Transforming mining equipment sustainable distribution 5.0 by adopting a human-centric focus: A perspective from a complex adaptive systems theory

The transition to sustainable Mining Equipment Distribution 5.0 requires the strategic integration of Supply Chain 5.0 (SC 5.0), human-centric design, and sustainable environmental management to enhance operational performance. This study examines how adopting a human-centric approach within SC 5.0, incorporating technologies such as Machine Learning (ML) and Artificial Intelligence (AI), can optimize the distribution of mining equipment while addressing environmental concerns and fostering sustainable practices. Grounded in Complex Adaptive Systems (CAS) theory, this research conceptualizes mining equipment distribution as a socio-technical system characterized by dynamic interactions among technological, human, and environmental agents. This study employs a hybrid methodology based on CAS theory, integrating the Interval-Valued Pythagorean Fuzzy Analytic Hierarchy Process (IVPF-AHP) and the Interval-Valued Pythagorean Fuzzy Decision-Making Trial and Evaluation Laboratory (IVPF-DEMATEL). This hybrid fuzzy multi-criteria decision-making (MCDM) framework enables the modeling of uncertainty, interdependencies, and feedback loops among decision criteria inherent in mining distribution networks, while supporting causal analysis and prioritization. IVPF-AHP is employed to rank critical enablers across human-centric design, sustainability, and Distribution 5.0 dimensions, whereas IVPF-DEMATEL identifies causal relationships and influence intensity among these enablers. This method captures participants' interdependencies and dynamic behaviors within the mining equipment distribution ecosystem and identifies critical elements that influence efficiency and sustainability. The findings underscore the importance of digitalization, automation, ML, AI, eco-friendly logistics, and adaptive, sustainable supply chain strategies in optimizing the distribution of mining equipment. The results further reveal strong causal linkages between human-centric capabilities and technological adoption, reinforcing the relevance of CAS theory within the Industry 5.0 paradigm in emerging economy contexts.