Factors Influencing Customer Attitudes towards Online Food Delivery Application after the COVID-19 Epidemic in Jordanian Restaurants
Abstract
Although several studies on technology trends and acceptance have been undertaken, few studies investigate the factors that influence customer attitudes toward food delivery apps depending on the Unified Theory of Acceptance and Use of Technology (UTAUT). The purpose of the study is to examine the use of Online Food Delivery (OFD) in Jordanian restaurants after the COVID-19 epidemic by applying UTAUT. In the northern and central regions of Jordan, 722 online questionnaires were gathered using Structural Equation Modeling (SEM). The results reveal that three factors significantly affect customers' decisions to use the OFD service: behavioral intention, pricing, and social influence. Furthermore, performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, habit positivity, trust, and perceived credibility significantly influence the behavioral intention to use. In addition, the moderating impacts of age, gender, and experience were examined using multigroup analysis. Some of the model's expected associations were shown to be moderated by the users' experience, but gender and age had no significant influence. The results have consequences for both research and practice implications.
References
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[32] Ray, A., Dhir, A., Bala, P., and Kaur, P. 2019. Why do people use food delivery apps (FDA)? A uses and gratification theory perspective. Journal of Retailing and Consumer Services, 51: 221–230. DOI:https://doi.org/10.1016/j.jretconser.2019.05.025
[33] Roh, M., and Park, K. 2019. Adoption of O2O food delivery services in South Korea: The moderating role of moral obligation in meal preparation. International Journal of Information Management, 47: 262–273. DOI:https://doi.org/10.1016/j.ijinfomgt.2018.09.017
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[37] Shatnawi, H., Al Najdawi, B., Kanaan, K., Khaleefah, Q., and Khasawneh, M. 2019. Factors affecting customers'behavior towards tipping intentions in Jordanian restaurants. Geojournal of Tourism and Geosites, 26(3): 761-768. DOI: https://doi.org/10.30892/gtg.26307-395
[38] Song, Ruan, and Jeon. 2021. An integrated approach to the purchase decision-making process of food-delivery apps: Focusing on the TAM and AIDA models. International Journal of Hospitality Management, 95: 102943. DOI: https://doi.org/10.1016/j.ijhm.2021.102943
[39] Tam, C., Santos, A., and Oliveira, T. 2020. Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers, 22(1): 243–257. DOI: https://doi.org/10.1007/s10796-018-9864-
[40] Tandon, A., Kaur, P., Bhatt, P., and Antym, M. 2021. Why do people purchase from food delivery apps? A consumer value perspective. Journal of Retailing and Consumer Services, 63: 102667. DOI:https://doi.org/10.1016/j.jretconser.2021.102667
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[42] Venkatesh, V., Thong, J., and Xu, X. 2012. Consumer acceptance and use of information technology: extending the unified theory. MIS Quarterly, 36 (1): 157–178. DOI: https://doi.org/10.2307/41410412
[43] Wen, J., Yang, F., Kozak, S., and Liu, F. 2020. COVID-19: Potential effects on Chinese citizens’ lifestyle and travel. Tourism Review, 76(1): 74–87. DOI: https://doi.org/10.1108/TR-03-2020-0110.
[44] Yan, M., Filieri, R., and Gorton, M. 2021. Continuance intention of online technologies: A systematic literature review. International Journal of Information Management, 58(6): 102315. DOI:https://doi.org/10.1016/j.ijinfomgt. 2021.102315
[45] Yeo, V., Goh, S. K., and Rezaei, S. 2017. Consumer experiences, attitude and behavioral intentiontoward online food delivery (OFD) services, Journal of Retailing and Consumer Services, 35: 150-162. DOI:https://doi.org/10.1016/ j.jretconser.2016.12.013
[46] Yu, S. C. 2012. Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT Model. Journal of Electronic Commerce Research,13 (2): 104–121.
