Health tourism strategy selection via SWOT analysis and integrated hesitant fuzzy linguistic AHP-MABAC approach

BÜYÜKÖZKAN FEYZİOĞLU G., MUKUL E., Kongar E.

SOCIO-ECONOMIC PLANNING SCIENCES, cilt.74, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 74
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.seps.2020.100929
  • Dergi Adı: SOCIO-ECONOMIC PLANNING SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, International Bibliography of Social Sciences, Business Source Elite, Business Source Premier, EconLit, Educational research abstracts (ERA), INSPEC, Political Science Complete, Public Affairs Index, Social services abstracts, Sociological abstracts, Worldwide Political Science Abstracts
  • Anahtar Kelimeler: Health tourism, Health tourism strategy selection, SWOT analysis, Hesitant fuzzy linguistic term set, AHP, MABAC, TERM SET, CARE, RESOURCES, WELLNESS, TOPSIS, MODEL
  • Galatasaray Üniversitesi Adresli: Evet

Özet

Health tourism focuses on the organizational and operational aspects of commercial trips for the treatment of individuals. In line with the economic growth, the industry has evolved significantly in the last few decades. Istanbul, Turkey is considered as one of the most viable markets in the region due to its thermal resources, mild climate, geographical accessibility, and natural resources. This study aims to present the SWOT analysis of Istanbul's health tourism with integrated hesitant fuzzy linguistic (HFL) AHP-HFL MABAC methodology to select the best strategy for its effective implementation. The proposed methodology initially determines SWOT factors required for the analysis. These factors are then weighted with HFL AHP. The results are then utilized to select the best health tourism strategy using HFL MABAC. The applicability of this approach is presented through a case study. This is the first study to propose an analytic based SWOT analysis with integrated HFL methods for the selection of most appealing health tourism strategy.