Data Driven Market Segmentation: The case of medical tourists in Lebanon

Samar Billi Noaman, Mazen Jabbour, Daniel Range, Leonardo José Mataruna-Dos-santos

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Purpose – This research aims to obtain an in-depth understanding of medical tourists’ segments and the variations that exist within them as tourists and patients. Design/Methodology/Approach – A data-driven segmentation approach using the two-step cluster analysis technique was applied on a sample of 212 participants visiting Lebanon for medical purposes. The research instruments combine travel motivation variables, along with socio-demographic, geographic, and behavioral characteristics. Findings and implications – The results identified two distinct segments: “the international patients” and “the elective medical tourists.” The delineated segments have significant implications for scholars, allowing them to understand the profile of tourists and their associated motivations and behaviors better. They can guide medical tourism service providers, marketers, and destination managers in providing specific medical tourism products and services that meet the expectations of each segment. Limitations – Limitations were experienced during the data collection process due to a lack of collaboration and prompt responses by some medical centers, as well as the political and economic contexts of Lebanon that discouraged tourism inflow. These limitations prevented the researchers from obtaining a larger sample size. Originality – There is limited understanding of medical tourists and their diversities in medical tourism literature to date. This study addresses the gap by proposing a new segmentation method in the field of medical tourism that delineates segments by investigating medical tourists’ travel motivations in line with their characteristics
Original languageEnglish
Article numberUDK 339.13.021:338.48-6:615.8(569.3)
Pages (from-to)57-75
Number of pages19
JournalMarket Trziste
Issue number1
Publication statusPublished - 12 Jun 2023

Bibliographical note

All content is published in open access for non-commercial purposes, users are allowed to copy and redistribute the material, transform, and build upon the material as long as they cite the source. CC BY-NC


  • Lebanon
  • medical tourists
  • motivations
  • data-driven
  • segmentation
  • typology


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