Developing and Validating the Measurement Model for Technology Acceptance Factors of Online Food Delivery Applications (OFDA) Usage Constructs in Sarawak Using Confirmatory Factor Analysis (CFA)

Gârdan, D., Epuran, G., Pas, C., Gârdan, I., Jiroveanu, D., Tec?u, A., … Pop, R.-A. (2021). Enhancing Consumer Experience through Development of Implicit Attitudes Using Food Delivery Applications. Journal of Theoretical and Applied Electronic Commerce Research, 16(7), 2858-2882
Alalwan, A. A. (2020). Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse. International Journal of Information Management, 50, 28–44.
Alassafi, M. O. (2022). E-learning intention material using TAM: A case study. Materials Today: Proceedings, 61, 873–877.
Antipode, L. R.-, & 2020, undefined. (2020). Platforms, markets, and contingent calculation: The flexible arrangement of the delivered meal. Wiley Online Library, 52(3), 619–636.
Zainuddin, A., Hui, L. S., & Zainudin, N. F. (2018). Pendekatan Mudah SEM- Structural Equation Modelling.
Zainudin, A. (2015a). SEM Made Simple: A Gentle Approach to Learning Sructural Equation Modelling. MPWS Rich Publication.
Zainudin, A. (2015b). SEM made simple: A gentle approach to learning structural equation modeling. MPWS Rich Publication, Bandar Baru Bangi.
Zainudin, A., S. H. L., & Zainudin, N. (2018). Pendekatan Mudah SEM- Structural Equation Modelling. Bandar Baru Bangi, MPWS Rich Resources.
Bonett, D. G., & Wright, T. A. (2015). Cronbach’s alpha reliability: Interval estimation, hypothesis testing, and sample size planning. Journal of Organizational Behavior, 36(1), 3–15.
Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1(3), 185–216.
Buschle, C., Reiter, H., & Bethmann, A. (2022). The qualitative pretest interview for questionnaire development: outline of programme and practice. Quality and Quantity, 56(2), 823–842.
Cai, R., & Leung, X. Y. (2020). Mindset matters in purchasing online food deliveries during the pandemic: The application of construal level and regulatory focus theories. International Journal of Hospitality Management, 91, 102677.
Cho, M., Bonn, M. A., & Li, J. (Justin). (2019). Differences in perceptions about food delivery apps between single-person and multi-person households. International Journal of Hospitality Management, 77, 108–116.
Dai, H., Ge, L., & Liu, Y. (2020). Information Matters: an Empirical Study of the Efficiency of On-Demand Services. Information Systems Frontiers, 22(4), 815–827.
Dowling, G. R., & Staelin, R. (1994). A Model of Perceived Risk and Intended Risk-Handling Activity. Journal of Consumer Research, 21(1), 119.
Fernández-Gómez, E., Martín-Salvador, A., Luque-Vara, T., Sánchez-Ojeda, M. A., Navarro-Prado, S., & Enrique-Mirón, C. (2020). Content Validation through Expert Judgement of an Instrument on the Nutritional Knowledge, Beliefs, and Habits of Pregnant Women. Nutrients, 12(4).
Statista. (n.d.). Global online food delivery market size 2027. [Online] Available at https://www.statista.com/statistics/1170631/online-food-delivery-market-size-worldwide/. [Assesed on March 21, 2023].
Gunden, N., Morosan, C., & DeFranco, A. (2020a). Consumers’ intentions to use online food delivery systems in the USA. International Journal of Contemporary Hospitality Management, 32(3), 1325–1345.
Gunden, N., Morosan, C., & DeFranco, A. L. (2020b). Consumers’ persuasion in online food delivery systems. Journal of Hospitality and Tourism Technology, 11(3), 495–509.
Gupta, V., & Duggal, S. (2021). How the consumer’s attitude and behavioural intentions are influenced: A case of online food delivery applications in India. International Journal of Culture, Tourism, and Hospitality Research, 15(1), 77–93.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis (7th ed.). Essex: Pearson Education Limited.
Hamid, S., Azhar, M., & Sujood. (2022). Behavioral Intention To Order Food And Beverage Items Using E-Commerce During COVID-19: An Integration Of Theory Of Planned Behavior (TPB) With Trust. British Food Journal, 125(1), 112-131.
Hong, C., Choi, H. (Hailey), Choi, E. K. (Cindy), & Joung, H. W. (David). (2021). Factors affecting customer intention to use online food delivery services before and during the COVID-19 pandemic. Journal of Hospitality and Tourism Management, 48, 509.
