Factors affecting Industry 4.0 adoption – A hybrid SEM-ANN approach

Abstract

Industry 4.0 is a technology-driven digital transformation to enable data-driven decision-making based on real-time data to enhance the competitiveness of traditional manufacturing. Moving forward, adopting Industry 4.0 is an evident requirement for manufacturers to remain competitive. Currently, in the early stages of adoption in most industries and countries, there is an evident lack of foundational Industry 4.0 knowledge among decision-makers. There are few studies on the adoption of Industry 4.0; however, they focus on specific domains like cloud computing, virtual reality, IoT, etc., and are primarily set in developed countries. This research proposes a multi-stage hybrid analytic approach whereby the research model was tested using Structural Equation Modelling (SEM). The SEM results were used as inputs for the Artificial Neural Networks (ANN) to determine significant predictors for the adoption of Industry 4.0 in Indian manufacturing industries. A comprehensive sample of 350 responses from various Indian manufacturers was collected and analyzed. Results revealed that the factors viz. Software Infrastructure (SI), System Flexibility (SF), Operational Accuracy (OA), and the Technical Capabilities (TC) play a dominant role in the successful adoption intentions of Industry 4.0 in India. Manufacturers from India and other emerging economies will benefit from the findings of this study by concentrating and improving on the dominant adoption factors of Industry 4.0. Concluding, we discuss the study’s results and derive lessons learned for stakeholders, including managers, consultants, policymakers, and regulatory authorities.