AI-ENABLED ONLINE SHOPPING FEATURES AND THEIR EFFECTS ON BRAND LOYALTY AND PURCHASE INTENTION IN FASHION RETAIL

Autor/innen

  • Haseeb Anwar Independent Researcher, United Kingdom
  • Muhammad Shoaib Independent Researcher, United Kingdom
  • Saud Ahmed Course director MSc Marketing, Ulster University, United Kingdom
  • Amanat Ullah Deputy course director, MSc Marketing, Ulster University, United Kingdom
  • Raja Muneeb Anwar Independent Researcher, United Kingdom
  • Faisal Majeed Dr., Faculty of Business, Ulster University, United Kingdom

DOI:

https://doi.org/10.46827/ejefr.v10i2.2144

Schlagwörter:

Artificial Intelligence (AI), AI-enabled online shopping features, brand loyalty, purchase intention, fashion retail

Abstract

The growing use of artificial intelligence (AI) in online fashion retail has shifted its role from a purely functional technology to a strategic tool for building consumer–brand relationships; however, limited empirical research explains how AI-enabled online shopping features influence brand loyalty and purchase intention. Addressing this gap, this study investigates the effects of AI-enabled online shopping features on purchase intention, with brand loyalty as a mediating variable in the UK fashion retail context. Drawing on the Technology Acceptance Model and brand loyalty theory, AI-enabled features are conceptualised in terms of perceived usefulness. Using a quantitative, cross-sectional survey of UK consumers with prior experience purchasing from H&M’s online platform, the proposed relationships were tested through regression-based mediation analysis. The findings indicate that AI-enabled online shopping features perceived as useful have a significant positive effect on both brand loyalty and purchase intention, and that brand loyalty partially mediates the relationship between AI-enabled features and purchase intention. These results suggest that AI-driven personalisation and usefulness enhance not only functional shopping efficiency but also emotional and behavioural attachment to brands. By integrating brand loyalty into a TAM-based framework, this study extends technology adoption research and highlights the strategic importance of AI as a long-term brand-building mechanism in digital fashion retail.

 

JEL: M15; M31; L81; D91

 

Article visualizations:

Hit counter

Autor/innen-Biografien

  • Haseeb Anwar, Independent Researcher, United Kingdom

    Haseeb Anwar is a postgraduate researcher with an academic background in International Business and Marketing. His research interests focus on digital consumer behaviour, AI-enabled retail technologies, brand engagement, and purchase intention in online environments. He is particularly interested in examining how artificial intelligence and data-driven personalisation strategies influence consumer decision-making and brand loyalty in competitive digital markets.

  • Muhammad Shoaib, Independent Researcher, United Kingdom

    Muhammad Shoaib is a postgraduate researcher specialising in Human Resource Management. He holds an MSc in Human Resource Management from Ulster University, United Kingdom. His research interests include employee behaviour, organisational commitment, workforce sustainability, and the strategic role of HR practices in improving employee retention and organisational performance within service-oriented and emerging economy contexts.

  • Saud Ahmed, Course director MSc Marketing, Ulster University, United Kingdom
    Saud Ahmed is Course Director and Lecturer in Marketing at QA Higher Education in partnership with Ulster University, United Kingdom. He has extensive experience delivering marketing and management modules at undergraduate and postgraduate levels. His academic interests focus on digital marketing strategy, AI in business applications, consumer behaviour, and technology-driven transform
  • Amanat Ullah, Deputy course director, MSc Marketing, Ulster University, United Kingdom

    Amanat Ullah is Deputy Course Director and Lecturer in Marketing at QA Higher Education in partnership with Ulster University, United Kingdom. He has over a decade of academic and professional experience in marketing, digital strategy, and executive education. His research and professional interests include artificial intelligence in business, digital marketing analytics, consumer engagement, and innovation in higher education and corporate training.

  • Raja Muneeb Anwar, Independent Researcher, United Kingdom

    Raja Muneeb Anwar is an independent researcher with interests in digital business transformation, data-driven strategy, and emerging technologies in retail and service industries. His research focuses on consumer experience, online engagement mechanisms, and the strategic implications of AI-enabled systems in modern business environments.

  • Faisal Majeed, Dr., Faculty of Business, Ulster University, United Kingdom

    Faisal Majeed is a senior academic and researcher specialising in international business strategy, entrepreneurship, and innovation management. He is affiliated with Ulster University, London Campus, where he supervises postgraduate and doctoral research in international business, digital transformation, and strategic leadership. His research interests include SME development, sustainability, innovation management, and cross-border entrepreneurship in emerging and developed economies.

