Empirical Analysis of Industry 4.0 Determinants in Moroccan Supply Chains: A Neural Network Approach

Abstract

This paper examines the factors shaping the adoption of Industry 4.0 (I4.0) technologies in Moroccan supply chains (SCs), with a focus on how digitalization, management practices, strategic planning, and financial resources contribute to SC optimization. The study aims to explore how these elements enhance resilience and competitiveness in an increasingly complex economic environment. Drawing on data from a structured survey of 151 Moroccan firms operating across various industries, the research employs a regression analysis based on multilayer neural network models to evaluate the relative importance of these drivers. The findings reveal that digitalization exerts the most substantial influence on supply chain optimization, accounting for nearly a half (47.78%) of the total effect. This is followed by management practices (31.74%), strategic alignment (14.26%), and financing (6.22%). These results highlight the critical role of digital transformation (DT) and effective management in fostering SC efficiency and competitiveness. By emphasizing the integration of advanced technologies and strategic approaches, this study provides practical insights for businesses seeking to enhance operational performance and adaptability. In focusing on the Moroccan context, this research offers a novel contribution by shedding light on the unique challenges and opportunities in developing economies. The use of neural network regression adds methodological depth, enabling a precise assessment of key factors. The findings provide actionable recommendations for companies aiming to align their investments and strategies with I4.0 priorities, ultimately contributing to economic growth and SC excellence.