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Psychological factors influencing customers’ acceptance of smartphone diet apps when ordering food at restaurants
Open accessAbstract
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.
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The value proposition of food delivery apps from the perspective of theory of consumption value
Kaur, P., Dhir, A., Talwar, S., & Ghuman, K. (2021) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-05-2020-0477 · Cited by 377
Arfi, W. B., Nasr, I. B., Kondrateva, G., & Hikkerova, L. (2021) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2021.120688 · Cited by 290
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Gunden, N., Morosan, C., & DeFranco, A. (2020) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-06-2019-0595 · Cited by 207
Mobile apps for healthy living: Factors influencing continuance intention for health apps
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Metadata
- Authors
- Okumus, B., Ali, F., Bilgihan, A., & Ozturk, A. B.
- Venue
- International Journal of Hospitality Management
- Publisher
- Elsevier BV
- Published
- 2018-06
- Volume
- 72
- Pages
- 67-77
- ISSN
- 0278-4319 (ISSN-L)
- OpenAlex
- W2781933708
- Cited by
- 331
- References
- 100
- FWCI
- 39.08
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.