Navigating influence: Unraveling the impact of micro-influencer attributes on consumer choices in the Chinese social media
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DOIhttp://dx.doi.org/10.21511/im.20(2).2024.13
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Article InfoVolume 20 2024, Issue #2, pp. 152-168
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Creative Commons Attribution 4.0 International License
This study aims to explore the relationship between consumer purchasing behavior and key micro-influencer attributes, including knowledge, entertainment value, credibility, and transparency, within the context of Chinese social media platforms. The paper adopts a quantitative approach, employing partial least squares structural equation modeling (PLS-SEM) to analyze the intricate relationships among latent variables. The respondents comprise active users of major Chinese social media platforms, such as Weibo and Xiaohongshu. For primary data collection, 329 respondents were surveyed online, utilizing a convenient sampling method as part of non-probability sampling. Data collection spanned four weeks, and participants were given the option to respond in either English or Mandarin. The findings suggest significant associations between consumer purchasing behavior and micro-influencer attributes. Specifically, knowledge, entertainment value, credibility, and transparency exhibit varying degrees of influence on consumer behavior within the Chinese social media landscape. The p-value for H1, H2, H3, and H7 appeared as 0.000 and shows that these are the highly significant relations, whereas the p-value for H3 (0.019), for H5 (0.001), and for H6 (0.028) shows that these relations play a moderate role in the proposed model. Elucidating the role of key attributes provides valuable insights for marketers and businesses seeking to leverage micro-influencer marketing strategies effectively in this rapidly evolving digital landscape.
- Keywords
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JEL Classification (Paper profile tab)M31, M37
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References66
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Tables8
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Figures3
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- Figure 1. Conceptual model
- Figure 2. Estimation model
- Figure 3. Structural model
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- Table 1. Cronbach’s alpha statistics
- Table 2. Reliability statistics
- Table 3. Fornell-Larcker criterion
- Table 4. Model fit
- Table 5. R-statistics
- Table 6. F-statistics
- Table 7. Path analysis results
- Table A1. Research variables
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- Anwar, R. S., Channa, K. A., & Shah, S. M. M. (2021). Scope of Combining the Research Methods in Human Resource Management (HRM) and Organizational Behavior (OB). Indian Journal of Economics and Business, 20(2), 1663-1674.
- Appel, G., Grewal, L., Hadi, R., & Stephen, A. T. (2020). The future of social media in marketing. Journal of the Academy of Marketing Science, 48(1), 79-95.
- Baker, J. J., & Nenonen, S. (2020). Collaborating to shape markets: Emergent collective market work. Industrial Marketing Management, 85, 240-253.
- Campbell, C., & Farrell, J. R. (2020). More than meets the eye: The functional components underlying influencer marketing. Business Horizons, 63(4), 469-479.
- Carrete, L., Castaño, R., Felix, R., Centeno, E., & González, E. (2012). Green consumer behavior in an emerging economy: Confusion, credibility, and compatibility. Journal of Consumer Marketing, 29(7), 470-481.
- Cartwright, S., Liu, H., & Davies, I. A. (2022). Influencer marketing within business-to-business organisations. Industrial Marketing Management, 106, 338-350.
- Connell, E. (2023). Pooshing the boundaries of Instagram influencers: How celebrity and color strategy impact source credibility perceptions and parasocial behavior within the online health community. University of Wyoming.
- Crnjak-Karanović, B., Kursan Milaković, I., & Elez, J. (2023). Which decision-making stages matter more? Influencer’s perceived credibility, sponsorship and moderating role of trust. Young Consumers, 24(6), 649-668.
- Dinh, T. C. T., & Lee, Y. (2022). “I want to be as trendy as influencers”– how “fear of missing out” leads to buying intention for products endorsed by social media influencers. Journal of Research in Interactive Marketing, 16(3), 346-364.
- Dou, W., Wu, J., Yan, M., & Tang, J. (2023). Impact of influencers’ influencing strategy on follower outcomes: Evidence from China. Asia Pacific Business Review.
