The impact of TikTok fashion haul videos towards Generation Z's purchase decision in Indonesia
List of Authors
  • Fitri Aprilianty , Maria Carla Pangalila

Keyword
  • EWOM, Generation Z, Purchase Decision, TikTok Fashion Haul Videos

Abstract
  • The COVID-19 pandemic limits fashion brands’ promotional alternatives. This means digital advertising is now a priority. TikTok is one of the social media that is progressively utilized and has made fashion haul videos more popular. Furthermore, electronic word-of-mouth (eWOM) is vital in the field of promotion. Based on past studies, there are several antecedents of eWOM. However, no research studies have examined potential predictors of eWOM in the context of TikTok fashion haul videos. Moreover, brands are unable to assess platform sales conversion yet. This research aims to assess the effectiveness of TikTok fashion haul videos in affecting generation Z's purchase decisions and identify the factors in TikTok fashion haul videos that attract generation Z's purchase decisions. This research is conducted using a qualitative approach through semi-structured interviews of 13 respondents and a quantitative approach through an online survey with 204 respondents who are from Generation Z who have purchased at least 1 fashion product because of watching TikTok fashion haul videos in the past 1 year. The interview results are analyzed using the open coding method and the survey results are analyzed using the PLS-SEM method. Based on the interview results, six factors can affect generation Z's purchase decisions in Indonesia which include argument quality, source credibility, source attractiveness, source perception, source style, and high TikTok engagement. However, based on the PLS-SEM, the result shows that the purchase decision is driven by information acceptance of TikTok fashion haul videos which is impacted by source style and high TikTok engagement, mediated by intention to use which means TikTok fashion haul videos have a significant impact on Generations Z's purchase decision. The findings will give insight into the factors and effectiveness of TikTok fashion haul videos in affecting Z's purchase decisions to increase sales.

Reference
  • 1. Bataineh, A. Q. (2015). The Impact of Perceived e-WOM on Purchase Intention: The Mediating Role of Corporate Image. International Journal of Marketing Studies, 7(1). https://doi.org/ 10.5539/ijms.v7n1p126

    2. Bhattacherjee, & Sanford. (2006). Influence Processes for Information Technology Acceptance: An Elaboration Likelihood Model. MIS Quarterly, 30(4), 805. https://doi.org/10. 2307/25148755

    3. Cheung, M. Y., Luo, C., Sia, C. L., & Chen, H. (2009). Credibility of Electronic Word-of-Mouth: Informational and Normative Determinants of On-line Consumer Recommendations. International Journal of Electronic Commerce, 13(4), 9–38. https://doi.org/10.275 3/jec1086-4415130402

    4. Cui, G., Lui, H., & Guo, X. (2010). Online Reviews as a Driver of New Product Sales. 2010 International Conference on Management of E-Commerce and E-Government. https://doi.org/10.1109/icmecg.2010.13

    5. Daugherty, T., & Hoffman, E. (2014). eWOM and the importance of capturing consumer attention within social media. Journal of Marketing Communications, 20(1-2), 82–102. https://doi.org/10.1080/13527266.2013.797764

    6. Davis, F. D. (1989a). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/ 249008

    7. Davis, F. D. (1989b). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/2 49008

    8. De Maeyer, P. (2012). Impact of online consumer reviews on sales and price strategies: a review and directions for future research. Journal of Product & Brand Management, 21(2), 132–139. https://doi.org/10.1108/10610421211215599

    9. Dellarocas, C., Zhang, X. (Michael), & Awad, N. F. (2007). Exploring the value of online product reviews in forecasting sales: The case of motion pictures. Journal of Interactive Marketing, 21(4), 23–45. https://doi.org/10.1002/dir.20087

    10. Delone, W. H., & McLean, E. R. (2003). The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748

    11. How fashion brands can Market and Communicate during Covid-19. (2020, April 14). Heuritech. https://www.heuritech.com/blog/articles/how-fashion-brands-can-market-and-communicate-during-covid-19/

    12. Huhn, R., Brantes Ferreira, J., Sabino de Freitas, A., & Leão, F. (2018). The effects of social media opinion leaders’ recommendations on followers’ intention to buy. Review of Business Management, 20(1), 57–73. https://doi.org/10.7819/rbgn.v20i1.3678

    13. J Paul Peter, & Olson, J. C. (2010). Consumer behavior & marketing strategy. Mcgraw-Hill Irwin.

    14. Jaradat, M. I. R. M., & Mashaqba, A. M. A. (2014). Understanding the adoption and usage of mobile payment services by using TAM3. International Journal of Business Information Systems, 16(3), 271. https://doi.org/10.1504/ijbis.2014.063768

    15. Kiecker, P., & Cowles, D. (2002). Interpersonal Communication and Personal Influence on the Internet: A Framework for Examining Online Word-of-Mouth. Journal of Euromarketing, 11(2), 71–88. https://doi.org/10.1300/j037v11n02_04

    16. Kisielius, J., & Sternthal, B. (1984). Detecting and Explaining Vividness Effects in Attitudinal Judgments. Journal of Marketing Research, 21(1), 54. https://doi.org/10.2307/3151792

