WDBA method for probabilistic linguistic MAGDM with entropy weight and application to consumer competitiveness evaluation in creative and cultural industries
Affiliations: [a] Faculty of Humanities and Social Sciences, City University of Macau, Macau, China
| [b] School of literature, Zhuhai College of Science and Technology, Guangdong, Zhuhai, China
Correspondence:
[*]
Corresponding author. Shengyan Liu, Faculty of Humanities and Social Sciences, City University of Macau, 99078, Macau, China. E-mail: [email protected].
Abstract: With the steady development of China’s economy, under the new economic normal, the creative cultural industry has been continuously optimized and developed in terms of structure, scale and quality, and the connotation of the creative cultural industry has been continuously enriched, forming a three-dimensional and diversified pattern. With the help of high-tech, culture, multimedia and other means, the current creative cultural industry is continuously absorbing and integrating it on a large scale, promoting the optimization, upgrading and innovative development of the industry. The consumer competitiveness evaluation in creative and cultural industries is a classical MAGDM problems. In this paper, WDBA method is designed for solving the probabilistic linguistic MAGDM(PL-MAGDM) with the completely unknown weights. In the end, an empirical application for consumer competitiveness evaluation in creative and cultural industries is used to demonstrate the use of the developed method. The proposed method can also contribute to the selection of suitable alternative successfully in other selection problems.
Keywords: Multiple attribute group decision making (MAGDM), probabilistic linguistic term sets (PLTSs), information entropy, WDBA method, consumer competitiveness evaluation in creative and cultural industries
