How to cite this paper
Raees, U., Shah, S., Khan, I., Elrayah, M., Albarq, A., Moustafa, M., Falah, K & Afaneh, J. (2025). Examining UTAUT model for mobile food ordering applications (MOFAs): A case study of Food-panda application.International Journal of Data and Network Science, 9(1), 97-114.
Refrences
Abbad, M. M. M. (2021). Using the UTAUT model to understand students’ usage of e-learning systems in developing countries. Education and Information Technologies, 1–20. https://doi.org/10.1007/s10639-021-10573-5
Ajzen, I., & Fishbein, M. (2005). The Influence of Attitudes on Behavior. In The Handbook of Attitudes, D. Albarracin, В. T. Johnson, and M. P. Zanna (Eds.), Mahwah, NJ: Erlbaum, Pp., 173–221.
Ajzen, I., & Fishbein, M. (1969). The prediction of behavioral intentions in a choice situation. Journal of Experimental Social Psychology, 5(4), 400–416. https://doi.org/10.1016/0022-1031(69)90033-X
Akel, G., & Armagan, E. (2021). Hedonic and utilitarian benefits as determinants of the application continuance intention in location-based applications: the mediating role of satisfaction. Multimedia Tools and Applications, 80(5), 7103–7124. https://doi.org/10.1007/s11042-020-10094-2
Albarq, A. (2024). The emergence of mobile payment acceptance in Saudi Arabia: the role of reimbursement condition. Journal of Islamic Marketing, 15(6), 1632-1650.
Al Amin, Md., Arefin, M. S., Sultana, N., Islam, M. R., Jahan, I., & Akhtar, A. (2021). Evaluating the customers’ dining attitudes, e-satisfaction, and continuance intention toward mobile food ordering apps (MFOAs): evidence from Bangladesh. European Journal of Management and Business Economics, 30(2), 211–229. https://doi.org/10.1108/ejmbe-04-2020-0066
Al Amin, Md, Arefin, M. S., Sultana, N., Islam, M. R., Jahan, I., & Akhtar, A. (2020). Evaluating the customers’ dining attitudes, e-satisfaction, and continuance intention toward mobile food ordering apps (MFOAs): evidence from Bangladesh Evaluating the customers’ dining attitudes. European Journal of Management and Business Economics. https://doi.org/10.1108/EJMBE-04-2020-0066
Alagoz, S. M., & Hekimoglu, H. (2012). A Study on Tam: Analysis of Customer Attitudes in Online Food Ordering System. Procedia - Social and Behavioral Sciences, 62, 1138–1143. https://doi.org/10.1016/j.sbspro.2012.09.195
Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37, 99–110. https://doi.org/10.1016/j.ijinfomgt.2017.01.002
Ali, S., Khalid, N., Javed, H. M. U., & Islam, D. M. Z. (2021). 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, 7(1), 1–23. https://doi.org/10.3390/joitmc7010010
Almarri, H., Ameen, A., Bhaumik, A., Alrajawy, I., & Khalifa, G. S. A. (2020). The Mediating Effect of Facilitating Conditions on The Relationship Between Actual Usage of Online Social Networks (OSN) and User Satisfaction. International Journal of Psychosocial Rehabilitation, 24(06), 6389–6400.
Ambarwati, R., Harja, Y. D., & Thamrin, S. (2020). The Role of Facilitating Conditions and User Habits: A Case of Indonesian Online Learning Platform. Journal of Asian Finance, Economics, and Business, 7(10), 481–489. https://doi.org/10.13106/jafeb.2020.vol7.no10.481
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
Amoroso, D., & Lim, R. (2017). The mediating effects of habit on continuance intention. International Journal of Information Management, 37(6), 693–702.
Anand, T., Ramachandran, J., Sambasivan, M., & Batra, G. S. (2019). Impact of Hedonic Motivation on Consumer Satisfaction Towards Online Shopping: Evidence from Malaysia. E-Service Journal, 11(1), 88. https://doi.org/10.2979/eservicej.11.1.03
Anderson, R. E., & Srinivasan, S. S. (2003). E-satisfaction and e-loyalty: A contingency framework. Psychology and Marketing, 20(2), 123–138.
Ashraf, M., Ahmad, J., Sharif, W., Raza, A. A., Salman Shabbir, M., Abbas, M., & Thurasamy, R. (2020). The role of continuous trust in the usage of online product recommendations. Online Information Review, 44(4), 745–766. https://doi.org/10.1108/OIR-05-2018-0156
Baabdullah, A. M., Alalwan, A. A., Rana, N. P., Kizgin, H., & Patil, P. (2019). Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model. International Journal of Information Management, 44, 38–52. https://doi.org/10.1016/j.ijinfomgt.2018.09.002
Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418–430. https://doi.org/10.1016/j.chb.2015.04.024
Becker, J. M., Ringle, C. M., Sarstedt, M., & Völckner, F. (2015). How collinearity affects mixture regression results. Marketing Letters, 26(4), 643–659. https://doi.org/10.1007/s11002-014-9299-9
Bert, F., Giacometti, M., Gualano, M. R., & Siliquini, R. (2014). Smartphones and health promotion: A review of the evidence. Journal of Medical Systems, 38(1), 1–11. https://doi.org/10.1007/s10916-013-9995-7
Bewley, A., Ge, Z., Ott, L., Ramos, F., & Upcroft, B. (2016). Simple online and real-time tracking. Proceedings - International Conference on Image Processing, ICIP, 2016-August, 3464–3468. https://doi.org/10.1109/ICIP.2016.7533003
Bolen, M. C. (2020). Exploring the determinants of users’ continuance intention in smartwatches. Technology in Society, 60, 101209. https://doi.org/10.1016/j.techsoc.2019.101209
Casaló, L. V., Flavián, C., Guinalíu, M., & Ekinci, Y. (2015). Do online hotel rating schemes influence booking behaviors? International Journal of Hospitality Management, 49, 28–36. https://doi.org/10.1016/j.ijhm.2015.05.005
Chan, F. K., Thong, J. Y., Venkatesh, V., Brown, S. A., Jen-Hwa Hu, P., & Yan Tam, K. (2010). Modeling Citizen Satisfaction with Mandatory Adoption of an E-Government Technology. Journal of the Association for Information, 11(10), 519–549.
Chen, Y., & Xie, J. (2008). Online consumer review: Word-of-mouth as a new element of the marketing communication mix. Management Science, 54(3), 477–491. https://doi.org/10.1287/mnsc.1070.0810
Chen, Z., Ling, K. ., Ying, G. ., & Meng, T. . (2012). Antecedents of online customer satisfaction in China. International Business Management, 6(2), 168–175.
