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E-loyalty formation of Generation Z: Personal characteristics and social influences

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  • Singh, Ranjit
  • Sibi, P.S.

Abstract

Purpose: This study examines the personal characteristics and social influence of Generation Z on their e-loyalty towards tourism websites. In contrast to previous models, this study explores the effect of perceived compatibility and innovativeness (personal characteristics) and subjective norm (social influence) on perceived usefulness and trust on tourism websites, which in turn influence e-loyalty in a generational context. These factors are crucial in e-commerce, but they have not been studied together in the context of tourism, especially for Generation Z. Methods: Using a sample size of 389 respondents falling within Generation Z in India, the proposed model was validated using PLS-SEM. A quantitative approach was followed in this study and the data was collected by using a survey questionnaire. Results: Within the wider context of technology adoption, the findings show the decisive role of both personal characteristics and social influence in determining the e-loyalty of Generation Z towards tourism websites. Implications: The implications of understanding the e-loyalty of Generation Z may assist tourism firms in retaining them by developing and implementing effective marketing strategies. Moreover, the study's most significant contribution is that it considers Generation Z, a generation that will shape the world's future economy and a digital sector with significant purchasing power and influence.

Suggested Citation

  • Singh, Ranjit & Sibi, P.S., 2023. "E-loyalty formation of Generation Z: Personal characteristics and social influences," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 9(1), pages 3-14.
    • Handle: RePEc:zbw:espost:272334
    DOI: 10.5281/zenodo.8054004
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    Cited by:

    1. Ron-Jay A. Bulante & Jennalyn M. Catalan & Noveleen Grace L. Miranda & Desiree T. Torres & Jose S. Sabaulan, 2025. "The Consumer Behavior of Generation Z: An Impact in Modern Marketing Innovations," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(14), pages 950-979, April.
    2. Christou, Evangelos & Fotiadis, Anestis & Giannopoulos, Antonios, 2025. "Generative AI as a tourism actor: Reconceptualising experience co-creation, destination governance and responsible innovation in the synthetic experience economy," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11(2), pages 16-41.
    3. Lee, Joseph Lok-Man & Lau, Chammy Yan-Lam & Wong, Charlaine Wai-Ga, 2023. "Reexamining brand loyalty and brand awareness with social media marketing: A collectivist country perspective," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 9(2), pages 3-10.
    4. Evangelos Christou & Anestis Fotiadis & Antonios Giannopoulos, 2025. "Generative KI als Akteur im Tourismus: Rekonzeptualisierung der Co‑Kreation von Erlebnissen, der Governance von Destinationen und der verantwortungsvollen Innovation in der synthetischen Erlebnisökono," Post-Print hal-05191936, HAL.
    5. Al Saba, Fatema & Mertzanis, Charilaos & Kampouris, Ilias, 2023. "Employee empowerment and tourism sector employment around the world," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 9(2), pages 28-40.
    6. Bejan Brindusa Mariana & Pop Ciprian Marcel, 2024. "Differences Between Generations: The Sustainable Characteristics Of Generation Z," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 191-198, December.

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    JEL classification:

    • A13 - General Economics and Teaching - - General Economics - - - Relation of Economics to Social Values
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • L84 - Industrial Organization - - Industry Studies: Services - - - Personal, Professional, and Business Services

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