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Open AccessArticle

Personalized Product Evaluation Based on GRA-TOPSIS and Kansei Engineering

School of Mechanical Engineering, Guizhou University, Guiyang 550025, China
Key Laboratory of Advanced Manfacturing Technology of the Ministry of Education, Guizhou University, Guiyang 550025, China
Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA
Authors to whom correspondence should be addressed.
Symmetry 2019, 11(7), 867;
Received: 27 April 2019 / Revised: 4 June 2019 / Accepted: 21 June 2019 / Published: 3 July 2019
PDF [5073 KB, uploaded 3 July 2019]


With the improvement of human living standards, users’ requirements have changed from function to emotion. Helping users pick out the most suitable product based on their subjective requirements is of great importance for enterprises. This paper proposes a Kansei engineering-based grey relational analysis and techniques for order preference by similarity to ideal solution (KE-GAR-TOPSIS) method to make a subjective user personalized ranking of alternative products. The KE-GRA-TOPSIS method integrates five methods, including Kansei Engineering (KE), analytic hierarchy process (AHP), entropy, game theory, and grey relational analysis-TOPSIS (GRA-TOPSIS). First, an evaluation system is established by KE and AHP. Second, we define a matrix variate—Kansei decision matrix (KDM)—to describe the satisfaction of user requirements. Third, the AHP is used to obtain subjective weight. Next, the entropy method is employed to obtain objective weights by taking the KDM as input. Then the two types of weights are optimized using game theory to obtain the comprehensive weights. Finally, the GRA-TOPSIS method takes the comprehensive weights and the KMD as inputs to rank alternatives. A comparison of the KE-GRA-TOPSIS, KE-TOPSIS, KE-GRA, GRA-TOPSIS, and TOPSIS is conducted to illustrate the unique merits of the KE-GRA-TOPSIS method in Kansei evaluation. Finally, taking the electric drill as an example, we describe the process of the proposed method in detail, which achieves a symmetry between the objectivity of products and subjectivity of users. View Full-Text
Keywords: KE-GRA-TOPSIS; KE; AHP; entropy; game theory; GRA-TOPSIS; personalized product evaluation KE-GRA-TOPSIS; KE; AHP; entropy; game theory; GRA-TOPSIS; personalized product evaluation

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Quan, H.; Li, S.; Wei, H.; Hu, J. Personalized Product Evaluation Based on GRA-TOPSIS and Kansei Engineering. Symmetry 2019, 11, 867.

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