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(February 2018), 108–116. https://doi.org/10.1016/j.ijhm.2018.06.019
Chong, A. Y.-L. (2013). Understanding mobile commerce continuance intentions: An empirical analysis of Chinese consumers. Journal of Computer Information Systems, 53(4), 22–30. https://doi.org/10.1080/08874417.2013.11645647
Chong, A. Y. L. (2013). Mobile commerce usage activities: The roles of demographic and motivation variables. Technological Forecasting and Social Change, 80(7), 1350–1359. https://doi.org/10.1016/j.techfore.2012.12.011
Chopdar, P. K., & Sivakumar, V. J. (2019). Impulsiveness and its impact on behavioral intention and use of mobile shopping apps: A mediation model. International Journal of Business Innovation and Research, 19(1), 29–56. https://doi.org/10.1504/IJBIR.2019.099754
Christino, J. M. M., Cardozo, E. A. A., Petrin, R., & Pinto, L. H. de A. (2020). Factors Influencing the Intent and Usage Behavior of Restaurant Delivery Apps. Review of Business Management - RBGN, 23(1), 21–42. https://doi.org/10.7819/rbgn.v23i1.4095
Christodoulides, G., & Michaelidou, N. (2011). Shopping motives as antecedents of e-satisfaction and e-loyalty. Journal of Marketing Management, 27(1–2), 181–197. https://doi.org/10.1080/0267257X.2010.489815
Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319–339.
Davis, Fred D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008
El-Adly, M. I. (2019). Modeling the relationship between hotel perceived value, customer satisfaction, and customer loyalty. Journal of Retailing and Consumer Services, 50, 322–332. https://doi.org/10.1016/j.jretconser.2018.07.007
Elwalda, A., Lü, K., & Ali, M. (2016). Perceived derived attributes of online customer reviews. Computers in Human Behavior, 56, 306–319. https://doi.org/10.1016/j.chb.2015.11.051
Filieri, R. (2015). What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM. Journal of Business Research, 68(6), 1261–1270. https://doi.org/10.1016/j.jbusres.2014.11.006
Filieri, R., & McLeay, F. (2014). E-WOM and Accommodation: An Analysis of the Factors That Influence Travelers’ Adoption of Information from Online Reviews. Journal of Travel Research, 53(1), 44–57. https://doi.org/10.1177/0047287513481274
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
Franke, G., & Sarstedt, M. (2019). Heuristics versus statistics in discriminant validity testing: a comparison of four procedures. Internet Research, 29(3), 430–447. https://doi.org/10.1108/IntR-12-2017-0515
Gutierrez, A., O’Leary, S., Rana, N. P., Dwivedi, Y. K., & Calle, T. (2019). Using privacy calculus theory to explore entrepreneurial directions in mobile location-based advertising: Identifying intrusiveness as the critical risk factor. Computers in Human Behavior, 95, 295–306. https://doi.org/10.1016/j.chb.2018.09.015
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
Hew, J. J., Lee, V. H., Ooi, K. B., & Wei, J. (2015). What catalyzes mobile apps usage intention: An empirical analysis. Industrial Management and Data Systems, 115(7), 1269–1291. https://doi.org/10.1108/IMDS-01-2015-0028
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
Hsu, C. L., & Lin, J. C. C. (2015). What drives purchase intention for paid mobile apps?-An expectation confirmation model with perceived value. Electronic Commerce Research and Applications, 14(1), 46–57. https://doi.org/10.1016/j.elerap.2014.11.003
Huang, C. Y., & Kao, Y. S. (2015). UTAUT2 Based Predictions of Factors Influencing the Technology Acceptance of Phablets by DNP. Mathematical Problems in Engineering, 2015, 1–39. https://doi.org/10.1155/2015/603747
Hung, M.-C., Yang, S.-T., & Hsieh, T.-C. (2012). An Examination Of The Determinants of Mobile Shopping Continuance. In International Journal of Electronic Business Management (Vol. 10, Issue 1).
Hussien, F. M., & Mansour, N. M. (2020). Factors Affecting Customer Satisfaction towards Mobile Food Ordering Applications (MFOAs). In Alexandria University (Vol. 17).
Im, I., Hong, S., & Kang, M. S. (2011). An international comparison of technology adoption: Testing the UTAUT model. Information and Management, 48(1), 1–8.
Islam, N. (2011). Understanding Continued Usage Intention in e-Learning Context. http://aisel.aisnet.org/bled2011/28
Iyer, P., Davari, A., & Mukherjee, A. (2018). Investigating the effectiveness of retailers’ mobile applications in determining customer satisfaction and patronage intentions? A congruency perspective. Journal of Retailing and Consumer Services, 44, 235–243. https://doi.org/10.1016/j.jretconser.2018.07.017
Joo, S., & Choi, N. (2016). Understanding users’ continuance intention to use online library resources based on an extended expectation-confirmation model. Electronic Library, 34(4), 554–571. https://doi.org/10.1108/EL-02-2015-0033
Kaewkitipong, L., Chen, C. C., & Ractham, P. (2016). A community-based approach to sharing knowledge before, during, and after crisis events: A case study from Thailand. Computers in Human Behavior, 54, 653–666. https://doi.org/10.1016/j.chb.2015.07.063
Kapoor, A. P., & Vij, M. (2018). Technology at the dinner table: Ordering food online through mobile apps. Journal of Retailing and Consumer Services, 43(March), 342–351. https://doi.org/10.1016/j.jretconser.2018.04.001
Kaynak, H. (2003). The relationship between total quality management practices and their effects on firm performance. Journal of Operations Management, 21(4), 405–435. https://doi.org/10.1016/S0272-6963(03)00004-4
Ketelaar, P. E., Willemsen, L. M., Sleven, L., & Kerkhof, P. (2015). The Good, the Bad, and the Expert: How Consumer Expertise Affects Review Valence Effects on Purchase Intentions in Online Product Reviews. Journal of Computer-Mediated Communication, 20(6), 649–666. https://doi.org/10.1111/jcc4.12139
Kim, S. S., Malhotra, N. K., & Narasimhan, S. (2005). Two competing perspectives on automatic use: A theoretical and empirical comparison. Information Systems Research, 16(4), 418–432. https://doi.org/10.1287/isre.1050.0070
King, R. A., Racherla, P., & Bush, V. D. (2014). What we know and do not know about online word-of-mouth: A review and synthesis of the literature. Journal of Interactive Marketing, 28(3), 167–183. https://doi.org/10.1016/j.intmar.2014.02.001
Korfiatis, N., García-Bariocanal, E., & Sánchez-Alonso, S. (2012). Evaluating content quality and helpfulness of online product reviews: The interplay of review helpfulness vs. review content. Electronic Commerce Research and Applications, 11(3), 205–217. https://doi.org/10.1016/j.elerap.2011.10.003
Lacey, R., Suh, J., & Morgan, R. M. (2007). Differential effects of preferential treatment levels on relational outcomes. Journal of Service Research, 9(3), 241–256. https://doi.org/10.1177/1094670506295850
Lai, I. K. W. (2015). Traveler Acceptance of an App-Based Mobile Tour Guide. Journal of Hospitality and Tourism Research, 39(3), 401–432. https://doi.org/10.1177/1096348013491596
Lee, S. W., Sung, H. J., & Mo Jeon, H. (n.d.). Determinants of Continuous Intention on Food Delivery Apps: Extending UTAUT2 with Information Quality. https://doi.org/10.3390/su11113141
Lee, W. K. (2014). The temporal relationships among habit, intention, and IS uses. Computers in Human Behavior, 32, 54–60. https://doi.org/10.1016/j.chb.2013.11.010
Li, C., Mirosa, M., & Bremer, P. (2020). Review of online food delivery platforms and their impacts on sustainability. Sustainability (Switzerland), 12(14), 1–17. https://doi.org/10.3390/su12145528
Limayem, M., Hirt, S. G., Cheung, C. M. K., & Hirt, S. G. (2007). How habit limits the predictive power of intention. The Case of Information Systems Continuance. MIS Quarterly, 31(4), 705–737.
