Main Article Content
Abstract
This research examines the issues that influence the behavioral intention of Gen Z customers to utilize online food delivery (OFD) services. This research focuses on the specific demographic of Gen Z clients who currently use online food delivery applications. In this regard, structural equation modeling (SEM) was employed to analyze the data collected from respondents. A purposeful sampling approach was used due to the characteristics of the research object. The findings demonstrate that convenience, hedonic motivation, indifference to the dining environment, service availability in unconventional hours, and time-saving significantly affect Gen Z customers' intention to choose OFD service. Therefore, this study might be crucial for app distribution operators, governmental and non-governmental entities, enterprises, and scholars to formulate policies and strategies that foster consumer engagement at a collective level. Finally, the findings of the present study provide valuable information for entrepreneurs and policymakers seeking to develop similar services.
Keywords
Article Details

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
- Abdullah, F., Ward, R., & Ahmed, E. (2016). Investigating the influence of the most commonly used external variables of TAM on students' perceived ease of use (PEOU) and perceived usefulness (PU) of e-portfolios. Computers in Human Behaviour, 63, 75–90. https://doi.org/10.1016/j.chb.2016.05.014
- Ajzen, I. (1991a). The theory of planned behaviour. Organizational Behaviour and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
- Ajzen, I. and Fishbein, M. (1985). The prediction of behaviour from attitudinal and normative variables. Journal of Experimental Social Psychology, Vol. 6, pp. 466-88. https://doi.org/10.1016/0022-1031(70)90057-0
- Akdim, K., Casaló, L. V., & Flavián, C. (2022). The role of utilitarian and hedonic aspects in the continuance intention to use social mobile apps. Journal of Retailing and Consumer Services, 66, 102888. https://doi.org/10.1016/j.jretconser.2021.102888
- Alagoz, S. M., & Hekimoglu, H. (2012). A study on tam: analysis of customer attitudes in online food ordering system. Procedia-Social and Behavioural Sciences, 62, 1138-1143. https://doi.org/10.1016/j.sbspro.2012.09.195
- 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
- Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Algharabat, R. (2018). Examining factors influencing Jordanian customers' intentions and adoption of internet banking: Extending UTAUT2 with risk. Journal of Retailing and Consumer Services, 40, 125138. https://doi.org/10.1016/j.jretconser.2017.08.026
- Andersen, J.C. and Gerbing, D.W. (1988). Structural equation modelling in practice. A review and recommended two-step approach. Psychological Bulletin, Vol. 103 No. 3, pp. 411-423. https://psycnet.apa.org/doi/10.1037/0033-2909.103.3.411
- Asheq, A. A., Tanchi, K. R., Akhter, S., Kamruzzaman, M., & Islam, K. A. (2022). Examining university students' behaviours towards online shopping: An empirical investigation in an emerging market. Innovative Marketing, 18(1), 94-103. http://dx.doi.org/10.21511/im.18(1).2022.08
- Banerjee, S. P., Jain, D., & Nayyar, R. (2019). Measuring service quality of food delivery services: a study of generation Z. African Journal of Hospitality, Tourism and Leisure, 8(2), 1–12.
- Barnard-Brak, L., Burley, H., & Crooks, S. M. (2010). Explaining youth mentoring behaviour using a theory of planned behaviour perspective. International Journal of Adolescence and Youth, 15(4), 365–379. https://doi.org/10.1080/02673843.2010.9748040
- Belanche, D., Flavian, M., & Perez-Rueda, A. (2020). Mobile Apps Use and WOM in the Food Delivery Sector: The Role of Planned Behaviour, Perceived Security and Customer Lifestyle Compatibility. Sustainability, 12(10), 4275-4275. https://doi.org/10.3390/su12104275
- Bentler, P. M., & Bonett, D. G. (1980). Significance Tests and Goodness-of-Fit in the Analysis of Covariance Structures. Psychological Bulletin, 88, 588-600.
- Berkup, S. B. (2014). Working with generations X and Y in generation Z period: Management of different generations in business life. Mediterranean journal of social Sciences, 5(19), 218-229. https://doi.org/10.5901/mjss.2014.v5n19p218
- Bhatnagar, A., Sanjog, M. and Rao, H.R. (2000). On Risk, Convenience, and Internet Shopping Behaviour. Communications of the ACM, 43, 98-105. https://doi.org/10.1145/353360.353371
- Bhattacherjee, Anol. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly. 25. 351-370. 10.2307/3250921.
- Blackwell, R.D., Paul, W.M. and James, F.E. (2006). Attributes of attitudes. Consumer Behaviour, Thomson Press, New York, NY, pp. 235-43.
- Bouarar, A. C., Mouloudj, S., & Mouloudj, K. (2021). Extending the theory of planned behaviour to explain intention to use online food delivery services in the context of COVID-19 pandemic. University of South Florida (USF) M3 Publishing, 5(2021), 47. https://www.doi.org/10.5038/9781955833035
- 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), 399-426.
- Burns, R.B. and Burns, R.A. (2008). Business Research Methods and Statistics Using SPSS. SAGE, Los Angeles, CA.
- Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). Routledge.
- Cai, S. and Jun, M. (2003). Internet users' perceptions of online service quality: a comparison of online buyers and information searchers. Managing Service Quality: an International Journal, Vol. 13 No. 6, pp. 504-519. https://doi.org/10.1108/09604520310506568
- Canny, I. U. (2014). Measuring the mediating role of dining experience attributes on customer satisfaction and its impact on behavioural intentions of casual dining restaurant in Jakarta. International Journal of Innovation, Management and Technology, 5(1), 25–29.
- Chai, L.T. and Yat, DNC (2019). Online food delivery services: making food delivery the new normal. Journal of Marketing Advances and Practices, Vol. 1 No. 1, pp. 62-77.
- Chan, K., & Li, Q. (2022). Attributes of young adults' favorite retail shops: a qualitative study. Young Consumers, 23(4), 555-569. https://doi.org/10.1108/YC-01-2022-1442
- Chandrasekhar, N., Gupta, S. and Nanda, N. (2019). Food delivery services and customer preference: a comparative analysis. Journal of Foodservice Business Research, Vol. 22 No. 4, pp. 375-386. https://doi.org/10.1080/15378020.2019.1626208
- Chang, M.K., Cheung, W. and Lai, V.S. (2005). Literature derived reference models for the adoption of online shopping. Information and Management, Vol. 42 No. 4, pp. 543-559. https://doi.org/10.1016/j.im.2004.02.006
- Chen, H. and Hsieh, Y. (2017). The driving success factors of the online food ordering system – empirical evidence from the UTAUT model.
