Sook Fern Yeo
Investigating the Impact of AI-powered Technologies on Instagrammers' Purchase Decisions in Digitalization Era: A Study of the Fashion and Apparel Industry
Yeo, Sook Fern; Tan, Cheng Ling; Kumar, Ajay; Tan, Kim Hua; Wong, Jee Kit
Authors
Cheng Ling Tan
Ajay Kumar
Professor Kim Tan kim.tan@nottingham.ac.uk
PROFESSOR OF OPERATIONS AND INNOVATION MANAGEMENT
Jee Kit Wong
Abstract
Over the last couple of decades, technological advancements have accelerated exponentially, especially in the realm of online social networking networks. The artificial intelligence (AI)-powered digital technologies applications continue to emerge to enhance and improve novel ways of communication on social media platforms, particularly Instagram. Indeed, this has caused a change in the behavioral and social customer journey, where customers need to embrace a digital experience adoption. The AI applications primarily aim to study the shoppers browsing trend to draw new clients and expand businesses. Even the fashion industry has tapped into Instagram's business benefits in this fast-paced and competitive industry. With this quick and compelling way to capture shoppers’ attention towards fashion products, the purchase decision may differ between e-shoppers and conventional shoppers. AI seems to be extremely promising and has the potential to be a game changer for Instagram users, advertisers, and influencers. This study applies the Engel-Kollat-Blackwell (EKB) theory to investigate the effects of AI-based digital technology experiences on Instagrammers’ fashion apparel purchase decisions - perceived eWOM, perceived emotional value, perceived quality, perceived risk and perceived price. Based on data collected from Instagram users, the framework of this study was evaluated using structural equation modelling (SEM). Semi-structured in-depth interviews were also conducted as part of the research to get a more in-depth understanding of the profiles and behaviors of Instagram users. Our findings from both methodologies confirm that perceived emotional value, perceived quality, and perceived eWOM revealed a statistically significant and positive influence on Instagrammers’ purchase decisions for fashion apparel. Meanwhile, the importance performance matrix analysis (IPMA) identified perceived emotional value as the most important factor for Instagrammers, but the highest performance was perceived quality. This research has important implications for Malaysian online retailers and shoppers to adapt to the fast-changing digital transformation. Assuredly, this study makes a noteworthy contribution to attitudinal research on social media commerce within the fashion industry.
Citation
Yeo, S. F., Tan, C. L., Kumar, A., Tan, K. H., & Wong, J. K. (2022). Investigating the Impact of AI-powered Technologies on Instagrammers' Purchase Decisions in Digitalization Era: A Study of the Fashion and Apparel Industry. Technological Forecasting and Social Change, 177, Article 121551. https://doi.org/10.1016/j.techfore.2022.121551
Journal Article Type | Article |
---|---|
Acceptance Date | Jan 29, 2022 |
Online Publication Date | Feb 3, 2022 |
Publication Date | 2022-04 |
Deposit Date | Feb 17, 2022 |
Publicly Available Date | Aug 4, 2023 |
Journal | Technological Forecasting and Social Change |
Print ISSN | 0040-1625 |
Electronic ISSN | 0040-1625 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 177 |
Article Number | 121551 |
DOI | https://doi.org/10.1016/j.techfore.2022.121551 |
Keywords | AI; Instagram; Purchase decision; Fashion; Digital transformation |
Public URL | https://nottingham-repository.worktribe.com/output/7472039 |
Publisher URL | https://www.sciencedirect.com/science/article/pii/S004016252200083X?via%3Dihub |
Files
Investigating The Impact Of AI-powered Technologies On Instagrammers' Purchase Decisions In Digitalization Era - A Study Of The Fashion And Apparel Industry
(1.2 Mb)
PDF
You might also like
Advance selling and service cancelation when consumers are overconfident
(2024)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search