Loureiro, S. M. C., Cavallero, L., & Miranda, F. J. (2018). Fashion brands on retail websites: Customer performance expectancy and e-word-of-mouth. Journal of Retailing and Consumer Services, 41, 131–141. https://doi.org/10.1016/j.jretconser.2017.12.005
Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29–39.
Ludwig, S., De Ruyter, K., Friedman, M., Brüggen, E. C., Wetzels, M., & Pfann, G. (2013). More than words: The influence of affective content and linguistic style matches online reviews on conversion rates. In Journal of Marketing (Vol. 77, Issue 1, pp. 87–103). American Marketing Association. https://doi.org/10.1509/jm.11.0560
Magni, M., Taylor, M. S., & Venkatesh, V. (2010). “To play or not to play”: A cross-temporal investigation using hedonic and instrumental perspectives to explain user intentions to explore a technology. International Journal of Human-Computer Studies, 68(9), 572–588. https://doi.org/10.1016/j.ijhcs.2010.03.004
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
Marinković, V., Đorđević, A., & Kalinić, Z. (2020). The moderating effects of gender on customer satisfaction and continuance intention in mobile commerce: a UTAUT-based perspective. Technology Analysis and Strategic Management, 32(3), 306–318. https://doi.org/10.1080/09537325.2019.1655537
Mason, C. H., & Perreault, W. D. (1991). Collinearity, Power, and Interpretation of Multiple Regression Analysis. Journal of Marketing Research, 28(3), 268–280. https://doi.org/10.1177/002224379102800302
Morosan, C., & DeFranco, A. (2016). It is about time: Revisiting UTAUT2 to examine consumers’ intentions to use NFC mobile payments in hotels. International Journal of Hospitality Management, 53, 17–29. https://doi.org/10.1016/j.ijhm.2015.11.003
Mun, Y. P., Khalid, H., & Nadarajah, D. (2017). Millennials’ Perception of Mobile Payment Services in Malaysia. Procedia Computer Science, 124, 397–404.
Ogara, S. O., Koh, C. E., & Prybutok, V. R. (2014). Investigating factors affecting the social presence and user satisfaction with Mobile Instant Messaging. Computers in Human Behavior, 36, 453–459. https://doi.org/10.1016/j.chb.2014.03.064
Okumus. (2016). Factors Affecting the Acceptance of Smartphone Diet Applications. Journal f Hospitality Marketing and Management, 25(6), 726–747.
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(October 2016), 67–77. https://doi.org/10.1016/j.ijhm.2018.01.001
Okumus, B., & Bilgihan, A. (2014). Proposing a model to test smartphone users’ intention to use smart applications when ordering food in restaurants. Journal of Hospitality and Tourism Technology, 5(1), 31–49. https://doi.org/10.1108/JHTT-01-2013-0003
Oliver, R. L. (1999). Whence consumer loyalty? Journal of Marketing, 63(4), 33–44. https://doi.org/10.2307/1252099
Oyedele, A., Saldivar, R., Hernandez, M. D., & Goenner, E. (2018). Modeling satisfaction and repurchase intentions of mobile smart wristbands: the role of social mindfulness and perceived value. Young Consumers, 19(3), 237–250. https://doi.org/10.1108/YC-09-2017-00737
https://doi.org/10.1016/j.ijhm.2016.06.007
Palau-Saumell, R., Forgas-Coll, S., Sánchez-García, J., & Robres, E. (2019). User acceptance of mobile apps for restaurants: An expanded and extended UTAUT-2. In Sustainability (Switzerland) (Vol. 11, Issue 4). https://doi.org/10.3390/su10021210
Pappas, I. O., Pateli, A. G., Giannakos, M. N., & Chrissikopoulos, V. (2014). Moderating effects of online shopping experience on customer satisfaction and repurchase intentions. International Journal of Retail and Distribution Management, 42(3), 187–204. https://doi.org/10.1108/IJRDM-03-2012-0034
Pavlou, P. A., & Dimoka, A. (2006). The nature and role of feedback text comments in online marketplaces: Implications for trust-building, price premiums, and seller differentiation. Information Systems Research, 17(4), 392–414. https://doi.org/10.1287/isre.1060.0106
Pigatto, G., Guilherme De Camargo, J., Machado, F., Dos, A., Negreti, S., & Machado, L. M. (2017). Have you chosen your request? Analysis of online food delivery companies in Brazil. British Food Journal. https://doi.org/10.1108/BFJ-05-2016-0207
Prasetyo, Y. T., Tanto, H., Mariyanto, M., Hanjaya, C., Young, M. N., Persada, S. F., Miraja, B. A., & Redi, A. A. N. P. (2021). Factors affecting customer satisfaction and loyalty in online food delivery service during the COVID-19 pandemic: Its relation with open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), 1–17. https://doi.org/10.3390/joitmc7010076
Jenny Preece, H. S., & Rogers, Y. (2015). Interaction design: Beyond human-computer interaction.
Pura, M. (2005). Linking perceived value and loyalty in location-based mobile services. Managing Service Quality, 15(6), 509–538. https://doi.org/10.1108/09604520510634005
Qiu, L., Pang, J., & Lim, K. H. (2012). Effects of conflicting aggregated rating on eWOM review credibility and diagnosticity: The moderating role of review valence. Decision Support Systems, 54(1), 631–643. https://doi.org/10.1016/j.dss.2012.08.020
Rafie, M., Arshad, M., & Gharaibeh, N. (2018). Using the UTAUT2 Model to Determine Factors Affecting Adoption of Mobile Banking Services: A Qualitative Approach. Article in International Journal of Interactive Mobile Technologies. https://doi.org/10.3991/ijim.v12i4.8525
Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V. (2016). Adoption of online public grievance redressal system in India: Toward developing a unified view. Computers in Human Behavior, 59, 265–282. https://doi.org/10.1016/j.chb.2016.02.019
Razak, F. Z. B. A., Bakar, A. A., & Abdullah, W. S. W. (2017). How perceived effort expectancy and social influence affects the continuance of intention to use e-government. A study of Malaysian government service. Electronic Government, 13(1), 69–80. https://doi.org/10.1504/EG.2017.083943
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. https://www.researchgate.net/publication/349552360
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(September 2018), 262–273.
https://doi.org/10.1016/j.ijinfomgt.2018.09.017
Roy, P. K., Ahmad, Z., Singh, J. P., Alryalat, M. A. A., Rana, N. P., & Dwivedi, Y. K. (2018). Finding and Ranking High-Quality Answers in Community Question Answering Sites. Global Journal of Flexible Systems Management, 19(1), 53–68.
https://doi.org/10.1007/s40171-017-0172-6
Ryu, K., Han, H., & Jang, S. S. (2010). Relationships among hedonic and utilitarian values, satisfaction, and behavioral intentions in the fast-casual restaurant industry. International Journal of Contemporary Hospitality Management, 22(3), 416–432.
https://doi.org/10.1108/09596111011035981
Sair, S. A., & Danish, R. Q. (2018). Effect of performance expectancy and effort expectancy on the mobile commerce adoption intention through personal innovativeness among Pakistani consumers. Pakistan Journal of Commerce and Social Science, 12(2), 501–520.
