عنوان مقاله [English]
Many products are produced in networks of firms connected to each other by transactions. From a supply network perspective, the relative position of individual firms with respect to one another affects both strategy and behavior. Despite the importance of such networks little is known about relationship patterns and structural complexity of them. Social network analysis (SNA) approach is a proper method for modelling and understanding structural attributes of such networks. Hence, this study identifies those centrality measures of SNA highly related with supply network efficiency, using buyer-supplier relationship data collected from 45 steel companies in Iran. In a multistage procedure, a DEA model (BCC-input oriented) is used to calculate firm level efficiencies and SNA is applied to measure centrality metrics in supply network. Then, these variables are applied in data panel regression with constant effects to identify those variables most relevant to productive efficiency. The results indicated productive efficiency has positive association with in- degree and betweenness centrality and negative association with out-degree centrality in logistic flow network. Also, in the contractual relationship network, productive efficiency has positive association with degree centrality and negative association with eigenvector Researches in the literature have confirmed although not without exceptions
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