- Chen, H. S., Liang, C. H., Liao, S. Y., & Kuo, H. Y. (2020). Consumer attitudes and purchase intentions toward food delivery platform services. Sustainability, 12(23), 10177. https://doi.org/10.3390/su122310177
- Chen, J.S., Tsou, T.H. and Huang, A.Y. (2009). Service delivery innovation: antecedents and impact on firm performance, Journal of Service Research, Vol. 12 No. 1, pp. 36-55. https://doi.org/10.1177/1094670509338619
- Chen, N. H., & Hung, Y.-W. (2015). Online shopping orientation and purchase behaviour for high-touch products. International Journal of Electronic Commerce Studies, 6(2), 187–202. https://doi.org/10.7903/ijecs.1401
- Chen, X. H., & Lee, T. J. (2022). Potential effects of green brand legitimacy and the biospheric value of eco-friendly behaviour on online food delivery: amediation approach. International Journal of Contemporary Hospitality Management, 34(11), 4080-4102. https://doi.org/10.1108/IJCHM-07-2021-0892
- Cho, M., Bonn, M. A., & Li, J. J. (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
- Correaa, J.C., Garzon, W., Brooker, P., Sakarkar, G., Carranzaa, S.A., Yunadoa, L. and Rincona, A. (2018). Evaluation of collaborative consumption of food delivery services through web mining techniques. Journal of Retailing and Consumer Services, Vol. 46, pp. 45-50. https://doi.org/10.1016/j.jretconser.2018.05.002
- Das, J. (2018). Consumer perception towards online food ordering and delivery services: an empirical study. Journal of Management, Vol. 5 No. 5, pp. 155-163
- Das, S. and Ghose, D. (2019).Influence of online food delivery apps on the operations of the restaurant business. International Journal of Scientific and Technology Research, Vol. 8 No. 12, pp. 1372-1377.
- Daud, D. and Yoong, H.M. (2019). The relationship between consumers' price-saving orientation and time-saving orientation towards food delivery intermediaries (fdi) services: an exploratory study. Global Scientific Journals, Vol. 7 No. 2, pp. 175-190 .
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
- Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research. Addison-Wesley.
- Fornell, C. and Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50. https://doi.org/10.1177/002224378101800104
- Francioni, B., Curina, I., Hegner, S. M., & Cioppi, M. (2022). Predictors of continuance intention of online food delivery services: gender as moderator. International Journal of Retail & Distribution Management, 50(12), 1437–1457. https://doi.org/10.1108/IJRDM-11-2021-0537
- Gerbing, D. W., & Hunter, J. E. (1987). ITAN: A statistical package for ITem ANalysis including multiple groups confirmatory factor analysis. Portland, OR: Portland State University, Department of Management.
- Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: an organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185–214.
- 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. https://doi.org/10.1108/IJCTHR-01-2020-0013
- Ha, DN (2013). Demand creation of online services for B2B and consumer market–food delivery in Vietnam, M.Sc. Thesis, Tampere University of Technology.
- Hair, J. F., Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. New York: Pearson New International Edition, United States of America.
- Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1-2), 1–12.
- Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26(2), 106–121.
- Hair, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate data analysis (6th Edition). Upper Saddle River: Pearson Prentice Hall.
- Hair, J.F., Sarstedt, M., Ringle, C.M. and Mena, J.A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, Vol. 40 No. 3, pp. 414-433. https://doi.org/10.1007/s11747-011-0261-6
- Hamid, S., & Azhar, M. (2023). Behavioural intention to order food and beverage items using e-commerce during COVID-19: an integration of theory of planned behaviour (TPB) with trust. British Food Journal, 125(1), 112-131. https://doi.org/10.1108/BFJ-03-2021-0338
- Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen, D. J., Hair, J. F., Hult, G. T. M., & Calantone, R. J. (2014). Common Beliefs and Reality About PLS. Organizational Research Methods, 17(2), 182–209. https://doi.org/10.1177/1094428114526928
- Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Industrial Management & Data Systems, 116 (1), 2-20.
- Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the Academy of Marketing Science, 43(1), 115-135.
- Hirschberg, C., Rajko, A., Schumacher, T. and Wrulich, M. (2016). The changing market for food delivery. Available at: https://www.mckinsey.com/industries/high-tech/our-insights/thechanging-market-for-food-delivery.
- Hong, C., Choi, H. H., Choi, E.-K. C., & Joung, H.-W. D. (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, 509–518. https://doi.org/10.1016/j.jhtm.2021.08.012
- Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.
- Humaidi, N. F. A., Jamil, S. N. M., Gannasin, S. P., & Samat, N. (2024). Enhancing Users' Satisfaction: Revealing the Key Factors Influencing the Usage of Online Food Delivery Service Applications Among University Students. Journal of Tourism, Hospitality & Culinary Arts, 16 (1), 993-1010.
- Jebarajakirthy, C., & Shankar, A. (2021). Impact of online convenience on mobile banking adoption intention: A moderated mediation approach. Journal of Retailing and Consumer Services, 58, 102323. https://doi.org/10.1016/j.jretconser.2020.102323
- Jiang, L. A. , Y. Z. , & J. M. (2013). Measuring consumer perceptions of online shopping convenience. Journal of Service Management, 191–214. https://doi.org/10.1108/09564231311323962
- Josiam, B. M., & Henry, W. (2014). Eatertainment: Utilitarian and hedonic motivations for patronizing fun experience restaurants. Procedia-Social and Behavioural Sciences, 144, 187-202. https://doi.org/10.1016/j.sbspro.2014.07.287
- Kapoor, A. P., & Vij, M. (2018). Technology at the dinner table: Ordering food online through mobile apps. Journal of retailing and consumer services, 43, 342-351. https://doi.org/10.1016/j.jretconser.2018.04.001
- Kim, J. J., & Hwang, J. (2020). Merging the norm activation model and the theory of planned behaviour in the context of drone food delivery services: Does the level of product knowledge really matter?. Journal of Hospitality and Tourism Management, 42, 1-11. https://doi.org/10.1016/j.jhtm.2019.11.002
- Kim, M. J., & Kang, Y. (2023). Older adults' user experience of virtual tourism: exploring presence and experiential value with respect to age difference. Virtual Reality, 27(4), 2967-2987. https://doi.org/10.1007/s10055-023-00849-1
- Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Press.