https://doi.org/10.1108/17579881011078340
Shah, S. A. M., Iqbal, N., Janjua, S. Y., & Amjad, S. (2013). Employee behavior towards adoption of E-learning courses: Validating technology acceptance model. Mediterranean Journal of Social Sciences, 4(14), 765–774.
https://doi.org/10.5901/mjss.2013.v4n14p765
Shareef, M. A., Baabdullah, A., Dutta, S., Kumar, V., & Dwivedi, Y. K. (2018). Consumer adoption of mobile banking services: An empirical examination of factors according to adoption stages. Journal of Retailing and Consumer Services, 43, 54–67. https://doi.org/10.1016/j.jretconser.2018.03.003
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
Shugan, S. M. (2004). The Impact of Advancing Technology on Marketing and Academic Research. Marketing Science, 23(4), 469–475. https://doi.org/10.1287/mksc.1040.0096
Simonson, I., & Rosen, E. (2014). What marketers misunderstand about online reviews - Dialnet. Harvard Business Review, 92(1), 23–25.
Singh, N., Sinha, N., & Liébana-Cabanillas, F. J. (2020). Determining factors in the adoption and recommendation of mobile wallet services in India: Analysis of the effect of innovativeness, stress to use, and social influence. International Journal of Information Management, 50, 191–205. https://doi.org/10.1016/j.ijinfomgt.2019.05.022
Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015). Modeling Consumers’ Adoption Intentions of Remote Mobile Payments in the United Kingdom: Extending UTAUT with Innovativeness, Risk, and Trust. Psychology and Marketing, 32(8), 860–873. https://doi.org/10.1002/mar.20823
Spyridou, A. (2017). Perceived Service Quality and Customer Revisiting Intention: The Case of “all you can eat” Asian Restaurants in Southern Taiwan. Journal of Tourism, Heritage & Services Marketing, 3(2), 30–31.
Susanto, A., Chang, Y., & Ha, Y. (2016). Determinants of continuance intention to use the smartphone banking services: An extension to the expectation-confirmation model. Industrial Management and Data Systems, 116(3), 508–525.
https://doi.org/10.1108/IMDS-05-2015-0195
Tran, L. T. T., Pham, L. M. T., & Le, L. T. (2019). E-satisfaction and continuance intention: The moderator role of online ratings. International Journal of Hospitality Management, 77, 311–322. https://doi.org/10.1016/j.ijhm.2018.07.011
Venkatesh, V., Morris, M.G., Davis, G. B. & D., & D.F. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(7), 425–478.
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. JSTOR, 36(1), 22.
Venkatesh. (2003a). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. https://doi.org/DOI: 10.2307/30036540
Venkatesh, V. (2003b). Angiogenesis induced by mast cell secretion in rat peritoneal connective tissue is a process of three phases. Microvascular Research, 47(2), 252–269. https://doi.org/10.1006/mvre.1994.1019
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, 27(3), 425–478. https://doi.org/10.2307/30036540
Verkijika, S. F. (2018). Factors influencing the adoption of mobile commerce applications in Cameroon. Telematics and Informatics, 35(6), 1665–1674.
https://doi.org/10.1016/j.tele.2018.04.012
Verplanken, B., & Wood, W. (2006). Interventions to break and create consumer habits. In Journal of Public Policy and Marketing (Vol. 25, Issue 1, pp. 90–103). American Marketing Association. https://doi.org/10.1509/jppm.25.1.90
Wang, C., Harris, J., & Patterson, P. (2013). The Roles of Habit, Self-Efficacy, and Satisfaction in Driving Continued Use of Self-Service Technologies: A Longitudinal Study. Journal of Service Research, 16(3), 400–414.
Wang, E. S. T., & Chou, N. P. Y. (2016). Examining social influence factors affecting consumer continuous usage intention for mobile social networking applications. International Journal of Mobile Communications, 14(1), 43–55.
Wang, H. Y., & Wang, S. H. (2010). Predicting mobile hotel reservation adoption: Insight from a perceived value standpoint. International Journal of Hospitality Management, 29(4), 598–608. https://doi.org/10.1016/j.ijhm.2009.11.001
Wang, Q., Khan, M. S., & Khan, M. K. (2021). Predicting user-perceived satisfaction and reuse intentions toward Massive Open Online Courses (MOOCs) in the Covid-19 pandemic. International Journal of Research in Business and Social Science (2147- 4478), 10(2), 1–11. https://doi.org/10.20525/ijrbs.v10i2.1045
Wang, Y. S., Tseng, T. H., Wang, W. T., Shih, Y. W., & Chan, P. Y. (2019). Developing and validating a mobile catering app success model. International Journal of Hospitality Management, 77(April 2018), 19–30. https://doi.org/10.1016/j.ijhm.2018.06.002
Wang, Y. S., Wang, Y. M., Lin, H. H., & Tang, T. I. (2003). Determinants of user acceptance of Internet banking: An empirical study. International Journal of Service Industry Management, 14(5), 501–519. https://doi.org/10.1108/09564230310500192
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information and Management, 42(5), 719–729. https://doi.org/10.1016/j.im.2004.07.001
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(December 2016), 150–162.
https://doi.org/10.1016/j.jretconser.2016.12.013
Yoon, Y. C., Kim, D. Y., Song, Y. M., Yoon, K., & Jeon, M. (2021). Online multiple pedestrians tracking using deep temporal appearance matching association. Information Sciences, 561, 326–351. https://doi.org/10.1016/j.ins.2020.10.002
Yu, C. S. (2012). Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT model. Journal of Electronic Commerce Research, 13(2), 105–121.
Yuan, Shunbo, Liu, Y., Yao, R., & Liu, J. (2016). An investigation of users’ continuance intention towards mobile banking in China. Information Development, 32(1), 20–34. https://doi.org/10.1177/0266666914522140
Yuan, Shupei, Ma, W., Kanthawala, S., & Peng, W. (2015). Keep Using My Health Apps: Discover Users’ Perception of Health and Fitness Apps with the UTAUT2 Model. Telemedicine and E-Health, 21(9), 735–741. https://doi.org/10.1089/tmj.2014.0148
Zadeh, S. M. M., Cheng, L., Ghanei-Yakhdan, H., & Kasaei, S. (2021). Deep Learning for Visual Tracking: A Comprehensive Survey. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/TITS.2020.3046478
Zahid, H., & Din, B. H. (2019). Determinants of Intention to Adopt E-Government Services in Pakistan: An Imperative for Sustainable Development.
https://doi.org/10.3390/resources8030128
Zhao, L., Lu, Y., Zhang, L., & Chau, P. Y. K. (2012). Assessing the effects of service quality and justice on customer satisfaction and the continuance intention of mobile value-added services: An empirical test of a multidimensional model. Decision Support Systems, 52(3), 645–656. https://doi.org/10.1016/j.dss.2011.10.022
Zhou, T. (2011). An empirical examination of initial trust in mobile banking. Internet Research, 21(5), 527–540. https://doi.org/10.1108/1066224111117
Zulkefli, N. H., Salleh, N. S. A., Ghani, F. A., Razali, N. A., & Idris, R. S. N. R. (2020). Determinants of Behavioral Intention on Online Food Delivery (OFD) APPS: Extending UTAUT2 with Information Quality. In Global Business and Management Research: An International Journal (Vol. 12, Issue 4).
