Abstract :

This study aims to measure the influence of behavioral intention involving UTAUT variables, Online Shopping Anxiety, Herd Behavior, and COVID-19 Pandemic Fear on online shopping users in the city of Bandung. The research method employed is quantitative, used to test the cause-and-effect relationships among variables that form the structural equation model. This is done using empirical data collected through a survey with a five-point Likert scale for 23 questionnaire items. The indicators of each variable obtained from the survey data were tested for validity and reliability. The data was collected from 331 respondents who are online shopping users in the city of Bandung. The collected data were analyzed using SmartPLS 3.2.9 software. The results of this study show that Performance Expectancy has a positive influence on Behavioral Intention, Facilitating Conditions have a positive influence on Behavioral Intention, Internet Shopping Anxiety has a negative influence on Behavioral Intention, Imitating Others has a positive influence on Behavioral Intention, Discounting One’s Own Information has a positive influence on Behavioral Intention. Moreover, COVID-19 Fear has a negative influence on Imitating Others, and COVID-19 Fear has a positive influence on Discounting One’s Own Information.

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Keywords :

Behavioral Intention, Covid-19 Fear, Herd Behaviour, Internet Online Shopping, Internet Shopping Anxiety, Unified Theory of Acceptance and Use of The Technology.

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References :

1. Bouri, E., Gupta, R., Roubaud, D., 2019. Herding behaviour in cryptocurrencies, Finance Res. Lett, 29, 216-221.
2. Chayomchai, A., Phonsiri, W., Junjit, A., Boongapim, R., Suwannapusit, U., 2020. Factors affecting acceptance and use of online technology in Thai people during COVID-19 quarantine time. Management Sci. Lett 10 (13), 3009-3016.
3. Celik, H., & Phau, I. (2016). Customer online shopping anxiety within the Unified Theory of Acceptance and Use Technology (UTAUT) framework. Asia Pacific Journal of Marketing and Logistics.
4. Dwivedi, Y.K., Rana, N.P., Jeyaraj, A., Clement, M., Williams, M.D., 2019. Re-examining the unified theory of acceptance and use of technology (UTAUT): towards a revised theoretical model. Syst. Front 21 (3), 719-734.
5. Faqih, K. M. (2016). Which is more important in e-learning adoption, perceived value or perceived usefulness? Examining the moderating influence of perceived 4th global summit on education GSE.
6. Hair, J., Anderson, R., Babin, B., & Black, W. (2010). Multivariate Data Analysis. (7th ed.). New jersey: Pearson Prentice Hall.
7. Henseler, J. (2017). Partial Least Squares Path Modeling. https://doi.org/10.1007/978-3-319-53469-5_12
8. (2015). Metode Penelitian Manajemen dan Bisnis Konvergensi Teknologi Komunikasi dan Informasi. Bandung: Aditama
9. Jasperson, S., Carter, P.E., Zmud, R.W., 2005. A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Q. 29 (3), 525–557
10. Liao, Z., Shi, X., 2017. Fungsionalitas web, konten web, keamanan informasi, dan kelanjutan layanan pariwisata online. J. Pengecer Konsumsi.
11. Liu, F., Bartz, L., Duke, N., 2016. Communicating crisis uncertainty: a review of the knowledge gaps. Publ. Relat. Rev. 42 (3), 479–487.
12. Mertens, G., Gerritsen, L., Duijndam, S., Salemink, E., Engelhard, I.M., 2020. Fear of the coronavirus (COVID-19): predictors in an online study conducted in March J. Anxiety Disord. 74 (June), 102258
13. Nagar, K. (2016). Drivers of E-store patronage intentions: Choice overload, Internet shopping anxiety, and impulse purchase tendency.Journal of Internet Commerce, 15(2), 97-124.
14. Sun, , 2013. A longitudinal study of herd behavior in the adoption and continued use of technology. MIS Q. 37 (4), 1013–1041
15. Trans, LTT (2021). Mengelola efektivitas platform e-commerce dalam pandemi. Jurnal Ritel dan Layanan Konsumen, 58, 102287.
16. Tuan, P.M.Q. (2012). The perception of customers about the online retailers’ service in Vietnam (Doctoral dissertation). International UniversityHCMC,
17. Venkatesh, Morris, Davis, Davis, 2003. User acceptance of information technology: toward a unified view. MIS Q. 27 (3), 425.
18. Venkatesh, , 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 Q.: Manag. Inf. Syst. 36 (1), 157–178.
19. Walden, A., Browne, G.J., 2009. Sequential adoption theory: a theory for understanding herding behavior in early adoption of novel technologies. J. Assoc. Inf. Syst. Online 10 (1), 31–62.
20. Yan, P., Hui, S., Heng, B., Selvachandran, G., Quynh, L., Hoang, A., Minh, T., 2020. Perception, acceptance and willingness of older adults in Malaysia towards online shopping: a study using the UTAUT and IRT J. Ambient Intellige. Humanized Comput.