Hwang, J., & Choe, J. Y. (Jacey). (2019). Exploring perceived risk in building successful drone food delivery services. International Journal of Contemporary Hospitality Management, 31(8), 3249–3269.
Hwang, J., & Kim, H. (2019). Consequences of a green image of drone food delivery services: The moderating role of gender and age. Business Strategy and the Environment, 28(5), 872–884.
Hwang, J., Lee, J. S., & Kim, H. (2019). Perceived innovativeness of drone food delivery services and its impacts on attitude and behavioral intentions: The moderating role of gender and age. International Journal of Hospitality Management, 81, 94–103.
Islam, H., Jebarajakirthy, C., & Shankar, A. (2019). An Experimental Based Investigation into the Effects of Website Interactivity on Customer Behaviour In On-Line Purchase Context. Journal of Strategic Marketing, 29(2), 117–140.
Jain, R., Verma, M., & Jaggi, C. K. (2020). Impact on bullwhip effect in food industry due to food delivery apps. OPSEARCH, 58(1), 148–159.
Jasim, N. I., Kasim, H., & Mahmoud, M. A. (2022). Towards the Development of Smart and Sustainable Transportation System for Foodservice Industry: Modelling Factors Influencing Customer: Intention to Adopt Drone Food Delivery (DFD) Services. Sustainability, 14(5), 2852.
Jebarajakirthy, C., Maseeh, H. I., Morshed, Z., Shankar, A., Arli, D., & Pentecost, R. (2021). Mobile advertising: A systematic literature review and future research agenda. International Journal of Consumer Studies, 45(6), 1258–1291.
Karulkar, Y., Pahuja, J., Uppal, B. S., & Sayed, S. (n.d.). Examining UTAUT Model To Explore Consumer Adoption In Online Food Delivery (OFD) Services. Pramana Research Journal, 9(8),146-162.
Koiri, S. K., Mukherjee, S., & Dutta, S. (2019). A Study on Determining the Factors Impacting Consumer Perception Regarding the Online Food Delivery Apps in Guwahati. Procedia - Social and Behavioral Sciences, 62, 1138–1143.
Kumar, S., Jain, A., & Hsieh, J. K. (2021). Impact of apps aesthetics on revisit intentions of food delivery apps: The mediating role of pleasure and arousal. Journal of Retailing and Consumer Services, 63.
Lee, S. W., Sung, H. J., & Jeon, H. M. (2019). Determinants of Continuous Intention on Food Delivery Apps: Extending UTAUT2 with Information Quality. Sustainability, 11(11), 3141.
Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How Habit Limits The Predictive Power Of Intention: The Case Of Information Systems Continuance. MIS Quarterly: Management Information Systems, 31(4), 705-737.
Muangmee, C., Kot, S., Meekaewkunchorn, N., Kassakorn, N., & Khalid, B. (2021). Factors determining the behavioral intention of using food delivery apps during covid-19 pandemics. Journal of Theoretical and Applied Electronic Commerce Research, 16(5), 1297–1310.
Okumus, B., Ali, F., Bilgihan, A., & Ozturk, A. B. (2018). Psychological factors influencing customers’ acceptance of smartphone diet apps when ordering food at restaurants. International Journal of Hospitality Management, 72, 67–77.
Palau-Saumell, R., Forgas-Coll, S., Sánchez-García, J., & Robres, E. (2019). User Acceptance of Mobile Apps for Restaurants: An Expanded and Extended UTAUT-2. Sustainability, 11(4), 1210.
Pavlou, P. A. (2002). What Drives Electronic Commerce? A Theory of Planned Behaviour Perspective. Academy of Management Proceedings, 2002(1), A1–A6.
Puriwat, W., & Tripopsakul, S. (2021). Understanding food delivery mobile application technology adoption: A utaut model integrating perceived fear of covid-19. Emerging Science Journal, 5(Special issue), 94–104.
Ramos de Luna, I., Thursamy, R., Javier Montoro-Ríos, F., M Christino, J. M., Aurélio Abreu Cardozo, É., Petrin, R., … de Aguiar, L. H. (2021). Factors Influencing the Intent and Usage Behavior of Restaurant Delivery Apps. Review of Business Management, 23(1), 21–42.
Ray, A., Dhir, A., Bala, P. K., & 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.
Saad, A. T. (2021). Factors affecting online food delivery service in Bangladesh: an empirical study. British Food Journal, 123(2), 535–550.
