FACTORS INFLUENCING CUSTOMER SATISFACTION AND REPURCHASE INTENTION OF ONLINE FOOD DELIVERY SERVICE IN CAMBODIA
DOI:
https://doi.org/10.60101/gbafr.2024.272298Keywords:
UTAUT-2, Customer satisfaction, Repurchase intention, Trust, Online food deliveryAbstract
Purpose – The focus of this research is to identify and analyze the key factors that influence repurchase intention of online food delivery services in Cambodia. It aims to understand how aspects such as performance expectancy, effort expectancy, social influence, facilitating condition, hedonic motivation, price value, habit, and trust, impact consumers' satisfaction to continue using these services.
Methodology – A quantitative method was employed using a purposive sampling survey, involving 400 respondents in Phnom Penh with prior experience using online food delivery services. Data were collected through a Google Form and analyzed using multiple regression to test the proposed model.
Results – The study revealed that performance expectancy, effort expectancy, and trust positively influence customer satisfaction (CS), with standardized regression weights of B = 0.194, B = 0.409, and B = 0.079, respectively. Among these factors, effort expectancy has the greatest impact on CS. Conversely, price value negatively affects CS, with a coefficient of B = -0.072. However, social influence, facilitating conditions, hedonic motivation, and habit do not positively impact customer satisfaction (CS) because their p-values exceeded 0.05. Lastly, customer satisfaction has a positive and significant effect on repurchase intention, with a coefficient of B = 0.635.
Implications – Enhancing performance expectancy, trust, and the ease of the ordering process while addressing pricing perceptions is crucial for improving customer satisfaction and driving repurchase intentions in online food delivery services in Cambodia.
Originality/Value – This study provides valuable insights for anyone seeking a comprehensive understanding of the food delivery service landscape on online platforms in Cambodia. In particular, the app developers, restaurants, and food providers can consider partnering with promising and quality-oriented online food delivery services to enhance their business prospects.
References
Al-Gahtani, S. S., Hubona, G. S., & Wang, J. (2007). Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT. Information & Management, 44(8), 681–691. http://dx.doi.org/10.1016/j.im.2007.09.002
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. https://doi.org/10.1016/j.ijinfomgt.2019.04.008
Amin, M., Rezaei, S., & Abolghasemi, M. (2014). User satisfaction with mobile websites: the impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust. Nankai Business Review International, 5(3), 258-274. https://doi.org/10.1108/NBRI-01-2014-0005
Armstrong, R. L. (1987). The Midpoint on a Five-Point Likert-Type Scale. Perceptual and Motor Skills, 64(2), 359–362. https://doi.org/10.2466/pms.1987.64.2.359
Brown, S. A., & Venkatesh, V. (2005). A model of adoption of technology in the household: A baseline model test and extension incorporating household life cycle. Management Information Systems Quarterly, 29(3), 11. http://dx.doi.org/10.2307/25148690
Carvalho, H., Saldanha, E., & Amaral, A. (2020). The Mediation Effects of Customer Satisfaction on the Relations Between Product Price, Service Quality and Purchasing Decision. Timor Leste Journal of Business and Management, 2(2), 14-26. https://doi.org/10.51703/bm.v2i2.18
Cha, S. S., & Lee, S. H. (2021). The effects of user experience factors on satisfaction and repurchase intention at online food market. The Journal of Industrial Distribution & Business, 12(4), 7–13. https://doi.org/10.13106/jidb.2021.vol12.no4.7
Chan, F. K. Y., Thong, J. Y. L., Venkatesh, V., Brown, S. A., Hu, P. J. H., & Tam, K. Y. (2010). Modeling citizen satisfaction with mandatory adoption of an e-government technology. Journal of the Association for Information Systems, 11(10), 519–549. https://doi.org/10.17705/1jais.00239
Chenarides, L., Grebitus, C., Lusk, J. L., Printezis, I., & Carey, W. P. (2020). Food consumption behavior during the COVID-19 pandemic. Agribusiness, 37. https://doi.org/10.1002/agr.21679
Chiu, C. M., Chang, C. C., Cheng, H. L., & Fang, Y. H. (2009). Determinants of customer repurchase intention in online shopping. Online Information Review, 33(4), 761–784. https://doi.org/10.1108/14684520910985710
Deng, Z., Mo, X., & Liu, S. (2014). Comparison of the middle-aged and older users’ adoption of mobile health services in China. International Journal of Medical Informatics, 83(3), 210–224. https://doi.org/10.1016/j.ijmedinf.2013.12.002
Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers’ product evaluations. Journal of Marketing Research, 28(3), 307–319. https://doi.org/10.2307/3172866
Duyck, P., Pynoo, B., Devolder, P., Voet, T., Adang, L., Ovaere, D., & Vercruysse, J. (2010). Monitoring the PACS implementation process in a large university hospital—discrepancies between radiologists and physicians. Journal of Digital Imaging, 23, 73–80. https://doi.org/10.1007/s10278-008-9163-7
Gilitwala, B., & Nag, A. K. (2019). A study of factors influencing repurchase intention of online food delivery in Bangkok, Thailand. International Journal on Emerging Technologies, 10(3), 193–201.