- El-Deeb, A. (2022). The Holy Grail of software products success: Great customer experience and the key elements needed to create one. ACM SIGSOFT Software Engineering Notes, 47(2), 8-9.
- Feng, W., & Wang, P. (2020). Research upon the relativity between digital media and tourism. In A. Marcus & E. Rosenzweig (Eds.), Design, User Experience, and Usability (pp. 594-607). Cham: Springer.
- Gerlich, M. (2022). Micro-influencer marketing during the COVID-19 pandemic: New vistas or the end of an era? Journal of Digital & Social Media Marketing, 9(4), 354-370.
- Gerlich, M. (2023). The power of personal connections in micro-influencer marketing: A study on consumer behaviour and the impact of micro-influencers. Transnational Marketing Journal, 11(1), 131-152.
- Guan, C., & Li, E. Y. (2021). Emerging issues in social media influencers. International Journal of Internet Marketing and Advertising, 15(2).
- Guenther, P., Guenther, M., Ringle, C. M., Zaefarian, G., & Cartwright, S. (2023). Improving PLS-SEM use for business marketing research. Industrial Marketing Management, 111, 127-142.
- Gulfraz, M. B., Sufyan, M., Mustak, M., Salminen, J., & Srivastava, D. K. (2022). Understanding the impact of online customers’ shopping experience on online impulsive buying: A study on two leading e-commerce platforms. Journal of Retailing and Consumer Services, 68, Article 103000.
- Ha, L., & Yang, Y. (2023). Research about persuasive effects of social media influencers as online opinion leaders 1990-2020: A review. International Journal of Internet Marketing and Advertising, 18(2-3), 220-241.
- Hair, J., Hollingsworth, C. L., Randolph, A. B., & Chong, A. Y. L. (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management & Data Systems, 117(3), 442-458.
- Hsieh, J.-K. (2023). The impact of influencers’ multi-SNS use on followers’ behavioral intentions: An integration of cue consistency theory and social identity theory. Journal of Retailing and Consumer Services, 74, Article 103397.
- Hurd, N. (2019). Instagram users’ meaning construction through micro-influencer-generated content (Master’s Thesis). Tampere University.
- Ihlen, Ø., Just, S. N., Kjeldsen, J. E., Mølster, R., Offerdal, T. S., Rasmussen, J., & Skogerbø, E. (2022). Transparency beyond information disclosure: Strategies of the Scandinavian public health authorities during the COVID-19 pandemic. Journal of Risk Research, 25(10), 1176-1189.
- Isyanto, P., Sapitri, R. G., & Sinaga, O. (2020). Micro influencers marketing and brand image to purchase intention of cosmetic products focallure. Systematic Reviews in Pharmacy, 11(1), 601-605.
- Jacobson, J., & Harrison, B. (2022). Sustainable fashion social media influencers and content creation calibration. International Journal of Advertising, 41(1), 150-177.
- Jordas, A. (2023). How to identify the right collaboration partner? A qualitative study of Finnish Instagram micro-influencers (Master’s Thesis). Åbo Akademi University.
- Kay, S., Mulcahy, R., & Parkinson, J. (2020). When less is more: The impact of macro and micro social media influencers’ disclosure. Journal of Marketing Management, 36(3-4), 248-278.
- Khan, M. A., Alhathal, F., Alam, S., & Minhaj, S. M. (2023). Importance of social networking sites and determining its impact on brand image and online shopping: An empirical study. Sustainability, 15(6), Article 5129.
- Kochhar, N. (2021). Social media marketing in the fashion industry: A systematic literature review and research agenda (Doctoral Thesis). The University of Manchester.
- Lafferty, B. A., & Goldsmith, R. E. (1999). Corporate credibility’s role in consumers’ attitudes and purchase intentions when a high versus a low credibility endorser is used in the ad. Journal of Business Research, 44(2), 109-116.
- Leung, F. F., Gu, F. F., & Palmatier, R. W. (2022). Online influencer marketing. Journal of the Academy of Marketing Science, 50, 226-251.