Shah, A. M., Yan, X., & Qayyum, A. (2021). Adoption Of Mobile Food Ordering Apps For O2O Food Delivery Services During The COVID-19 Outbreak. British Food Journal, 124(11), 3368-3395.
Shankar, A., & Jain, S. (2021). Factors affecting luxury consumers’ webrooming intention: A moderated-mediation approach. Journal of Retailing and Consumer Services, 58, 102306.
Shankar, A., Jebarajakirthy, C., Nayal, P., Maseeh, H. I., Kumar, A., & Sivapalan, A. (2022). Online food delivery: A systematic synthesis of literature and a framework development. International Journal of Hospitality Management, 104.
Shao, Z., Zhang, L., Li, X., & Guo, Y. (2019). Antecedents of trust and continuance intention in mobile payment platforms: The moderating effect of gender. Electronic Commerce Research and Applications, 33.
Shaw, N., & Sergueeva, K. (2019). The non-monetary benefits of mobile commerce: Extending UTAUT2 with perceived value. International Journal of Information Management, 45, 44-55.
Shroff, A., Shah, B. J., & Gajjar, H. (2022). Online food delivery research: a systematic literature review. International Journal of Contemporary Hospitality Management, 34(8), 2852–2883.
Tamilmani, K., Rana, N. P., Wamba, S. F., & Dwivedi, R. (2021). The extended Unified Theory of Acceptance and Use of Technology (UTAUT2): A systematic literature review and theory evaluation. International Journal of Information Management, 57.
Tandon, A., Jabeen, F., Talwar, S., Sakashita, M., & Dhir, A. (2021). Facilitators and inhibitors of organic food buying behavior. Food Quality and Preference, 88, 104077.
Tandon, A., Kaur, P., Bhatt, Y., Mäntymäki, M., & Dhir, A. (2021). Why do people purchase from food delivery apps? A consumer value perspective. Journal of Retailing and Consumer Services, 63.
Tang, D., Gong, X., & Liu, M. (2022). Residents’ behavioural intention to participate in neighbourhood micro-renewal based on an extended theory of planned behaviour: A case study in Shanghai, China. Habitat International, 129.
Tomacruz, M. D. G., & Flor, N. T. (2018). Family perception and their buying behaviour for home-delivered food. Undefined, 18(4), 237-246.
Troise, C., O’Driscoll, A., Tani, M., & Prisco, A. (2021). Online food delivery services and behavioural intention – a test of an integrated TAM and TPB framework. British Food Journal, 123(2), 664-683.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance Of Information Technology: Toward A Unified View. MIS Quarterly: Management Information Systems, 27(3), 425-478.
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer Acceptance And Use Of Information Technology: Extending The Unified Theory Of Acceptance And Use Of Technology. MIS Quarterly: Management Information Systems, 36(1), 157-178.
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2016). Unified Theory Of Acceptance And Use Of Technology: A Synthesis And The Road Ahead. Journal of the Association for Information Systems, 17(5).
Wang, O., & Scrimgeour, F. (2022). Consumer adoption of online-to-offline food delivery services in China and New Zealand. British Food Journal, 124(5), 1590–1608.
Wen, H., Pookulangara, S., & Josiam, B. M. (2022). A comprehensive examination of consumers’ intentions to use food delivery apps. British Food Journal, 124(5), 1737–1754.
Yen, Y. S. (2022). Channel Integration Affects Usage Intention In Food Delivery Platform Services: The Mediating Effect Of Perceived Value. Asia Pacific Journal of Marketing and Logistics, 35(1), 54-73.
Yeo, S. F., Tan, C. L., Teo, S. L., & Tan, K. H. (2021). The role of food apps servitization on repurchase intention: A study of FoodPanda. International Journal of Production Economics, 234.
Yeo, V. C. S., Goh, S. K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services. Journal of Retailing and Consumer Services, 35, 150–162.
Zanetta, L. D. A., Hakim, M. P., Gastaldi, G. B., Seabra, L. M. A. J., Rolim, P. M., Nascimento, L. G. P., … da Cunha, D. T. (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 (Ottawa, Ont.), 149, 110671.
Zhao, Y., & 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

Gadiman, N. S. B., & Mohamed, N. N. (2024). Developing and Validating the Measurement Model for Technology Acceptance Factors of Online Food Delivery Applications (OFDA) Usage Constructs in Sarawak Using Confirmatory Factor Analysis (CFA). International Journal of Academic Research in Business and Social Sciences, 14(10), 2551–2574.

Copyright: © 2024 The Author(s)
Published by HRMARS (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode