Purpose: This study aimed to find the factors that affected the usage of OFD platforms during the emergent situation of the COVID-19 pandemic.Design/Methodology/Approach : The extended valence framework and UTUAT2 model were integrated to develop a parsimonious model comprising trust, perceived risk, performance expectancy, habit, and buying intention. The model was tested by employing structural equation modeling with a sample of 362 respondents from India.

Findings: The relationship between trust and buying intention was found to be the strongest amongst all factors. All modeled predictors of trust were found to impact trust significantly, while perceived risk was found to have an inverse relation with trust.Research Limitations/

Implications: The constructs presented in the model successfully explained the factors that impacted OFD platforms during the COVID-19 pandemic. The understanding of consumers’ responses developed in the study is a useful addition to the literature.Practical

Implications: The study provides direction to promoters and marketers of OFD platforms to identify specific factors that can help boost the buyers’ intention to purchase during emergency situations.Originality/

Value: The integration of two theoretical models: the extended valence framework and UTUAT2 is unique in the context of OFD platforms. The COVID-19 situation and circumstances therein provide a unique research situation for an improved understanding on the subject.

1. Aarts, H., Verplanken, B., & Knippenberg, A. (1998). Predicting behavior from actions in the past: Repeated decision making or a matter of habit ? Journal of Applied Social Psychology, 28(15), 1355–1374.https://doi.org/10.1111/j.1559-1816.1998.tb01681.x
2. 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
3. Al-Somali, S. A., Gholami, R., & Clegg, B. (2009). An investigation into the acceptance of online banking in Saudi Arabia. Technovation, 29(2), 130–141. https://doi.org/10.1016/j.technovation.2008.07.004
4. Ashraf, M. A., Joarder, M. H., & Ratan, SR (2019). Consumers’ anti-consumption behaviour toward organic food purchase: An analysis using SEM. British Food Journal, 121(1), 104–122. https://doi.org/10.1108/BFJ-02-2018-0072
5. Bagla, R. K., & Khan, J. (2017). Customers’ expectations and satisfaction with online food ordering portals. Prabandhan: Indian Journal of Management, 10(11), 31–44. https://doi.org/10.17010/pijom/2017/v10i11/119401
6. Bhukya, R., & Singh, S. (2015). The effect of perceived risk dimensions on purchase intention: An empirical evidence from Indian private labels market. American Journal of Business, 30(4), 218–230. https://doi.org/10.1108/AJB-10-2014-0055
7. Biswas, S. (2020, March 30). Coronavirus: India’s pandemic lockdown turns into a human tragedy. BBC News. https://www.bbc.com/news/world-asia-india-52086274
8. Chahal, H., & Rani, A. (2017). How trust moderates social media engagement and brand equity. Journal of Research in Interactive Marketing, 11(3), 312–335. https://doi.org/10.1108/JRIM-10-2016-0104
9. Chakraborty, D. (2018). Impact of celebrity endorsed advertisements on rural consumers’ purchase intention towards mobile SIM cards: A study conducted in West Bengal. Indian Journal of Marketing, 48(10), 52–63. https://doi.org/10.17010/ijom/2018/v48/i10/132335
10. Chakraborty, D. (2019). Customer satisfaction towards food service apps in Indian metro cities. FIIB Business Review, 8(3), 245–255. https://doi.org/10.1177/2319714519844651
11. Chakraborty, D. (2020). Elements impacting the utilization expectation of various health-care apps in India: A study conducted on smartphone users. Foresight, 22(3), 385–400. https://doi.org/10.1108/FS-11-2019-0098
12. Chang, H. H. (2008). Intelligent agent’s technology characteristics applied to online auctions’ task : A combined model of TTF and TAM. Technovation, 28(9), 564–577. https://doi.org/10.1016/j.technovation.2008.03.006
13. Chi, V. L. (2020). Trust in strangers: “Online food vendors” in Urban Vietnam. Keio Communication Review, 42, 35–51.
14. Correa, J. C., Garzón, W., Brooker, P., Sakarkar, G., Carranza, S. A., Yunado, L., & Rincón, A. (2019). Evaluation of collaborative consumption of food delivery services through web mining techniques. Journal of Retailing and Consumer Services, 46, 45–50. https://doi.org/10.1016/j.jretconser.2018.05.002