Ajzen, I., & Fishbein, M. (2005). The Influence of Attitudes on Behavior. In The Handbook of Attitudes, D. Albarracin, В. T. Johnson, and M. P. Zanna (Eds.), Mahwah, NJ: Erlbaum, Pp., 173–221.
Ajzen, I., & Fishbein, M. (1969). The prediction of behavioral intentions in a choice situation. Journal of Experimental Social Psychology, 5(4), 400–416. https://doi.org/10.1016/0022-1031(69)90033-X
Akel, G., & Armagan, E. (2021). Hedonic and utilitarian benefits as determinants of the application continuance intention in location-based applications: the mediating role of satisfaction. Multimedia Tools and Applications, 80(5), 7103–7124. https://doi.org/10.1007/s11042-020-10094-2
Albarq, A. (2024). The emergence of mobile payment acceptance in Saudi Arabia: the role of reimbursement condition. Journal of Islamic Marketing, 15(6), 1632-1650.
Al Amin, Md., Arefin, M. S., Sultana, N., Islam, M. R., Jahan, I., & Akhtar, A. (2021). Evaluating the customers’ dining attitudes, e-satisfaction, and continuance intention toward mobile food ordering apps (MFOAs): evidence from Bangladesh. European Journal of Management and Business Economics, 30(2), 211–229. https://doi.org/10.1108/ejmbe-04-2020-0066
Al Amin, Md, Arefin, M. S., Sultana, N., Islam, M. R., Jahan, I., & Akhtar, A. (2020). Evaluating the customers’ dining attitudes, e-satisfaction, and continuance intention toward mobile food ordering apps (MFOAs): evidence from Bangladesh Evaluating the customers’ dining attitudes. European Journal of Management and Business Economics. https://doi.org/10.1108/EJMBE-04-2020-0066
Alagoz, S. M., & Hekimoglu, H. (2012). A Study on Tam: Analysis of Customer Attitudes in Online Food Ordering System. Procedia - Social and Behavioral Sciences, 62, 1138–1143. https://doi.org/10.1016/j.sbspro.2012.09.195
Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37, 99–110. https://doi.org/10.1016/j.ijinfomgt.2017.01.002
Ali, S., Khalid, N., Javed, H. M. U., & Islam, D. M. Z. (2021). 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, 7(1), 1–23. https://doi.org/10.3390/joitmc7010010
Almarri, H., Ameen, A., Bhaumik, A., Alrajawy, I., & Khalifa, G. S. A. (2020). The Mediating Effect of Facilitating Conditions on The Relationship Between Actual Usage of Online Social Networks (OSN) and User Satisfaction. International Journal of Psychosocial Rehabilitation, 24(06), 6389–6400.
Ambarwati, R., Harja, Y. D., & Thamrin, S. (2020). The Role of Facilitating Conditions and User Habits: A Case of Indonesian Online Learning Platform. Journal of Asian Finance, Economics, and Business, 7(10), 481–489. https://doi.org/10.13106/jafeb.2020.vol7.no10.481
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
Amoroso, D., & Lim, R. (2017). The mediating effects of habit on continuance intention. International Journal of Information Management, 37(6), 693–702.
Anand, T., Ramachandran, J., Sambasivan, M., & Batra, G. S. (2019). Impact of Hedonic Motivation on Consumer Satisfaction Towards Online Shopping: Evidence from Malaysia. E-Service Journal, 11(1), 88. https://doi.org/10.2979/eservicej.11.1.03
Anderson, R. E., & Srinivasan, S. S. (2003). E-satisfaction and e-loyalty: A contingency framework. Psychology and Marketing, 20(2), 123–138.
Ashraf, M., Ahmad, J., Sharif, W., Raza, A. A., Salman Shabbir, M., Abbas, M., & Thurasamy, R. (2020). The role of continuous trust in the usage of online product recommendations. Online Information Review, 44(4), 745–766. https://doi.org/10.1108/OIR-05-2018-0156
Baabdullah, A. M., Alalwan, A. A., Rana, N. P., Kizgin, H., & Patil, P. (2019). Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model. International Journal of Information Management, 44, 38–52. https://doi.org/10.1016/j.ijinfomgt.2018.09.002
Baptista, G., & Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptance and use of technology combined with cultural moderators. Computers in Human Behavior, 50, 418–430. https://doi.org/10.1016/j.chb.2015.04.024
Becker, J. M., Ringle, C. M., Sarstedt, M., & Völckner, F. (2015). How collinearity affects mixture regression results. Marketing Letters, 26(4), 643–659. https://doi.org/10.1007/s11002-014-9299-9
Bert, F., Giacometti, M., Gualano, M. R., & Siliquini, R. (2014). Smartphones and health promotion: A review of the evidence. Journal of Medical Systems, 38(1), 1–11. https://doi.org/10.1007/s10916-013-9995-7
Bewley, A., Ge, Z., Ott, L., Ramos, F., & Upcroft, B. (2016). Simple online and real-time tracking. Proceedings - International Conference on Image Processing, ICIP, 2016-August, 3464–3468. https://doi.org/10.1109/ICIP.2016.7533003
Bolen, M. C. (2020). Exploring the determinants of users’ continuance intention in smartwatches. Technology in Society, 60, 101209. https://doi.org/10.1016/j.techsoc.2019.101209
Casaló, L. V., Flavián, C., Guinalíu, M., & Ekinci, Y. (2015). Do online hotel rating schemes influence booking behaviors? International Journal of Hospitality Management, 49, 28–36. https://doi.org/10.1016/j.ijhm.2015.05.005
Chan, F. K., Thong, J. Y., Venkatesh, V., Brown, S. A., Jen-Hwa Hu, P., & Yan Tam, K. (2010). Modeling Citizen Satisfaction with Mandatory Adoption of an E-Government Technology. Journal of the Association for Information, 11(10), 519–549.
Chen, Y., & Xie, J. (2008). Online consumer review: Word-of-mouth as a new element of the marketing communication mix. Management Science, 54(3), 477–491. https://doi.org/10.1287/mnsc.1070.0810
Chen, Z., Ling, K. ., Ying, G. ., & Meng, T. . (2012). Antecedents of online customer satisfaction in China. International Business Management, 6(2), 168–175.
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(February 2018), 108–116. https://doi.org/10.1016/j.ijhm.2018.06.019
Chong, A. Y.-L. (2013). Understanding mobile commerce continuance intentions: An empirical analysis of Chinese consumers. Journal of Computer Information Systems, 53(4), 22–30. https://doi.org/10.1080/08874417.2013.11645647
Chong, A. Y. L. (2013). Mobile commerce usage activities: The roles of demographic and motivation variables. Technological Forecasting and Social Change, 80(7), 1350–1359. https://doi.org/10.1016/j.techfore.2012.12.011
Chopdar, P. K., & Sivakumar, V. J. (2019). Impulsiveness and its impact on behavioral intention and use of mobile shopping apps: A mediation model. International Journal of Business Innovation and Research, 19(1), 29–56. https://doi.org/10.1504/IJBIR.2019.099754
Christino, J. M. M., Cardozo, E. A. A., Petrin, R., & Pinto, L. H. de A. (2020). Factors Influencing the Intent and Usage Behavior of Restaurant Delivery Apps. Review of Business Management - RBGN, 23(1), 21–42. https://doi.org/10.7819/rbgn.v23i1.4095
Christodoulides, G., & Michaelidou, N. (2011). Shopping motives as antecedents of e-satisfaction and e-loyalty. Journal of Marketing Management, 27(1–2), 181–197. https://doi.org/10.1080/0267257X.2010.489815
Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319–339.