Literaturhinweise

Ameen, N., Tarhini, A., Reppel, A. & Anand, A. (2021). Customer experiences in the age of artificial intelligence, Journal of Retailing and Consumer Services, 58. https://doi.org/10.1016/j.chb.2020.106548

Bag, S., Wood, L.C., Mangla, S.K. & Luthra, S. (2021). Big data analytics as an operational excellence approach to enhance sustainable supply chain performance, Resources, Conservation and Recycling, 153. https://doi.org/10.1016/j.resconrec.2019.104559

Batool, S. & Mou, Y. (2024). Artificial intelligence in online retail: Consumer adoption and behavioural outcomes, Journal of Retailing and Consumer Services, 74. https://doi.org/10.1016/j.dim.2023.100060

Bialkova, S. & Barr, J. (2022). The role of virtual try-on technologies in online fashion retail, Journal of Fashion Marketing and Management, 26(3), pp. 482–498.

Blázquez, M. (2014). Fashion shopping in multichannel retail: The role of technology, International Journal of Electronic Commerce, 18(4), pp. 97–116. https://doi.org/10.2753/JEC1086-4415180404

Cheng, Y. and Jiang, H. (2021). Customer–brand relationship in AI-enabled services, Journal of Business Research, 132, pp. 438–449. https://doi.org/10.1108/JPBM-05-2020-2907

Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13(3), pp. 319–340. https://doi.org/10.2307/249008

Dillman, D.A., Smyth, J.D. & Christian, L.M. (2014). Internet, phone, mail, and mixed-mode surveys: The tailored design method. 4th edn. Hoboken: Wiley. Retrieved from https://psycnet.apa.org/record/2014-34233-000

Dokcen, C., Obedgiu, V. and Nkurunziza, G. (2021). Technology adoption and purchase intention in online retail, Journal of Business Research, 124, pp. 296–305.

Felzmann, H., Villaronga, E.F., Lutz, C. & Tamò-Larrieux, A. (2020). Transparency you can trust: Transparency requirements for artificial intelligence, Ethics and Information Technology, 22(2), pp. 91–106. https://doi.org/10.1177/2053951719860542

Gao, Q. & Liu, X. (2022). Artificial intelligence-enabled personalization and brand trust, Information Technology & People, 35(7), pp. 2256–2277.

Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2019). Multivariate data analysis. 8th edn. Harlow: Pearson Education. Retrieved from https://books.google.ro/books/about/Multivariate_Data_Analysis.html?id=PONXEAAAQBAJ&redir_esc=y

Haleem, A., Javaid, M., Qadri, M.A. & Suman, R. (2022). Understanding the role of digital technologies in sustainable retail, Sustainable Production and Consumption, 30, pp. 353–365.

Lu, L.C., Chang, W.P. & Chang, H.H. (2014). Consumer attitudes toward blogger recommendations and purchase intention, Internet Research, 24(1), pp. 2–22. https://doi.org/10.1016/j.chb.2014.02.007

Molinillo, S., Japutra, A., Nguyen, B. & Chen, C.H.S. (2017). Responsible brands vs active brands, Journal of Business Research, 70, pp. 38–45. https://doi.org/10.1108/MIP-04-2016-0064

Nikhashemi, S.R., Tarofder, A.K., Gaur, S.S. & Haque, A. (2020). The effect of customer experience on brand loyalty, Journal of Retailing and Consumer Services, 54, 102032.

Oliver, R.L. (1999). Whence consumer loyalty?, Journal of Marketing, 63(Special Issue), pp. 33–44. https://www.jstor.org/stable/1252099

Rather, R.A., Tehseen, S., Parrey, S.H. & Sajjad, A. (2021). Customer brand engagement and loyalty, Journal of Retailing and Consumer Services, 61.

Saunders, M., Lewis, P. & Thornhill, A. (2019). Research methods for business students. 8th edn. Harlow: Pearson Education. Retrieved from https://www.pearson.com/se/Nordics-Higher-Education/subject-catalogue/business-and-management/Research-methods-for-business-students-8e-saunders.html

Shankar, V., Kalyanam, K., Setia, P. et al. (2021). How technology is changing retail, Journal of Retailing, 97(1), pp. 13–27. Retrieved from https://ideas.repec.org/a/eee/jouret/v97y2021i1p13-27.html

Sohn, H.K. & Kim, M. (2020). Effects of AI-based recommendation systems on purchase intention, Journal of Retailing and Consumer Services, 54.

Venkatesh, V., Morris, M.G., Davis, G.B. & Davis, F.D. (2003). User acceptance of information technology, MIS Quarterly, 27(3), pp. 425–478. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3375136

Wang, Y., Cao, Y. & Ameen, N. (2022). Artificial intelligence adoption in online retail, Information Technology & People, 35(7), pp. 2230–2255.

Yau, A., Saad, M. & Chong, A.Y.L. (2021). Artificial intelligence service quality and consumer engagement, Journal of Retailing and Consumer Services, 63.

Yen, C. & Chiang, M. (2020). Trust in artificial intelligence and purchase intention, Journal of Retailing and Consumer Services, 54.

Yu, T. (2021). Consumer response to AI-powered retail technologies, Technological Forecasting and Social Change, 169.

Downloads

Veröffentlicht

2026-03-02

Ausgabe

Bd. 10 Nr. 2 (2026)

Rubrik

Articles