Title: The application of big data in fashion retailing: a narrative review

Authors: Dag Øivind Madsen; Emmanuel Sirimal Silva; Hossein Hassani

Addresses: School of Business, University of South-Eastern Norway, Bredalsveien 11, 3511 Hønefoss, Norway ' Centre for Fashion Business and Innovation Research, Fashion Business School, London College of Fashion, University of the Arts London, 272 High Holborn, Holborn, WC1V 7EY, UK ' Research Institute of Energy Management and Planning, University of Tehran, Tehran, Iran

Abstract: Big data continues to disrupt the fashion retail industry and has revolutionised traditional business models. Today, both leading fashion brands and new start-ups are using big data analytics to improve business operations and maximise profitability. The current paper aims to take stock of the literature on big data in fashion and concisely summarise the fashion industry's current position. We uncover five main reasons that are driving the utilisation and application of big data analytics in the fashion industry. These are: 1) trend prediction; 2) waste reduction; 3) consumer experience, consumer engagement and marketing; 4) better quality control and the need for a world with fewer counterfeits; 5) shortening supply chains. We also identify key challenges which must be overcome as the most fashionable industry now seeks to model the fashion market and consumer behaviour with big data.

Keywords: big data; fashion; fashion industry; retail; trend forecast; consumer experience; review.

DOI: 10.1504/IJMCP.2020.112160

International Journal of Management Concepts and Philosophy, 2020 Vol.13 No.4, pp.247 - 274

Received: 20 Jan 2020
Accepted: 26 Jul 2020

Published online: 21 Dec 2020 *

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