Davis, Fred D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008
El-Adly, M. I. (2019). Modeling the relationship between hotel perceived value, customer satisfaction, and customer loyalty. Journal of Retailing and Consumer Services, 50, 322–332. https://doi.org/10.1016/j.jretconser.2018.07.007
Elwalda, A., Lü, K., & Ali, M. (2016). Perceived derived attributes of online customer reviews. Computers in Human Behavior, 56, 306–319. https://doi.org/10.1016/j.chb.2015.11.051
Filieri, R. (2015). What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM. Journal of Business Research, 68(6), 1261–1270. https://doi.org/10.1016/j.jbusres.2014.11.006
Filieri, R., & McLeay, F. (2014). E-WOM and Accommodation: An Analysis of the Factors That Influence Travelers’ Adoption of Information from Online Reviews. Journal of Travel Research, 53(1), 44–57. https://doi.org/10.1177/0047287513481274
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
Franke, G., & Sarstedt, M. (2019). Heuristics versus statistics in discriminant validity testing: a comparison of four procedures. Internet Research, 29(3), 430–447. https://doi.org/10.1108/IntR-12-2017-0515
Gutierrez, A., O’Leary, S., Rana, N. P., Dwivedi, Y. K., & Calle, T. (2019). Using privacy calculus theory to explore entrepreneurial directions in mobile location-based advertising: Identifying intrusiveness as the critical risk factor. Computers in Human Behavior, 95, 295–306. https://doi.org/10.1016/j.chb.2018.09.015
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
Hew, J. J., Lee, V. H., Ooi, K. B., & Wei, J. (2015). What catalyzes mobile apps usage intention: An empirical analysis. Industrial Management and Data Systems, 115(7), 1269–1291. https://doi.org/10.1108/IMDS-01-2015-0028
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
Hsu, C. L., & Lin, J. C. C. (2015). What drives purchase intention for paid mobile apps?-An expectation confirmation model with perceived value. Electronic Commerce Research and Applications, 14(1), 46–57. https://doi.org/10.1016/j.elerap.2014.11.003
Huang, C. Y., & Kao, Y. S. (2015). UTAUT2 Based Predictions of Factors Influencing the Technology Acceptance of Phablets by DNP. Mathematical Problems in Engineering, 2015, 1–39. https://doi.org/10.1155/2015/603747
Hung, M.-C., Yang, S.-T., & Hsieh, T.-C. (2012). An Examination Of The Determinants of Mobile Shopping Continuance. In International Journal of Electronic Business Management (Vol. 10, Issue 1).
Hussien, F. M., & Mansour, N. M. (2020). Factors Affecting Customer Satisfaction towards Mobile Food Ordering Applications (MFOAs). In Alexandria University (Vol. 17).
Im, I., Hong, S., & Kang, M. S. (2011). An international comparison of technology adoption: Testing the UTAUT model. Information and Management, 48(1), 1–8.
Islam, N. (2011). Understanding Continued Usage Intention in e-Learning Context. http://aisel.aisnet.org/bled2011/28
Iyer, P., Davari, A., & Mukherjee, A. (2018). Investigating the effectiveness of retailers’ mobile applications in determining customer satisfaction and patronage intentions? A congruency perspective. Journal of Retailing and Consumer Services, 44, 235–243. https://doi.org/10.1016/j.jretconser.2018.07.017
Joo, S., & Choi, N. (2016). Understanding users’ continuance intention to use online library resources based on an extended expectation-confirmation model. Electronic Library, 34(4), 554–571. https://doi.org/10.1108/EL-02-2015-0033
Kaewkitipong, L., Chen, C. C., & Ractham, P. (2016). A community-based approach to sharing knowledge before, during, and after crisis events: A case study from Thailand. Computers in Human Behavior, 54, 653–666. https://doi.org/10.1016/j.chb.2015.07.063
Kapoor, A. P., & Vij, M. (2018). Technology at the dinner table: Ordering food online through mobile apps. Journal of Retailing and Consumer Services, 43(March), 342–351. https://doi.org/10.1016/j.jretconser.2018.04.001
Kaynak, H. (2003). The relationship between total quality management practices and their effects on firm performance. Journal of Operations Management, 21(4), 405–435. https://doi.org/10.1016/S0272-6963(03)00004-4
Ketelaar, P. E., Willemsen, L. M., Sleven, L., & Kerkhof, P. (2015). The Good, the Bad, and the Expert: How Consumer Expertise Affects Review Valence Effects on Purchase Intentions in Online Product Reviews. Journal of Computer-Mediated Communication, 20(6), 649–666. https://doi.org/10.1111/jcc4.12139
Kim, S. S., Malhotra, N. K., & Narasimhan, S. (2005). Two competing perspectives on automatic use: A theoretical and empirical comparison. Information Systems Research, 16(4), 418–432. https://doi.org/10.1287/isre.1050.0070
King, R. A., Racherla, P., & Bush, V. D. (2014). What we know and do not know about online word-of-mouth: A review and synthesis of the literature. Journal of Interactive Marketing, 28(3), 167–183. https://doi.org/10.1016/j.intmar.2014.02.001
Korfiatis, N., García-Bariocanal, E., & Sánchez-Alonso, S. (2012). Evaluating content quality and helpfulness of online product reviews: The interplay of review helpfulness vs. review content. Electronic Commerce Research and Applications, 11(3), 205–217. https://doi.org/10.1016/j.elerap.2011.10.003
Lacey, R., Suh, J., & Morgan, R. M. (2007). Differential effects of preferential treatment levels on relational outcomes. Journal of Service Research, 9(3), 241–256. https://doi.org/10.1177/1094670506295850
Lai, I. K. W. (2015). Traveler Acceptance of an App-Based Mobile Tour Guide. Journal of Hospitality and Tourism Research, 39(3), 401–432. https://doi.org/10.1177/1096348013491596
Lee, S. W., Sung, H. J., & Mo Jeon, H. (n.d.). Determinants of Continuous Intention on Food Delivery Apps: Extending UTAUT2 with Information Quality. https://doi.org/10.3390/su11113141
Lee, W. K. (2014). The temporal relationships among habit, intention, and IS uses. Computers in Human Behavior, 32, 54–60. https://doi.org/10.1016/j.chb.2013.11.010
Li, C., Mirosa, M., & Bremer, P. (2020). Review of online food delivery platforms and their impacts on sustainability. Sustainability (Switzerland), 12(14), 1–17. https://doi.org/10.3390/su12145528
Limayem, M., Hirt, S. G., Cheung, C. M. K., & Hirt, S. G. (2007). How habit limits the predictive power of intention. The Case of Information Systems Continuance. MIS Quarterly, 31(4), 705–737.