[47] Zhao, R., and Bacao, F. 2020. What factors determining customer continuingly using food delivery apps during 2019 novel coronavirus pandemic period? International Journal of Hospitality Management, 91: 102683. DOI: https://doi.org/10.1016/j.ijhm.2020.102683
[48] Zhou, Rau, and Salvendy. 2014. Age-related difference in the use of mobile phones. Universal Access in the Information Society, 13(4): 401–413. DOI: https://doi.org/10.1007/s10209-013-0324-1
[49] Control, D., & Prevention. 2020. Social distancing. what is social distancing? Available at: https://www.cdc.gov/coronavirus/2019 ncov/prevent-gettingsick/
[50] GSMA. 2020.The mobile economy. Available at: https://www.gsma.com/mobileeconomy/wpcontent/uploads/2020/03/GSMA_ MobileEconomy2020_Global.pdf
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[52] Simform. 2021. App usage statistics 2021 that’ll Surprise You (Updated). Mobile App Development. Available at: https://www.simform.com/the-state-of-mobile-app-usage/
[2] Al Najdawi, B. M., Khaleefah, Q. Q., Shatnawi, H. S., and Al Momani, E. M. 2017. Measuring local tourists' perceptions in Petra city as one of seven wonders of world. Journal of Environmental Management & Tourism, Volume VIII, Summer, (2 (18): 427. DOI: https://doi.org/10.14505//jemt.v8.2(18).15
[3] Byrd, Her, Fan, Almanza, and Liu. 2021. Restaurants and COVID-19: What are consumers’ risk perceptions about restaurant food and its packaging during the pandemic? International Journal of Hospitality Management, 94, DOI: https://doi.org/10.1016/j.ijhm.2020.102821
[4] Chen, H., and Hsieh, Y. 2017. The driving success factors of the online food ordering system empirical evidence from the UTAUT model.
[5] Chen, J. S., Tsou, T. H., and Huang, A. Y. 2009. Service delivery innovation: Antecedents and impact on firm performance, Journal of Service Research, 12 (1): 36-55. DOI: https://doi.org/10.1177/1094670509338619
[6] Cho, Bonn, and Li. 2019. Differences in perceptions about food delivery apps between single-person and multi-person households. International Journal of Hospitality Management, 77: 108–116. DOI:https://doi.org/10.1016/ j.ijhm.2018
[7] Chopdar, P. K., and Sivakumar, J. P. 2019. Understanding continuance usage of mobileshopping applications in India: The role of espoused cultural values and perceived risk. Behaviour & Information Technology, 38(1): 42–64. DOI: https://doi.org/10.1080/0144929X.2018.1513563
[8] Davis, F. D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13(3): 319—339. DOI: 10.2307/249008
[9] Fame RN. 2020. The COVID-19 Pandemic: A family affair. Journal of Family Nursing, 26(2): 87–89. DOI:https://doi.org/10.1177/1074840720920883
[10] Fang, I. C., and Fang, S. C. 2016. Factors affecting consumer stickiness to continue using mobile applications. International Journal of Mobile Communications, 14(5), 431. DOI:https://doi.org/10.1504/IJMC.2016.078720
[11] Gavilan, D., Balderas-Cejudo, A., and Fern´andez-Lores. 2021. INNOVATION in online food delivery: Learnings from COVID-19. International Journal of Gastronomy and Food Science, 100330. DOI:https://doi.org/10.1016/ j.ijgfs.2021.100330
[12] Goh, T., and Sun, S. 2014. Exploring gender differences in Islamic mobile banking acceptance. Electron. Commer. Research.14 (4): 435–458. DOI: 10.1007/s10660-014-9150-7
[13] Ha, D. N. 2013. Demand creation of online services for B2B and consumer market–food delivery in Vietnam, M.Sc. Thesis, Tampere University of Technology.
[14] Hair J. F., et al. 1995. Multivariate data analysis with readings, 4th edition, Pearson College Div; 4th Edition, ISBN: 978-0139133107
[15] Hill, R., Betts, L., and Gardner, S. 2015. Older adults’ experiences and perceptions of digital technology: (Dis)empowerment, wellbeing, and inclusion. Computers in Human Behavior, 48: 415–423. DOI:https://doi.org/ 10.1016/j.chb.2015.01.062
[16] Hirschberg, C., Rajko, H., Schumacher, A., and Wrul, T. 2016. The changing market for food delivery. Available at: https://www.mckinsey.com/industries/high-tech/our-insights/thechanging-market-for-food-delivery
[17] Hoffman, K. D., Bateson, E. J., and Ikeda, A.A. 2010. Princiıpios de marketing de serviços, 3rd Ed., Cengage Sao Paulo, 599 pp.