- Lan, H., Yanan, L. and Shuhua, W. (2016). Improvement of online food delivery service based on consumers' negative comments. Canadian Social Science, 12 (5), 84-88.
- Lee, E. Y., Lee, S. B., & Jeon, Y. J. J. (2017). Factors influencing the behavioural intention to use food delivery apps. Social Behaviour and Personality: an international journal, 45(9), 1461-1473. https://doi.org/10.2224/sbp.6185
- Lee, W. S., Song, M., Moon, J., & Tang, R. (2023). Application of the technology acceptance model to food delivery apps. British Food Journal, 125(1), 49-64. https://doi.org/10.1108/BFJ-05-2021-0574
- Lin, T., Chen, Y., & Liu, C. (2022). Determinants of consumer intentions to use online food delivery services. Journal of Hospitality and Tourism Technology, 13(1), 1-19. https://doi.org/10.1108/BFJ-03-2021-0332
- Lina, Y., Hou, D., & Ali, S. (2022). Impact of online convenience on generation Z online impulsive buying behaviour: The moderating role of social media celebrity. Frontiers in Psychology, 13, 951249. https://doi.org/10.3389/fpsyg.2022.951249
- Marcoulides, G.A. and Saunders, C. (2006). PLS: a silver bullet?. MIS Quarterly, 30 (2), 3-9.
- Mehrolia S., Alagarsamy S., Solaikutty V.M. (2021). Customers response to online food delivery services during COVID-19 outbreak using binary logistic regression. International Journal of Consumer Studies, 45(3), 396–408. https://doi.org/10.1111/ijcs.12630
- Morganosky, M. A., & Cude, B. J. (2000). Consumer response to online grocery shopping. International Journal of Retail & Distribution Management, 28(1), 17–26. https://doi.org/10.1108/09590550010306737
- Na-Nan, K. (2020). Organizational behavior scale development. Bangkok: Triple Education.
- Nasir, A., Ahmed, M. A., Nazir, I., Zafar, H., & Zahid, Z. (2014). Impact of different determinants on customers satisfaction level (a case of fast food restaurant). International Journal of Business and Management Invention, 3(9), 32–40.
- Nguyen, T. T. H., Nguyen, N., Nguyen, T. B. L., Phan, T. T. H., Bui, L. P., & Moon, H. C. (2019). Investigating consumer attitude and intention towards online food purchasing in an emerging economy: An extended TAM approach. Foods, 8(11), 576. https://doi.org/10.3390/foods8110576
- Okumus, B. (2021). A qualitative investigation of Millennials' healthy eating behaviour, food choices, and restaurant selection. Food, Culture & Society, 24(4), 509-524. https://doi.org/10.1080/15528014.2021.1882168
- 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. https://doi.org/10.1016/j.ijhm.2018.01.001
- Ozturk, A. B., Nusair, K., Okumus, F., & Hua, N. (2016). The role of utilitarian and hedonic values on users' continued usage intention in a mobile hotel booking environment. International Journal of Hospitality Management, 57, 106–115. https://doi.org/10.1016/j.ijhm.2016.06.007
- Pan, J. Y., & Liu, D. (2022). Mask-wearing intentions on airplanes during COVID-19 – Application of theory of planned behaviour model. Transport Policy, 119, 32–44. https://doi.org/10.1016/j.tranpol.2022.01.023
- Pigatto, G., Machado, J.G., Negreti, A. and Machado, L. (2017). Have you chosen your request? Analysis of online food delivery companies in Brazil. British Food Journal, 119 (3), 639-657. https://doi.org/10.1108/BFJ-05-2016-0207
- Pillai, S. G., Kim, W. G., Haldorai, K., & Kim, H. S. (2022). Online food delivery services and consumers' purchase intention: Integration of theory of planned behaviour, theory of perceived risk, and the elaboration likelihood model. International journal of hospitality management, 105, 103275. https://doi.org/10.1016/j.ijhm.2022.103275
- Polas, M. R. H., Raju, V., Hossen, S. M., Karim, A. M., & Tabash, M. I. (2022). Customer's revisit intention: Empirical evidence on Gen‐Z from Bangladesh towards halal restaurants. Journal of Public Affairs, 22(3), e2572. https://doi.org/10.1002/pa.2572
- Poon, W. C., & Tung, S. E. H. (2024). The rise of online food delivery culture during the COVID-19 pandemic: an analysis of intention and its associated risk. European Journal of Management and Business Economics, 33(1), 54–73. https://doi.org/10.1108/EJMBE-04-2021-0128
- Pop, R. A., Saplacan, Z., Dabija, D. C., & Alt, M. A. (2022). The impact of social media influencers on travel decisions: The role of trust in consumer decision journey. Current Issues in Tourism, 25(5), 823-843. https://doi.org/10.1080/13683500.2021.1895729
- Prabowo, G. T., & Nugroho, A. (2019, March). Factors that influence the attitude and behavioural intention of Indonesian users toward online food delivery service by the Go-Food application. In 12th International Conference on Business and Management Research (ICBMR 2018) (pp. 204-210). Atlantis Press.
- Pramezwary, A., Yulius, K. G., Viensa, V. P., & Pujangga, J. F. (2023). Factors driving generation z's use of online food delivery service at the end of pandemic. Jurnal Manajemen Perhotelan, 9(2), 101–112. https://doi.org/10.9744/jmp.9.2.101-112
- Preetha, S., & Iswarya, S. (2019). Factors influencing the intension to use food online order and delivery appvia platforms-using TAM (Technology Acceptance Model). International Journal of Recent Technology and Engineering, 7(65), 1141-1147.
