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Understanding mobile hotel booking loyalty: an integration of privacy calculus theory and trust-risk framework

Author

Listed:
  • Ahmet Bulent Ozturk

    (University of Central Florida)

  • Khaldoon Nusair

    (Sultan Qaboos University)

  • Fevzi Okumus

    (University of Central Florida)

  • Dipendra Singh

    (University of Central Florida)

Abstract

With the increased popularity of mobile devices, hotels and online travel agencies have started focusing on mobile hotel booking (MHB) in recent years. However, there has been limited research on users” loyalty intentions toward MHB technology. This research attempted to provide an integrated theoretical model that examines the determinants of MHB loyalty. The proposed model, which incorporates personalization, privacy concern, trust, perceived risk, and loyalty, was tested via structural equation modeling (SEM) by using data collected from 396 MHB users. The study results demonstrated that personalization is a strong predictor of MHB users” privacy concerns, trust, and risk perceptions. In addition, privacy concern had a significant impact on trust, and trust significantly influenced perceived risk. Finally, the results revealed that trust and perceived risk were associated with loyalty. This study provides valuable theoretical contributions for researchers and practical implications for online travel agencies, hotel operators and hospitality technology vendors.

Suggested Citation

  • Ahmet Bulent Ozturk & Khaldoon Nusair & Fevzi Okumus & Dipendra Singh, 0. "Understanding mobile hotel booking loyalty: an integration of privacy calculus theory and trust-risk framework," Information Systems Frontiers, Springer, vol. 0, pages 1-15.
    • Handle: RePEc:spr:infosf:v::y::i::d:10.1007_s10796-017-9736-4
    DOI: 10.1007/s10796-017-9736-4
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    References listed on IDEAS

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    Cited by:

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    6. Alraja, Mansour, 2022. "Frontline healthcare providers’ behavioural intention to Internet of Things (IoT)-enabled healthcare applications: A gender-based, cross-generational study," Technological Forecasting and Social Change, Elsevier, vol. 174(C).

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