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Investigating the Relationship between Technology Acceptance Factors and Behavioural Intention to Use of Online Food Delivery Applications in Sarawak

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The current study investigated the relationships between technology acceptance factors and behavioural intention to use of online food delivery applications in Sarawak. The framework of this research was drawn from the perspective of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) model with two additional constructs, namely trust and risk. The study was based on a sample gathered from users of online food delivery applications in Sarawak. Data were collected using a self-administered online questionnaire. Of the 411 returned questionnaires, 400 questionnaires were valid for analysis. IBM-SPSS Amos 24.0 procedures were utilised to analyse the data and test the hypotheses. The findings of the study lead to the conclusion that the relationship between 6 constructs (effort expectancy, facilitating condition, hedonic motivation, trust and risk) and behavioural intention to use online food delivery applications are significant. Meanwhile, there are not significant relationship between 4 constructs (performance expectancy, social influence, price value and habit) and behavioural intention to use online food delivery applications. The significance of the findings enable to highlight the important factors for promoting online food delivery applications among users in aforesaid context.
Agus, A., Sabang, T. I. E. S., & Aceh, B. (n.d.). The Influence of Online Food Delivery Service Quality on Customer Satisfaction and Customer Loyalty: The Role of Personal Innovativeness. Journal of Environmental Treatment Techniques, 2020(1), 6–12. Retrieved January 25, 2022, from http://www.jett.dormaj.com
Alalwan, A. A. (2020a). 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.
https://doi.org/10.1016/J.IJINFOMGT.2019.04.008
Alalwan, A. A. (2020b). Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse. Undefined, 50, 28–44. https://doi.org/10.1016/J.IJINFOMGT.2019.04.008
Pitchay, A., Ganesan, Y., Zulkifli, N. S., & Khaliq, A. (2021). Determinants of customers’ intention to use online food delivery application through smartphone in Malaysia. British Food Journal. https://doi.org/10.1108/BFJ-01-2021-0075/FULL/HTML
Alvi. (2016). Munich Personal RePEc Archive A Manual for Selecting Sampling Techniques in Research.
Awang, Z. (2015). SEM made simple: A gentle approach to learning structural equation modeling. MPWS Rich Publication, Bandar Baru Bangi.
Awang, Z., SH., L., & Zainudin, N. (2018). Pendekatan Mudah SEM- Structural Equation Modelling. Bandar Baru Bangi, MPWS Rich Resources.
Awang, Z., Wan Afthanorhan, W. M. A., & Asri, M. A. M. (2015). Parametric and Non Parametric Approach in Structural Equation Modeling (SEM): The Application of Bootstrapping. Modern Applied Science, 9(9). https://doi.org/10.5539/MAS.V9N9P58
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.
https://doi.org/10.1016/J.IJHM.2020.102677
Chai, L. T., Ng, D., & Yat, C. (2019). Online Food Delivery Services: Making Food Delivery the New Normal. 1(1).
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. https://doi.org/10.1016/J.IJHM.2018.06.019
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. https://doi.org/10.1007/S10796-018-9883-2
Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/BF03193146
Foodpanda records 100pct growth in 2017. (n.d.). Retrieved May 2, 2023, from https://www.nst.com.my/business/2018/06/381431/foodpanda-records-100pct-growth-2017
Forsythe, S. M., & Shi, B. (2003). Consumer patronage and risk perceptions in Internet shopping. Journal of Business Research, 56(11), 867–875.
https://doi.org/10.1016/S0148-2963(01)00273-9
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. https://doi.org/10.1108/IJCHM-06-2019-0595
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. https://doi.org/10.1108/JHTT-10-2019-0126
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
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. https://doi.org/10.1108/BFJ-03-2021-0338
Hassan, M. (2018). Effect of rebranding on the customer satisfaction of Foodpanda Bangladesh Limited. BRAC Business School.
https://www.academia.edu/72761878/Effect_of_rebranding_on_the_customer_satisfaction_of_Foodpanda_Bangladesh_Limited
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. https://doi.org/10.1108/IJCHM-07-2018-0558
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. https://doi.org/10.1002/BSE.2289
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. https://doi.org/10.1007/S12597-020-00469-2.PDF
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’s Intention to Adopt Drone Food Delivery (DFD) Services. Sustainability 2022, Vol. 14, Page 2852, 14(5), 2852. https://doi.org/10.3390/SU14052852
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.
https://doi.org/10.1111/IJCS.12728
Kang, H. (2021). Sample size determination and power analysis using the G*Power software. J Educ Eval Health Prof. https://doi.org/10.3352/jeehp.2021.18.17
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.
