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A genetic algorithm-based learning approach to understand customer satisfaction with OTA websites

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  • Hao, Jin-Xing
  • Yu, Yan
  • Law, Rob
  • Fong, Davis Ka Chio

Abstract

In an extremely competitive marketplace, it is increasingly important for online travel agencies (OTAs) to understand customer satisfaction of different segments. The survey method has been widely used to gain such understanding. However, few previous studies on the tourism and hospitality business have proposed intelligent solutions to analyze such survey data to understand customer preferences on different criteria for different segments, and to determine how customers obtain overall satisfaction across different criteria. In this study, we follow a design-science research paradigm to develop a genetic algorithm-based learning approach to understand customer satisfaction and their psychometric reasons. We further validate this approach through an empirical study for evaluating OTA websites. The results show that different customer segments have different opinions on the importance of various evaluation criteria. The results also reveal that customers tend to judge OTA websites in terms of certain important criteria, instead of by the weighted average of every factor concerned. The proposed approach and the findings of this study can provide constructive suggestions to practitioners and researchers for developing customized marketing campaigns and improving the services of OTA websites.

Suggested Citation

  • Hao, Jin-Xing & Yu, Yan & Law, Rob & Fong, Davis Ka Chio, 2015. "A genetic algorithm-based learning approach to understand customer satisfaction with OTA websites," Tourism Management, Elsevier, vol. 48(C), pages 231-241.
    • Handle: RePEc:eee:touman:v:48:y:2015:i:c:p:231-241
    DOI: 10.1016/j.tourman.2014.11.009
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    References listed on IDEAS

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    Cited by:

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    3. Vasile Mazilescu, 2019. "Tourism and Travel can Effectively Benefit from Technologies Associated with Industry 4.0," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 53-63.
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    5. Ahani, Ali & Nilashi, Mehrbakhsh & Yadegaridehkordi, Elaheh & Sanzogni, Louis & Tarik, A. Rashid & Knox, Kathy & Samad, Sarminah & Ibrahim, Othman, 2019. "Revealing customers’ satisfaction and preferences through online review analysis: The case of Canary Islands hotels," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 331-343.
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    8. Tang Yao & Yigang Wei & Jianhong Zhang & Yani Wang & Yunjiang Yu & Wenyang Huang, 2022. "What influences the urban sewage discharge in China? The effect of diversified factors on the urban sewage discharge in different regions of China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(5), pages 6099-6135, May.
    9. Reyner Pérez Campdesuñer & Gelmar García Vidal & Alexander Sánchez Rodríguez & Rodobaldo Martínez Vivar, 2017. "Structural equation model: influence on tourist satisfaction with destination atributes," Tourism and Hospitality Management, University of Rijeka, Faculty of Tourism and Hospitality Management, vol. 23(2), pages 219-233, November.

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