Main Article Content
Abstract
In recent years, sales in online platforms have received huge attention from generation Z in Indonesia, along with live streaming business model which has undergone rapid development in recent years. Although the way live streaming with consumers has been known as the key to influence consumer behavior, only a few research has studied the style of streaming communication in affecting purchase intentions. Based on the social influence theory, this study attempts to examine the influence of interaction orientation, parasocial relation, and digital influencer credibility on purchase intention. In addition, the present study also investigates the role of product involvement advertised by streamers as moderator. The quantitative approach with the survey is used through samples of 200 respondents selected by purposive sampling. The data is collected online through disseminating questionnaires using Google Form, which is then analyzed using SEM-PLS technique. The findings indicate that interaction orientation positively influences purchase intention and parasocial relation, while parasocial relation positively influences digital influencer credibility, and digital influencer credibility positively influences purchase intention. In addition, product involvement has a moderating role that can strengthen the influence of interaction orientation and purchase intention. This study provides implications for how an interaction can be delivered online and how the involvement of a credible influencer can affect purchase intention.
Keywords
Article Details
Copyright (c) 2023 Adjeng Mariana Febrianti, Nurul Hermina, Maman Suratman
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References
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Ambroise, L., Bérard, C., & Prim-Allaz, I. (2020). Performance implications of exploration and exploitation in SMEs: The mediating role of interaction orientation. Journal of Business and Industrial Marketing, 35(12), 1971-1981. https://doi.org/10.1108/JBIM-06-2019-0279.
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Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40, 414-433. https://doi.org/10.1007/s11747-011-0261-6.
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., ... & Calantone, R. J. (2014). Common beliefs and reality about PLS: Comments on Rönkkö and Evermann (2013). Organizational Research Methods, 17(2), 182-209. https://doi.org/10.1177/1094428114526928.
Herzallah, D., Muñoz-Leiva, F., & Liebana-Cabanillas, F. (2022). Drivers of purchase intention in Instagram Commerce. Spanish Journal of Marketing - ESIC, 26(2), 168-188. https://doi.org/10.1108/SJME-03-2022-0043.
Itani, O. S., Krush, M. T., Agnihotri, R., & Trainor, K. J. (2020). Social media and customer relationship management technologies: Influencing buyer-seller information exchanges. Industrial Marketing Management, 90(October 2019), 264–275. https://doi.org/10.1016/j.indmarman.2020.07.015.
Kautish, P., Paço, A., & Thaichon, P. (2022). Sustainable consumption and plastic packaging: Relationships among product involvement, perceived marketplace influence and choice behavior. Journal of Retailing and Consumer Services, 67(May), 103032. https://doi.org/10.1016/j.jretconser.2022.103032.
Kwon, W., Lee, M., Back, K. J., & Lee, K. Y. (2021). Assessing restaurant review helpfulness through big data: Dual-process and social influence theory. Journal of Hospitality and Tourism Technology, 12(2), 177-195. https://doi.org/10.1108/JHTT-04-2020-0077.
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Li, M., Wang, Q., & Cao, Y. (2022). Understanding consumer online impulse buying in live streaming e-commerce: A stimulus-organism-response framework. International Journal of Environmental Research and Public Health, 19(7), 4378. https://doi.org/10.3390/ijerph19074378.
Liao, J., Chen, K., Qi, J., Li, J., & Yu, I. Y. (2023). Creating immersive and parasocial live shopping experience for viewers: The role of streamers’ interactional communication style. Journal of Research in Interactive Marketing, 17(1), 140–155. https://doi.org/10.1108/JRIM-04-2021-0114.
Lou, C. (2022). Social media influencers and followers: Theorization of a trans-parasocial relation and explication of its implications for influencer advertising. Journal of Advertising, 51(1), 4-21. https://doi.org/10.1080/00913367.2021.1880345
Ma, L., Gao, S., & Zhang, X. (2022). How to use live streaming to improve consumer purchase intentions: Evidence from China. Sustainability (Switzerland), 14(2), 1045. https://doi.org/10.3390/su14021045.
Melnychuk, H. A., Arasli, H., & Nevzat, R. (2024). How to engage and attract virtual influencers’ followers: A new non-human approach in the age of influencer marketing. Marketing Intelligence & Planning, vol. ahead-of-print, no. ahead-of-print. https://doi.org/10.1108/MIP-06-2023-0251.
Mittal, B. (1995). A comparative analysis of four scales of consumer involvement. Psychology & Marketing, 12(7), 663–682. https://doi.org/10.1002/mar.4220120708.
Munnukka, J., Maity, D., Reinikainen, H., & Luoma-aho, V. (2019). “Thanks for watching”. The effectiveness of YouTube vlogendorsements. Computers in Human Behavior, 93, 226-234. https://doi.org/10.1016/j.chb.2018.12.014.
Palmié, M., Miehé, L., Oghazi, P., Parida, V., & Wincent, J. (2022). The evolution of the digital service ecosystem and digital business model innovation in retail: The emergence of meta-ecosystems and the value of physical interactions. Technological Forecasting and Social Change, 177, 121496. https://doi.org/10.1016/j.techfore.2022.121496.
Penttinen, V., Ciuchita, R., & Čaić, M. (2022). YouTube it before you buy it: The role of parasocial interaction in consumer-to-consumer video reviews. Journal of Interactive Marketing, 57(4), 561-582. https://doi.org/10.1177/10949968221102825.
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