- Liu, G. H. W., Li, Y., & Lee, N. C.-A. (2021). Size does matter: How do micro-influencers impact follower purchase intention on social media? Proceedings of The International Conference on Electronic Business (pp. 402-412). Nanjing, China.
- 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.
- Mabkhot, H., Isa, N. M., & Mabkhot, A. (2022). The influence of the credibility of social media influencers SMIs on the consumers’ purchase intentions: Evidence from Saudi Arabia. Sustainability, 14(19), Article 12323.
- Maraz, A., Eisinger, A., Hende, B., Urbán, R., Paksi, B., Kun, B., Kökönyei, G., Griffiths, M. D., & Demetrovics, Z. (2014). Measuring compulsive buying behaviour: Psychometric validity of three different scales and prevalence in the general population and in shopping centres. Psychiatry Research, 225(3), 326-334.
- Myers, S., Syrdal, H. A., Mahto, R. V., & Sen, S. S. (2023). Social religion: A cross-platform examination of the impact of religious influencer message cues on engagement – The Christian context. Technological Forecasting and Social Change, 191, Article 122442.
- Njathi, A. W. (2023). The glitz and glamour platform economy: Issues for Instagram monetization for influencers in Nairobi, Kenya. North Carolina State University.
- Pornsrimate, K., & Khamwon, A. (2021). How to convert Millennial consumers to brand evangelists through social media micro-influencers. Innovative Marketing, 17(2), 18-32.
- Pozharliev, R., Rossi, D., & De Angelis, M. (2022). Consumers’ self-reported and brain responses to advertising post on Instagram: The effect of number of followers and argument quality. European Journal of Marketing, 56(3), 922-948.
- Pradhan, D., Kuanr, A., Anupurba Pahi, S., & Akram, M. S. (2023). Influencer marketing: When and why gen Z consumers avoid influencers and endorsed brands. Psychology & Marketing, 40(1), 27-47.
- Purcărea, T., Ioan-Franc, V., Ionescu, Ş.-A., Purcărea, I. M., Purcărea, V. L., Purcărea, I., Cristina, M., Platon, O., & Orzan, A.-O. (2022). Major shifts in sustainable consumer behavior in Romania and retailers’ priorities in agilely adapting to it. Sustainability, 14(3), Article 1627.
- Reinikainen, H., Munnukka, J., Maity, D., & Luoma-Aho, V. (2020). ‘You really are a great big sister’ – Parasocial relationships, credibility, and the moderating role of audience comments in influencer marketing. Journal of Marketing Management, 36(3-4), 279-298.
- Roshandel, A., Miöen Dahlström, F., & Ekström, K. (2023). Unveiling the art of illusion: Exploring the fabrication of authenticity and trustworthiness by social media micro-influencers to engage their audience: An exploratory multiple case study that aims to analyze how social media micro-influencers fabricate authenticity and trustworthiness to engage their audience (Bachelor’s Thesis). Jönköping University.
- Rungruangjit, W., & Charoenpornpanichkul, K. (2022). Building stronger brand evangelism for sustainable marketing through micro-influencer-generated content on Instagram in the fashion industry. Sustainability, 14(23), Article 15770.
- Saima, & Khan, M. A. (2021). Effect of social media influencer marketing on consumers’ purchase intention and the mediating role of credibility. Journal of Promotion Management, 27(4), 503-523.
- Shaikh, F., Afshan, G., Anwar, R. S., Abbas, Z., & Chana, K. A. (2023). Analyzing the impact of artificial intelligence on employee productivity: The mediating effect of knowledge sharing and well-being. Asia Pacific Journal of Human Resources, 61(4), 794-820.
- Shen, Z. (2021). A persuasive eWOM model for increasing consumer engagement on social media: Evidence from Irish fashion micro-influencers. Journal of Research in Interactive Marketing, 15(2), 181-199.
- Sheng, J., Lee, Y. H., & Lan, H. (2023). Parasocial relationships with micro-influencers: Do sponsorship disclosure and electronic word-of-mouth disrupt? Internet Research.