Gruen, T. W., Osmonbekov, T., & Czaplewski, A. J. (2006). eWOM: The impact of customer-to-customer online know-how exchange on customer value and loyalty. Journal of Business Research, 59(4), 449–456. https://doi.org/10.1016/j.jbusres.2005.10.004
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
Hellier, P. K., Geursen, G. M., Carr, R. A., & Rickard, J. A. (2003). Customer repurchase intention: A general structural equation model. European Journal of Marketing, 37(11/12), 1762–1800. https://doi.org/10.1108/03090560310495456
Hsiao, C.-H., Chang, J.-J., & Tang, K.-Y. (2016). Exploring the influential factors in continuance usage of mobile social Apps: Satisfaction, habit, and customer value perspectives. Telematics and Informatics, 33(2), 342–355. https://doi.org/10.1016/j.tele.2015.08.014
Iyer, P., Davari, A., & Mukherjee, A. (2018). Investigating the effectiveness of retailers’ mobile applications in determining customer satisfaction and repatronage intentions? A congruency perspective. Journal of Retailing and Consumer Services, 44, 235–243. https://doi.org/10.1016/j.jretconser.2018.07.017
Jasperson, ’Jon, Carter, P. E., & Zmud, R. W. (2005). A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Quarterly, 525–557. https://doi.org/10.2307/25148694
Kaewkitipong, L., Chen, C. C., & Ractham, P. (2016). Using social media to enrich information systems field trip experiences: Students’ satisfaction and continuance intentions. Computers in Human Behavior, 63, 256–263. https://doi.org/10.1016/j.chb.2016.05.030
Kemp, S. (2022). Digital 2022: Global Overview Report. https://datareportal.com/reports/digital-2022-global-overview-report
Kim, M. J., Chung, N., & Lee, C. K. (2011). The effect of perceived trust on electronic commerce: Shopping online for tourism products and services in South Korea. Tourism Management, 32(2), 256–265. https://doi.org/10.1016/j.tourman.2010.01.011
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, 705–737. https://doi.org/10.2307/25148817
Lim, W. M., & Rasul, T. (2022). Customer engagement and social media: Revisiting the past to inform the future. Journal of Business Research, 148, 325-342. https://doi.org/10.1016/j.jbusres.2022.04.068
Lin, C.-C., Wu, H.-Y., & Chang, Y.-F. (2011). The critical factors impact on online customer satisfaction. Procedia Computer Science, 3, 276–281. https://doi.org/10.1016/j.procs.2010.12.047
Lin, C., & Lekhawipat, W. (2014). Factors affecting online repurchase intention. Industrial Management & Data Systems, 114(4), 597-611. https://doi.org/10.1108/IMDS-10-2013-0432
Mahande, R. D., & Malago, J. D. (2019). An E-Learning Acceptance Evaluation through UTAUT Model in a Postgraduate Program. Journal of Educators Online, 16(2), n2. https://doi.org/10.9743/JEO.2019.16.2.7
Maillet, É., Mathieu, L., & Sicotte, C. (2015). Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an Electronic Patient Record in acute care settings: An extension of the UTAUT. International Journal of Medical Informatics, 84(1), 36–47. https://doi.org/10.1016/j.ijmedinf.2014.09.004
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
Nordhoff, S., Louw, T., Innamaa, S., Lehtonen, E., Beuster, A., Torrao, G., Bjorvatn, A., Kessel, T., Malin, F., Happee, R., & others. (2020). Using the UTAUT2 model to explain public acceptance of conditionally automated (L3) cars: A questionnaire study among 9,118 car drivers from eight European countries. Transportation Research Part F: Traffic Psychology and Behaviour, 74, 280–297. https://doi.org/10.1016/j.trf.2020.07.015
Raman, A., Don, Y., Khalid, R., & Rizuan, M. (2014). Usage of learning management system (Moodle) among postgraduate students: UTAUT model. Asian Social Science, 10(14), 186–192. https://doi.org/10.5539/ass.v10n14p186
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-12-2022-1141
Rasli, M. A. M., Zulkefli, N. H., Salleh, N. S. A., Ghani, F. A., Razali, N. A., & Idris, R. S. N. R. (2020). Determinants of Behavioural Intention on Online Food Delivery (OFD) APPS: Extending UTAUT2 with Information Quality. Global Business & Management Research, 12(4), 679-689.
