Equipment planning within global construction operations has become increasingly complex due to the expansion of geographically dispersed projects, multinational subcontractor ecosystems, fluctuating operational conditions, and rising capital intensity associated with heavy equipment fleets. Traditionally, organizations have approached fleet governance through either centralized or distributed planning structures. Centralized systems prioritize standardization, capital efficiency, and strategic oversight, while distributed systems emphasize local responsiveness, operational agility, and site-level autonomy. However, practical industrial experience demonstrates that neither extreme fully satisfies the operational demands of modern global construction environments. This paper examines the comparative strengths and limitations of centralized and distributed equipment-planning models through a systems-management perspective focused on operational scalability, decision architecture, and organizational adaptability. The study argues that the conventional centralized-versus-distributed debate is fundamentally incomplete because effective global construction operations require differentiated authority structures rather than absolute governance models. Particular attention is given to capital-allocation efficiency, local operational responsiveness, organizational learning systems, leadership development, performance-governance structures, transparency mechanisms, and exception-management frameworks. The paper further analyzes hybrid comparative models where authority is assigned according to decision type rather than according to organizational hierarchy alone. Drawing from practical large-scale construction environments, the analysis concludes that sustainable equipment planning depends on balancing centralized strategic discipline with distributed tactical responsiveness through integrated governance systems capable of maintaining both organizational consistency and operational adaptability simultaneously.
TAHA GUNDOGAR (Mon,) studied this question.