Journal of Optimization Theory and Applications

, Volume 159, Issue 2, pp 518–535 | Cite as

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



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.


Fuzzy principal component analysis Fuzzy hierarchical evaluation model Multicollinearity Performance management Balance scorecard 



This work was supported by the National Natural Science Foundation of China (Grant No. 11201512), the Science and Technology Research Program of Chongqing Municipal Educational Committee (Grant No. KJ120515) and National Science Foundation of Chongqing Province (Grant No. cstc2012jjA00001).

The authors express their gratitude to the Associate Editor and the anonymous Reviewers for their valuable and constructive comments.


  1. 1.
    Gunasekaran, A., Patel, C., Tirtiroglu, E.: Performance measures and metrics in a supply chain environment. Int. J. Oper. Prod. Manag. 21(1), 71–78 (2001) CrossRefGoogle Scholar
  2. 2.
    Lee, H.L., Billington, C.: Managing supply chain inventory: pitfall and opportunities. Sloan Manag. Rev. 33, 65–73 (1992) Google Scholar
  3. 3.
    Kaplan, R.S., Norton, D.P.: Putting the balanced scorecard to work. Harv. Bus. Rev. 70(4), 71–79 (1992) Google Scholar
  4. 4.
    Kaplan, R.S., Norton, D.P.: Using the balanced scorecard as a strategic management system. Boston Harv. Bus. Rev. 74(1), 75–85 (1996) Google Scholar
  5. 5.
    Hollenbeck, H.: Achieving excellence. Strateg. Finance. 40–46 (2000) Google Scholar
  6. 6.
    Marr, B.: Scored for life. Financ. Manag. 29–30 (2001) Google Scholar
  7. 7.
    Olson, E., Slater, S.: The balanced scorecard, competitive strategy and performance. Bus. Horizons. 11–16 (2002) Google Scholar
  8. 8.
    Brignall, S., Ballantine, J.: Strategic enterprise management systems: new directions for research. Manag. Account. Res. 15(2), 225–240 (2004) CrossRefGoogle Scholar
  9. 9.
    Lambert, D.M., Cooper, M.C., Pagh, J.D.: Supply chain management: implementation issues and research opportunities. Int. J. Logist. Manag. 9(2), 1–19 (1998) CrossRefGoogle Scholar
  10. 10.
    Shi, L.P., Cai, X.: The application of balanced scorecard measures that drive performance based on the supply chain enterprise. J. Harbin Univ. Commer. 2, 69–70 (2003) (Social Science Edition) Google Scholar
  11. 11.
    Sun, S.M., Luo, N.: Design of supply chain based on balanced scorecard system at three levels in six perspectives. J. Northeast. Univ. 7(5), 350–353 (2005) (Social Science) Google Scholar
  12. 12.
    Song, W., Teng, H.: The BSC in the supply chain performance measurement. Value Eng. 23(4), 57–62 (2004) Google Scholar
  13. 13.
    Ma, L.J.: Explore on the supply chain performance evaluation. Mod. Manag. Sci. 10, 94–95 (2005) Google Scholar
  14. 14.
    Ma, S.H., Lin, Y.: Supply Chain Management. China Machine Press, Beijing (2005) Google Scholar
  15. 15.
    Zheng, P., Kin, K.L.: Research on supply chain dynamic balanced scorecard based on fuzzy evaluation and Markov forecast techniques. Syst. Eng. Theory Pract. 4, 93–97 (2008) Google Scholar
  16. 16.
    Beechey, J., Garlick, D.: Using the balanced scorecard in banking. J. Aust. Inst. Bank. 113(1), 28–31 (1999) Google Scholar
  17. 17.
    Stewart, L.J., Bestor, W.E.: Applying a balanced scorecard to health care organizations. J. Corp. Account. Finance 11(3), 75–82 (2000) CrossRefGoogle Scholar
  18. 18.
    Zelman, W.N., Pink, G.H., Matthias, C.B.: Use of the balanced scorecard in health care. J. Health Care Finance 29(4), 1–16 (2003) Google Scholar
  19. 19.
    Denton, G.A., White, B.: Implementing a balanced-scorecard approach to managing hotel operations: the case of white lodging services. Cornell Hotel Restaur. Adm. Q. 41(1), 94–107 (2000) Google Scholar