15. Dabholkar, P. A., van Dolen, W. M., & de Ruyter, K. (2009). A dual-sequence framework for B2C relationship formation: Moderating effects of employee communication style in online group chat. Psychology & Marketing, 26(2), 145–174. https://doi.org/10.1002/mar.20265
16. 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
17. Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474. https://doi.org/10.1016/S1071-5819(03)00111-3
18. Field, A. (2009). Discovering statistics using SPSS:(and sex and drugs and rock’n’roll). Sage.
19. 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/10.2307/3151312
20. Gefen, D. (2003). TAM or just plain habit: A look at experienced online shoppers. Journal of Organizational and End User Computing, 15(3), 1–13.
21. Gunden, N., Morosan, C., & DeFranco, A. (2020). Consumers’ intentions to use online food delivery systems in the USA. International Journal of Contemporary Hospitality Management, 32(3), 1325–1345. https://doi.org/10.1108/IJCHM-06-2019-0595
22. Gupta, V. (2019). The influencing role of social media in the consumer’s hotel decision-making process. Worldwide Hospitality and Tourism Themes, 11(4), 378–391. https://doi.org/10.1108/WHATT-04-2019-0019
23. Hair, J., Black, W., Babin, B., & Anderson, R. (2010). Multivariate data analysis (7th ed.). Pearson Hall.
24. Hebbar, N. (2020, March 24). PM Modi announces 21-day lockdown as COVID-19 toll touches 12. The Hindu. https://www.thehindu.com/news/national/pm-announces-21-day-lockdown-as-covid-19-toll-touches-10/article31156691.ece
25. Hwang, Y., & Kim, D. J. (2007). Customer self-service systems: The effects of perceived web quality with service contents on enjoyment, anxiety, and e-trust. Decision Support Systems, 43(3), 746–760. https://doi.org/10.1016/j.dss.2006.12.008
26. Izzati, B. M. (2020). Analysis of customer behavior in mobile food ordering application using UTAUT model (case study: GoFood application). International Journal of Innovation in Enterprise System, 4(01), 23–34.
27. Keelery, S. (2020). COVID - 19 impact on use of food ordering apps India 2020. https://www.statista.com/topics/6304/covid-19-economic-impact-on-india/
28. Keymolen, E. (2013). Trust and technology in collaborative consumption. Why it is not just about you and me. In R. Leenes & E. Kosta (Eds.), Bridging distances in technology and regulation (pp. 135–150). Wolf Legal Publishers.
29. Kim, S., & Park, H. (2013). Effects of various characteristics of social commerce (s-commerce) on consumers’ trust and trust performance. International Journal of Information Management, 33(2), 318–332. https://doi.org/10.1016/j.ijinfomgt.2012.11.006
30. 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. https://doi.org/10.1287/mnsc.1040.0326
31. Kim, D. J., Ferrin, D. L., & Rao, H. R. (2009) Trust and satisfaction, two stepping stones for successful E-commerce relationships: A longitudinal exploration. Information Systems Research, 20(2), 237–257. https://doi.org/10.1287/isre.1080.0188
32. Kumar, S., Dhir, A., Talwar, S., Chakraborty, D., & Kaur, P. (2021). What drives brand love for natural products ? The moderating role of household size. Journal of Retailing and Consumer Services, 58, 102329. https://doi.org/10.1016/j.jretconser.2020.102329
33. Lal, N. (2020, October 16). Online grocery shopping is clicking with consumers amid pandemic. The Times of India. https://timesofindia.indiatimes.com/life-style/food-news/online-grocery-shopping-is-clicking-with-consumers-amid-pandemic/articleshow/78680170.cms
34. Lee, S.-H. (2009). How do online reviews affect purchasing intention? African Journal of Business Management, 3(10), 576–581. https://doi.org/10.5897/AJBM09.204
35. Lee, Z. W., Chan, T. K., Balaji, M. S., & Chong, A. Y.- L. (2018). Why people participate in the sharing economy: An empirical investigation of Uber. Internet Research, 28(3), 829–850. https://doi.org/10.1108/IntR-01-2017-0037
36. Leedy, P. P., & Ormrod, J. E. (2014). Practical research: Planning and design. Pearson Education.
37. Liao, C., To, P. L., Liu, C. - C., Kuo, P. - Y., & Chuang, S. - H. (2011). Factors influencing the intended use of web portals. Online Information Review, 35(2), 237–254. https://doi.org/10.1108/14684521111128023
38. Liao, S. - H., Chung, Y. - C., & Chang, W. - J. (2019). Interactivity, engagement, trust, purchase intention and word-of-mouth: A moderated mediation study. International Journal of Services Technology and Management, 25(2), 116–137. https://doi.org/10.1504/IJSTM.2019.098203
39. Maadi, M., Maadi, M., & Javidnia, M. (2016). Identification of factors influencing building initial trust in e-commerce. Iranian Journal of Management Studies, 9(3), 483–503. https://dx.doi.org/10.22059/ijms.2016.57482
40. Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1–13. https://doi.org/10.1016/j.ijinfomgt.2013.06.002
41. McLeod, A., Pippin, S., & Mason, R. (2008). Individual taxpayer intention to use tax preparation software: Examining experience, trust, and perceived risk. In, Proceedings of ISOneWorld Conference, 2 (4), 1–16.
42. 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
43. Morosan, C., & DeFranco, A. (2016). It’s 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
44. Nunnally, J. C. (1994). Psychometric theory (3rd ed.). Tata McGraw-Hill Education.
45. Panigrahi, S. K., Azizan, N. A., & Khan, M. W. (2018). Investigating the empirical relationship between service quality, trust, satisfaction, and intention of customers purchasing life insurance products. Indian Journal of Marketing, 48(1), 28–46. https://doi.org/10.17010/ijom/2018/v48/i1/120734
46. Park, J., Amendah, E., Lee, Y., & Hyun, H. (2019). M - payment service: Interplay of perceived risk, benefit, and trust in service adoption. Human Factors and Ergonomics in Manufacturing & Service Industries, 29(1), 31–43. https://doi.org/10.1002/hfm.20750
47. Quevedo-Silva, F., Freire, O., Lima-Filho, D. D., Brandão, M. M., Isabella, G., & Moreira, L. B. (2016). Intentions to purchase food through the internet: Developing and testing a model. British Food Journal, 118(3), 572–587. https://doi.org/10.1108/BFJ-09-2015-0305
48. Rao, K. S., & Rao, B. (2019). Examining eWOM credibility - consumer purchase intention relationship in Facebook: A mediation analysis. Indian Journal of Marketing,
49. (8), 7–22. https://doi.org/10.17010/ijom/2019/v49/i8/146169
50. Reardon, T., Mishra, A., Nuthalapati, C. S., Bellemare, M. F., & Zilberman, D. (2020). COVID-19’s disruption of India’s transformed food supply chains. Economic & Political Weekly, 55(18), 18–22.
51. Sanzo, M. J., Santos, M. L., García, N., & Trespalacios, J. A. (2012). Trust as a moderator of the relationship between organizational learning and marketing capabilities: Evidence from Spanish SMEs. International Small Business Journal, 30(6), 700–726. https://doi.org/10.1177/0266242611418907
52. Shao, Z., Zhang, L., Li, X., & Guo, Y. (2019). Antecedents of trust and continuance intention in mobile payment platforms: The moderating effect of gender. Electronic Commerce Research and Applications, 33, 100823. https://doi.org/10.1016/j.elerap.2018.100823
53. Thakur, A., Shabnam, & Kaur, R. (2017). An empirical study on consumer trust in online shopping in Punjab. Indian Journal of Marketing, 47(2), 47–59. https://doi.org/10.17010/ijom/2017/v47/i2/110027
54. Thiesse, F. (2007). RFID, privacy and the perception of risk: A strategic framework. The Journal of Strategic Information Systems, 16(2), 214–232. https://doi.org/10.1016/j.jsis.2007.05.006
55. Van der Heijden, H., Verhagen, T., & Creemers, M. (2003). Understanding online purchase intentions: Contributions from technology and trust perspectives. European Journal of Information Systems, 12(1), 41–48. https://doi.org/10.1057/palgrave.ejis.3000445
56. 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
57. 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. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
58. Venkatesh, V., Thong, J. Y., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376. https://doi.org/10.17705/1jais.00428
59. Verplanken, B., & Aarts, H. (1999). Habit, attitude, and planned behaviour : Is habit an empty construct or an interesting case of goal-directed automaticity? European Review of Social Psychology, 10(1), 101–134. https://doi.org/10.1080/14792779943000035
60. Zhang, K. Z., Cheung, C. M., & Lee, M. K. (2014). Examining the moderating effect of inconsistent reviews and its gender differences on consumers’ online shopping decision. International Journal of Information Management, 34(2), 89–98. https://doi.org/10.1016/j.ijinfomgt.2013.12.001
61. Zhou, T. (2014). An empirical examination of initial trust in mobile payment. Wireless Personal Communications, 77(2), 1519–1531. https://doi.org/10.1007/s11277-013-1596-8