Modeling the Decision Structure of Contractor Selection in Medium-Scale Mining: An Analytic Hierarchy Process Approach

The increasing outsourcing of critical activities in the mining industry has transformed contractor selection into a strategic decision that is closely associated with operational risk management and the integration of critical capabilities within highly interdependent production systems. Despite its practical importance, the literature has devoted limited attention to understanding how the criteria used in real-world contractor selection processes are structured and prioritized. This study addresses this gap by applying the Analytic Hierarchy Process (AHP) to reconstruct and analyze the decision structure employed by medium-scale mining companies during contractor selection, rather than to rank specific companies. A hierarchical structure was developed and implemented in Expert Choice software (v.11) based on the expert judgments of 24 mining professionals from the Coquimbo Region, Chile. Matrix consistency was verified using the consistency ratio (CR), and model robustness was evaluated through performance, gradient, and head-to-head sensitivity analysis. The model results indicated that Safety (53.1%) was the dominant criterion, followed by Personnel (22.3%), whereas Costs received a substantially lower weight (5.5%). At the subcriteria level, Accident rate emerged as the most influential factor, followed by Continuous personnel training and Work quality. The sensitivity analyses demonstrated that these priorities remained stable under different weighting scenarios, confirming a robust decision structure. Rather than producing a ranking of contractor companies, the proposed framework reconstructs the internal decision logic of mining companies and provides a structural perspective to support strategic decision-making, operational risk management, and resource management in highly outsourced mining systems.