Global Journal of Management and Business Research, E: Marketing, Volume 23 Issue 2

16 Global Journal of Management and Business Research Volume XXIII Issue II Version I Year 2023 ( )E © 2023 Global Journals 54. Hair Jr, J. F., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1 (2), 107-123. 55. Hasan, S., Shohag, M. I. H., Chowdhury, I. U., Miswar, R., & Ashaduzzaman, M. (2023). From eating out to online food ordering amid COVID-19: a case of food delivery apps. International Journal of Knowledge Management in Tourism and Hospitality, 3 (1), 50-68. 56. Hassan, M. (2021, Thursday, May 25, 2023). Covid- 19: Bangladesh extends restrictions on public movement, gatherings till July 15. Retrieved from https://archive.dhakatribune.com/bangladesh/2021/ 06/16/covid-19-restrictions-on-public-movement- extended-till-july-15 57. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43 (1), 115-135. 58. Hew, J.-J., Lee, V.-H., Ooi, K.-B., & Wei, J. (2015). What catalyses mobile apps usage intention: an empirical analysis. Industrial Management & Data Systems . 59. Holden, R. J., & Karsh, B.-T. (2010). The technology acceptance model: its past and its future in health care. Journal of biomedical informatics, 43 (1), 159- 172. 60. 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. 61. Hossain, M. (2022). Bangladesh's food delivery startups are scaling back and shotting down. Retrieved from https://restofworld.org/2022/food- delivery-startups-struggle-in-bangladesh/ 62. Jain, K., Sharma, I., & Singh, G. (2018). An empirical study of factors determining wearable fitness tracker continuance among actual users. International Journal of Technology Marketing, 13 (1), 83-109. 63. Janairo, J. I. B. (2021). Unsustainable plastic consumption associated with online food delivery services in the new normal. Cleaner and Responsi- ble Consumption, 2 , 100014. 64. Jaroenwanit, P., Abbasi, A., & Hongthong, P. (2022). Determinants of customers’ intention to use online food delivery platforms in Thailand. Uncertain Supply Chain Management, 10 (3), 747-758. 65. Javed, M., Malik, F. A., Awan, T. M., & Khan, R. (2021). Food photo posting on social media while dining: an evidence using embedded correlational mixed methods approach. Journal of Food Products Marketing, 27 ( 1), 10-26. 66. Kader, R. (2020). The State of online food delivery in Bangladesh at the beginning of 2020: Subsidies make true demand hard to guage. Retrieved from https://futurestartup.com/2020/02/04/online-food- delivery-in-bangladesh-subsidies-make-true- demand-hard-to-gauge/ 67. Kaium, M. A., Bao, Y., Alam, M. Z., & Hoque, M. R. (2020). Understanding continuance usage intention of mHealth in a developing country. International Journal of Pharmaceutical and Healthcare Marketing, 14 (2), 251-272. doi:10.1108/IJPHM-06-2019-0041 68. 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. 69. Khalil, A.-A., Hidayanto, A. N., & Prabowo, H. (2020). Identification of factor Affecting continuance usage intention of mHealth application: a systematic literature review. Paper presented at the 2020 4th International Conference on Informatics and Computational Sciences (ICICoS). 70. Khatimah, H., Susanto, P., & Abdullah, N. L. (2019). Hedonic motivation and social influence on behavioral intention of e-money: The role of payment habit as a mediator. International Journal of Entrepreneurship, 23 (1), 1-9. 71. Khosasih, M. M., & Lisana, L. (2023). Intention to Adopt Online Food Delivery Using Augmented Reality Mobile Apps: A Perspective of SOR Framework. International Journal on Advanced Science, Engineering and Information Technology, 13 (2), 618-624. 72. Kim, S. S., & Malhotra, N. K. (2005). A longitudinal model of continued IS use: An integrative view of four mechanisms underlying postadoption phenomena. Management science, 51 (5), 741-755. 73. Kimes, S. E. (2011). The current state of online food ordering in the US restaurant industry. 74. 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. GIS Business, 14 . 75. Kupfer, A., Ableitner, L., Schöb, S., & Tiefenbeck, V. (2016). Technology adoption vs. Continuous usage intention: do decision criteria change when using a technology? 76. Lee, S. W., Sung, H. J., & Jeon, H. M. (2019). Determinants of continuous intention on food delivery apps: extending UTAUT2 with information quality. Sustainability, 11 (11), 3141. 77. Lee, Y.-P., Tsai, H.-Y., & Ruangkanjanases, A. (2020). The determinants for food safety push notifications on continuance intention in an e- appointment system for public health medical services: The perspectives of utaut and information system quality. International Journal of Environmental Research and Public Health, 17 (21), 8287. 78. Liao, C., Palvia, P., & Lin, H.-N. (2006). The roles of habit and web site quality in e-commerce. Consumers’ Food Delivery Apps (FDAs) Continuance Intention: An Empirical Investigation using the Extended UTAUT2 Model