[18] Jadi, Rana, and Dwivedi. 2021. A meta-analysis of the UTAUT model in the mobile banking literature: The moderating role of sample size and culture. Journal of Business Research, 132: 354–372. DOI:https://doi.org/10.1016/ j.jbusres.2021.04.052
[19] Kang, S. 2014. Factors influencing intention of mobile application use. International Journal of Mobile Communications, 12: 360–379. DOI: https://doi.org/10.1504/IJMC.2014.063653
[20] Laforet, A., and Li, X. 2005. Consumers’ attitudes towards online and mobile banking in China. International. Journal Bank Marketing, 23(5): 362–380.
[21] Lai, I., and Shi, G. 2015. The impact of privacy concerns on the intention for continued use of an integrated mobile instant messaging and social network platform. International Journal of Mobile Communications, 13: 641–669. DOI: https://doi.org/10.1504/IJMC.20
[22] Lan, Yanan, and Shuhua. 2016. Improvement of online food delivery service based on consumers’ negative comments, Canadian Social Science, 12 (5): 84-88.
[23] Lee, S., Sung, H., and Jeon, H. M. 2019. Determinants of continuous intention on food delivery apps: Extending UTAUT2 with Information Quality. Sustainability, 11(11): 3141. DOI:https://doi.org/10.3390/su11113141.
[24] LI, and Mo. 2015. The O2O mode in electronic commerce. Proceedings of the International Conference on Education, Management, Commerce and Society, 17: 238–241. DOI: https://doi.org/10.2991/emcs-15.2015.50
[25] Liu, Xiao, Lim, and Tan. 2017. The art of appeal in electronic commerce: Understanding the impact of product and website quality on online purchases. Internet Research, 27(4): 752–771. DOI:https://doi.org/10.1108/IntR-09-2016-0280
[26] Lu, Y., Yang, E., Chau, S., and Cao, Y. 2011. Dynamics between the trust transfer process and intention to use mobile payment services: A cross-environment perspective. Information & Management, 48: (8): 393–403. DOI: https://doi.org/10.1016/j.im.2011.09.006
[27] Luarn, P., and Lin, H. 2005. Toward an understanding of the behavioral intention to use mobile banking. Computers in Human Behavoir. 21(6): 873–891. DOI: https://doi.org/10.1016/j.chb.2004.03.003
[28] Luis et al. 2021. The use of food delivery apps during the COVID-19 pandemic in Brazil: The role of solidarity, perceived risk, and regional aspects. Food Research International, 149: 110671. DOI:https://doi.org/10.1016/j.food res.2021.110671
[29] Mohammad, A. R. A. F., Al Najdawi, B. M., ElZoghbi, M., and Abdelhadi, A. S. A. 2014. A study of some factors affecting employee turnover in fast food restaurant in Amman. Journal of Association of Arab Universities for Tourism and Hospitality, 11(1): 71-80.
[30] Nascimento, B., Oliveira, C., and Tam, C. 2018. Wearable technology: What explains continuance intention in smartwatches? Journal of Retailing and Consumer Services, 43: 157–169. DOI:https://doi.org/10.1016/j.jretconser. 2018.03.017
[31] Pigatto, Machado, and Negreti. 2017. Have you chosen your request? Analysis of online food delivery companies in Brazil, British Food Journal, 119(3): 639-657. DOI: https://doi.org/10.1108/bfj-05-2016-0207
[32] Ray, A., Dhir, A., Bala, P., and Kaur, P. 2019. Why do people use food delivery apps (FDA)? A uses and gratification theory perspective. Journal of Retailing and Consumer Services, 51: 221–230. DOI:https://doi.org/10.1016/j.jretconser.2019.05.025
[33] Roh, M., and Park, K. 2019. Adoption of O2O food delivery services in South Korea: The moderating role of moral obligation in meal preparation. International Journal of Information Management, 47: 262–273. DOI:https://doi.org/10.1016/j.ijinfomgt.2018.09.017
[34] Saad, A. T. 2020. Factors affecting online food delivery service in Bangladesh:an empirical study. British Food Journal, 11(5): 1-16. DOI: https://doi.org/10.1108/BFJ-05-2020-0449
[35] Saksena, M., Okrent, Y., Anekwe, T., and Cho, A. 2018. America’s eating habits: Food away from home, Economic Research Service Economic Information Bulletin No. (EIB-196) 172 pp.