- Rahaman, M. A., Hassan, H. K., Asheq, A. A., & Islam, K. A. (2022). The interplay between
- eWOM information and purchase intention on social media: Through the lens of IAM and TAM theory. PloS One, 17(9), e0272926. https://doi.org/10.1371/journal.pone.0272926
- Ramayah, T., Lee, J. W. C., & In, J. B. C. (2011). Network collaboration and performance in the tourism sector. Service Business, 5, 411-428. https://doi.org/10.1007/s11628-011-0120-z
- 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
- Ringle, C. M., Wende, S., & Will, A. (2005, September). Customer segmentation with FIMIX-PLS. In Proceedings of PLS-05 International Symposium, SPAD Test&go, Paris (pp. 507-514).
- Rodríguez-López, M. E., Alcántara-Pilar, J. M., Del Barrio-García, S., & Muñoz-Leiva, F. (2020). A review of restaurant research in the last two decades: A bibliometric analysis. International Journal of Hospitality Management, 87, 102387. https://doi.org/10.1016/j.ijhm.2019.102387
- Rohm, A.J. and Swaminathan, V. (2004). A Typology of Online Shoppers Based on Shopping Motivations. Journal of Business Research, 57, 748-757. https://doi.org/10.1016/S0148-2963(02)00351-X
- Rohm, Andrew & Swaminathan, Vanitha. (2004). A Typology of Online Shoppers Based on Shopping Motivations. Journal of Business Research. 57. 748-757. https://doi.org/10.1016/S0148-2963(02)00351-X
- Ryu, K., & Han, H. (2010). Influence of the quality of food, service, and physical environment on customer satisfaction and behavioural intention in quick-casual restaurants: Moderating role of perceived price. Journal of Hospitality & Tourism Research, 34(3), 310–329. https://doi.org/10.1177/1096348009350624
- 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
- Salunkhe, S., Udgir, S., & Petkar, S. (2018). Technology acceptance model in context with online food ordering and delivery services: An extended conceptual framework. Journal of Management (JOM), 5(5), 73-79.
- Sari, P., Agustin, D., & Musyaffi, M. A. (2023). Exploring Convenience Motivation in the Using Delivery Service Intention. Quality-Access to Success, 24(192).
- Sethu, H. S., & Saini, B. (2016). Proceedings of the seventh Asia-Pacific Conference on global business, economics, finance and social sciences. In AP16 Malaysia Conference (pp. 15-17).
- Shah, A. M., Yan, X., & Qayyum, A. (2022). Adoption of mobile food ordering apps for O2O food delivery services during the COVID-19 outbreak. British Food Journal, 124(11), 3368-3395. https://doi.org/10.1108/BFJ-09-2020-0781
- Shanka, M. S., & Gebremariam Kotecho, M. (2023). Combining rationality with morality – integrating theory of planned behaviour with norm activation theory to explain compliance with COVID-19 prevention guidelines. Psychology, Health and Medicine, 28(2), 305–315. https://doi.org/10.1080/13548506.2021.1946571
- Shankar, A., & Rishi, B. (2020). Convenience matter in mobile banking adoption intention? Australasian Marketing Journal, 28(4), 273–285. https://doi.org/10.1016/j.ausmj.2020.06.008
- Sharma, N. & Varshney, D. (2019). Factors affecting attitude towards online Food Ordering Services. Paper presented at the 7th PAN IIM WORLD MANAGEMENT CONFERENCE, India.
- Sjahroeddin, F. (2018, October). The role of ES-Qual and food quality on customer satisfaction in online food delivery service. In Prosiding Industrial Research Workshop and National Seminar (Vol. 9, pp. 551-558).
- Statista (2024). Revenue of the online food delivery market worldwide from 2017 to 2028, by segment. Available at https://www.statista.com/statistics/1170631/online-food-delivery-market-size-worldwide/
- Suhartanto, D., Helmi Ali, M., Tan, K. H., Sjahroeddin, F., & Kusdibyo, L. (2019). Loyalty toward online food delivery service: the role of e-service quality and food quality. Journal of Foodservice Business Research, 22(1), 81–97. https://doi.org/10.1080/15378020.2018.1546076
- Sultan, M.U. and Uddin, M. (2011). Consumers' attitude towards online shopping: factors influencing gotland consumers to shop online. Masters Thesis, Department of Business Administration, The University of Gotland.
- Tan, S. Y., Lim, S. Y., & Yeo, S. F. (2024). Online food delivery services: cross-sectional study of consumers' attitude in Malaysia during and after the COVID-19 pandemic. F1000Research, 10(972), 972. https://doi.org/10.12688/f1000research.73014.2
- Taufik, N., & Hanafiah, M. H. (2019). Airport passengers' adoption behaviour towards self-check-in Kiosk Services: The roles of perceived ease of use, perceived usefulness and need for human interaction. Heliyon, 5(12), e02960–e02960. https://doi.org/10.1016/j.heliyon.2019.e02960
- Troise, C., O'Driscoll, A., Tani, M., & Prisco, A. (2020). Online food delivery services and behavioural intention–a test of an integrated TAM and TPB framework. British Food Journal, 123(2), 664–683. https://doi.org/10.1108/BFJ-05-2020-0418
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
- Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer Acceptance and use of Information technology: Extending the unified theory of acceptance and use of technology. Management Information Systems Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412
- Vinaik, A., Goel, R., Sahai, S. and Garg, V. (2019). The study of interest of consumers in mobile food ordering apps. International Journal of Recent Technology and Engineering, 8 (1), 3424-3429.
- Wang, L., Zhang, Q., & Wong, P. P. W. (2022). Purchase intention for green cars among Chinese millennials: Merging the value-attitude-behaviour theory and theory of planned behaviour. Frontiers in Psychology, 13, 786292–786292. https://doi.org/10.3389/fpsyg.2022.786292
- Wiastuti, R. D., Prawira, O., Lusyana, L., Lestari, N. S., Masatip, A., & Ngatemin, N. (2022). The Relationship Between Convenience Motivation, Attitude, And Behavioral Intention Of Food Delivery Applications'users. Geo Journal of Tourism and Geosites, 41(2), 548-554.
