Driving Millennial Satisfaction in L-Commerce: Perceived Price Advantage, Real-Time Interactivity, and Perceived Visibility as Key Factors
Keywords:
Live Commerce, Customer Satisfaction
Abstract
The advent of Live-Commerce has spurred changes in consumer shopping preferences. Millennials play a pivotal role in current consumer trends, being highly digitally active and predominant users across various online platforms. The objective of this study is to investigate how three dimensions of Live-Commerce including perceived price advantage, real-time interactivity, and perceived visibility affect millennial satisfaction in the context of online shopping within Live-Commerce platforms. Employing a quantitative approach, this study utilizes multiple linear regression analysis to identify factors influencing millennial consumer satisfaction. The findings reveal that perceived price advantage, real-time interactivity, and perceived visibility partially and significantly impact millennial satisfaction in live commerce, with perceived price advantage emerging as the most dominant factor. The findings of this study provide both theoretical insights and practical implications for advancing Live-Commerce enterprises within the province of Bangka Belitung Islands.
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References
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Eid, M. I. (2011). Determinants of e-commerce customer satisfaction, trust, and loyalty in Saudi Arabia. Journal of Electronic Commerce Research, 12(1), 78–93.
Flavián, C., Gurrea, R., & Orús, C. (2019). Feeling Confident and Smart with Webrooming: Understanding the Consumer’s Path to Satisfaction. Journal of Interactive Marketing, 47, 1–15. https://doi.org/https://doi.org/10.1016/j.intmar.2019.02.002
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Ghozali, I. (2013). Aplikasi Analisis Multivariate dengan Program IBM SPSS 21, Edisi Ketujuh. Semarang: Universitas Diponegoro.
Gudigantala, N., Bicen, P., & Eom, M. (Tae-in). (2016). An examination of antecedents of conversion rates of e-commerce retailers. Management Research Review, 39(1), 82–114. https://doi.org/10.1108/MRR-05-2014-0112
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Hallikainen, H., Luongo, M., Dhir, A., & Laukkanen, T. (2022). Consequences of personalized product recommendations and price promotions in online grocery shopping. Journal of Retailing and Consumer Services, 69, 103088. https://doi.org/https://doi.org/10.1016/j.jretconser.2022.103088
Hilvert-Bruce, Z., Neill, J. T., Sjöblom, M., & Hamari, J. (2018). Social motivations of live-streaming viewer engagement on Twitch. Computers in Human Behavior, 84, 58–67. https://doi.org/https://doi.org/10.1016/j.chb.2018.02.013
Hung, S.-W., Cheng, M.-J., & Hsieh, S.-C. (2015). Consumers’ satisfaction with online group buying – an incentive strategy. International Journal of Retail & Distribution Management, 43(2), 167–182. https://doi.org/10.1108/IJRDM-09-2013-0183
Joo, E., & Yang, J. (2023). How perceived interactivity affects consumers’ shopping intentions in live stream commerce: roles of immersion, user gratification and product involvement. Journal of Research in Interactive Marketing, 17(5), 754–772. https://doi.org/10.1108/JRIM-02-2022-0037
Kalinić, Z., Marinković, V., Kalinić, L., & Liébana-Cabanillas, F. (2021). Neural network modeling of consumer satisfaction in mobile commerce: An empirical analysis. Expert Systems with Applications, 175, 114803. https://doi.org/https://doi.org/10.1016/j.eswa.2021.114803
Kim, H.-W., & Gupta, S. (2009). A comparison of purchase decision calculus between potential and repeat customers of an online store. Decision Support Systems, 47(4), 477–487. https://doi.org/https://doi.org/10.1016/j.dss.2009.04.014
