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Articles

Vol. 1 No. 1 (2026): Strategic Dynamics in Emerging Markets: Psychological Mechanisms in Consumer Behavior and Organizational Performance

The Influence of Social Media Influencers and E-WOM on Purchase Intention: The Mediating Role of Brand Trust

DOI:
https://doi.org/10.66452/702785
Submitted
February 10, 2026
Published
2026-02-16

Abstract

Purpose: This study examines brand trust as a mediating mechanism linking social media influencers and electronic word-of-mouth (e-WOM) to purchase intention for cosmetics products among Indonesian Gen Z consumers, addressing theoretical gaps in process-oriented digital marketing research.

Method/Approach: Survey data from 75 business students at Universitas Timor were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. Direct and indirect effects were tested through bias-corrected bootstrapping procedures with 5,000 resamples following contemporary mediation analysis best practices.

Findings: Influencers (β = 0.445, p < .001) and e-WOM (β = 0.460, p < .001) significantly predicted brand trust. Brand trust strongly predicted purchase intention (β = 0.550, p < .001). Direct effects of influencers and e-WOM on purchase intention were non-significant. Brand trust fully mediated both relationships (indirect effects: 0.245 and 0.253, p < .05), with 60-77% variance mediated.

Limitations: Cross-sectional design limits causal inference. Small sample size (n = 75) may affect generalizability. Future research should employ longitudinal designs with larger samples (n > 200) across diverse product categories and regions.

Implications: Cosmetics brands should prioritize trust-building through authentic influencer partnerships and genuine e-WOM cultivation rather than direct sales promotions. Trust-first strategies prove more effective than sales-first tactics in emerging digital markets.

Contribution: First study quantifying full mediation mechanism in Indonesian Gen Z cosmetics context, extending social cognitive theory and trust-based mediation frameworks to emerging market digital marketing, demonstrating trust as prerequisite for behavioral outcomes.

References

  1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
  2. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice Hall.
  3. Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52(1), 1–26. https://doi.org/10.1146/annurev.psych.52.1.1
  4. Bandura, A. (2006). Toward a psychology of human agency. Perspectives on Psychological Science, 1(2), 164–180. https://doi.org/10.1111/j.1745-6916.2006.00011.x
  5. Bauer, R. A. (1960). Consumer behavior as risk taking. In R. S. Hancock (Ed.), Dynamic marketing for a changing world (pp. 389–398). American Marketing Association.
  6. Bettman, J. R. (1973). Perceived risk and its components: A model and empirical test. Journal of Marketing Research, 10(2), 184–190. https://doi.org/10.1177/002224377301000211
  7. Boerman, S. C., van Reijmersdal, E. A., & Neijens, P. C. (2017). Influencer marketing: The effects of disclosure on persuasion knowledge and brand attitudes. International Journal of Advertising, 36(5), 1–20. https://doi.org/10.1080/02650487.2016.1247848
  8. Brown, D., & Fiorella, S. (2013). Influencer marketing: Who really influences your customers? Que Publishing.
  9. Brown, D., & Hayes, N. (2008). Influencer marketing: Who really influences your customers? Routledge. https://doi.org/10.4324/9780080557700
  10. Chaudhuri, A., & Holbrook, M. B. (2001). The chain of effects from brand trust and brand affect to brand performance: The role of brand loyalty. Journal of Marketing, 65(2), 81–93. https://doi.org/10.1509/jmkg.65.2.81.18255
  11. Cheung, C. M. K., & Thadani, D. R. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54(1), 461–470. https://doi.org/10.1016/j.dss.2012.06.008
  12. Cialdini, R. B. (2009). Influence: Science and practice (5th ed.). Pearson.
  13. Darby, M. R., & Karni, E. (1973). Free competition and the optimal amount of fraud. Journal of Law and Economics, 16(1), 67–88. https://doi.org/10.1086/466756
  14. Deutsch, M., & Gerard, H. B. (1955). A study of normative and informational social influences upon individual judgment. Journal of Abnormal and Social Psychology, 51(3), 629–636. https://doi.org/10.1037/h0046408
  15. Faul, F., Erdfelder, E., Buchner, A., & Lang, A. G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149
  16. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Addison-Wesley.
  17. Freberg, K., Graham, K., McGaughey, K., & Freberg, L. A. (2011). Who are the social media influencers? A study of public perceptions of personality. Public Relations Review, 37(1), 90–92. https://doi.org/10.1016/j.pubrev.2010.11.001
  18. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90. https://doi.org/10.2307/30036519
  19. Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS SEM) (3rd ed.). SAGE.
  20. Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2nd ed.). Guilford Press.
  21. Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the internet? Journal of Interactive Marketing, 18(1), 38–52. https://doi.org/10.1002/dir.10073
  22. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
  23. Hofstede Insights. (2021). Country comparison: Indonesia. https://www.hofstede-insights.com
  24. Hovland, C. I., Janis, I. L., & Kelley, H. H. (1953). Communication and persuasion: Psychological studies of opinion change. Yale University Press.
  25. Jalilvand, M. R., & Samiei, N. (2012). The effect of electronic word of mouth on brand image and purchase intention. Marketing Intelligence & Planning, 30(4), 460–476. https://doi.org/10.1108/02634501211231946
  26. King, R. A., Racherla, P., & Bush, V. D. (2014). What we know and don’t know about online word-of-mouth: A review and synthesis of the literature. Journal of Interactive Marketing, 28(3), 167–183. https://doi.org/10.1016/j.intmar.2014.02.001
  27. Lewis, J. D., & Weigert, A. (1985). Trust as a social reality. Social Forces, 63(4), 967–985. https://doi.org/10.2307/2578601
  28. Lou, C., & Yuan, S. (2019). Influencer marketing: How message value and credibility affect consumer trust of branded content on social media. Journal of Interactive Advertising, 19(1), 58–73. https://doi.org/10.1080/15252019.2018.1533501
  29. McAllister, D. J. (1995). Affect- and cognition-based trust as foundations for interpersonal cooperation in organizations. Academy of Management Journal, 38(1), 24–59. https://doi.org/10.2307/256727
  30. McCracken, G. (1989). Who is the celebrity endorser? Cultural foundations of the endorsement process. Journal of Consumer Research, 16(3), 310–321. https://doi.org/10.1086/209217
  31. Mitchell, V. W. (1999). Consumer perceived risk: Conceptualisations and models. European Journal of Marketing, 33(1/2), 163–195. https://doi.org/10.1108/03090569910249229
  32. Nelson, P. (1970). Information and consumer behavior. Journal of Political Economy, 78(2), 311–329. https://doi.org/10.1086/259630
  33. Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
  34. Roselius, T. (1971). Consumer rankings of risk reduction methods. Journal of Marketing, 35(1), 56–61. https://doi.org/10.1177/002224297103500110
  35. Rousseau, D. M., Sitkin, S. B., Burt, R. S., & Camerer, C. (1998). Not so different after all: A cross-discipline view of trust. Academy of Management Review, 23(3), 393–404. https://doi.org/10.5465/amr.1998.926617
  36. Spears, N., & Singh, S. N. (2004). Measuring attitude toward the brand and purchase intentions. Journal of Current Issues & Research in Advertising, 26(2), 53–66. https://doi.org/10.1080/10641734.2004.10505164
  37. Zhao, X., Lynch, J. G., Jr., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and truths about mediation analysis. Journal of Consumer Research, 37(2), 197–206. https://doi.org/10.1086/651257

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