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How big data analytics will transform the future of fashion retailing

In: Handbook of Big Data Research Methods

Author

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  • Niloofar Ahmadzadeh Kandi

Abstract

The primary purpose of this book chapter is to investigate the applications and benefits of big data analytics in fashion retailing to discover the opportunities created by big data in this industry. Fashion has a substantial share of data production, and big data in the fashion industry has created countless challenges and opportunities. Today, the analysis of data obtained from various sources as a critical factor to smart fashion retailing can lead to strategies for better decision-making under conditions and environments of uncertainty. Machine learning algorithms can accelerate the analysis of big data by finding patterns and uncovering trends. By categorizing and recognizing patterns, it can turn incoming data into insights useful for business process operations. This study is based on various secondary sources, which are inherently descriptive and qualitative. This section of the book examines the potentials of big data and machine learning in the fashion retail industry. In the end, it discusses possible ways that big data can be applied in fashion retailing in order to gain insights and identify customer behavior patterns through big data analytics and AI applications and the ethics-related issues in retailing.

Suggested Citation

  • Niloofar Ahmadzadeh Kandi, 2023. "How big data analytics will transform the future of fashion retailing," Chapters, in: Shahriar Akter & Samuel Fosso Wamba (ed.), Handbook of Big Data Research Methods, chapter 5, pages 72-85, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:20820_5
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