Risk Evaluation of Dynamic Alliance Based on Fuzzy Analytic Network Process and Fuzzy TOPSIS

Xiaoguang Zhou, Mi Lu

Department of Electrical and Computer Engineering, Texas A&M University, College Station, USA..
Dongling School of Economics and Management, University of Science and Technology Beijing, Beijing, China.

DOI: 10.4236/jssm.2012.53028                

Abstract

Dynamic alliance formations have increased dramatically over the past decade for its adaptation to environmental change and market competition. However, many fail, while an even greater proportion perform poorly. The risk analysis of dynamic alliance will help enterprises to choose a coalition partner and make a reasonable benefit allocation plan. It’s also good for reducing the risk and keeping the stability of the alliance. Based on the interaction and feedback relationships between criteria and/or indices, an index system for evaluating the risk of dynamic alliance is developed. With the information uncertainty and inaccuracy being considered, a new hybrid model based on fuzzy analytic network process (FANP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) is proposed. The local weights of criteria and indices are obtained by fuzzy preference programming (FPP), and the comprehensive weights are derived by FANP. According to fuzzy TOPSIS, an optimal alternative is chosen by the closeness coefficient based on the shortest distance from the positive and the farthest distance from the negative ideal solutions. Finally, a numerical case is given by the proposed method.

Keywords

Fuzzy Analytic Network Process; TOPSIS; Dynamic Alliance; Risk Evaluation

Conflicts of Interest

The authors declare no conflicts of interest.

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