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Reinvestigating millennial shopping behavior on the sharing economy platform: The moderating role of COVID-19 awareness level

1Department of Management, Universitas Muslim Indonesia, Indonesia

2Department of Management, Universitas Muslim Indonesia, Indonesia

3Institute of Advanced Studies (IAS), University of Malaya, Malaysia

Open Access Copyright 2023 Diponegoro International Journal of Business under http://creativecommons.org/licenses/by-sa/4.0.

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Abstract
Drawing from the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), this study aims to develop a predictive model concerning the shopping behaviour of millennials within the realm of the sharing economy (SE) mobile application. To accommodate prior research findings while providing novelty, this study integrates hedonic enjoyment and price-saving orientation as predictive factors, alongside the level of COVID-19 awareness as a moderating variable. An online survey was administered, and primary data was collected by distributing an electronic questionnaire link randomly via email and social media platforms. Employing a sampling judgement technique, 260 millennials in Indonesia who utilize the SE (Gojek) mobile app were identified as participants. Results from the PLS-SEM analysis reveal that performance expectancy, effort expectancy, social influence,  price-saving orientation, and habits exert a favorable and significant impact on behavioral intentions. Furthermore, habits and behavioral intentions were found to significantly influence the actual usage of the SE app among millennials. Conversely, hedonic enjoyment demonstrated no significant influence on behavioral intentions. Moreover, the moderating role of COVID-19 awareness was observed to both enhance and diminish direct relationships. The implications, both theoretical and practical, along with recommendations for future research, are deliberated upon.
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Keywords: UTAUT2; Hedonic enjoyment; Price-saving orientation; Level of COVID-19 awareness; Sharing economy app; PLS-SEM