[36] Sethu, H. S., and Saini, B. 2016. Proceedings of the seventh Asia-Pacific conference on global business, Economics, Finance and Social Sciences (AP16 Malaysia Conference), Kuala Lumpur,15th – 17th July 2016. Paper ID: KL631. ISBN 978-1-943579-81-5
[37] Shatnawi, H., Al Najdawi, B., Kanaan, K., Khaleefah, Q., and Khasawneh, M. 2019. Factors affecting customers'behavior towards tipping intentions in Jordanian restaurants. Geojournal of Tourism and Geosites, 26(3): 761-768. DOI: https://doi.org/10.30892/gtg.26307-395
[38] Song, Ruan, and Jeon. 2021. An integrated approach to the purchase decision-making process of food-delivery apps: Focusing on the TAM and AIDA models. International Journal of Hospitality Management, 95: 102943. DOI: https://doi.org/10.1016/j.ijhm.2021.102943
[39] Tam, C., Santos, A., and Oliveira, T. 2020. Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers, 22(1): 243–257. DOI: https://doi.org/10.1007/s10796-018-9864-
[40] Tandon, A., Kaur, P., Bhatt, P., and Antym, M. 2021. Why do people purchase from food delivery apps? A consumer value perspective. Journal of Retailing and Consumer Services, 63: 102667. DOI:https://doi.org/10.1016/j.jretconser.2021.102667
[41] Venkatesh, V., Morris, M. G., Davis, G. B., and Davis, S. 2003. User acceptance of information technology: Toward a unified view. MIS Quarterly, 7(3): 425–478. DOI: https://doi.org/10.2307/30036540
[42] Venkatesh, V., Thong, J., and Xu, X. 2012. Consumer acceptance and use of information technology: extending the unified theory. MIS Quarterly, 36 (1): 157–178. DOI: https://doi.org/10.2307/41410412
[43] Wen, J., Yang, F., Kozak, S., and Liu, F. 2020. COVID-19: Potential effects on Chinese citizens’ lifestyle and travel. Tourism Review, 76(1): 74–87. DOI: https://doi.org/10.1108/TR-03-2020-0110.
[44] Yan, M., Filieri, R., and Gorton, M. 2021. Continuance intention of online technologies: A systematic literature review. International Journal of Information Management, 58(6): 102315. DOI:https://doi.org/10.1016/j.ijinfomgt. 2021.102315
[45] Yeo, V., Goh, S. K., and Rezaei, S. 2017. Consumer experiences, attitude and behavioral intentiontoward online food delivery (OFD) services, Journal of Retailing and Consumer Services, 35: 150-162. DOI:https://doi.org/10.1016/ j.jretconser.2016.12.013
[46] Yu, S. C. 2012. Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT Model. Journal of Electronic Commerce Research,13 (2): 104–121.
[47] Zhao, R., and Bacao, F. 2020. What factors determining customer continuingly using food delivery apps during 2019 novel coronavirus pandemic period? International Journal of Hospitality Management, 91: 102683. DOI: https://doi.org/10.1016/j.ijhm.2020.102683
[48] Zhou, Rau, and Salvendy. 2014. Age-related difference in the use of mobile phones. Universal Access in the Information Society, 13(4): 401–413. DOI: https://doi.org/10.1007/s10209-013-0324-1
[49] Control, D., & Prevention. 2020. Social distancing. what is social distancing? Available at: https://www.cdc.gov/coronavirus/2019 ncov/prevent-gettingsick/
[50] GSMA. 2020.The mobile economy. Available at: https://www.gsma.com/mobileeconomy/wpcontent/uploads/2020/03/GSMA_ MobileEconomy2020_Global.pdf
[51] Food. 2020. Comoe a relaçao do iFood com os restaurantes? Transparencia. Available at: https://institucional.i food.com.br/abrindo-a-cozinha/ifood-restaurantes
[52] Simform. 2021. App usage statistics 2021 that’ll Surprise You (Updated). Mobile App Development. Available at: https://www.simform.com/the-state-of-mobile-app-usage/
Published
2023-03-31
How to Cite
NAJDAWI, Bashar M. AL et al.
Factors Influencing Customer Attitudes towards Online Food Delivery Application after the COVID-19 Epidemic in Jordanian Restaurants.
Journal of Environmental Management and Tourism, [S.l.], v. 14, n. 2, p. 500 - 512, mar. 2023.
ISSN 2068-7729.
Available at: <https://journals.aserspublishing.eu/jemt/article/view/7698>. Date accessed: 26 apr. 2024.
doi: https://doi.org/10.14505/jemt.v14.2(66).19.
Section
Article
Copyright© 2023 The Author(s). Published by ASERS Publishing 2023. This is an open access article distributed under the terms of CC-BY 4.0 license.