Medical tourism is emerging both as a business and as an academic research area that provides patients access to medical institutions for treatment/rehabilitation outside their country of residence. Since the transnational medical travels are interrupted due to the COVID-19 pandemic, the medical tourism, especially the mostly requested elective low-risk treatments like dentistry, laser eye surgery, esthetics and hair transplantation are almost come to a standstill. Therefore, this study aims to identify the barriers to the development and execution of medical tourism during the COVID-19 Pandemic and to analyze the causal relationships between these barriers. In order to that, text mining and Interpretive Structural Modeling (ISM) analysis were conducted. Text mining was applied to the medical tourism related tweets in English from January to June 2020 via RapidMiner software and the current barriers in medical tourism were identified. The relationships between these barriers were examined via expert evaluations. Interpretive Structural Modeling (ISM) was applied to construct a structural model of the barriers that presents how the barriers are related and the hierarchy between them. According to the hierarchical structure the prominent obstacles were: restrictions on transportation, disruption of hospital operations, increasing complexity of medical tourism services and unexpected fluctuations in exchange rates. The main contributions of the study can be listed as: determining the barriers to medical tourism under pandemic conditions by using text mining, and the analysis of the relationships between these barriers with interpretive structural modeling and revealing the root barriers.

Author Name: Saliha KARADAYI USTA, Şeyda SERDAR ASAN

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Keywords: Medical tourism, Barrier Analysis, Text mining, Interpretive Structural Modeling

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EISSN: 2757-9093

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