Factors affecting the choice of medical tourism destination: Spain as a host country

Author(s):  
Javier Tapia ◽  
Marcos Dieste ◽  
Elena Royo ◽  
Elena Calvo
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Arvind Chhabra ◽  
Mehak Munjal ◽  
Prabhu Chandra Mishra ◽  
Kritika Singh ◽  
Debjanee Das ◽  
...  

PurposeThe novel coronavirus has not only caused significant illness and loss of life, it has caused major disruption at local, national and global levels. While the healthcare industry is experiencing growth during the pandemic, disruption to travel has affected medical tourism. This article considers the short-term factors affecting medical tourism and how they could be mitigated by incorporating technological advances to secure long-term growth.Design/methodology/approachThe study examines data provided by the Indian government as well as from non-government sources available in the public domain to review the impact of coronavirus disease 2019 (COVID-19) on medical tourism. The authors also examine data on technological advances in the healthcare industry that could help to reduce the impact of the pandemic.FindingsThis study’s findings show that while in-person services have been seriously impacted in the short term, technological adaptation of medical services to facilitate remote medical consultation has significantly increased. This has enlarged the business opportunities available to hospitals and general practitioners, and it could be leveraged to enhance medical tourism.Originality/valueThe article provides an analysis of the impact of the pandemic on medical tourism and how technology could be used to overcome short-term negative impacts and support longer-term development.


Author(s):  
Mohd Hafiz Hanafiah ◽  
Muhammad Izzat Zulkifly

Purpose This study aims to examine the relationships between tourism destination competitiveness (TDC) determinants and tourism performance. This study specifically assessed the soundness of the TDC attributes and evaluated their ability in explaining tourism performance. Design/methodology/approach The Dwyer and Kim’s (2003) destination competitiveness integrated model (IM) was used. Secondary data of 115 nations available from the Travel and Tourism Competitiveness Index (TTCI) and other international reports were also used. The hypothesised relationships were tested via partial least square-structural equation modelling (PLS-SEM). Findings This study confirms that the core resources, complementary condition, globalisation and tourism price significantly explain tourism performance. Results have shown differences in the competitiveness level and actual performance among nations, highlighting specific limitations of the current TDC model and TTCI report reliability. Research limitations/implications Future study could segment the sample base on destinations characteristic and then analyse it based on smaller sub-samples of similar destinations. Moreover, drivers of destination performance in developed and less develop destinations are quite diverse. Practical implications The incorrect competitiveness ranking evaluation will affect inward investment decisions. This study framework enables policymakers to arrive at more informed decisions than merely relying on the original competitiveness rankings. Originality/value The widespread acknowledgment of the importance of competitiveness for a tourism destination's success suggests that there is a crucial need for sound benchmarking of countries’ competitive capabilities. The proposed competitiveness determinants aid the policymakers in identifying the best competitiveness and tourism performance predictors, as well as how to identify crucial factors affecting the rankings.


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