both buyers and sellers attempt to interact in a context of new knowledge domains in which they may be trying to find a venue to bring a radical idea to fruition. New knowledge domains may draw upon interactions between new employees, lead users, new customers, or new suppliers (Roy et al., 2004). Thus, it is proposed that increased relationship learning will facilitate the creation of new knowledge, which in turn results in the potential for exploration. Thus, we propose the following hypotheses: Hypothesis 1: The higher the extent of relationship learning, the better will be the upgrading of exploration competence for a supplier. Hypothesis 2: The higher the extent of relationship learning, the better will be the upgrading of exploitation competence for a supplier.

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 who are often embedded in vertical interorganizational relationships characterized by considerable power asymmetries in which supply firms are vulnerable to the exercise of power by more powerful buyer firms. From the perspective of the supplier, safeguarding relationship specificity investments is essential. Heide and John (1990) suggest developing long-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 and Sallis, 2003; Subramani and Venkatraman, 2003). Similarly, Celly et al. (1999) found that buyers reciprocate by sharing information with suppliers that make relationship-specific investments. These results support their arguments concerning overseas suppliers who may proactively manage uncertainty by making customized investments to serve their buyers. Thus, it is argued that through relationship learning, the supplier would have opportunities to turn the asymmetric interorganizational relationship into a mutually reliant relationship, thus reducing the transaction costs resulting from being hostage to the buyer. As a consequence, it is expected that relationship learning is an important governance strategy adopted by suppliers to safeguard their specificity investments. Thus, we propose the following hypothesis: Hypotheses 3: In a buyer-supplier relationship, a supplier’s specificity investments have a positive effect on the supplier’s relationship learning.

The Relationship between the Supplier’s Specificity Investments and Competence Upgrading Concerning the trend toward suppliers upgrading mentioned in the previous section, could a supplier’s specificity investments enhance its potential to pursue exploration as well as exploitation? According to Granovetter (1973), strong ties are characterized by durability, high frequency of interaction, reciprocity and possibly intimacy. From this high density and strength in relations strong “social cohesiveness” results, facilitating the build-up of social capital that resides in the presence of dense social ties (Coleman, 1988). It seems that dense ties among firms accommodate a small cognitive distance that enhances mutual understanding and facilitates the transfer of tacit knowledge. Thus, it is expected that a supplier’s specificity investments could facilitate the connections between buyers and sellers, which in turn enhance the potential to upgrade exploitation. However, all these benefits accrue to a dense network structure only as long as change occurs incrementally. When change becomes more radical, these benefits disappear and it may appear that there is also a danger in dense structure. For example, many studies have identified situations variously described as “lock-in” (Arthur, 1988), or “over-embeddedness” (Uzzi, 1997), or “inertia” (Nooteboom, 2001). In these situations, established firms become blind in that they ignore exposure to other practices (e.g. other markets or new technologies) outside their immediate geographic, cognitive and /or cultural environment. Thus, it is proposed that the more a supplier’s specificity investments are deployed on one specific customer, the more constraints there are on the potential for exploration by the supplier. Further, some scholars have questioned the optimistic view that OEM leads progressively to ODM and OBM. Research on the footwear industry suggests that in some supply chains, global buyers discourage, if not obstruct, design, marketing and branding by local producers because such upgrading encroaches on their core competence. (Schmitz and Knorringa, 2000). Similarly, Humphrey and Schmitz (2002) observed global value chains finding that local upgrading opportunities vary with the way the chains are governed. In the case of developing countries, chains are often characterized by a quasi-hierarchy: the global buyers set product parameters in order to determine product design, and process parameters to reduce the risks associated with non-compliance with standards. 663

Quasi-hierarchical governance promotes fast upgrading for local producers in the sphere of production, but these firms find it difficult to move into higher value activities. Accordingly, it is argued that supplier’s specificity investments would enhance exploitation competence upgrading, rather than facilitate exploration competence upgrading. Since idiosyncratic investments will deepen the level of a supplier’s dependence on a buyer, the more embedded they are, the more likely they are to be excluded from other buyers; hence, the less exploring opportunities there are. Therefore, we propose the following hypotheses: Hypotheses 4: In a buyer-supplier relationship, the supplier’s specificity investments have a negative effect on the supplier’s exploration competence upgrading. Hypotheses 5: In a buyer-supplier relationship, the supplier’s specificity investments have a positive effect on the supplier’s exploitation competence upgrading.