- Xu, F., Huang, S.(S). and Li, S. (2019). Time, money, or convenience: what determines Chinese consumers' continuance usage intention and behavior of using tourism mobile apps?. International Journal of Culture, Tourism and Hospitality Research, Vol. 13 No. 3, pp. 288-302. https://doi.org/10.1108/IJCTHR-04-2018-0052
- Yeo, V. C. S., Goh, S.-K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioural 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
- Zaheer, M. A., Anwar, T. M., Iantovics, L. B., Raza, M. A., & Khan, Z. (2024). Enticing attributes of consumers' purchase intention to use online food delivery applications (OFDAs) in a developing country. Journal of Electronic Business & Digital Economics. https://doi.org/10.1108/JEBDE-10-2023-0025
- 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, 1- 12. https://doi.org/10.1016/j.ijhm.2020.102683
- Zulkarnain, K., Ahasanul, H., & Selim, A. (2015). Key success factors of online food ordering services: An empirical study. Malaysian institute of Management, 50(2), 19-36.
References
Abdullah, F., Ward, R., & Ahmed, E. (2016). Investigating the influence of the most commonly used external variables of TAM on students' perceived ease of use (PEOU) and perceived usefulness (PU) of e-portfolios. Computers in Human Behaviour, 63, 75–90. https://doi.org/10.1016/j.chb.2016.05.014
Ajzen, I. (1991a). The theory of planned behaviour. Organizational Behaviour and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Ajzen, I. and Fishbein, M. (1985). The prediction of behaviour from attitudinal and normative variables. Journal of Experimental Social Psychology, Vol. 6, pp. 466-88. https://doi.org/10.1016/0022-1031(70)90057-0
Akdim, K., Casaló, L. V., & Flavián, C. (2022). The role of utilitarian and hedonic aspects in the continuance intention to use social mobile apps. Journal of Retailing and Consumer Services, 66, 102888. https://doi.org/10.1016/j.jretconser.2021.102888
Alagoz, S. M., & Hekimoglu, H. (2012). A study on tam: analysis of customer attitudes in online food ordering system. Procedia-Social and Behavioural Sciences, 62, 1138-1143. https://doi.org/10.1016/j.sbspro.2012.09.195
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
Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Algharabat, R. (2018). Examining factors influencing Jordanian customers' intentions and adoption of internet banking: Extending UTAUT2 with risk. Journal of Retailing and Consumer Services, 40, 125138. https://doi.org/10.1016/j.jretconser.2017.08.026
Andersen, J.C. and Gerbing, D.W. (1988). Structural equation modelling in practice. A review and recommended two-step approach. Psychological Bulletin, Vol. 103 No. 3, pp. 411-423. https://psycnet.apa.org/doi/10.1037/0033-2909.103.3.411
Asheq, A. A., Tanchi, K. R., Akhter, S., Kamruzzaman, M., & Islam, K. A. (2022). Examining university students' behaviours towards online shopping: An empirical investigation in an emerging market. Innovative Marketing, 18(1), 94-103. http://dx.doi.org/10.21511/im.18(1).2022.08
Banerjee, S. P., Jain, D., & Nayyar, R. (2019). Measuring service quality of food delivery services: a study of generation Z. African Journal of Hospitality, Tourism and Leisure, 8(2), 1–12.
Barnard-Brak, L., Burley, H., & Crooks, S. M. (2010). Explaining youth mentoring behaviour using a theory of planned behaviour perspective. International Journal of Adolescence and Youth, 15(4), 365–379. https://doi.org/10.1080/02673843.2010.9748040
Belanche, D., Flavian, M., & Perez-Rueda, A. (2020). Mobile Apps Use and WOM in the Food Delivery Sector: The Role of Planned Behaviour, Perceived Security and Customer Lifestyle Compatibility. Sustainability, 12(10), 4275-4275. https://doi.org/10.3390/su12104275
Bentler, P. M., & Bonett, D. G. (1980). Significance Tests and Goodness-of-Fit in the Analysis of Covariance Structures. Psychological Bulletin, 88, 588-600.
Berkup, S. B. (2014). Working with generations X and Y in generation Z period: Management of different generations in business life. Mediterranean journal of social Sciences, 5(19), 218-229. https://doi.org/10.5901/mjss.2014.v5n19p218
Bhatnagar, A., Sanjog, M. and Rao, H.R. (2000). On Risk, Convenience, and Internet Shopping Behaviour. Communications of the ACM, 43, 98-105. https://doi.org/10.1145/353360.353371
Bhattacherjee, Anol. (2001). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly. 25. 351-370. 10.2307/3250921.
Blackwell, R.D., Paul, W.M. and James, F.E. (2006). Attributes of attitudes. Consumer Behaviour, Thomson Press, New York, NY, pp. 235-43.
Bouarar, A. C., Mouloudj, S., & Mouloudj, K. (2021). Extending the theory of planned behaviour to explain intention to use online food delivery services in the context of COVID-19 pandemic. University of South Florida (USF) M3 Publishing, 5(2021), 47. https://www.doi.org/10.5038/9781955833035
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), 399-426.
Burns, R.B. and Burns, R.A. (2008). Business Research Methods and Statistics Using SPSS. SAGE, Los Angeles, CA.
Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). Routledge.
Cai, S. and Jun, M. (2003). Internet users' perceptions of online service quality: a comparison of online buyers and information searchers. Managing Service Quality: an International Journal, Vol. 13 No. 6, pp. 504-519. https://doi.org/10.1108/09604520310506568
Canny, I. U. (2014). Measuring the mediating role of dining experience attributes on customer satisfaction and its impact on behavioural intentions of casual dining restaurant in Jakarta. International Journal of Innovation, Management and Technology, 5(1), 25–29.
Chai, L.T. and Yat, DNC (2019). Online food delivery services: making food delivery the new normal. Journal of Marketing Advances and Practices, Vol. 1 No. 1, pp. 62-77.
Chan, K., & Li, Q. (2022). Attributes of young adults' favorite retail shops: a qualitative study. Young Consumers, 23(4), 555-569. https://doi.org/10.1108/YC-01-2022-1442
Chandrasekhar, N., Gupta, S. and Nanda, N. (2019). Food delivery services and customer preference: a comparative analysis. Journal of Foodservice Business Research, Vol. 22 No. 4, pp. 375-386. https://doi.org/10.1080/15378020.2019.1626208
Chang, M.K., Cheung, W. and Lai, V.S. (2005). Literature derived reference models for the adoption of online shopping. Information and Management, Vol. 42 No. 4, pp. 543-559. https://doi.org/10.1016/j.im.2004.02.006
Chen, H. and Hsieh, Y. (2017). The driving success factors of the online food ordering system – empirical evidence from the UTAUT model.
