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A Rough Set Approach on Supply Chain Dynamic Performance Measurement

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Agent and Multi-Agent Systems: Technologies and Applications (KES-AMSTA 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4953))

Abstract

Most of the times, traditional supply chain performance measurement is a static method. However, in the real world, the supply chain is a dynamic system, which needs dynamic performance measurement methods. For the sake of integrative performance measurement of agile virtual enterprise, the traditional Balanced Scorecard is extended into 5 dimensions. According to it, incorporated with the Rough Set theory, the decision table of dynamic performance measurement is constructed. The decision rule set of performance measurement prediction is obtained by attribute reduct and value reduct of decision table. Finally, a calculation example of performance measurement is provided, which shows that the suggested evaluation method is feasible and efficient for dynamic performance measurement and forecasts. Thus, it supplies reasonable analysis and policy making tools for supply chain management.

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Author information

Authors and Affiliations

  1. College of Business Administration, Hunan University, Changsha, 410082, China

    Pei Zheng & Kin Keung Lai

  2. Department of Management Science, City University of Hong Kong, Hong Kong,  

    Kin Keung Lai

Authors
  1. Pei Zheng
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  2. Kin Keung Lai
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Editor information

Ngoc Thanh Nguyen Geun Sik Jo Robert J. Howlett Lakhmi C. Jain

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© 2008 Springer-Verlag Berlin Heidelberg

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Zheng, P., Lai, K.K. (2008). A Rough Set Approach on Supply Chain Dynamic Performance Measurement. In: Nguyen, N.T., Jo, G.S., Howlett, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2008. Lecture Notes in Computer Science(), vol 4953. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78582-8_32

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  • DOI: https://doi.org/10.1007/978-3-540-78582-8_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78581-1

  • Online ISBN: 978-3-540-78582-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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