Influencers Marketing and its Impacts on Sustainable Fashion Consumption Among Generation Z

Authors

DOI:

https://doi.org/10.31181/jscda21202438

Keywords:

Influencer Marketing, Sustainable Fashion, Generation Z

Abstract

This research explores the intersection of influencer marketing and sustainable fashion purchase intentions among Generation Z in the UK and China, addressing critical challenges in the fashion industry, such as environmental impacts and overconsumption. The study introduces sustainable fashion as a potential solution and emphasizes the role of influencers in shaping Generation Z's attitudes and behaviours. The research delves into the environmental consequences of fast fashion and the emergence of sustainable fashion, providing a comprehensive understanding of the challenges and potential solutions within the industry. The focus then shifts to influencer marketing, recognizing its significance in the digital age, especially among Generation Z, who are considered crucial influencers in the fashion market.The study develops hypotheses that investigate the impact of influencers' experiences, similarity between influencers and Generation Z, and influencers' expertise in sustainable fashion on Generation Z's purchase intentions. Additionally, the research considers consumer attitudes, subjective norms influenced by influencers, and perceived behavioral control, including affordability concerns, as factors influencing sustainable fashion purchase intentions. Positioning Generation Z as a key demographic, the research aims to contribute valuable insights into the complex dynamics of influencer marketing, consumer attitudes, and sustainable fashion consumption. The formulated hypotheses offer a framework for understanding the nuanced relationships between influencers and Generation Z's decision-making processes in the context of sustainable fashion.

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Published

2024-02-07

How to Cite

Ge, J. (2024). Influencers Marketing and its Impacts on Sustainable Fashion Consumption Among Generation Z. Journal of Soft Computing and Decision Analytics, 2(1), 118-143. https://doi.org/10.31181/jscda21202438