RESEARCH DESIGN AND RESEARCH ANALYSIS For the purposes of this study, the following major constructs are operationalized: (1) supplier’s specificity investments, (2) relationship learning, (3) competence upgrading. To measure the supplier’s specificity investments, we adopted a total of five questionnaire items, based on Wang, et al. (2001). Regarding relationship learning, it is composed of three distinct elements: information sharing (4 items), joint sense making (3 items), and integrating knowledge into a firm’s memory (5 items). We adopted most of the questionnaire items developed by Selnes and Sallis (2003). In addressing the supplier’s competence upgrading, namely exploitation competence as well as exploration competence, we adopted five items from He and Wong (2004). A sampling plan was developed to ensure that certain types of firms were included in this study. We restricted our interest to relationships between Taiwanese export oriented manufacturers and their major foreign customers. Following previous research (Kalwani and Narayandas, 1995), this study focused on manufacturers in the computer and peripheral equipment, machine tool equipment, electronics and other electrical equipment, automotive product, and scientific instruments sectors. It is proposed that the firms supplying these industries are required to deploy a high level of specificity investments to retain their relationships with buyer firms (Kerrin, 2002; Celly et al., 1999). Thus, it is expected that these industries are quite suitable as a focus of this study. The sampling frame is obtained from “Taiwan Exporters (2004),” published by the Taiwan External Trade Development Council. Totally, 900 questionnaires were sent to the heads of the marketing departments of the sample firms. It was expected that they would well understand the constructs of this study. The data were gathered using one pilot test and one final survey over one and a half month period from mid August, 2004 to the end of September, 2004. For the final survey, a total of 900 survey questionnaires were mailed to the sample firms. Follow-up telephone calls were made and 155 sample firms completed and returned the questionnaires. A total of 148 questionnaires were usable, producing a response of 16.44 percent. Since the response rate was lower than expected, to test for non-response bias, we divided the usable questionnaires into two equally sized groups according to the time of receipt; forming one early and one late response group. Then, we compared the total sales volume, number of employees, type of industry, and the key variables using Chi square and t tests with the null hypothesis that an early respondent has the same characteristics as a late respondent (Armstrong and Overton, 1977). The observed significance level p of the Chi square and t test for all variables was much higher than 0.05. This implies that in this research the extent of non-response bias is insignificant, and the results are generalizable to the sampling frame. Our respondents profile shows that more than 29.73% of sample firms are computer related, 37.16% are electronics related, 13.51% are automotive product related, and 19.59% are from the scientific instruments industry. More than 58% of the firms are comparatively large scale with more than 1500 employees. Only 22.1% of the firms have an annual R&D expenditure less than 3% of sales. The others (77.9%) are more concerned with their innovation capabilities. Finally, more than 58% of the respondents are upper level managers; therefore, it is proposed that these managers are highly experienced in interacting with customers, and are appropriate respondents to these questionnaires. To verify the dimensionality and reliability of constructs, purification processes, including factor analysis, correlation analysis, and coefficient alpha analysis were conducted. The results show 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 α on each factor further confirms the reliability of the measurement items. In addition, a structure equation model is employed to test the interrelationship of all the variables in the entire model. Five indices were used to test the fit of the model. The first was the chi-square test, which is essential for the nested model comparison. As shown in Table 1, the chi-square value of 103.8 with 121 degrees of freedom (probability level = 0.869 ) is acceptable at the 0.05 significance level. In addition, GFI is 0.938 and AGFI is 0.892. These fit indices indicated a good fit for this model and encouraged further identification of the magnitudes and significance of the path structural coefficients of the model. Specificity investments appear to have a significant impact on information sharing, joint sense making, and integrating knowledge into memory (γ 1 = 0.239; γ 2 = 0.471; γ 3 = 0.548). In addition, specificity investments have a significant negative impact on exploration, as well as a 664