Chen, H. S., Liang, C. H., Liao, S. Y., & Kuo, H. Y. (2020). Consumer attitudes and purchase intentions toward food delivery platform services. Sustainability, 12(23), 10177. https://doi.org/10.3390/su122310177
Chen, J.S., Tsou, T.H. and Huang, A.Y. (2009). Service delivery innovation: antecedents and impact on firm performance, Journal of Service Research, Vol. 12 No. 1, pp. 36-55. https://doi.org/10.1177/1094670509338619
Chen, N. H., & Hung, Y.-W. (2015). Online shopping orientation and purchase behaviour for high-touch products. International Journal of Electronic Commerce Studies, 6(2), 187–202. https://doi.org/10.7903/ijecs.1401
Chen, X. H., & Lee, T. J. (2022). Potential effects of green brand legitimacy and the biospheric value of eco-friendly behaviour on online food delivery: amediation approach. International Journal of Contemporary Hospitality Management, 34(11), 4080-4102. https://doi.org/10.1108/IJCHM-07-2021-0892
Cho, M., Bonn, M. A., & Li, J. J. (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
Correaa, J.C., Garzon, W., Brooker, P., Sakarkar, G., Carranzaa, S.A., Yunadoa, L. and Rincona, A. (2018). Evaluation of collaborative consumption of food delivery services through web mining techniques. Journal of Retailing and Consumer Services, Vol. 46, pp. 45-50. https://doi.org/10.1016/j.jretconser.2018.05.002
Das, J. (2018). Consumer perception towards online food ordering and delivery services: an empirical study. Journal of Management, Vol. 5 No. 5, pp. 155-163
Das, S. and Ghose, D. (2019).Influence of online food delivery apps on the operations of the restaurant business. International Journal of Scientific and Technology Research, Vol. 8 No. 12, pp. 1372-1377.
Daud, D. and Yoong, H.M. (2019). The relationship between consumers' price-saving orientation and time-saving orientation towards food delivery intermediaries (fdi) services: an exploratory study. Global Scientific Journals, Vol. 7 No. 2, pp. 175-190 .
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research. Addison-Wesley.
Fornell, C. and Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50. https://doi.org/10.1177/002224378101800104
Francioni, B., Curina, I., Hegner, S. M., & Cioppi, M. (2022). Predictors of continuance intention of online food delivery services: gender as moderator. International Journal of Retail & Distribution Management, 50(12), 1437–1457. https://doi.org/10.1108/IJRDM-11-2021-0537
Gerbing, D. W., & Hunter, J. E. (1987). ITAN: A statistical package for ITem ANalysis including multiple groups confirmatory factor analysis. Portland, OR: Portland State University, Department of Management.
Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: an organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185–214.
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. https://doi.org/10.1108/IJCTHR-01-2020-0013
Ha, DN (2013). Demand creation of online services for B2B and consumer market–food delivery in Vietnam, M.Sc. Thesis, Tampere University of Technology.
Hair, J. F., Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. New York: Pearson New International Edition, United States of America.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1-2), 1–12.
Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26(2), 106–121.
Hair, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate data analysis (6th Edition). Upper Saddle River: Pearson Prentice Hall.
Hair, J.F., Sarstedt, M., Ringle, C.M. and Mena, J.A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, Vol. 40 No. 3, pp. 414-433. https://doi.org/10.1007/s11747-011-0261-6
Hamid, S., & Azhar, M. (2023). Behavioural intention to order food and beverage items using e-commerce during COVID-19: an integration of theory of planned behaviour (TPB) with trust. British Food Journal, 125(1), 112-131. https://doi.org/10.1108/BFJ-03-2021-0338
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen, D. J., Hair, J. F., Hult, G. T. M., & Calantone, R. J. (2014). Common Beliefs and Reality About PLS. Organizational Research Methods, 17(2), 182–209. https://doi.org/10.1177/1094428114526928
Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Industrial Management & Data Systems, 116 (1), 2-20.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the Academy of Marketing Science, 43(1), 115-135.
Hirschberg, C., Rajko, A., Schumacher, T. and Wrulich, M. (2016). The changing market for food delivery. Available at: https://www.mckinsey.com/industries/high-tech/our-insights/thechanging-market-for-food-delivery.
Hong, C., Choi, H. H., Choi, E.-K. C., & Joung, H.-W. D. (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, 509–518. https://doi.org/10.1016/j.jhtm.2021.08.012
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.
Humaidi, N. F. A., Jamil, S. N. M., Gannasin, S. P., & Samat, N. (2024). Enhancing Users' Satisfaction: Revealing the Key Factors Influencing the Usage of Online Food Delivery Service Applications Among University Students. Journal of Tourism, Hospitality & Culinary Arts, 16 (1), 993-1010.
Jebarajakirthy, C., & Shankar, A. (2021). Impact of online convenience on mobile banking adoption intention: A moderated mediation approach. Journal of Retailing and Consumer Services, 58, 102323. https://doi.org/10.1016/j.jretconser.2020.102323
Jiang, L. A. , Y. Z. , & J. M. (2013). Measuring consumer perceptions of online shopping convenience. Journal of Service Management, 191–214. https://doi.org/10.1108/09564231311323962
Josiam, B. M., & Henry, W. (2014). Eatertainment: Utilitarian and hedonic motivations for patronizing fun experience restaurants. Procedia-Social and Behavioural Sciences, 144, 187-202. https://doi.org/10.1016/j.sbspro.2014.07.287
Kapoor, A. P., & Vij, M. (2018). Technology at the dinner table: Ordering food online through mobile apps. Journal of retailing and consumer services, 43, 342-351. https://doi.org/10.1016/j.jretconser.2018.04.001
Kim, J. J., & Hwang, J. (2020). Merging the norm activation model and the theory of planned behaviour in the context of drone food delivery services: Does the level of product knowledge really matter?. Journal of Hospitality and Tourism Management, 42, 1-11. https://doi.org/10.1016/j.jhtm.2019.11.002
Kim, M. J., & Kang, Y. (2023). Older adults' user experience of virtual tourism: exploring presence and experiential value with respect to age difference. Virtual Reality, 27(4), 2967-2987. https://doi.org/10.1007/s10055-023-00849-1
Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Press.
Lan, H., Yanan, L. and Shuhua, W. (2016). Improvement of online food delivery service based on consumers' negative comments. Canadian Social Science, 12 (5), 84-88.