Kim, K., Chung, T.-L. (Doreen), & Fiore, A. M. (2023). The role of interactivity from Instagram advertisements in shaping young female fashion consumers’ perceived value and behavioral intentions. Journal of Retailing and Consumer Services, 70, 103159. https://doi.org/https://doi.org/10.1016/j.jretconser.2022.103159
Labrecque, L. I. (2014). Fostering Consumer–Brand Relationships in Social Media Environments: The Role of Parasocial Interaction. Journal of Interactive Marketing, 28(2), 134–148. https://doi.org/10.1016/j.intmar.2013.12.003
Leonardi, P. M. (2011). When Flexible Routines Meet Flexible Technologies: Affordance, Constraint, and the Imbrication of Human and Material Agencies. MIS Quarterly, 35(1), 147–167. https://doi.org/10.2307/23043493
Li, L., Yuan, L., & Tian, J. (2023). Influence of online E-commerce interaction on consumer satisfaction based on big data algorithm. Heliyon, 9(8), e18322. https://doi.org/https://doi.org/10.1016/j.heliyon.2023.e18322
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Lu, B., Fan, W., & Zhou, M. (2016). Social presence, trust, and social commerce purchase intention: An empirical research. Computers in Human Behavior, 56, 225–237. https://doi.org/https://doi.org/10.1016/j.chb.2015.11.057
Ma, Y. (2021). Elucidating determinants of customer satisfaction with live-stream shopping: An extension of the information systems success model. Telematics and Informatics, 65, 101707. https://doi.org/https://doi.org/10.1016/j.tele.2021.101707
Melović, B., Šehović, D., Karadžić, V., Dabić, M., & Ćirović, D. (2021). Determinants of Millennials’ behavior in online shopping – Implications on consumers’ satisfaction and e-business development. Technology in Society, 65, 101561. https://doi.org/https://doi.org/10.1016/j.techsoc.2021.101561
Moon, N. N., Talha, I. M., & Salehin, I. (2021). An advanced intelligence system in customer online shopping behavior and satisfaction analysis. Current Research in Behavioral Sciences, 2, 100051. https://doi.org/https://doi.org/10.1016/j.crbeha.2021.100051
Nisar, T. M., & Prabhakar, G. (2017). What factors determine e-satisfaction and consumer spending in e-commerce retailing? Journal of Retailing and Consumer Services, 39, 135–144. https://doi.org/https://doi.org/10.1016/j.jretconser.2017.07.010
Nofrizal, Juju, U., Sucherly, N, A., Waldelmi, I., & Aznuriyandi. (2023). Changes and determinants of consumer shopping behavior in E-commerce and social media product Muslimah. Journal of Retailing and Consumer Services, 70, 103146. https://doi.org/https://doi.org/10.1016/j.jretconser.2022.103146
Parchoma, G. (2014). The contested ontology of affordances: Implications for researching technological affordances for collaborative knowledge production. Computers in Human Behavior, 37, 360–368. https://doi.org/https://doi.org/10.1016/j.chb.2012.05.028
Park, E. J., Kim, E. Y., Funches, V. M., & Foxx, W. (2012). Apparel product attributes, web browsing, and e-impulse buying on shopping websites. Journal of Business Research, 65(11), 1583–1589. https://doi.org/https://doi.org/10.1016/j.jbusres.2011.02.043
Phonthanukitithaworn, C., & Sellitto, C. (2017). Facebook as a second screen: An influence on sport consumer satisfaction and behavioral intention. Telematics and Informatics, 34(8), 1477–1487. https://doi.org/https://doi.org/10.1016/j.tele.2017.06.011
Pink, M., & Djohan, N. (2021). Effect Of Ecommerce Post-Purchase Activities On Customer Retention In Shopee Indonesia. Enrichment: Journal of Management, 12(1), 519–526.
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Published
2024-03-22
How to Cite
Sah, T. (2024). Driving Millennial Satisfaction in L-Commerce: Perceived Price Advantage, Real-Time Interactivity, and Perceived Visibility as Key Factors. Journal of Applied Business Administration, 8(1), 14-28. https://doi.org/10.30871/jaba.v8i1.7325
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Articles
Copyright (c) 2024 Tomi Sah
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
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