Over the past decade conceptual and empirical research in operations management has embraced the idea that collaborative supplier–buyer relationships are a source of competitive advantage for manufacturing firms. Anecdotal evidence from the Japanese and U.S. automotive industry and emerging research suggests that inter-organizational identification of suppliers with their buyers, termed supplier-to-buyer identification, is an unexplored factor of relational advantage. This study presents a model and empirical test that supplier-to-buyer identification fosters superior operational performance by enhancing trust, supplier relation-specific investments, and information exchange. Through a survey of 346 automotive supplier–buyer relationships, the findings show that supplier-to-buyer identification directly impacts supplier relationship-specific investments and information exchange, although most of the latter effect is mediated by trust. The findings also indicate that supplier relation-specific investments and information exchange play different but complementary roles in influencing operational performance. The results suggest new directions for supplier–buyer relationship research in operations management and important managerial implications.
Over the past two decades conceptual and empirical research in operations management has embraced the idea that collaborative supplier–buyer relationships can be a source of competitive advantage for manufacturing firms (Carr and Pearson, 1999, Ellram, 1991 and Krause, 1999). Among the theories that have influenced the vast literature pertaining to this important aspect of operations management, transaction cost economics and the resource-based view of the firm are of particular interest. Transaction cost economics (Williamson, 1985) has inspired researchers to investigate the role of relation-specific assets (Bensaou and Anderson, 1999, Dyer, 1996 and Grover and Malhotra, 2003), trust (Johnston et al., 2004, Zaheer et al., 1998 and Corsten and Kumar, 2005), and commitment (Ross et al., 1997) in supplier–buyer relationships. The resource-based view of the firm (Barney, 1991, Rungtusanatham et al., 2003 and Wernerfelt, 1984) and, more recently, the knowledge-based view of the firm (Grant, 1996, Hult et al., 2003 and Kogut and Zander, 1996) have sparked interest in the role of tangible and intangible resources, or more specifically, the role of information exchange and knowledge sharing in supplier–buyer relationships (Dyer and Nobeoka, 2000).
We used structural equation modeling with maximum likelihood (ML) estimation to test our research hypotheses employing AMOS 4.0. Structural equation modeling has the advantage over standard ordinary least square (OLS) regression analysis of explicitly considering the measurement error in the indicators and simultaneously estimating a system of structural equations. We used the full sample of 346 suppliers for the estimation. All variables conformed to the multivariate normality assumptions of ML estimations. Due to the high correlation (r = .442) and their theoretical complementarity as components of the common construct of disturbances, the volatility and failure factors were allowed to correlate in the SEM.