An integrated multi-criteria decision making approach with linguistic hesitant fuzzy sets for E-learning website evaluation and selection

Jia-Wei Gong; Hu-Chen Liu; Xiao-Yue You; Linsen Yin

doi:10.1016/j.asoc.2021.107118

An integrated multi-criteria decision making approach with linguistic hesitant fuzzy sets for E-learning website evaluation and selection

Appl Soft Comput. 2021 Apr:102:107118. doi: 10.1016/j.asoc.2021.107118. Epub 2021 Jan 20.

Authors

Jia-Wei Gong¹, Hu-Chen Liu², Xiao-Yue You³, Linsen Yin⁴

Affiliations

¹ School of Management, Shanghai University, Shanghai 200444, PR China.
² School of Economics and Management, Tongji University, Shanghai 200092, PR China.
³ Sino-German College of Applied Sciences, Tongji University, Shanghai 200092, PR China.
⁴ School of Financial Technology, Shanghai Lixin University of Accounting and Finance, Shanghai 201209, PR China.

Abstract

Network teaching has been widely developed under the influence of COVID-19 pandemic to guarantee the implementation of teaching plans and protect the learning rights of students. Selecting a particular website for network teaching can directly affects end users' performance and promote network teaching quality. Normally, e-learning website selection can be considered as a complex multi-criteria decision making (MCDM) problem, and experts' evaluations over the performance of e-learning websites are often imprecise and fuzzy due to the subjective nature of human thinking. In this article, we propose a new integrated MCDM approach on the basis of linguistic hesitant fuzzy sets (LHFSs) and the TODIM (an acronym in Portuguese of interactive and multi-criteria decision making) method to evaluate and select the best e-learning website for network teaching. This introduced method deals with the linguistic assessments of experts based on the LHFSs, determines the weights of evaluation criteria with the best-worst method (BWM), and acquires the ranking of e-learning websites utilizing an extended TODIM method. The applicability and superiority of the presented linguistic hesitant fuzzy TODIM (LHF-TODIM) approach are demonstrated through a realistic e-learning website selection example. Results show that the LHF-TODIM model being proposed is more practical and effective for solving the e-learning website selection problem under vague and uncertain linguistic environment.

Keywords: Best-worst method; E-learning website; Linguistic hesitant fuzzy set; Network teaching; TODIM method.