University of Lincoln
Browse
1/1
4 files

Smart mirror fashion technology for the retail chain transformation

Download all (3.2 MB)
Version 2 2024-03-13, 16:18
Version 1 2023-12-20, 12:04
journal contribution
posted on 2024-03-13, 16:18 authored by Ogunjimi Ayotunde, Mizanur RahmanMizanur Rahman, Nazrul Islam, Rajibul Hasan

As the digitalisation of businesses continues to change customers’ purchasing habits, brick-and-mortar retail SMEs (Small and Medium Enterprises) are confronted with unprecedented challenges. The proliferation of e-commerce and digital businesses is not only changing the rules of business but disrupting them by introducing new possibilities, especially with the integration of new technology. Studies that have attempted to measure technology-based service quality in retail settings are limited to online service experiences, creating a significant gap in the literature. The primary purpose of this paper is to explore how the service quality of brick-and-mortar clothing retail chains can be improved using innovative technology such as smart mirror fashion technology (SMFT), something academic research has not yet specifically addressed. This study used a qualitative approach with Soft System Methodology (SSM), based upon interviews triangulated with observations and field notes. It focused on the top five UK clothing retail chains, measured by market capitalisation. We found that the quality of service received is currently perceived as low when compared to customers’ expectations; however, use of technology enhanced service quality and influenced customer satisfaction. There was a positive relationship between service quality, customer satisfaction and the use of SMFT. The contribution of this study lies in the development of a new framework that integrates SMFT with traditional in-store transaction processes, resulting in improvements in service delivery and managerial practices of the offline clothing retail service providers. The study concludes that embracing SMFT can help provide high-quality service, creating value for customers.

History

School affiliated with

  • Lincoln Business School (Research Outputs)

Publication Title

Technological Forecasting & Social Change

Volume

173

Pages/Article Number

121118

Publisher

Elsevier

ISSN

0040-1625

Date Submitted

2021-10-29

Date Accepted

2021-08-12

Date of First Publication

2021-09-06

Date of Final Publication

2021-12-01

Date Document First Uploaded

2021-10-29

ePrints ID

46715

Usage metrics

    University of Lincoln (Research Outputs)

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC