International Journal of Academic Research in Business and Social Sciences

search-icon

Investigating the Mediating Effect of Behavioural Intention to Use in the Relationships between Technology Acceptance Factors and Usage of Online Food Delivery Applications in Sarawak

Open access
The current study investigated the mediating of behavioural intention to use in the relationships between technology acceptance factors and usage 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. This study focused on the significance of all constructs of the proposed conceptual model, and new findings pertaining to these constructs have been highlighted. The findings of the study lead to the conclusion that there are significant relationship was supported (effort expectancy, facilitating condition, hedonic motivation, trust and risk). For the remaining constructs (performance expectancy, social influence, price value and habit) no significant relationship was found. Meanwhile, there is a significant relationship between behavioural intention to use and online food delivery applications usage. Further, behavioural intention to use was found to be a strong mediator for most of the relationships investigated in the theoretical model of this study. The significance of the findings enable to highlight the important factors for promoting online food delivery applications among users in aforesaid context.
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
Memon, A. M., Cheah, J.-H., Ting, R. H. T., & Chuah, F. (2018). Journal of Applied Structural Equation Modeling Editorial Mediation Analysis Issues And Recommendations. Journal of Applied Structural Equation Modeling, 2(1), 2590–4221.
Ali, S., Khalid, N., Javed, H. M. U., & Islam, D. M. Z. (2020). Consumer Adoption of Online Food Delivery Ordering (OFDO) Services in Pakistan: The Impact of the COVID-19 Pandemic Situation. Journal of Open Innovation: Technology, Market, and Complexity 2021, Vol. 7, Page 10, 7(1), 10. https://doi.org/10.3390/JOITMC7010010
Allah 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., Hui, L. S., & Zainudin, N. F. (2018). Pendekatan Mudah SEM- Structural Equation Modelling.
Awang, Z. (2015a). SEM Made Simple: A Gentle Approach to Learning Sructural Equation Modelling. MPWS Rich Publication.
Awang, Z. (2015b). 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., 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
Bhattacherjee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems. https://doi.org/10.1016/S0167-9236(01)00111-7
Bhattacherjee, A., & Lin, C. P. (2015). A unified model of IT continuance: Three complementary perspectives and crossover effects. In European Journal of Information Systems. https://doi.org/10.1057/ejis.2013.36
Candra, S., Ayudina, M., & Arashi, M. A. (2021). The Impact of Online Food Applications during the Covid-19 Pandemic. International Journal of Technology, 12(3), 472–484. https://doi.org/10.14716/IJTECH.V12I3.4195
Chai, L. T., Ng, D., & Yat, C. (2019). Online Food Delivery Services: Making Food Delivery the New Normal. 1(1).
Dat Tran, V., Rizov, M., & Rosen, M. A. (2021). Using Mobile Food Delivery Applications during the COVID-19 Pandemic: Applying the Theory of Planned Behavior to Examine Continuance Behavior. Sustainability 2021, Vol. 13, Page 12066, 13(21), 12066. https://doi.org/10.3390/SU132112066
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
Gunden, N., Morosan, C., & DeFranco, A. (2020). 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
Gurbuz, S., & Bayik, M. E. (2021). Summary A New Approach for Mediation Analysis: Is Baron and Kenny’s Method Still Valid? Turkish Journal of Psychology, 36(88), 15–19. https://doi.org/10.31828/tpd1300443320191125m000031
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
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
Jenayah tipu dalam talian meningkat kepada 2,816 kes sepanjang 2021 | Utusan Borneo Online. (n.d.). Retrieved March 31, 2023, from
https://www.utusanborneo.com.my/2022/03/21/jenayah-tipu-dalam-talian-meningkat-kepada-2816-kes-sepanjang-2021
Jugah, I., Yi, S. C., Yusuf, A. N., Alfred, O., & Sawai, A. (2022). Public Readiness and Acceptance Towards Implementation of Sarawak Digital Economy: A Case Study in Kuching, Sarawak. Journal of Administrative Science, 19, 109–118. http:jas@uitm.edu.my
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
Karulkar, Y., Pahuja, J., Uppal, B. S., & Sayed, S. (n.d.). Examining UTAUT model to explore consumer adoption in Online Food Delivery (OFD) services. Retrieved July 30, 2022, from https://pramanaresearch.org
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
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
MacKinnon, D. P., Coxe, S., & Baraldi, A. N. (2012). Guidelines for the Investigation of Mediating Variables in Business Research. Journal of Business and Psychology, 27(1), 1–14. https://doi.org/10.1007/S10869-011-9248-Z
Mat Nayan, 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
Meule, A. (2019). Contemporary Understanding of Mediation Testing. 3. https://doi.org/10.15626/MP.2018.870
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, S. E. H. (2022). Consumer risk perception of online food delivery during the COVID-19 Movement Control Order (MCO) in Malaysia. Journal of Foodservice Business Research. https://doi.org/10.1080/15378020.2022.2054657
Prabowo, G. T., & Nugroho, A. (2019). Factors that Influence the Attitude and Behavioral Intention of Indonesian Users toward Online Food Delivery Service by the Go-Food Application. 204–210. https://doi.org/10.2991/ICBMR-18.2019.34
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. https://doi.org/10.28991/ESJ-2021-SPER-08
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
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
Sarawak has very high level of low-income families based on latest poverty criteria | The Star. (n.d.). Retrieved March 22, 2023, from https://www.thestar.com.my/news/nation/2020/07/13/sarawak-has-very-high-level-of-low-income-families-based-on-latest-poverty-criteria
Sarawak serius bangunkan sistem penghantaran e-dagang | Utusan Borneo Online. (n.d.). Retrieved April 1, 2023, from https://www.utusanborneo.com.my/2021/11/11/sarawak-serius-bangunkan-sistem-penghantaran-e-dagang
Saunders, M., Lewis, P., & Thornhill, A. (2019). Understanding Reseach Philisophy and Approaches to Theory Development. Research Methods for Business Students.
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
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., Mäntymäki, 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
Time To Narrow Economic Gap Between Peninsular And East Malaysia | BusinessToday. (n.d.). Retrieved March 22, 2023, from https://www.businesstoday.com.my/2021/10/04/time-to-narrow-economic-gap-between-peninsular-and-east-malaysia/
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
Top 12 food delivery platforms for F&B merchants in Malaysia – Yellow Bees. (n.d.). Retrieved September 10, 2022, from https://www.yellowbees.com.my/top-food-delivery-platforms-malaysia/
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
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. https://doi.org/10.2307/30036540
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. https://doi.org/10.2307/41410412
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
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. https://doi.org/10.1108/APJML-05-2021-0372
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