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  1. Anwar, A., Thongpapanl, N., & Ashraf, A. R. (2021). Strategic imperatives of mobile commerce in developing countries: the influence of consumer innovativeness, ubiquity, perceived value, risk, and cost on usage. Journal of Strategic Marketing, 29(8), 722–742. https://doi.org/10.1080/0965254X.2020.1786847
  2. Ashoer, M., Syahnur, M. H., Tjan, J. S., Junaid, A., Pramukti, A., & Halim, A. (2022). The Future of Mobile Commerce Application in a Post Pandemic Period; An Integrative Model of UTAUT2. E3S Web of Conferences, 359, 05005. https://doi.org/10.1051/E3SCONF/202235905005
  3. Barnes, S. J., & Mattsson, J. (2016). Understanding current and future issues in collaborative consumption: A four-stage Delphi study. Technological Forecasting and Social Change, 104, 200–211. https://doi.org/10.1016/j.techfore.2016.01.006
  4. Chan, T., Wok, S., Sari, N. N., Afiq, M., & Abd, H. (2021). Factors Influencing the Intention to Use Mysejahtera Application Among Malaysian Citizens During Covid-19. Journal of Applied Structural Equation Modeling, 5(July), 1–21. https://doi.org/10.47263/JASEM.5(2)06
  5. Chen, Y., & Salmanian, W. (2017). User Acceptance in the Sharing Economy : An explanatory study of Transportation Network Companies in China based on UTAUT2. Jönköping University, Jönköping International Business School. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-38100
  6. Chin, W. W. (2010). How to Write Up and Report PLS Analyses. Handbook of Partial Least Squares, 655–690. https://doi.org/10.1007/978-3-540-32827-8_29
  7. Chopdar, P. K., Korfiatis, N., Sivakumar, V. J., & Lytras, M. D. (2018). Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and Use of Technology. Computers in Human Behavior, 86, 109–128. https://doi.org/10.1016/j.chb.2018.04.017
  8. Chopdar, P. K., Lytras, M. D., & Visvizi, A. (2022). Exploring factors influencing bicycle-sharing adoption in India: a UTAUT 2 based mixed-method approach. International Journal of Emerging Markets, ahead-of-print(ahead-of-print). https://doi.org/10.1108/IJOEM-06-2021-0862/FULL/XML
  9. Cooper, D. R., & Schindler, P. S. (2014). Business Research Methods (12th ed.). New York: McGrew-Hill
  10. Davis, F. 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
  11. Escobar-Rodríguez, T., & Carvajal-Trujillo, E. (2014). Online purchasing tickets for low cost carriers: An application of the unified theory of acceptance and use of technology (UTAUT) model. Tourism Management, 43, 70–88
  12. Fielding, N. G., Lee, R. M., & Blank, G. (2017). The SAGE Handbook of Online Research Methods. The SAGE Handbook of Online Research Methods. SAGE Publications Ltd. https://doi.org/10.4135/9781473957992
  13. García-Milon, A., Olarte-Pascual, C., & Juaneda-Ayensa, E. (2021). Assessing the moderating effect of COVID-19 on intention to use smartphones on the tourist shopping journey. Tourism Management, 87(March), 104361. https://doi.org/10.1016/j.tourman.2021.104361
  14. Garson, G. D. (2016). Partial Least Squares: Regression and Structural Equation Models. Asheboro, NC : Statistical Associates Publishers. https://doi.org/ISBN-13: 978-1-62638-039-4
  15. 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
  16. 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, 115(7), 1291–1269. https://doi.org/10.1108/imds-01-2015-0028
  17. Jensen, J. M. (2012). Shopping orientation and online travel shopping: The role of travel experience. International Journal of Tourism Research, 14(1), 56–70
  18. Kim, B., & Lee, E. (2022). What Factors Affect a User’s Intention to Use Fitness Applications? The Moderating Effect of Health Status: A Cross-Sectional Study. Inquiry : A Journal of Medical Care Organization, Provision and Financing, 59, 469580221095826. https://doi.org/10.1177/00469580221095826
  19. 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
  20. Lee, H. E., & Cho, J. (2017). What Motivates Users to Continue Using Diet and Fitness Apps? Application of the Uses and Gratifications Approach. Health Communication, 32(12), 1445–1453. https://doi.org/10.1080/10410236.2016.1167998
  21. Lee, Y., Lee, J., & Hwang, Y. (2015). Relating motivation to information and communication technology acceptance: Self-determination theory perspective. Computers in Human Behavior, 51(PA), 418–428. https://doi.org/10.1016/j.chb.2015.05.021
  22. Li, C. Y., & Fang, Y. H. (2022). The more we get together, the more we can save? A transaction cost perspective. International Journal of Information Management, 62. https://doi.org/10.1016/j.ijinfomgt.2021.102434
  23. Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly: Management Information Systems, 31(4), 705–737. https://doi.org/10.2307/25148817
  24. Mondal, S., & Samaddar, K. (2022). Future of sharing economy and its resilience post pandemic: a study on Indian travel and tourism industry. Management of Environmental Quality: An International Journal, 33(6), 1591–1610. https://doi.org/10.1108/MEQ-12-2021-0284/FULL/XML
  25. 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
