Examining the Nexus between the Vs of Big Data and the Sustainable Challenges in the Textile Industry

Rosangela de Fátima Pereira Marquesone and Tereza Cristina Melo de Brito Carvalho
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Rosangela de Fátima Pereira Marquesone: Escola Politécnica, Universidade de São Paulo, São Paulo 05508-010, Brazil
Tereza Cristina Melo de Brito Carvalho: Escola Politécnica, Universidade de São Paulo, São Paulo 05508-010, Brazil

Sustainability, 2022, vol. 14, issue 8, 1-17

Abstract: Despite its substantial economic power, the textile industry currently faces environmental and social challenges, such as continuous extraction of natural resources, extensive water consumption and contamination, greenhouse gas emissions, increasing generation of waste, and inadequate working conditions. In this context, the literature indicates that Big Data contributes to solving these challenges, enabling the extraction of insights and the improvement of decision-making processes from the volume, variety and velocity of data. However, there is still a gap in the literature regarding the directions of how Big Data must be applied by an organization to achieve this goal. Therefore, this article aims to explore this gap, presenting an analysis regarding the nexus between Big Data and sustainability challenges of the textile industry. To this end, a set of 12 textile industry challenges were extracted from an assessment of 108 case studies. These challenges were categorized and contextualized according to Big Data dimensions, and a discussion of the applicability of Big Data to solving each challenge was presented. From this approach, this article contributes to the textile industry by presenting a categorization of sustainable challenges of the industry and also by providing directions regarding the resolution of such challenges from a data-driven perspective.

Keywords: big data; sustainability; textile industry; sustainable textile; sustainable fashion; data-driven decision making (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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