  20. 20.
    Chow, C.W., Haddad, K.M., Williamson, J.E.: Applying the balanced scorecard to small companies. Manag. Account. 79(2), 21–27 (1997) Google Scholar
  21. 21.
    Curtis, C.C., Ellis, L.W.: Balanced scorecards for new product development. J. Cost Manag. 11(3), 12–19 (1997) Google Scholar
  22. 22.
    Fleisher, C.S., Mahaffy, D.: A balanced scorecard approach to public relations management assessment. Public Relat. Rev. 23(2), 117–142 (1997) CrossRefGoogle Scholar
  23. 23.
    Ziegenfuss, D.E.: Developing an internal auditing department balanced scorecard. Manag. Audit. J. 15(1), 12–19 (2000) CrossRefGoogle Scholar
  24. 24.
    Zee, V.D., De, J.B.: Alignment is not enough: integrating business and information technology management with the balanced business scorecard. J. Manag. Inf. Syst. 16(2), 137–156 (1999) Google Scholar
  25. 25.
    Jones, S., Hughes, J.: Understanding IS evaluation as a complex social process: a case study of a UK local authority. Eur. J. Inf. Syst. 10(4), 189–203 (2001) CrossRefGoogle Scholar
  26. 26.
    Martinsons, M., Davison, R., Tse, D.: The balanced scorecard: a foundation for the strategic management of information systems. Decis. Support Syst. 25(1), 71–88 (1999) CrossRefGoogle Scholar
  27. 27.
    Hasan, H., Tibbits, H.: Strategic management of electronic commerce: an adaptation of the balanced scorecard. Internet Res. 10(5), 439–450 (2000) CrossRefGoogle Scholar
  28. 28.
    Kim, J., Suh, E., Hwang, H.: A model for evaluating the effectiveness of CRM using the balanced scorecard. J. Interact. Mark. 17(2), 5–19 (2003) CrossRefGoogle Scholar
  29. 29.
    Brewer, P.C., Speh, W.: Using the balanced scorecard to measure supply chain performance. J. Bus. Logist. 21(1), 75–93 (2000) Google Scholar
  30. 30.
    Beamon, B.M.: Measuring supply chain performance. Int. J. Oper. Prod. Manag. 10( 3), 275–292 (1999) CrossRefGoogle Scholar
  31. 31.
    Lapide, L.: What about measuring supply chain performance?. Achiev. Supply Chain Excell. Through Technol. 2, 287–297 (2000) Google Scholar
  32. 32.
    Hollenbeck, H.: Achieving excellence. Strateg. Finance. 40–46 (2000) Google Scholar
  33. 33.
    Saaty, T.L.: Multicriteria Decision Making: The Analytic Hierarchy Process. RWS Publications, Pittsburgh (1990) Google Scholar
  34. 34.
    Sugihara, K., Tanaka, H.: Interval evaluations in the analytic hierarchy process by possibility analysis. Comput. Intell. 17(3), 567–579 (2001) CrossRefGoogle Scholar
  35. 35.
    Saaty, T.L.: How to make a decision: the analytic decision processes. Interfaces 24(6), 19–43 (1994) MathSciNetCrossRefGoogle Scholar
  36. 36.
    Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965) MathSciNetCrossRefMATHGoogle Scholar
  37. 37.
    Saaty, T.L.: The Analytic Hierarchy Process. McGraw-Hill, New York (1980) MATHGoogle Scholar
  38. 38.
    Watada, J., Tanaka, H., Asai, K.: Fuzzy discriminant analysis in fuzzy groups. Fuzzy Sets Syst. 19, 261–271 (1986) MathSciNetCrossRefMATHGoogle Scholar
  39. 39.
    Pop, H.F.: Principal components analysis based on a fuzzy sets approach. Stud. Univ. BabesBolyai, Ser. Inform. 46, 45–52 (2001) MATHGoogle Scholar
  40. 40.
    Xian, S.-d.: A new fuzzy comprehensive evaluation model based on the support vector machine. Fuzzy Inf. Eng. 2(1), 75–86 (2010) CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.College of Mathematics and PhysicsChongqing University of Posts and TelecommunicationsChongqingP.R. China
  2. 2.School of Economics and ManagementChongqing University of Posts and TelecommunicationsChongqingP.R. China

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