  26. Muñoz-Leiva, F., Climent-Climent, S., & Liébana-Cabanillas, F. (2017). Determinants of intention to use the mobile banking apps: An extension of the classic TAM model. Spanish Journal of Marketing - ESIC, 21(1), 25–38. https://doi.org/10.1016/j.sjme.2016.12.001
  27. 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. Sustainability 2019, Vol. 11, Page 1210, 11(4), 1210. https://doi.org/10.3390/SU11041210
  28. Park, S., & Ahn, D. (2022). Seeking Pleasure or Meaning? The Different Impacts of Hedonic and Eudaimonic Tourism Happiness on Tourists’ Life Satisfaction. International Journal of Environmental Research and Public Health, 19(3). https://doi.org/10.3390/ijerph19031162
  29. Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce. https://doi.org/10.1080/10864415.2003.11044275
  30. Poon, W. C., & Tung, S. E. H. (2022). 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. https://doi.org/10.1108/EJMBE-04-2021-0128/FULL/HTML
  31. Rehman, R., Jawed, S., Ali, R., Noreen, K., Baig, M., & Baig, J. (2021). COVID-19 Pandemic Awareness, Attitudes, and Practices Among the Pakistani General Public. Frontiers in Public Health, 9, 588537. https://doi.org/10.3389/FPUBH.2021.588537/BIBTEX
  32. Ringle, C. M., Rigdon, E., & Sarstedt, M. (2018, January 15). On Comparing Results from CB-SEM and PLS-SEM: Five Perspectives and Five Recommendations. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3128192
  33. Saefi, M., Fauzi, A., Kristiana, E., Adi, W. C., Muchson, M., Setiawan, M. E., … Ramadhani, M. (2020). Survey data of COVID-19-related knowledge, attitude, and practices among indonesian undergraduate students. Data in Brief, 31, 105855. https://doi.org/10.1016/j.dib.2020.105855
  34. Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial Least Squares Structural Equation Modeling. Handbook of Market Research, 1–47. https://doi.org/10.1007/978-3-319-05542-8_15-2
  35. Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J. H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347. https://doi.org/10.1108/EJM-02-2019-0189
  36. Slade, E., Williams, M., Dwivedi, Y., & Piercy, N. (2015). Exploring consumer adoption of proximity mobile payments. Journal of Strategic Marketing, 23(3), 209–223. https://doi.org/10.1080/0965254X.2014.914075
  37. Suh, A., & Cheung, C. M. K. (2017). Beyond hedonic enjoyment: Conceptualizing eudaimonic motivation for personal informatics technology usage. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10289 LNCS, 119–133. https://doi.org/10.1007/978-3-319-58637-3_9/FIGURES/3
  38. Tamilmani, K., Rana, N. P., Nunkoo, R., Raghavan, V., & Dwivedi, Y. K. (2022). Indian Travellers’ Adoption of Airbnb Platform. Information Systems Frontiers, 24(1), 77–96. https://doi.org/10.1007/S10796-020-10060-1/FIGURES/2
  39. 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
  40. Venkatesh, V. (2000). Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Https://Doi.Org/10.1287/Isre.11.4.342.11872, 11(4), 342–365.
  41. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003a). Human Acceptance of Information Technology. International Encyclopedia of Ergonomics and Human Factors, Second Edition - 3 Volume Set, 27(3), 425–478. https://doi.org/10.1201/9780849375477.ch230
  42. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003b). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478. https://doi.org/10.2307/30036540
  43. Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly: Management Information Systems, 36(1), 157–178. https://doi.org/10.2307/41410412
  44. Venkatesh, V., Thong, J. Y. L., & 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
  45. Vinerean, S., Budac, C., Baltador, L. A., & Dabija, D. C. (2022). Assessing the Effects of the COVID-19 Pandemic on M-Commerce Adoption: An Adapted UTAUT2 Approach. Electronics 2022, Vol. 11, Page 1269, 11(8), 1269. https://doi.org/10.3390/ELECTRONICS11081269
  46. Waterman, A. S. (1993). Two Conceptions of Happiness: Contrasts of Personal Expressiveness (Eudaimonia) and Hedonic Enjoyment. Journal of Personality and Social Psychology, 64(4), 678–691. https://doi.org/10.1037/0022-3514.64.4.678
  47. Wu, M. C., & Kuo, F. Y. (2008). An empirical investigation of habitual usage and past usage on technology acceptance evaluations and continuance intention. ACM SIGMIS Database: The DATABASE for Advances in Information Systems, 39(4), 48–73. https://doi.org/10.1145/1453794.1453801
  48. Yeo, V. C. S., Goh, S.-K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services. Journal of Retailing and Consumer Services, 35, 150–162. https://doi.org/10.1016/J.JRETCONSER.2016.12.013
  49. Yin, G., & Zhu, L. (2014). Habit: How does it develop, and affect continued usage of Chinese users on social networking websites? Journal of Organizational and End User Computing, 26(4), 1–22. https://doi.org/10.4018/JOEUC.2014100101
  50. Yuduang, N., Ong, A. K. S., Prasetyo, Y. T., Chuenyindee, T., Kusonwattana, P., Limpasart, W., … Nadlifatin, R. (2022). Factors Influencing the Perceived Effectiveness of COVID-19 Risk Assessment Mobile Application MorChana in Thailand: UTAUT2 Approach. International Journal of Environmental Research and Public Health 2022, Vol. 19, Page 5643, 19(9), 5643. https://doi.org/10.3390/IJERPH19095643

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