- Sinha, M., & Srivastava, M. (2023). Augmented reality: New future of social media influencer marketing. Vision.
- Sun, Y., Leng, K., & Xiong, H. (2022). Research on the influencing factors of consumers’ green purchase behavior in the post-pandemic era. Journal of Retailing and Consumer Services, 69, Article 103118.
- Swan, A. L. (2021). Ordinary outsiders: Transnational content creation and the reclamation of agency by “foreign” women in South Korea. University of Washington.
- Syrdal, H. A., Myers, S., Sen, S., Woodroof, P. J., & McDowell, W. C. (2023). Influencer marketing and the growth of affiliates: The effects of language features on engagement behavior. Journal of Business Research, 163, 113875.
- Todorov, I., Lazarević, K., & Cvetković, M. (2023). The impact of social media influencers on consumer behavior in digital marketing. E-Business Technologies Conference Proceedings, 3(1), 63-68.
- Triastuti, E. (2019). Indonesian blogger communities: Display of digital artefacts as the legitimate ruling mechanism. Jurnal Komunikasi Indonesia, 8(3), 187-197.
- Tsang, M. M., Ho, S.-C., & Liang, T.-P. (2004). Consumer attitudes toward mobile advertising: An empirical study. International Journal of Electronic Commerce, 8(3), 65-78.
- Tunpornchai, W., Thamma, N., & Sirikajohndechsakun, S. (2021). Micro influencer strategy in the men’s cosmetics industry on Thailand’s Facebook and brand fit an effect on intention to buy. Asian Administration & Management Review, 4(1).
- Wachler, B. B. (2022). Influenced: The impact of social media on our perception. Rowman & Littlefield.
- Wang, F., Xu, H., Hou, R., & Zhu, Z. (2023). Designing marketing content for social commerce to drive consumer purchase behaviors: A perspective from speech act theory. Journal of Retailing and Consumer Services, 70, Article 103156.
- Whitehead, G. E. K., & Greenier, V. T. (2019). Beyond good teaching practices: Language teacher leadership from the learners’ perspective. TESOL Quarterly, 53(4), 960-985.
- Wong, K. K.-K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32.
- Woodroof, P. J., Howie, K. M., Syrdal, H. A., & VanMeter, R. (2020). What’s done in the dark will be brought to the light: Effects of influencer transparency on product efficacy and purchase intentions. Journal of Product & Brand Management, 29(5), 675-688.
- Yang, S., Isa, S. M., Wu, H., Thurasamy, R., Fang, X., Fan, Y., & Liu, D. (2022). Effects of stores’ environmental components on Chinese consumers’ emotions and intentions to purchase luxury brands: Integrating partial least squares-structural equation modeling and fuzzy-set qualitative comparative analysis approaches. Frontiers in Psychology, 13, Article 840413.
- Yang, Y., Liu, Y., Lv, X., Ai, J., & Li, Y. (2022). Anthropomorphism and customers’ willingness to use artificial intelligence service agents. Journal of Hospitality Marketing & Management, 31(1), 1-23.
- Zaharani, G. F. R., Kusumawati, N., & Aprilianty, F. (2021). The impact of micro-influencer on brand image and purchase intention in local culinary products on Instagram. The 6th International Conference on Management in Emerging Markets (ICMEM 2021). Bandung, Indonesia.
- Zhang, L.-T., & Zhao, S. (2020). Diaspora micro-influencers and COVID-19 communication on social media: The case of Chinese-speaking YouTube vloggers. Multilingua, 39(5), 553-563.
- Zheng, L., Huang, B., Qiu, H., & Bai, H. (2024). The role of social media followers’ agency in influencer marketing: A study based on the heuristic–systematic model of information processing. International Journal of Advertising, 43(3), 554-579.
- Zhou, S., Blazquez, M., McCormick, H., & Barnes, L. (2021). How social media influencers’ narrative strategies benefit cultivating influencer marketing: Tackling issues of cultural barriers, commercialised content, and sponsorship disclosure. Journal of Business Research, 134, 122-142.