A Two-Stage MCDM Model for Exploring the Influential Relationships of Sustainable Sports Tourism Criteria in Taichung City.

Bayesian BWM MCDM rough DEMATEL sports for all sustainable sports tourism

Journal

International journal of environmental research and public health
ISSN: 1660-4601
Titre abrégé: Int J Environ Res Public Health
Pays: Switzerland
ID NLM: 101238455

Informations de publication

Date de publication:
30 03 2020
Historique:
received: 11 03 2020
revised: 26 03 2020
accepted: 27 03 2020
entrez: 3 4 2020
pubmed: 3 4 2020
medline: 30 10 2020
Statut: epublish

Résumé

Many countries advocate sports for all to cultivate people's interest in sports. In cities, cross-industry alliances between sports and tourism are one of the common practices. The following two important issues need to be discussed, namely, what factors should be paid attention to in the development of sports tourism, and what are the mutual influential relationships among these factors. This study proposes a novel two-stage multi-criteria decision-making (MCDM) model to incorporate the concept of sustainable development into sports tourism. First, the Bayesian best-worst method (Bayesian BWM) is used to screen out important criteria. Bayesian BWM solves the problem of expert opinion integration of conventional BWM. It is based on the statistical probability to estimate the optimal group criteria weights. Secondly, the rough decision making trial and evaluation laboratory (rough DEMATEL) technique is used to map out complex influential relationships. The introduction of DEMATEL from the rough set theory has better practicality. In the calculation program, interval types are used to replace crisp values in order to retain more expert information. A city in central Taiwan was used to demonstrate the effectiveness of the model. The results show that the quality of urban security, government marketing, business sponsorship and mass transit planning are the most important criteria. In addition, in conjunction with local festivals is the most influential factor for the overall evaluation system.

Identifiants

pubmed: 32235528
pii: ijerph17072319
doi: 10.3390/ijerph17072319
pmc: PMC7177340
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Références

Int J Environ Res Public Health. 2020 Mar 09;17(5):
pubmed: 32182805
Heliyon. 2019 Nov 14;5(11):e02707
pubmed: 31840122
Int J Environ Res Public Health. 2019 Dec 01;16(23):
pubmed: 31805635
Environ Monit Assess. 2019 Oct 16;191(11):647
pubmed: 31620901
Int J Environ Res Public Health. 2019 Jan 08;16(1):
pubmed: 30626073
Int J Environ Res Public Health. 2019 Apr 15;16(8):
pubmed: 30991706
Int J Environ Res Public Health. 2019 Apr 22;16(8):
pubmed: 31013666
Int J Environ Res Public Health. 2018 Dec 06;15(12):
pubmed: 30563291

Auteurs

Jen-Jen Yang (JJ)

Office of Physical Education General Education Center, Chaoyang University of Technology, 168, Jifeng E. Rd., Wufeng District, Taichung 413310, Taiwan.

Yen-Ching Chuang (YC)

Graduate Institute of Urban Planning, College of Public Affairs, National Taipei University, 151, University Rd., Sanxia District, New Taipei City 23741, Taiwan.

Huai-Wei Lo (HW)

Department of Industrial Engineering and Management, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan.

Ting-I Lee (TI)

Office of Physical Education General Education Center, Chaoyang University of Technology, 168, Jifeng E. Rd., Wufeng District, Taichung 413310, Taiwan.

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Classifications MeSH