Psychological factors influencing customers’ acceptance of smartphone diet apps when ordering food at restaurants

By B. Okumus, Faizan Ali, Anil Bilgihan, Anastasia Ozturk. International Journal of Hospitality Management, 2018

284 citations recorded by the source corpus.

Abstract This paper examines the adoption of smartphone diet apps by restaurant customers and, more specifically, the psychological factors that influence their intention to use such apps when ordering food at restaurants. Data was collected from 395 individuals and analyzed using partial least squares structural equation modeling. Results showed that customers’ intention to use smartphone diet apps is predicted by expected performance of the application, anticipated effort of usage, social influence, and degree of user innovativeness. Following the Unified Theory of Acceptance and Use of Technology (UTAUT), this study proposes five determinants of mobile diet apps’ usage intentions: performance expectancy, effort expectancy, social influence, facilitating conditions, and personal innovativeness. Based on the study results, theoretical and practical implications are provided for scholars, health professionals, restaurant operators, and smartphone application developers.

Subfields: Information Systems and Management, Marketing, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/e709a73ca58161d1386e52d95576d4dd4b77cd06

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Citations in the corpus

User Acceptance of Mobile Apps for Restaurants: An Expanded and Extended UTAUT-2 (2019, methodology): “Previous empirical studies on mobile app adoption have supported the idea that effort expectancy influences intentions to use [17,19,24], but not in the MARSR environment.”
Determinants of Continuous Intention on Food Delivery Apps: Extending UTAUT2 with Information Quality (2019, background): “Although the rapid growth of delivery apps has drawn much discussion, there have been relatively few academic studies [2,7,13] on the subject.”
Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse (2020, background): “, customized help, interactive communication channels, FAQs) that help them capture any assistance or information required at any time that they require it (Okumus et al., 2018).”
Unearthing the determinants of Blockchain adoption in supply chain management (2020, methodology): “In addition to examining R 2 value, the study also assesses the effect size using the Cohen f 2 values using the suggested guideline of 0.02 for small effects, 0.15 for medium effects and 0.35 for large effect size (Okumus et al. 2018).”
Institutional Pressures, Green Supply Chain Management Practices on Environmental and Economic Performance: A Two Theory View (2018, methodology): “To assess any existence of non-response bias, a wave analysis was conducted by forming groups of early and late respondents after the follow-up emails [89].”