Investigating the impact of AI-powered technologies on Instagrammers’ purchase decisions in digitalization era–A study of the fashion and apparel industry

Sook Fern Yeo, Cheng Ling Tan, Ajay Kumar (akumar@em-lyon.com), Kim Hua Tan and Jee Kit Wong
Additional contact information
Sook Fern Yeo: MMU - Multimedia University, DIU - Daffodil International University [Dhaka]
Cheng Ling Tan: USM - Universiti Sains Malaysia, DIU - Daffodil International University [Dhaka]
Ajay Kumar: EM - EMLyon Business School
Kim Hua Tan: Nottingham University Business School [Nottingham]
Jee Kit Wong: MMU - Multimedia University

Post-Print from HAL

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.

Keywords: AI; Instagram; Purchase decision; fashion; digital transformation (search for similar items in EconPapers)
Date: 2022-04-01
Note: View the original document on HAL open archive server: https://hal.science/hal-03628402v1
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Published in Technological Forecasting and Social Change, 2022, 177, ⟨10.1016/j.techfore.2022.121551⟩

Downloads: (external link)
https://hal.science/hal-03628402v1/document (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03628402

DOI: 10.1016/j.techfore.2022.121551

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD (hal@ccsd.cnrs.fr).