This study considers the potential role of organizational learning as a strategic resource in supply management. A model of learning in supply management processes is examined using samples representing three nodes of one Fortune 500 organization’s supply chains (internal SBU customers, n=141; corporate buyers, n=115, and external suppliers, n=58). Organizational learning is viewed as a composite construct arising from four tangible indicators: team-, systems-, learning-, and memory-orientations (each of those orientations is measured with four to five items). The results indicate that learning has a positive effect on a set of learning consequences, supply management consequences, management consequences, and performance consequences.
Understanding the determinants of success in the supply management process is a key goal of the operations management field (cf. Spekman et al., 1994). Given this goal, it is surprising that a theory aimed at explaining supply management success has not yet made significant inroads in this field. In this study, we argue that the resource-based view (RBV) of the firm offers a promising theoretical foundation to help explain supply management success. The RBV posits that organizations can improve performance through amassing and utilizing “strategic” assets and capabilities (Chi, 1994 and Wernerfelt, 1984). Strategic resources are those that are valuable, rare, and difficult to imitate (Barney, 1991). Growing bodies of work in both strategic management and marketing argue that firms possessing such resources can develop competitive advantages over rivals lacking such resources, and can leverage these advantages to gain sustained superior performance (e.g., Chaterrjee and Wernerfelt, 1991 and Hunt and Morgan, 1995). Although operations management scholars recognize the general importance of resources to the supply management function (e.g., Handfield, 1993), the value of strategic resources remains unclear.
This paper examines the role of organizational learning as a strategic resource in supply management. We broadly define learning as the values and beliefs associated with the development of new knowledge that has the potential to influence behavior. Our definition follows the insights of Huber (1991, p. 89), who notes: “an entity learns if, through its processing of information, the range of its potential behaviors is changed.” Given supply management processes’ complex and dynamic nature (Choi et al., 2001), they represent an area in which learning can create competitive advantages (Hult et al., 2000); learning in this context can be viewed as a form of supply management orientation (cf. Shin et al., 2000). Conversely, a corporation’s ability to provide value to external customers can be severely impeded by a dysfunctional supply management system (Bowersox et al., 1999 and Narasimhan and Jayaram, 1998).
Specifically, we depict learning as an intangible resource that is deeply embedded in the fabric of the supply management system. Consistent with this intangibility, learning is conceptualized as a composite construct that arises from four more tangible “orientations”—team-, systems-, learning-, and memory-orientations (e.g., Hult, 1998). Additionally, as a strategic resource, learning is proposed to influence several measures of success in the supply management process (cf. Barney, 1986 and Dyer and Singh, 1998). We examine these relationships using data from three nodes (internal customers of the firm’s strategic business units (SBUs), corporate buyers, and external suppliers) involved in supply management processes of a Fortune 500 transportation firm. The remainder of this paper presents the theoretical framework and hypotheses, the three samples, the analyses and results, and discussion of the implications of the study.
The results are presented in Table 5 and Table 6. Table 5 summarizes the testing of the aggregate effects of organizational learning on select learning-, supply management-, management-, and performance-consequences. Table 6 summarizes the testing of the disaggregate effects.In the aggregate analyses, 30 different models were tested using learning as predictor variable on the four learning consequences (information acquisition, knowledge distribution, information interpretation, and organizational memory), two supply management consequences (relationship commitment and customer orientation), two management consequences (innovativeness and entrepreneurship), and two performance consequences (cycle time and overall performance). Except for the model of learning → entrepreneurship in the supplier sample, all other modeled relationships were supported. The standardized beta values ranged from 0.28 to 0.82 (P<0.05) with R2 values between 9 and 67%.
In the disaggregate analyses, another 30 models were tested using team orientation, systems orientation, learning orientation, and memory orientation as predictor variables on each of the same criterion variables used in models 1–30. Given that the collective measure of learning influenced the consequences in all but one model, the disaggregate analyses provide an additional level of analysis that allows for the examination of the intricacies of the learning relationships. In the disaggregate analysis, we found that memory and systems orientations appear to be the primary drivers of the effect of learning on the learning-specific consequences. For the supply management consequences, all four learning orientations appear to be important to various degrees. Learning and memory orientations appear the most significant in terms of affecting management consequences, while all four orientations function to affect the performance consequences in various ways.