Loureiro, S. M. C., Cavallero, L., & Miranda, F. J. (2018). Fashion brands on retail websites: Customer performance expectancy and e-word-of-mouth. Journal of Retailing and Consumer Services, 41, 131–141. https://doi.org/10.1016/j.jretconser.2017.12.005
Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29–39.
Ludwig, S., De Ruyter, K., Friedman, M., Brüggen, E. C., Wetzels, M., & Pfann, G. (2013). More than words: The influence of affective content and linguistic style matches online reviews on conversion rates. In Journal of Marketing (Vol. 77, Issue 1, pp. 87–103). American Marketing Association. https://doi.org/10.1509/jm.11.0560
Magni, M., Taylor, M. S., & Venkatesh, V. (2010). “To play or not to play”: A cross-temporal investigation using hedonic and instrumental perspectives to explain user intentions to explore a technology. International Journal of Human-Computer Studies, 68(9), 572–588. https://doi.org/10.1016/j.ijhcs.2010.03.004
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
Marinković, V., Đorđević, A., & Kalinić, Z. (2020). The moderating effects of gender on customer satisfaction and continuance intention in mobile commerce: a UTAUT-based perspective. Technology Analysis and Strategic Management, 32(3), 306–318. https://doi.org/10.1080/09537325.2019.1655537
Mason, C. H., & Perreault, W. D. (1991). Collinearity, Power, and Interpretation of Multiple Regression Analysis. Journal of Marketing Research, 28(3), 268–280. https://doi.org/10.1177/002224379102800302
Morosan, C., & DeFranco, A. (2016). It is about time: Revisiting UTAUT2 to examine consumers’ intentions to use NFC mobile payments in hotels. International Journal of Hospitality Management, 53, 17–29. https://doi.org/10.1016/j.ijhm.2015.11.003
Mun, Y. P., Khalid, H., & Nadarajah, D. (2017). Millennials’ Perception of Mobile Payment Services in Malaysia. Procedia Computer Science, 124, 397–404.
Ogara, S. O., Koh, C. E., & Prybutok, V. R. (2014). Investigating factors affecting the social presence and user satisfaction with Mobile Instant Messaging. Computers in Human Behavior, 36, 453–459. https://doi.org/10.1016/j.chb.2014.03.064
Okumus. (2016). Factors Affecting the Acceptance of Smartphone Diet Applications. Journal f Hospitality Marketing and Management, 25(6), 726–747.
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(October 2016), 67–77. https://doi.org/10.1016/j.ijhm.2018.01.001
Okumus, B., & Bilgihan, A. (2014). Proposing a model to test smartphone users’ intention to use smart applications when ordering food in restaurants. Journal of Hospitality and Tourism Technology, 5(1), 31–49. https://doi.org/10.1108/JHTT-01-2013-0003
Oliver, R. L. (1999). Whence consumer loyalty? Journal of Marketing, 63(4), 33–44. https://doi.org/10.2307/1252099
Oyedele, A., Saldivar, R., Hernandez, M. D., & Goenner, E. (2018). Modeling satisfaction and repurchase intentions of mobile smart wristbands: the role of social mindfulness and perceived value. Young Consumers, 19(3), 237–250. https://doi.org/10.1108/YC-09-2017-00737
https://doi.org/10.1016/j.ijhm.2016.06.007
Palau-Saumell, R., Forgas-Coll, S., Sánchez-García, J., & Robres, E. (2019). User acceptance of mobile apps for restaurants: An expanded and extended UTAUT-2. In Sustainability (Switzerland) (Vol. 11, Issue 4). https://doi.org/10.3390/su10021210
Pappas, I. O., Pateli, A. G., Giannakos, M. N., & Chrissikopoulos, V. (2014). Moderating effects of online shopping experience on customer satisfaction and repurchase intentions. International Journal of Retail and Distribution Management, 42(3), 187–204. https://doi.org/10.1108/IJRDM-03-2012-0034
Pavlou, P. A., & Dimoka, A. (2006). The nature and role of feedback text comments in online marketplaces: Implications for trust-building, price premiums, and seller differentiation. Information Systems Research, 17(4), 392–414. https://doi.org/10.1287/isre.1060.0106
Pigatto, G., Guilherme De Camargo, J., Machado, F., Dos, A., Negreti, S., & Machado, L. M. (2017). Have you chosen your request? Analysis of online food delivery companies in Brazil. British Food Journal. https://doi.org/10.1108/BFJ-05-2016-0207
Prasetyo, Y. T., Tanto, H., Mariyanto, M., Hanjaya, C., Young, M. N., Persada, S. F., Miraja, B. A., & Redi, A. A. N. P. (2021). Factors affecting customer satisfaction and loyalty in online food delivery service during the COVID-19 pandemic: Its relation with open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), 1–17. https://doi.org/10.3390/joitmc7010076
Jenny Preece, H. S., & Rogers, Y. (2015). Interaction design: Beyond human-computer interaction.
Pura, M. (2005). Linking perceived value and loyalty in location-based mobile services. Managing Service Quality, 15(6), 509–538. https://doi.org/10.1108/09604520510634005
Qiu, L., Pang, J., & Lim, K. H. (2012). Effects of conflicting aggregated rating on eWOM review credibility and diagnosticity: The moderating role of review valence. Decision Support Systems, 54(1), 631–643. https://doi.org/10.1016/j.dss.2012.08.020
Rafie, M., Arshad, M., & Gharaibeh, N. (2018). Using the UTAUT2 Model to Determine Factors Affecting Adoption of Mobile Banking Services: A Qualitative Approach. Article in International Journal of Interactive Mobile Technologies. https://doi.org/10.3991/ijim.v12i4.8525
Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V. (2016). Adoption of online public grievance redressal system in India: Toward developing a unified view. Computers in Human Behavior, 59, 265–282. https://doi.org/10.1016/j.chb.2016.02.019
Razak, F. Z. B. A., Bakar, A. A., & Abdullah, W. S. W. (2017). How perceived effort expectancy and social influence affects the continuance of intention to use e-government. A study of Malaysian government service. Electronic Government, 13(1), 69–80. https://doi.org/10.1504/EG.2017.083943
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. https://www.researchgate.net/publication/349552360
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(September 2018), 262–273.
https://doi.org/10.1016/j.ijinfomgt.2018.09.017
Roy, P. K., Ahmad, Z., Singh, J. P., Alryalat, M. A. A., Rana, N. P., & Dwivedi, Y. K. (2018). Finding and Ranking High-Quality Answers in Community Question Answering Sites. Global Journal of Flexible Systems Management, 19(1), 53–68.
https://doi.org/10.1007/s40171-017-0172-6
Ryu, K., Han, H., & Jang, S. S. (2010). Relationships among hedonic and utilitarian values, satisfaction, and behavioral intentions in the fast-casual restaurant industry. International Journal of Contemporary Hospitality Management, 22(3), 416–432.
https://doi.org/10.1108/09596111011035981
Sair, S. A., & Danish, R. Q. (2018). Effect of performance expectancy and effort expectancy on the mobile commerce adoption intention through personal innovativeness among Pakistani consumers. Pakistan Journal of Commerce and Social Science, 12(2), 501–520.
https://doi.org/10.1108/17579881011078340
Shah, S. A. M., Iqbal, N., Janjua, S. Y., & Amjad, S. (2013). Employee behavior towards adoption of E-learning courses: Validating technology acceptance model. Mediterranean Journal of Social Sciences, 4(14), 765–774.
https://doi.org/10.5901/mjss.2013.v4n14p765
Shareef, M. A., Baabdullah, A., Dutta, S., Kumar, V., & Dwivedi, Y. K. (2018). Consumer adoption of mobile banking services: An empirical examination of factors according to adoption stages. Journal of Retailing and Consumer Services, 43, 54–67. https://doi.org/10.1016/j.jretconser.2018.03.003
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
Shugan, S. M. (2004). The Impact of Advancing Technology on Marketing and Academic Research. Marketing Science, 23(4), 469–475. https://doi.org/10.1287/mksc.1040.0096
Simonson, I., & Rosen, E. (2014). What marketers misunderstand about online reviews - Dialnet. Harvard Business Review, 92(1), 23–25.
