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

Sidong Xian (), Dong Qiu and Shiyun Zhang
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Sidong Xian: Chongqing University of Posts and Telecommunications
Dong Qiu: Chongqing University of Posts and Telecommunications
Shiyun Zhang: Chongqing University of Posts and Telecommunications

Journal of Optimization Theory and Applications, 2013, vol. 159, issue 2, No 13, 518-535

Abstract: 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.

Keywords: Fuzzy principal component analysis; Fuzzy hierarchical evaluation model; Multicollinearity; Performance management; Balance scorecard (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s10957-013-0337-1

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