non-significant impact on exploitation (γ 4 = -0.250; γ 5 = -0.054) . Concerning the impacts of relationship learning on competence upgrading, joint sense- making appears to have a significant direct effect on exploitation (γ 9 = 0.491). Further, integrating into memory has a significant direct effect on exploration (γ 10 = 0.552). With an acceptable goodness of fit for the model, these results seem to suggest that different dimensions of relationship learning have different impacts on competence upgrading. The results indicate that if firms want to enhance exploration, suppliers should seize the chance of learning from their customers, especially by way of integrating knowledge into memory. On the other hand, if firms want to achieve exploitation, joint sense making works better than other factors. Further, the results also indicate that, when ignoring the indirect effects (mediated by relationship learning), the higher level of specificity investments accompanies a lower level of exploration. In other words, although specificity investments may bring more integration potential to explore learning benefits, they may also block a firm’s exploration opportunities. It is suggested that only in firms with higher relationship learning, especially by way of integrating acquired knowledge into corporate memory, will specificity investments achieve higher exploration. Without relationship learning, specificity investments may constrain the future development of suppliers. Standardized Coefficients .865 * .900 * .738 * .737 *

Relations SI 1 Specificity Investments SI 2 SI 3 RL 1

C. R.

invested in production equipment 10.323 committed a lot of time and specific resources 10.611 adjusted ordering effectuation A information on successful and unsuccessful exA periences RL 2 information related to changes in end-user .868 * 9.375 Information needs, preferences, and behavior Sharing RL 3 information related to changes in market struc.710 * 8.090 ture RL 4 information related to changes in the technology .791 * 7.923 RL 5 solve operational problems .695 * A Joint Sense RL 6 analyze and discuss strategic issues .848 * 12.753 Making RL 7 stimulates productive discussion .833 * 5.209 Variables RL 8 adjust our common understanding of end-user .716 * A needs, preferences, and behavior RL 9 adjust our common understanding of trends in .816 * 10.562 Integrating technology into Memory RL 10 adjust our routines in order-delivery processes .724 * 7.889 RL 11 update the formal contracts .723 * 7.665 RL 12 update information about the relationship .707 * 7.762 LE 1 broadness to the new knowledge/technology .714 * A Exploration LE 2 generality to the new knowledge/technology .848 * 8.440 LE 3 wide-ranging to the new knowledge/technology .629 * 5.849 LE 4 complexity to the new knowledge/technology .830 * A Exploitation LE 5 depth to the new knowledge/technology .991 * 13.023 γ 1 : Specificity Investments->Information Sharing 0.239 * 2.601 γ 2 : Specificity Investments->Joint Sense making 0.471 * 4.545 γ 3 : Specificity Investments->Integrating into Memory 0.548 * 5.320 γ 4 : Specificity Investments->Exploration -0.250 * -2.023 γ 5 : Specificity Investments->Exploitation -0.054 -0.534 Paths γ 6 : Information Sharing->Exploration 0.018 0.121 γ 7 : Information Sharing->Exploitation -0.105 -0.839 γ 8 : Joint Sense making->Exploration 0.216 1.156 γ 9 : Joint Sense making->Exploitation 0.491 * 2.572 γ 10 : Integrating into Memory->Exploration 0.552 * 2.772 0.236 1.430 γ 11 : Integrating into Memory->Exploitation Chi-Square 103.800 Degree of freedom (d. f.) 121 Probability Level 0.869 Fit index GFI 0.938 AGFI 0.892 RMR 0.064 Note: 1. *: C. R.>1.96; using a significance level of 0.05, critical ratios that exceed 1.96 would be called significant. 2. a: the parameter compared by others is set as 1, therefore there is no C. R.. It is determined as significant. Table 1 The Results of Structure Equation Model of Specificity Investments, Relationship Learning, and Competence Upgrading 665

