The evaluation of financial performance for Taiwan container shipping companies by fuzzy TOPSIS

In this paper, financial performance of Taiwan container shipping companies are evaluated by fuzzy multi-criteria decision-making (FMCDM). In the evaluating problem, we first apply grey relation analysis to partition financial ratios into several clusters and find representative indices from the clusters. Then the representative indices are considered as evaluation criteria on financial performance assessment of Taiwan container shipping companies, and an FMCDM method called fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) is utilized to evaluate financial performance. By fuzzy TOPSIS, financial performances of container shipping companies are ranked, and thus a container shipping company can realize its finance competitive strength and weakness between container shipping companies.

[1]  Ali S. Hadi,et al.  Finding Groups in Data: An Introduction to Chster Analysis , 1991 .

[2]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[3]  Francisco Herrera,et al.  A model of consensus in group decision making under linguistic assessments , 1996, Fuzzy Sets Syst..

[4]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[5]  Kuang Lin,et al.  A Fuzzy Multiple Objective DEA for the Human Development Index , 2006, KES.

[6]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[7]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[8]  Hsuan-Shih Lee,et al.  A Fuzzy Method for Evaluating Suppliers , 2006, FSKD.

[9]  Y J Wang,et al.  FUZZY TOPSIS FOR MULTI-CRITERIA DECISION MAKING , 2003 .

[10]  L. J. Truitt,et al.  Evaluating service quality and productivity in the regional airline industry , 1994 .

[11]  Hsuan-Shih Lee,et al.  Evaluating financial performance of Taiwan container shipping companies by strength and weakness indices , 2010, Int. J. Comput. Math..

[12]  Hsuan-Shih Lee,et al.  On fuzzy preference relation in group decision making , 2005, Int. J. Comput. Math..

[13]  Chung-Hsing Yeh,et al.  A survey analysis of service quality for domestic airlines , 2002, Eur. J. Oper. Res..

[14]  Chen-Tung Chen,et al.  Extensions of the TOPSIS for group decision-making under fuzzy environment , 2000, Fuzzy Sets Syst..

[15]  Yu-Jie Wang,et al.  Combining grey relation analysis with FMCGDM to evaluate financial performance of Taiwan container lines , 2009, Expert Syst. Appl..

[16]  Gin-Shuh Liang,et al.  Fuzzy MCDM based on ideal and anti-ideal concepts , 1999, Eur. J. Oper. Res..

[17]  Witold Pedrycz,et al.  Logic-oriented fuzzy clustering , 2002, Pattern Recognit. Lett..

[18]  Hsuan-Shih Lee,et al.  Automatic clustering of business processes in business systems planning , 1999, Eur. J. Oper. Res..

[19]  Chen-Tung Chen,et al.  Fuzzy Credibility Relation Method for Multiple Criteria Decision-Making Problems , 1997, Inf. Sci..

[20]  C. Feng,et al.  Performance evaluation for airlines including the consideration of financial ratios , 2000 .

[21]  J. Deng,et al.  Introduction to Grey system theory , 1989 .

[22]  José L. Verdegay,et al.  Linguistic decision‐making models , 1992, Int. J. Intell. Syst..

[23]  Sheng-Hshiung Tsaur,et al.  The evaluation of airline service quality by fuzzy MCDM. , 2002 .

[24]  Hsuan-Shih Lee,et al.  A Multiple Criteria Decision Making Model Based on Fuzzy Multiple Objective DEA , 2006, KES.

[25]  A. Schwartz Accounting The Basis For Business Decisions , 2016 .

[26]  Shusaku Tsumoto,et al.  Comparison of clustering methods for clinical databases , 2004, Inf. Sci..

[27]  Kie B. Eom Fuzzy clustering approach in unsupervised sea-ice classification , 1999, Neurocomputing.

[28]  T. O'Brien,et al.  Service Quality and Customer Loyalty in the Commercial Airline Industry , 1993 .

[29]  Hsuan-Shih Lee,et al.  A Fuzzy Multiple Criteria Decision Making Model for Airline Competitiveness Evaluation , 2006, KES.

[30]  H. Zimmermann Fuzzy sets, decision making, and expert systems , 1987 .

[31]  Robert F. Meigs Accounting: the Basis for Business Decisions , 1967 .

[32]  Yu-Jie Wang,et al.  Applying FMCDM to evaluate financial performance of domestic airlines in Taiwan , 2008, Expert Syst. Appl..

[33]  Jitender S. Deogun,et al.  An Approximation Algorithm for Clustering Graphs with Dominating Diametral Path , 1997, Inf. Process. Lett..

[34]  Sadaaki Miyamoto,et al.  Information clustering based on fuzzy multisets , 2003, Inf. Process. Manag..

[35]  Ramesh C. Jain A procedure for multiple-aspect decision making using fuzzy sets , 1977 .

[36]  James M. Keller,et al.  A possibilistic approach to clustering , 1993, IEEE Trans. Fuzzy Syst..

[37]  Hsuan-Shih Lee,et al.  A Fuzzy Multi-criteria Decision Making Model for the Selection of the Distribution Center , 2005, ICNC.

[38]  A. Parasuraman,et al.  SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. , 1988 .

[39]  F. A. Lootsma,et al.  Multicriteria decision analysis with fuzzy pairwise comparisons , 1989 .