PMID- 36570416
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20230103
IS  - 1568-4946 (Print)
IS  - 1872-9681 (Electronic)
IS  - 1568-4946 (Linking)
VI  - 102
DP  - 2021 Apr
TI  - An integrated multi-criteria decision making approach with linguistic hesitant 
      fuzzy sets for E-learning website evaluation and selection.
PG  - 107118
LID - 10.1016/j.asoc.2021.107118 [doi]
AB  - 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.
CI  - (c) 2021 Elsevier B.V. All rights reserved.
FAU - Gong, Jia-Wei
AU  - Gong JW
AD  - School of Management, Shanghai University, Shanghai 200444, PR China.
FAU - Liu, Hu-Chen
AU  - Liu HC
AD  - School of Economics and Management, Tongji University, Shanghai 200092, PR China.
FAU - You, Xiao-Yue
AU  - You XY
AD  - Sino-German College of Applied Sciences, Tongji University, Shanghai 200092, PR 
      China.
FAU - Yin, Linsen
AU  - Yin L
AD  - School of Financial Technology, Shanghai Lixin University of Accounting and 
      Finance, Shanghai 201209, PR China.
LA  - eng
PT  - Journal Article
DEP - 20210120
PL  - United States
TA  - Appl Soft Comput
JT  - Applied soft computing
JID - 101536968
PMC - PMC9760212
OTO - NOTNLM
OT  - Best-worst method
OT  - E-learning website
OT  - Linguistic hesitant fuzzy set
OT  - Network teaching
OT  - TODIM method
COIS- The authors declare that they have no known competing financial interests or 
      personal relationships that could have appeared to influence the work reported in 
      this paper.
EDAT- 2021/04/01 00:00
MHDA- 2021/04/01 00:01
PMCR- 2021/01/20
CRDT- 2022/12/26 04:33
PHST- 2020/09/10 00:00 [received]
PHST- 2020/12/14 00:00 [revised]
PHST- 2021/01/17 00:00 [accepted]
PHST- 2022/12/26 04:33 [entrez]
PHST- 2021/04/01 00:00 [pubmed]
PHST- 2021/04/01 00:01 [medline]
PHST- 2021/01/20 00:00 [pmc-release]
AID - S1568-4946(21)00041-7 [pii]
AID - 107118 [pii]
AID - 10.1016/j.asoc.2021.107118 [doi]
PST - ppublish
SO  - Appl Soft Comput. 2021 Apr;102:107118. doi: 10.1016/j.asoc.2021.107118. Epub 2021 
      Jan 20.