CONCLUSIONS The major objectives of this study have been to identify the strategic benefits of specificity investments in terms of relationship learning, and competence upgrading . Based on the results of this study, several conclusions can be drawn. The first conclusion is that there are significant relationships between specificity investments and relationship learning. Several factors may contribute to the above findings. First, as Madhok (2000) argues, the establishment of a value-creating contractual alliance not only lies in an efficient governance arrangement, which yields rents through lower transaction costs, but also in an effective governance, which could realize relation-specific rents through value-creating initiatives that are unique to the partnership. Thus, from the viewpoint of transaction value, it is expected that the firms who would like to exploit the strategic benefits of alliances will devote more effort to promoting relationship learning. Secondly, our results are consistent with extant research that suggests that one partner’s unilateral commitments to a relationship can increase the level of mutual dependence of both partners. According to Celly, et al. (1999), suppliers make relationship-specific investments despite the attendant risk and without guarantees of reciprocity from the buyer, but with the intention of conveying assurances of relationship commitment. In turn, buyers will share information on their requirements and possible changes with such suppliers, thereby facilitating learning and adaptation. The second conclusion is that there are significant relationships between relationship learning and a supplier’s competence upgrading. Responding to calls (e.g., Roy, et al., 2004) for more research to examine the factors in innovation generation in upstream supply chain relationships, our results verify that the supplier’s relationship learning in upstream manufacturing sections of the supply chain may enhance the potential for both exploration and exploitation. It is suggested that when a firm’s success is contingent on quick response to customer demands, relationship learning emphasizing joint sense making can enhance the potential for exploitation, while integrating tacit knowledge raised from customers into a firm’s memory can promote the potential for exploration. However, it is surprising that information sharing does not appear to be related to competence upgrading. A plausible interpretation may be that supplier-customer partnerships are customarily classified as efficiency alliances (Grant and Baden-Fuller, 2004) in which suppliers are sometimes more knowledge intensive than customers. If an exchange does not contain matching and complementary know-how and capabilities needed by the supplier, the supplier’s competence upgrading based on information sharing may be limited. The third conclusion, concerning the relationship between specificity investments and competence upgrading, is that the positive influence of specificity investments on exploitation is significant; mediated by relationship learning. In addition, it was also found that a higher level of specificity investments is significantly negatively associated with the potential for exploration upgrading. These results find support in two main areas of theory and research. First, relation exchange theory suggests a facilitating role for a supplier’s specificity investments. The relational view proposes that networks and partnerships can have a strong positive influence on the performance of firms through the development of joint resources with individual partners (Dyer, 1996; Dyer and Nobeoka, 2000; Donada, 2002). It is suggested that the ability to create such resources is linked to the way partnerships are structured. Whereas suppliers devote more specificity investments, they create an opportunity to cooperate more closely to improve their competence base. Thus, it is concluded that the strategic benefits of supplier competence exploitation upgrading could be exploited by supplier’s specificity investments is significant; through the relational rent which is generating from relationship learning, especially, focusing on how to integrating tacit knowledge into firm’s memory. Second, the restraining role of suppliers, i.e. specificity investments in what previous research called “lock-in” (Arthur, 1988), “overembeddedness” (Uzzi, 1997), or “inertia” (Nooteboom, 2001) should be considered. The results of this investigation suggest that although suppliers could raise exploration opportunities indirectly through more integration with customers, suppliers’ specificity investments have a direct significant negative effect on exploration. As a result, it may be better to commit resources to facilitating integration with customers, as well as raising the firm’s absorptive capability. Without these efforts, supplier’s specificity investments only bring more burdens. In summary, this research makes several contributions to our understanding of the relationships between a supplier’s specificity investments, relationship learning, and competence upgrading in business-to-business markets. The proposed specificity investments/relationship learning/competence upgrading framework provides a more comprehensive view of the relationships between these constructs than is available from the extant theory.

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