Singh, N., Sinha, N., & Liébana-Cabanillas, F. J. (2020). Determining factors in the adoption and recommendation of mobile wallet services in India: Analysis of the effect of innovativeness, stress to use, and social influence. International Journal of Information Management, 50, 191–205. https://doi.org/10.1016/j.ijinfomgt.2019.05.022
Slade, E. L., Dwivedi, Y. K., Piercy, N. C., & Williams, M. D. (2015). Modeling Consumers’ Adoption Intentions of Remote Mobile Payments in the United Kingdom: Extending UTAUT with Innovativeness, Risk, and Trust. Psychology and Marketing, 32(8), 860–873. https://doi.org/10.1002/mar.20823
Spyridou, A. (2017). Perceived Service Quality and Customer Revisiting Intention: The Case of “all you can eat” Asian Restaurants in Southern Taiwan. Journal of Tourism, Heritage & Services Marketing, 3(2), 30–31.
Susanto, A., Chang, Y., & Ha, Y. (2016). Determinants of continuance intention to use the smartphone banking services: An extension to the expectation-confirmation model. Industrial Management and Data Systems, 116(3), 508–525.
https://doi.org/10.1108/IMDS-05-2015-0195
Tran, L. T. T., Pham, L. M. T., & Le, L. T. (2019). E-satisfaction and continuance intention: The moderator role of online ratings. International Journal of Hospitality Management, 77, 311–322. https://doi.org/10.1016/j.ijhm.2018.07.011
Venkatesh, V., Morris, M.G., Davis, G. B. & D., & D.F. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(7), 425–478.
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. JSTOR, 36(1), 22.
Venkatesh. (2003a). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. https://doi.org/DOI: 10.2307/30036540
Venkatesh, V. (2003b). Angiogenesis induced by mast cell secretion in rat peritoneal connective tissue is a process of three phases. Microvascular Research, 47(2), 252–269. https://doi.org/10.1006/mvre.1994.1019
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, 27(3), 425–478. https://doi.org/10.2307/30036540
Verkijika, S. F. (2018). Factors influencing the adoption of mobile commerce applications in Cameroon. Telematics and Informatics, 35(6), 1665–1674.
https://doi.org/10.1016/j.tele.2018.04.012
Verplanken, B., & Wood, W. (2006). Interventions to break and create consumer habits. In Journal of Public Policy and Marketing (Vol. 25, Issue 1, pp. 90–103). American Marketing Association. https://doi.org/10.1509/jppm.25.1.90
Wang, C., Harris, J., & Patterson, P. (2013). The Roles of Habit, Self-Efficacy, and Satisfaction in Driving Continued Use of Self-Service Technologies: A Longitudinal Study. Journal of Service Research, 16(3), 400–414.
Wang, E. S. T., & Chou, N. P. Y. (2016). Examining social influence factors affecting consumer continuous usage intention for mobile social networking applications. International Journal of Mobile Communications, 14(1), 43–55.
Wang, H. Y., & Wang, S. H. (2010). Predicting mobile hotel reservation adoption: Insight from a perceived value standpoint. International Journal of Hospitality Management, 29(4), 598–608. https://doi.org/10.1016/j.ijhm.2009.11.001
Wang, Q., Khan, M. S., & Khan, M. K. (2021). Predicting user-perceived satisfaction and reuse intentions toward Massive Open Online Courses (MOOCs) in the Covid-19 pandemic. International Journal of Research in Business and Social Science (2147- 4478), 10(2), 1–11. https://doi.org/10.20525/ijrbs.v10i2.1045
Wang, Y. S., Tseng, T. H., Wang, W. T., Shih, Y. W., & Chan, P. Y. (2019). Developing and validating a mobile catering app success model. International Journal of Hospitality Management, 77(April 2018), 19–30. https://doi.org/10.1016/j.ijhm.2018.06.002
Wang, Y. S., Wang, Y. M., Lin, H. H., & Tang, T. I. (2003). Determinants of user acceptance of Internet banking: An empirical study. International Journal of Service Industry Management, 14(5), 501–519. https://doi.org/10.1108/09564230310500192
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information and Management, 42(5), 719–729. https://doi.org/10.1016/j.im.2004.07.001
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(December 2016), 150–162.
https://doi.org/10.1016/j.jretconser.2016.12.013
Yoon, Y. C., Kim, D. Y., Song, Y. M., Yoon, K., & Jeon, M. (2021). Online multiple pedestrians tracking using deep temporal appearance matching association. Information Sciences, 561, 326–351. https://doi.org/10.1016/j.ins.2020.10.002
Yu, C. S. (2012). Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT model. Journal of Electronic Commerce Research, 13(2), 105–121.
Yuan, Shunbo, Liu, Y., Yao, R., & Liu, J. (2016). An investigation of users’ continuance intention towards mobile banking in China. Information Development, 32(1), 20–34. https://doi.org/10.1177/0266666914522140
Yuan, Shupei, Ma, W., Kanthawala, S., & Peng, W. (2015). Keep Using My Health Apps: Discover Users’ Perception of Health and Fitness Apps with the UTAUT2 Model. Telemedicine and E-Health, 21(9), 735–741. https://doi.org/10.1089/tmj.2014.0148
Zadeh, S. M. M., Cheng, L., Ghanei-Yakhdan, H., & Kasaei, S. (2021). Deep Learning for Visual Tracking: A Comprehensive Survey. IEEE Transactions on Intelligent Transportation Systems. https://doi.org/10.1109/TITS.2020.3046478
Zahid, H., & Din, B. H. (2019). Determinants of Intention to Adopt E-Government Services in Pakistan: An Imperative for Sustainable Development.
https://doi.org/10.3390/resources8030128
Zhao, L., Lu, Y., Zhang, L., & Chau, P. Y. K. (2012). Assessing the effects of service quality and justice on customer satisfaction and the continuance intention of mobile value-added services: An empirical test of a multidimensional model. Decision Support Systems, 52(3), 645–656. https://doi.org/10.1016/j.dss.2011.10.022
Zhou, T. (2011). An empirical examination of initial trust in mobile banking. Internet Research, 21(5), 527–540. https://doi.org/10.1108/1066224111117
Zulkefli, N. H., Salleh, N. S. A., Ghani, F. A., Razali, N. A., & Idris, R. S. N. R. (2020). Determinants of Behavioral Intention on Online Food Delivery (OFD) APPS: Extending UTAUT2 with Information Quality. In Global Business and Management Research: An International Journal (Vol. 12, Issue 4).