The Barriers to the Adoption of Emerging Technologies in the Apparel Manufacturing Industry: A Dynamic Framework Analysis Focused on India

Despite the transformative potential of advanced technologies—such as Artificial Intelligence (AI), soft robotics, and mandated Digital Product Passports (DPPs)—the Indian apparel manufacturing sector exhibits a critical lag in achieving comprehensive, integrated digitalization. While end-to-end digital transformation is projected to shorten the production timeline by up to 40%, implementation is hampered by systemic, multi-dimensional barriers. Analysis reveals these constraints include acute data fragmentation coupled with poor IT infrastructure; severe financial stress resulting from high implementation costs with uncertain Return on Investment (ROI); and the persistent technical difficulty of automating the handling of limp, deformable fabrics. Furthermore, India-specific challenges like cyber security risk are dominant cause barriers to Industry 4.0 adoption. This report addresses this pervasive adoption gap by analyzing constraints across four integrated dimensions: Technological, Organizational, Environmental, and Dynamics (post-adoption processes). Existing models, notably the Technology-Organization-Environment (TOE) framework, are deemed insufficient as they fail to account for the unique material-specific challenges and provide limited consideration of dynamic adoption processes. This research introduces the Dynamic Apparel Technology Adoption and Supply Chain Resilience (DATAR) Framework to model the actual assimilation process necessary for industry modernization and strategic resilience.

Adoption, Emerging, Technologies

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