Factors Influencing the Implementation of Industry 4.0 for Sustainability in Manufacturing.

Digital transformation leveraging Industry 4.0 is referred to as a strategic solution to handle the challenges given by growing competition and unpredictable customer demands in today's highly competitive business environment. However, transitioning to Industry 4.0 for sustainable manufacturing would require a thorough understanding of key implementation factors. The objective of this paper is to examine and validate the interrelationships among the factors influencing the implementation of Industry 4.0 for achieving sustainability in manufacturing. To accomplish this objective, the paper used an integrated methodological approach (i.e., TISM and PLS-SEM) to model the factors influencing Industry 4.0 implementation. The total interpretive structural equation modeling (TISM) technique was used to develop the hierarchical structural model in order to investigate the interrelationships among the Industry 4.0 implementation factors. The partial least squares structural equation modeling (PLS-SEM) approach was used to validate the interrelationships identified through TISM. Initially, implementation factors of Industry 4.0 for sustainable manufacturing have been identified. Following the identification of the factors, the opinion of experts was sought through a questionnaire-based survey to finalize them. The hypotheses were analyzed to test the significance of interrelationships among different constructs of Industry 4.0 factors. The findings indicate that factors like environmental regulations for sustainability, adequate labor laws for workforce working in the digital environment, continuous support and commitment from top management, effective restructuring of the organization, adequate support from different stakeholders, and strategic roadmap for digital transformation and branding of green image have the maximum influence on Industry 4.0 implementation for sustainability. Furthermore, the obtained results were in accordance when validated using PLS-SEM. This research will assist practitioners in gaining a thorough understanding of the significance of various implementation factors and their interrelationships. [ABSTRACT FROM AUTHOR]