An Improved TOPSIS Within the DEA Framework

Jin-Cheng Lu () and Mei-Juan Li
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Jin-Cheng Lu: School of Economics & Management, Fuzhou University, Fuzhou 350108, P. R. China
Mei-Juan Li: School of Economics & Management, Fuzhou University, Fuzhou 350108, P. R. China2Research Center of Fujian Economic High-Quality, Development Based on Social Science, Planning of Fujian Province in China, Fuzhou 350108, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2023, vol. 40, issue 06, 1-20

Abstract: Decision-maker (DM) can assign the weights of the distance measures in the relative closeness of technique for order preference by similarity to ideal solution (TOPSIS) for achieving his/her desirable ranking of alternatives. This phenomenon is called strategically setting distance measure weights in this study, which may affect the fairness of the results. In order to prevent this phenomenon, the idea of data envelopment analysis (DEA) is introduced to determine the objective weights of distance measures, and an improved TOPSIS is proposed in this study. The proposed method not only determines weights of the distance measures from an objective perspective and achieves the fully ranking of alternatives, but also provides the directions for improvement. Moreover, in comparison with the other methods, the advantages of the proposed method are analyzed, and the meanings and properties of the new relative closeness are discussed and proved. Finally, an example of evaluating the innovation development of high-tech industries in central and western regions of China is investigated to illustrate the effectiveness and the usefulness of the proposed method.

Keywords: TOPSIS; data envelopment analysis; objective perspective; relative closeness (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0217595922500348

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