An empirical study of supply network: Combining social network analysis with econometric approaches
Kao, Ta-Wei Daniel
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When the concepts of social network analysis (SNA) are imported and interpreted in operations management studies, little research has been carried out to empirically evaluate and validate the impacts of supply network characteristics on individual firms, seller-buyer dyads, and concentrated supply chains. Hence, using archival inter-firm relationships data collected from U.S. public companies, we apply both econometrics and SNA methods to conduct three essays to investigate how firm’s supply network embeddedness affects its productivity growth, its performance in the dyad, and its supply chain efficiency. As firm’s supply network characteristics could be translated into the power or influences that it exercises over other network members, the first essay aims to analyze the effects of firm’s network position on its productivity growth patterns. Specifically, we adopt the fixed-effect panel stochastic frontier model, which incorporates the influences of firm’s network centralities in the productive inefficiency function, to evaluate firm’s technical efficiency change and technological change, which are utilized to calculate its Malmquist productivity index. Meanwhile, little research has been conducted and examined the impacts of bargaining power and network centrality on both seller and buyer performance. Without simultaneously considering these two types of power and investigating their effects on both sides of the seller-buyer dyad, we might fail to capture and portray the overall power that firms exert in the network and evaluate their impacts on both seller’s and buyer’s performance improvements. Leveraging Resource-Based View (RBV), Resource Dependency Theory (RDT) and Social Network Theory (SNT), we seek to bridge these gaps by evaluating the simultaneous impacts of relationship specific bargaining power and firms’ centrality metrics on the both seller’s and buyer’s operational performance. Constructing a simultaneous equations system, the second essay investigates the interactions between sellers and buyers in the supply network, and the relationships between buyer’s bargaining power, node-level centrality measures, and performance metrics measured by their value added. The third essay is designed to identify those SNA measures most closely associated with supply chain efficiency. In a three stage procedure, a DEA model is applied to measure firm- and chain-level efficiencies, followed by a correlation analysis to group SNA variables into clusters of high correlation. These clusters are then used in a step-wise regression algorithm to identify those variables that are most relevant to technical (or productive) efficiency while accounting for multicollinearity. The supply network structural characteristics that emerge as significant are consistent with many hypothesized relationships in the literature, and an interesting tradeoff between the benefit of connectedness and the cost of closeness is also identified and discussed in this part of dissertation.