https://doi.org/10.1016/J.SBSPRO.2012.09.195
Kumar, S., & Shah, A. (2021). Revisiting food delivery apps during COVID-19 pandemic? Investigating the role of emotions. Journal of Retailing and Consumer Services, 62. https://doi.org/10.1016/J.JRETCONSER.2021.102595
Lee, S. W., Sung, H. J., & Jeon, H. M. (2019). Determinants of continuous intention on food delivery apps: Extending UTAUT2 with information quality. Sustainability (Switzerland), 11(11). https://doi.org/10.3390/SU11113141
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. https://doi.org/10.2307/25148817
Nayan, M. N., & Hassan, M. K. A. (2020). CUSTOMER SATISFACTION EVALUATION FOR ONLINE FOOD SERVICE DELIVERY SYSTEM IN MALAYSIA. Journal of Information System and Technology Management, 5(19), 123–136. https://doi.org/10.35631/JISTM.5190010
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. https://doi.org/10.3390/JTAER16050073
Palau-Saumell, R., Forgas-Coll, S., Sanchez-Garcia, J., & Robres, E. (2019). User Acceptance of Mobile Apps for Restaurants: An Expanded and Extended UTAUT-2. Sustainability, 11(4), 1210. https://doi.org/10.3390/SU11041210
Poon, W. C., & Tung, H., En, S. (2022). The rise of online food delivery culture during the COVID-19 pandemic?: an analysis of intention and its associated risk culture. European Journal of Management and Business Economics, 0(0), 00–00. https://doi.org/10.1108/EJMBE-04-2021-0128
Ramli, N., Abd Ghani, F., Nazriah Wan Nawawi, W., & Adilin Mohd Abd Majid, H. (2021). Intention to Use Online Food Ordering Services Among Universities Students During COVID-19 Pandemic. International Journal of Academic Research in Business and Social Sciences, 1(13), 394–405. https://doi.org/10.6007/IJARBSS/v11-i13/8556
Ramos, K. (2022). Factors influencing customers’ continuance usage intention of food delivery apps during COVID-19 quarantine in Mexico. British Food Journal, 124(3), 833–852. https://doi.org/10.1108/BFJ-01-2021-0020
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. https://doi.org/10.1016/J.JRETCONSER.2019.05.025
Roh, M., & 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. https://doi.org/10.1016/J.IJINFOMGT.2018.09.017
Saad, A. T. (2021). Factors affecting online food delivery service in Bangladesh: an empirical study. British Food Journal, 123(2), 535–550. https://doi.org/10.1108/BFJ-05-2020-0449
Saunders, M., Lewis, P., & Thornhill, A. (2019). Understanding Reseach Philisophy and Approaches to Theory Development. Research Methods for Business Students.
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. https://doi.org/10.1016/J.IJHM.2022.103240
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. https://doi.org/10.1016/J.IJINFOMGT.2018.10.024
Siva, M., Nayak, D. P., & Narayan, K. A. (n.d.). Strengths and weaknesses of online surveys. IOSR Journal of Humanities and Social Sciences (IOSR-JHSS, 24(5). https://doi.org/10.9790/0837-2405053138
Suruhanjaya Komunikasi Dan Multimedia Malaysia Malaysian Communications And Multimedia Commission Internet Users Survey 2020. (n.d.). Retrieved July 18, 2021, from http://www.mcmc.gov.my
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. https://doi.org/10.1016/J.IJINFOMGT.2020.102269
Tan, S. Y., Lim, S. Y., & Yeo, S. F. (2021). Online food delivery services: cross-sectional study of consumers’ attitude in Malaysia during and after the COVID-19 pandemic. F1000Research 2021 10:972, 10, 972. https://doi.org/10.12688/f1000research.73014.1
Tandon, A., Kaur, P., Bhatt, Y., Mantymaki, M., & Dhir, A. (2021). Why do people purchase from food delivery apps? A consumer value perspective. Journal of Retailing and Consumer Services, 63. https://doi.org/10.1016/J.JRETCONSER.2021.102667
Tomacruz, M. D. G., & Flor, N. T. (2018). Family perception and their buying behavior for home-delivered food. Undefined, 18(4), 237–246.
https://doi.org/10.1080/15980634.2018.1551308
Uttley, J. (2019). Power Analysis, Sample Size, and Assessment of Statistical Assumptions—Improving the Evidential Value of Lighting Research.
Https://Doi.Org/10.1080/15502724.2018.1533851, 15(2–3), 143–162.
https://doi.org/10.1080/15502724.2018.1533851
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. https://doi.org/10.1108/BFJ-06-2021-0655
Wu, M. J., Zhao, K., & Fils-Aime, F. (2022). Response rates of online surveys in published research: A meta-analysis. Computers in Human Behavior Reports, 7, 100206. https://doi.org/10.1016/J.CHBR.2022.100206
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. https://doi.org/10.1016/J.IJPE.2021.108063
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. https://doi.org/10.1016/J.JRETCONSER.2016.12.013
Zanetta, L. D. A., Hakim, M. P., Gastaldi, G. B., Seabra, L. M. A. J., Rolim, P. M., Nascimento, L. G. P., Medeiros, C. O., & 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, 149. https://doi.org/10.1016/J.FOODRES.2021.110671
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. https://doi.org/10.1016/J.IJHM.2020.102683