Abstract :

This study aims to examine the effect of perceived effectiveness on consumer economic benefits in predicting sustainable consumption interest, by contributing to adding moderating variables, namely technology anxiety, resistance to change, and pandemic fear in e-commerce users during the Covid-19 pandemic in Bandung City. The research method used is a quantitative method used to test the causal relationship between variables that form a structural equation model. The survey was conducted with five Likert scales for 20 question items. Data were obtained from 330 respondents, and analyzed using SmartPLS 3.2.9 software. The results prove that perceived effectiveness has a positive effect on economic benefits, economic benefits have a positive effect on sustainable consumption interest, and perceived effectiveness has a positive effect on sustainable consumption interest, but technology anxiety, resistance to change, and fear of pandemics cannot moderate the relationship between perceived effectiveness on economic benefits and economic benefits on sustainable consumption interest.

---

Keywords :

Change Resistance, Economic Benefits, Pandemic Fear, Perceived Effectiveness, Sustainable Consumption Interest, Technology Anxiety Variables.

---

References :

1. Guillen-Royo, “Sustainable consumption and wellbeing: Does on-line shopping matter?,” J Clean Prod, vol. 229, pp. 1112–1124, Aug. 2019, doi: 10.1016/j.jclepro.2019.05.061.
2. T. T. Tran, “Managing the effectiveness of e-commerce platforms in a pandemic,” Journal of Retailing and Consumer Services, vol. 58, p. 102287, Jan. 2021, doi: 10.1016/j.jretconser.2020.102287.
3. Song, W. Li, and S. Geng, “Effect of online product reviews on third parties’ selling on retail platforms,” Electron Commer Res Appl, vol. 39, Jan. 2020, doi: 10.1016/j.elerap.2019.100900.
4. Bandara, M. Fernando, and S. Akter, “Explicating the privacy paradox: A qualitative inquiry of online shopping consumers,” Journal of Retailing and Consumer Services, vol. 52, Jan. 2020, doi: 10.1016/j.jretconser.2019.101947.
5. Hubert, M. Blut, C. Brock, C. Backhaus, and T. Eberhardt, “Acceptance of Smartphone-Based Mobile Shopping: Mobile Benefits, Customer Characteristics, Perceived Risks, and the Impact of Application Context,” Psychol Mark, vol. 34, no. 2, pp. 175–194, Feb. 2017, doi: 10.1002/mar.20982.
6. Liao and X. Shi, “Web functionality, web content, information security, and online tourism service continuance,” Journal of Retailing and Consumer Services, vol. 39, pp. 258–263, Nov. 2017, doi: 10.1016/j.jretconser.2017.06.003.
7. Ray, A. Dhir, P. K. Bala, and P. Kaur, “Why do people use food delivery apps (FDA)? A uses and gratification theory perspective,” Journal of Retailing and Consumer Services, vol. 51, pp. 221–230, Nov. 2019, doi: 10.1016/j.jretconser.2019.05.025.
8. Compeau, C. A. Higgins, and S. Huff, “Social Cognitive Theory and Individual Reactions to Computing Technology: A Longitudinal Study A LONGITUDINAL STUDY1,” 1999.
9. M. Lim, “Inside the sustainable consumption theoretical toolbox: Critical concepts for sustainability, consumption, and marketing,” J Bus Res, vol. 78, pp. 69–80, Sep. 2017, doi: 10.1016/j.jbusres.2017.05.001.
10. Katz, J. G. Blumler, and M. Gurevitch, “Uses And Gratifications Research.” [Online]. Available: http://poq.oxfordjournals.org/
11. A. Barber, D. C. Taylor, and D. Remar, “Desirability bias and perceived effectiveness influence on willingness-to-pay for pro-environmental wine products,” International Journal of Wine Business Research, vol. 28, no. 3, pp. 206–227, Aug. 2016, doi: 10.1108/IJWBR-09-2015-0042.
12. Liu, Q. Li, T. Edu, L. Jozsa, and I. C. Negricea, “Mobile shopping platform characteristics as consumer behavior determinants,” Asia Pacific Journal of Marketing and Logistics, vol. 32, no. 7, pp. 1565–1587, Oct. 2020, doi: 10.1108/APJML-05-2019-0308.
13. Seyfang, “Growing sustainable consumption communities: The case of local organic food networks,” International Journal of Sociology and Social Policy, vol. 27, pp. 120–134, May 2007, doi: 10.1108/01443330710741066.
14. Costanza and B. C. Patten, “ECOLOGICAL ECONOMICS Commentary Defining and predicting sustainability,” 1995.
15. Sharma and M. Jha, “Values influencing sustainable consumption behaviour: Exploring the contextual relationship,” J Bus Res, vol. 76, pp. 77–88, Jul. 2017, doi: 10.1016/j.jbusres.2017.03.010.
16. Fargnoli, M. De Minicis, and M. Tronci, “Design Management for Sustainability: An integrated approach for the development of sustainable products,” Journal of Engineering and Technology Management – JET-M, vol. 34, pp. 29–45, 2014, doi: 10.1016/j.jengtecman.2013.09.005.
17. A. Daruwala, “Generation Lockdown: Exploring possible predictors of technology phobia during the Coronavirus self-isolation period,” Aloma: Revista de Psicologia, Ciències de l’Educació i de l’Esport, vol. 38, no. 1, pp. 15–19, May 2020, doi: 10.51698/aloma.2020.38.1.15-19.
18. Oreg, “Personality, context, and resistance to organizational change,” European Journal of Work and Organizational Psychology, vol. 15, no. 1, pp. 73–101, Mar. 2006, doi: 10.1080/13594320500451247.
19. M. Descotes and V. Pauwels-Delassus, “The impact of consumer resistance to brand substitution on brand relationship,” Journal of Consumer Marketing, vol. 32, no. 1, pp. 34–42, Jan. 2015, doi: 10.1108/JCM-07-2014-1041.
20. WHO, “Coronavirus disease (COVID-19) 28 March 2023 | Q&A,” WORLD HEALTH ORGANIZATION, Mar. 28, 2020.
21. Schimmenti, J. Billieux, and V. Starcevic, “The Four Horsemen of Fear: An Integrated Model of Understanding Fear Experiences During the Covid-19 Pandemic.,” Clin Neuropsychiatry, vol. 17, no. 2, pp. 41–45, Apr. 2020, doi: 10.36131/CN20200202.
22. Z. and R. P. M. Solomon, “Consumer Behaviour: Buying, Having, and Being,” Pearson Prentice Hall. 2020.
23. Indrawati, Metode Penelitian Manajemen dan Bisnis Konvergensi Teknologi Komunikasi dan Informasi. . Bandung , 2015.
24. Bouri, R. Gupta, and D. Roubaud, “Herding behaviour in cryptocurrencies,” Financ Res Lett, vol. 29, pp. 216–221, Jun. 2019, doi: 10.1016/j.frl.2018.07.008.
25. , A. R. , B. B. , & B. W. Hair, Multivariate Data Analysis. 2010.
26. Henseler, “Partial Least Squares Path Modeling,” 2017, pp. 361–381. doi: 10.1007/978-3-319-53469-5_12.