Big data analytics and sustainable textile manufacturing

Abstract

Purpose: This article discusses issues associated with the application Big Data Analytics for decision-making about the introduction of new technologies in the textile industry in the developing world. Methodology:We use the LMX theoretical framework to consider the nature of the relationships between owners and followers to identify the potential issues that affect decisionmaking. However, decisions to adopt such environmentally friendly biotechnologies are hampered by the lack of awareness among owners, intergenerational conflict and cultural impediments. Findings:The article found that the limited use of this valuable technological resource is linked to several factors, mainly cultural, generational and educational. The article exposes two key new technologies that could help the industry reduce its carbon footprint.Originality/Value: The study suggests more awareness raising among plant owners and greater empowerment of new generations in decision-making in the industry. This study, therefore, bears significant implications for environmental sustainability in the developing world where the textile industry is one of the major polluting industries affecting water quality and human health.

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