Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Sheriff, Naadia Ghalib; Bhattacharjee, Pragya; Kumar, B. R. Gagan Title A name given to the resource Predictive Analytics as a Catalyst for Disruption in the Fashion Ecosystem Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Smart Business and Education in the Age of VUCA and BANI;pp.243-272 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-7922-7.ch010" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-7922-7.ch010</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105027118569?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105027118569?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Sheriff N.G., Christ University, Bangalore, India; Bhattacharjee P., Christ University, Bangalore, India; Kumar B.R.G., Christ University, Bangalore, India Description An account of the resource The fashion industry is one of the most dynamic industries, with trends that change constantly being moulded by the changing preferences of consumers. In this dynamic environment it is crucial for companies to adjust to the current market demand, failing which companies might plunge into losses and even face shutdowns. Predictive analytics plays an important role in trend prediction, demand forecasting, optimizing the supply chain and inventory management, personalization, dynamic pricing, waste minimization and prediction of sustainable materials. This, of course, is not without challenges. Data privacy concerns and over reliance on AI algorithms leading to inhibition of human creativity stand out as the most concerning challenges that need to be addressed to ensure that predictive analytics is utilised to its fullest potential in the fashion industry. Predictive analytics and AI can ensure that the fashion industry is not just profitable but also consumer centric and sustainable in its operations thus ensuring long term growth and sustenance of businesses in this industry. 2026 by IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available CRC Press Relation A related resource ISBN: 979-833737924-1; 979-833737922-7; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online