    17. Kyung, H., Kwon, O., & Sung, Y. (2010). The Effects of Spokes-Characters’ Personalities of Food Products on Source Credibility. Journal of Food Products Marketing, 17(1), 65–78. https://doi.org/10.1080/10454446.2011.532402

    18. Li, C., Hall, S., & World Economic Forum. (2020, June 8). This is how COVID-19 is affecting the advertising industry. World Economic Forum. https://www.weforum.org/agenda/ 2020/06/coronavirus-advertising-marketing-covid19-pandemic-business/

    19. Luo, C., Luo, X. (Robert), Schatzberg, L., & Sia, C. L. (2013). Impact of informational factors on online recommendation credibility: The moderating role of source credibility. Decision Support Systems, 56(1), 92–102. https://doi.org/10.1016/j.dss.2013.05.005

    20. Magyar, J. (2021, January 19). SAP BrandVoice: How COVID-19 Is Nudging The Fashion Industry To Go Circular. Forbes. https://www.forbes.com/sites/sap/2021/01/12/how-covid-19-is-nudging-the-fashion-industry-to-go-circular/?sh=120a0b4c2a63

    21. Martawilaga, A., & Purwanegara, M. (2016). Information acceptance of electronic words of mouth (EWOM) and purchase intention through haul videos youtube. Journal of business and management, 5(5), 651–660.

    22. Martin, W. C., & Lueg, J. E. (2013). Modeling word-of-mouth usage. Journal of Business Research, 66(7), 801–808. https://doi.org/10.1016/j.jbusres.2011.06.004

    23. Meehan, F. (2021, May 13). The problem with Tiktok, hauls and consumerism - Shift London. Shift London. https://www.shiftlondon.org/features/the-problem-with-fashion-tiktok-hauls-and-consumerist-culture/

    24. Nistanto, R. K. (2021, February 23). Berapa Lama Orang Indonesia Akses Internet dan Medsos Setiap Hari? Halaman all - Kompas.com. KOMPAS.com; Kompas.com. https://tekno. kompas.com/read/2021/02/23/11320087/berapa-lama-orang-indonesia-akses-internet-dan-medsos-setiap-hari-?page=all#:~:text=Dari%20total%20populasi%20Indonesia% 20sebanyak,3%20persen%20dibandingkan%20tahun%20lalu

    25. Rahmaningtyas, A., Hartono, S., & Suryantini, A. (2017). Factors Affecting Indonesia’s Consumer Purchasing Intention and Decision Local Food by Online. Agro Ekonomi, 28(2), 189. https://doi.org/10.22146/jae.26129

    26. Ratna Roostika, R., & Rafi, H. (n.d.). E-Wom Source Credibility, Risk Perceptions, Argument Quality, Information Usefulness, and Information Adoption on The Use of Online Travel Agent Services in Indonesia. https://dspace.uii.ac.id/bitstream/handle/123456 789/17222/08.%20naskah%20publikasi.pdf?sequence=12&isAllowed=y

    27. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.

    28. Sánchez Torres, J. A., Arroyo-Cañada, F.-J., Solé-Moro, M.-L., & Argila-Irurita, A. (2018). Impact of gender on the acceptance of electronic word-of-mouth (eWOM) information in Spain. Contaduría Y Administración, 63(4), 61. https://doi.org/10.22201/fca. 24488410e.2018.1428

    29. Schiffer, J. (2019, November). Do fashion brands need TikTok? Vogue Business; Vogue Business. https://www.voguebusiness.com/companies/tiktok-social-networking-video-app-gen-z-mac-ralph-lauren

    30. Smith, S. (2021, November 29). How TikTok is influencing fashion retail - TheIndustry.fashion. TheIndustry.fashion. https://www.theindustry.fashion/how-tiktok-is-influencing-fashi on-retail/

    31. Steffes, E. M., & Burgee, L. E. (2009). Social ties and online word of mouth. Internet Research, 19(1), 42–59. https://doi.org/10.1108/10662240910927812

    32. Teng, S., Wei Khong, K., Wei Goh, W., & Yee Loong Chong, A. (2014). Examining the antecedents of persuasive eWOM messages in social media. Online Information Review, 38(6), 746–768. https://doi.org/10.1108/oir-04-2014-0089

    33. Triandis. (1971). Attitude and attitude change. Wiley.

    34. Verhagen, T., Nauta, A., & Feldberg, F. (2013). Negative online word-of-mouth: Behavioral indicator or emotional release? Computers in Human Behavior, 29(4), 1430–1440. https://doi.org/10.1016/j.chb.2013.01.043

    35. Xu, X., & Yao, Z. (2015). Understanding the role of argument quality in the adoption of online reviews. Online Information Review, 39(7), 885–902. https://doi.org/10.1108/oir-05-2015-0149

    36. Yoo, B., Donthu, N., & Lee, S. (2000). An Examination of Selected Marketing Mix Elements and Brand Equity. Journal of the Academy of Marketing Science, 28(2), 195–211. https://doi.org/10.1177/0092070300282002.