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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Sook Fern Yeo & Cheng Ling Tan & Ajay Kumar & Kim Hua Tan & Jee Kit Wong, 2022. "Investigating the impact of AI-powered technologies on Instagrammers’ purchase decisions in digitalization era–A study of the fashion and apparel industry," Post-Print hal-03628402, HAL.
    • Handle: RePEc:hal:journl:hal-03628402
    DOI: 10.1016/j.techfore.2022.121551
    Note: View the original document on HAL open archive server: https://hal.science/hal-03628402v1
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    2. Bigne, Enrique & Ruiz, Carla & Curras-Perez, Rafael, 2024. "How consumers process online review types in familiar versus unfamiliar destinations. A self-reported and neuroscientific study," Technological Forecasting and Social Change, Elsevier, vol. 199(C).
    3. Zhou, Zhongsheng & Li, Zhuo & Du, Shanzhong & Cao, June, 2024. "Robot adoption and enterprise R&D manipulation: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    4. Nofrizal, & Juju, Undang & Sucherly, & N, Arizal & Waldelmi, Idel & Aznuriyandi,, 2023. "Changes and determinants of consumer shopping behavior in E-commerce and social media product Muslimah," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    5. Goh, Choon Fu & Long, Chiau Ming & Humaira Fedelis, Nur Aisyah & Hamdan, Halimaton & Chuah, Soo Cheng & Yeo, Sook Fern & Tan, Cheng Ling & Wong, Tin Wui, 2023. "Critical insights of nano-based pharmaceutical, cosmeceutical and nutraceutical products: Empirical evidence from the consumption values perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    6. Akbari, Morteza & Foroudi, Pantea & Zaman Fashami, Rahime & Mahavarpour, Nasrin & Khodayari, Maryam, 2022. "Let us talk about something: The evolution of e-WOM from the past to the future," Journal of Business Research, Elsevier, vol. 149(C), pages 663-689.
    7. El Bhilat, El Mehdi & El Jaouhari, Asmae & Hamidi, L. Saadia, 2024. "Assessing the influence of artificial intelligence on agri-food supply chain performance: the mediating effect of distribution network efficiency," Technological Forecasting and Social Change, Elsevier, vol. 200(C).

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