Lee, E. Y., Lee, S. B., & Jeon, Y. J. J. (2017). Factors influencing the behavioural intention to use food delivery apps. Social Behaviour and Personality: an international journal, 45(9), 1461-1473. https://doi.org/10.2224/sbp.6185
Lee, W. S., Song, M., Moon, J., & Tang, R. (2023). Application of the technology acceptance model to food delivery apps. British Food Journal, 125(1), 49-64. https://doi.org/10.1108/BFJ-05-2021-0574
Lin, T., Chen, Y., & Liu, C. (2022). Determinants of consumer intentions to use online food delivery services. Journal of Hospitality and Tourism Technology, 13(1), 1-19. https://doi.org/10.1108/BFJ-03-2021-0332
Lina, Y., Hou, D., & Ali, S. (2022). Impact of online convenience on generation Z online impulsive buying behaviour: The moderating role of social media celebrity. Frontiers in Psychology, 13, 951249. https://doi.org/10.3389/fpsyg.2022.951249
Marcoulides, G.A. and Saunders, C. (2006). PLS: a silver bullet?. MIS Quarterly, 30 (2), 3-9.
Mehrolia S., Alagarsamy S., Solaikutty V.M. (2021). Customers response to online food delivery services during COVID-19 outbreak using binary logistic regression. International Journal of Consumer Studies, 45(3), 396–408. https://doi.org/10.1111/ijcs.12630
Morganosky, M. A., & Cude, B. J. (2000). Consumer response to online grocery shopping. International Journal of Retail & Distribution Management, 28(1), 17–26. https://doi.org/10.1108/09590550010306737
Na-Nan, K. (2020). Organizational behavior scale development. Bangkok: Triple Education.
Nasir, A., Ahmed, M. A., Nazir, I., Zafar, H., & Zahid, Z. (2014). Impact of different determinants on customers satisfaction level (a case of fast food restaurant). International Journal of Business and Management Invention, 3(9), 32–40.
Nguyen, T. T. H., Nguyen, N., Nguyen, T. B. L., Phan, T. T. H., Bui, L. P., & Moon, H. C. (2019). Investigating consumer attitude and intention towards online food purchasing in an emerging economy: An extended TAM approach. Foods, 8(11), 576. https://doi.org/10.3390/foods8110576
Okumus, B. (2021). A qualitative investigation of Millennials' healthy eating behaviour, food choices, and restaurant selection. Food, Culture & Society, 24(4), 509-524. https://doi.org/10.1080/15528014.2021.1882168
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. https://doi.org/10.1016/j.ijhm.2018.01.001
Ozturk, A. B., Nusair, K., Okumus, F., & Hua, N. (2016). The role of utilitarian and hedonic values on users' continued usage intention in a mobile hotel booking environment. International Journal of Hospitality Management, 57, 106–115. https://doi.org/10.1016/j.ijhm.2016.06.007
Pan, J. Y., & Liu, D. (2022). Mask-wearing intentions on airplanes during COVID-19 – Application of theory of planned behaviour model. Transport Policy, 119, 32–44. https://doi.org/10.1016/j.tranpol.2022.01.023
Pigatto, G., Machado, J.G., Negreti, A. and Machado, L. (2017). Have you chosen your request? Analysis of online food delivery companies in Brazil. British Food Journal, 119 (3), 639-657. https://doi.org/10.1108/BFJ-05-2016-0207
Pillai, S. G., Kim, W. G., Haldorai, K., & Kim, H. S. (2022). Online food delivery services and consumers' purchase intention: Integration of theory of planned behaviour, theory of perceived risk, and the elaboration likelihood model. International journal of hospitality management, 105, 103275. https://doi.org/10.1016/j.ijhm.2022.103275
Polas, M. R. H., Raju, V., Hossen, S. M., Karim, A. M., & Tabash, M. I. (2022). Customer's revisit intention: Empirical evidence on Gen‐Z from Bangladesh towards halal restaurants. Journal of Public Affairs, 22(3), e2572. https://doi.org/10.1002/pa.2572
Poon, W. C., & Tung, S. E. H. (2024). The rise of online food delivery culture during the COVID-19 pandemic: an analysis of intention and its associated risk. European Journal of Management and Business Economics, 33(1), 54–73. https://doi.org/10.1108/EJMBE-04-2021-0128
Pop, R. A., Saplacan, Z., Dabija, D. C., & Alt, M. A. (2022). The impact of social media influencers on travel decisions: The role of trust in consumer decision journey. Current Issues in Tourism, 25(5), 823-843. https://doi.org/10.1080/13683500.2021.1895729
Prabowo, G. T., & Nugroho, A. (2019, March). Factors that influence the attitude and behavioural intention of Indonesian users toward online food delivery service by the Go-Food application. In 12th International Conference on Business and Management Research (ICBMR 2018) (pp. 204-210). Atlantis Press.
Pramezwary, A., Yulius, K. G., Viensa, V. P., & Pujangga, J. F. (2023). Factors driving generation z's use of online food delivery service at the end of pandemic. Jurnal Manajemen Perhotelan, 9(2), 101–112. https://doi.org/10.9744/jmp.9.2.101-112
Preetha, S., & Iswarya, S. (2019). Factors influencing the intension to use food online order and delivery appvia platforms-using TAM (Technology Acceptance Model). International Journal of Recent Technology and Engineering, 7(65), 1141-1147.
Rahaman, M. A., Hassan, H. K., Asheq, A. A., & Islam, K. A. (2022). The interplay between
eWOM information and purchase intention on social media: Through the lens of IAM and TAM theory. PloS One, 17(9), e0272926. https://doi.org/10.1371/journal.pone.0272926
Ramayah, T., Lee, J. W. C., & In, J. B. C. (2011). Network collaboration and performance in the tourism sector. Service Business, 5, 411-428. https://doi.org/10.1007/s11628-011-0120-z
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
Ringle, C. M., Wende, S., & Will, A. (2005, September). Customer segmentation with FIMIX-PLS. In Proceedings of PLS-05 International Symposium, SPAD Test&go, Paris (pp. 507-514).
