Evaluating the cross-efficiency of information sharing in supply chains

  • Authors:

  • Ming-Min Yu;Shih-Chan Ting;Mu-Chen Chen

  • Affiliations:

  • Department of Transportation and Navigation Science, National Taiwan Ocean University, No. 2, Pei-Ning Road, Keelung 20224, Taiwan, ROC;Department of Transportation and Navigation Science, National Taiwan Ocean University, No. 2, Pei-Ning Road, Keelung 20224, Taiwan, ROC;Institute of Traffic and Transportation, National Chiao Tung University, 4F, No. 118, Section 1, Chung Hsiao W. Road, Taipei 10012, Taiwan, ROC

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2010

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Abstract

Supply chain management integrates the intra- and inter-corporate processes as a whole system. Through information technology, companies can efficiently manage the product flow and information related to the issues such as production capacity, customer demand and inventory at lower costs. Information sharing can significantly improve the performance of the supply chain, how the different combination of information sharing affects the performance is not yet understood. This study designs different information-sharing scenarios to analyze the supply chain performance through a simulation model. Since there are not only desirable measures but also undesirable measures in supply chains, the usual data envelopment analysis (DEA) model allows measuring performance for complete weight flexibility. In this paper, a cross-efficiency DEA approach is applied to solve this problem. We identify the most efficient scenario and estimate the each efficiency of information-sharing scenarios. Contrary to the previous findings in the literature suggesting sharing as much as information possible to increase benefits, the results of this study show that the scenario of demand information sharing is the most efficient one. In addition, sharing information on capacity and demand, and full information sharing in general are good practices. Sharing only information on capacity and/or inventory information, without sharing information on demand, interferes with production at manufacturers, and causes misunderstandings, which can magnify the bullwhip effect.