Ren, S., Kwon, S. D., & Cho, W. S. (2020). Online Food Delivery (OFD) services in Cambodia: A study of the factors influencing consumers’ behavioral intentions to use. ResearchGate. https://www.researchgate.net/publication/349552360_Online_Food_Delivery_OFD_services_in_Cambodia_A_study_of_the_factors_influencing_consumers'_behavioral_intentions_to_use
Schiffman, L. G., & Kanuk, L. L. (2004). Consumer Behaviour (8th edition). Prentice Hall.
Statista. (n.d.). Online Food Delivery - Cambodia. https://www.statista.com/outlook/dmo/online-food-delivery/cambodia.
Uzir, M. U. H., Al Halbusi, H., Thurasamy, R., Hock, R. L. T., Aljaberi, M. A., Hasan, N., & Hamid, M. (2021). The effects of service quality, perceived value and trust in home delivery service personnel on customer satisfaction: Evidence from a developing country. Journal of Retailing and Consumer Services, 63, 102721. https://doi.org/10.1016/j.jretconser.2021.102721
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425–478. 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, 157–178. https://doi.org/10.2307/41410412
Verkasalo, H., López-Nicolás, C., Molina-Castillo, F. J., & Bouwman, H. (2010). Analysis of users and non-users of smartphone applications. Telematics and Informatics, 27(3), 242–255. https://doi.org/10.1016/j.tele.2009.11.001
Wang, E. S.-T., & Chu, Y.-H. (2020). Influence of consumer’s long-term orientation and safety consciousness on intention to repurchase certified functional foods. Journal of Food Products Marketing, 26(4), 247–261. https://doi.org/10.1080/10454446.2020.1757554
Wang, Y.-T., & Lin, K.-Y. (2021). Understanding continuance usage of mobile learning applications: The moderating role of habit. Frontiers in Psychology, 12, 736051. https://doi.org/10.3389/fpsyg.2021.736051
Yamane, T. (1967). Statistics: An Introductory Analysis (2nd Edition). Harper and Row.
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
Yoon, S.-J. (2002). The antecedents and consequences of trust in online-purchase decisions. Journal of Interactive Marketing, 16(2), 47–63. https://doi.org/10.1002/dir.10008
Zhou, T. (2011). An empirical examination of initial trust in mobile banking. Internet Research, 21(5), 527-540. https://doi.org/10.1108/10662241111176353
Zhu, Q., Feng, Y., & Choi, S. (2017). The role of customer relational governance in environmental and economic performance improvement through green supply chain management. Journal of Cleaner Production, 155(2), 46-53. https://doi.org/10.1016/j.jclepro.2016.02.124
Zulkarnain, K., Ahasanul, H., Selim, A., & others. (2015). Key success factors of online food ordering services: An empirical study. Malaysian Institute of Management, 50(2), 19–36.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Faculty of Business Administration, Rajamangala University of Technology Thanyaburi
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
