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Predicting intention to follow online restaurant community advice: a trust-integrated technology acceptance model

Author

Listed:
  • Aya K. Shaker
  • Rasha H.A. Mostafa
  • Reham I. Elseidi

Abstract

Purpose - This research investigates consumer intention to follow online community advice. Applying the technology acceptance model (TAM) to the context of online restaurant communities, the study empirically examines the effects of perceived usefulness, perceived ease of use, attitude and trust on the intention to follow online advice. Design/methodology/approach - The data were collected from 360 members of online restaurant communities on Facebook and analyzed using structural equation modeling (SEM). Findings - The findings revealed that trust, perceived usefulness and attitude are key predictors of the intention to follow online restaurant community advice. Originality/value - Extant research on the influence of online reviews on consumer behavior in the restaurant industry has largely focused on the characteristics of the review, reviewers or readers. Moreover, other studies have investigated consumers' motivations to write online restaurant reviews. This study, however, takes a different approach and examines what drives consumers to follow the advice from online restaurant communities.

Suggested Citation

  • Aya K. Shaker & Rasha H.A. Mostafa & Reham I. Elseidi, 2021. "Predicting intention to follow online restaurant community advice: a trust-integrated technology acceptance model," European Journal of Management and Business Economics, Emerald Group Publishing Limited, vol. 32(2), pages 185-202, October.
    • Handle: RePEc:eme:ejmbep:ejmbe-01-2021-0036
    DOI: 10.1108/EJMBE-01-2021-0036
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