Rodríguez-López, M. E., Alcántara-Pilar, J. M., Del Barrio-García, S., & Muñoz-Leiva, F. (2020). A review of restaurant research in the last two decades: A bibliometric analysis. International Journal of Hospitality Management, 87, 102387. https://doi.org/10.1016/j.ijhm.2019.102387
Rohm, A.J. and Swaminathan, V. (2004). A Typology of Online Shoppers Based on Shopping Motivations. Journal of Business Research, 57, 748-757. https://doi.org/10.1016/S0148-2963(02)00351-X
Rohm, Andrew & Swaminathan, Vanitha. (2004). A Typology of Online Shoppers Based on Shopping Motivations. Journal of Business Research. 57. 748-757. https://doi.org/10.1016/S0148-2963(02)00351-X
Ryu, K., & Han, H. (2010). Influence of the quality of food, service, and physical environment on customer satisfaction and behavioural intention in quick-casual restaurants: Moderating role of perceived price. Journal of Hospitality & Tourism Research, 34(3), 310–329. https://doi.org/10.1177/1096348009350624
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
Salunkhe, S., Udgir, S., & Petkar, S. (2018). Technology acceptance model in context with online food ordering and delivery services: An extended conceptual framework. Journal of Management (JOM), 5(5), 73-79.
Sari, P., Agustin, D., & Musyaffi, M. A. (2023). Exploring Convenience Motivation in the Using Delivery Service Intention. Quality-Access to Success, 24(192).
Sethu, H. S., & Saini, B. (2016). Proceedings of the seventh Asia-Pacific Conference on global business, economics, finance and social sciences. In AP16 Malaysia Conference (pp. 15-17).
Shah, A. M., Yan, X., & Qayyum, A. (2022). Adoption of mobile food ordering apps for O2O food delivery services during the COVID-19 outbreak. British Food Journal, 124(11), 3368-3395. https://doi.org/10.1108/BFJ-09-2020-0781
Shanka, M. S., & Gebremariam Kotecho, M. (2023). Combining rationality with morality – integrating theory of planned behaviour with norm activation theory to explain compliance with COVID-19 prevention guidelines. Psychology, Health and Medicine, 28(2), 305–315. https://doi.org/10.1080/13548506.2021.1946571
Shankar, A., & Rishi, B. (2020). Convenience matter in mobile banking adoption intention? Australasian Marketing Journal, 28(4), 273–285. https://doi.org/10.1016/j.ausmj.2020.06.008
Sharma, N. & Varshney, D. (2019). Factors affecting attitude towards online Food Ordering Services. Paper presented at the 7th PAN IIM WORLD MANAGEMENT CONFERENCE, India.
Sjahroeddin, F. (2018, October). The role of ES-Qual and food quality on customer satisfaction in online food delivery service. In Prosiding Industrial Research Workshop and National Seminar (Vol. 9, pp. 551-558).
Statista (2024). Revenue of the online food delivery market worldwide from 2017 to 2028, by segment. Available at https://www.statista.com/statistics/1170631/online-food-delivery-market-size-worldwide/
Suhartanto, D., Helmi Ali, M., Tan, K. H., Sjahroeddin, F., & Kusdibyo, L. (2019). Loyalty toward online food delivery service: the role of e-service quality and food quality. Journal of Foodservice Business Research, 22(1), 81–97. https://doi.org/10.1080/15378020.2018.1546076
Sultan, M.U. and Uddin, M. (2011). Consumers' attitude towards online shopping: factors influencing gotland consumers to shop online. Masters Thesis, Department of Business Administration, The University of Gotland.
Tan, S. Y., Lim, S. Y., & Yeo, S. F. (2024). Online food delivery services: cross-sectional study of consumers' attitude in Malaysia during and after the COVID-19 pandemic. F1000Research, 10(972), 972. https://doi.org/10.12688/f1000research.73014.2
Taufik, N., & Hanafiah, M. H. (2019). Airport passengers' adoption behaviour towards self-check-in Kiosk Services: The roles of perceived ease of use, perceived usefulness and need for human interaction. Heliyon, 5(12), e02960–e02960. https://doi.org/10.1016/j.heliyon.2019.e02960
Troise, C., O'Driscoll, A., Tani, M., & Prisco, A. (2020). Online food delivery services and behavioural intention–a test of an integrated TAM and TPB framework. British Food Journal, 123(2), 664–683. https://doi.org/10.1108/BFJ-05-2020-0418
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer Acceptance and use of Information technology: Extending the unified theory of acceptance and use of technology. Management Information Systems Quarterly, 36(1), 157-178. https://doi.org/10.2307/41410412
Vinaik, A., Goel, R., Sahai, S. and Garg, V. (2019). The study of interest of consumers in mobile food ordering apps. International Journal of Recent Technology and Engineering, 8 (1), 3424-3429.
Wang, L., Zhang, Q., & Wong, P. P. W. (2022). Purchase intention for green cars among Chinese millennials: Merging the value-attitude-behaviour theory and theory of planned behaviour. Frontiers in Psychology, 13, 786292–786292. https://doi.org/10.3389/fpsyg.2022.786292
Wiastuti, R. D., Prawira, O., Lusyana, L., Lestari, N. S., Masatip, A., & Ngatemin, N. (2022). The Relationship Between Convenience Motivation, Attitude, And Behavioral Intention Of Food Delivery Applications'users. Geo Journal of Tourism and Geosites, 41(2), 548-554.
Xu, F., Huang, S.(S). and Li, S. (2019). Time, money, or convenience: what determines Chinese consumers' continuance usage intention and behavior of using tourism mobile apps?. International Journal of Culture, Tourism and Hospitality Research, Vol. 13 No. 3, pp. 288-302. https://doi.org/10.1108/IJCTHR-04-2018-0052
Yeo, V. C. S., Goh, S.-K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioural 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
Zaheer, M. A., Anwar, T. M., Iantovics, L. B., Raza, M. A., & Khan, Z. (2024). Enticing attributes of consumers' purchase intention to use online food delivery applications (OFDAs) in a developing country. Journal of Electronic Business & Digital Economics. https://doi.org/10.1108/JEBDE-10-2023-0025
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, 1- 12. https://doi.org/10.1016/j.ijhm.2020.102683
Zulkarnain, K., Ahasanul, H., & Selim, A. (2015). Key success factors of online food ordering services: An empirical study. Malaysian institute of Management, 50(2), 19-36.