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A Fuzzy Principal Component Analysis Approach to Hierarchical Evaluation Model for Balanced Supply Chain Scorecard Grading

Author

Listed:
  • Sidong Xian

    (Chongqing University of Posts and Telecommunications)

  • Dong Qiu

    (Chongqing University of Posts and Telecommunications)

  • Shiyun Zhang

    (Chongqing University of Posts and Telecommunications)

Abstract

Effective performance management is critical to efficient supply chain management systems with the balanced scorecard as well as to effective evaluation models and their algorithms. Problems often encountered in the modeling of the balanced scorecard for supply chain are how to overcome the multicollinearity in its index system. In this paper, a new fuzzy hierarchical evaluation model featuring the criteria of the balanced supply chain scorecard is proposed and analyzed on the basis of data about Chinese firms. The model, based on the fuzzy weight’s matrix derived from a fuzzy principal component analysis, overcomes the multicollinearity in the index system of the balanced supply chain scorecard. This method proves good performance in determining the weight distribution matrix of the fuzzy hierarchical evaluation and improves the evaluation accuracy and generalization as shown for a group of firms in western China.

Suggested Citation

  • Sidong Xian & Dong Qiu & Shiyun Zhang, 2013. "A Fuzzy Principal Component Analysis Approach to Hierarchical Evaluation Model for Balanced Supply Chain Scorecard Grading," Journal of Optimization Theory and Applications, Springer, vol. 159(2), pages 518-535, November.
    • Handle: RePEc:spr:joptap:v:159:y:2013:i:2:d:10.1007_s10957-013-0337-1
    DOI: 10.1007/s10957-013-0337-1
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    References listed on IDEAS

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    1. Olson, Eric M. & Slater, Stanley F., 2002. "The balanced scorecard, competitive strategy, and performance," Business Horizons, Elsevier, vol. 45(3), pages 11-16.
    2. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    3. Thomas L. Saaty, 1994. "How to Make a Decision: The Analytic Hierarchy Process," Interfaces, INFORMS, vol. 24(6), pages 19-43, December.
    4. Si-dong Xian, 2010. "A new fuzzy comprehensive evaluation model based on the support vector machine," Fuzzy Information and Engineering, Springer, vol. 2(1), pages 75-86, March.
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