A decision-making architecture for sustainability: Optimization of human resource management with triple bottom line in the extractive sector using a multi-objective approach

Abstract

Purpose This research develops a mathematical decision-making model to optimise sustainable human resource management (HRM) performance based on the Triple Bottom Line (TBL), using the Iranian oil industry as an empirical case within resource-intensive sectors. Design/methodology/approach Drawing on stakeholder theory, 22 validated HRM practices across five dimensions were operationalised at five implementation modes. Costs and contributions to social, economic and environmental outcomes were assessed via expert interviews and Fuzzy Analytic Hierarchy Process (Fuzzy AHP). The practical multi-objective problem – how to allocate limited budgets while reconciling conflicting stakeholder expectations – has not previously been solved using HRM practices as primary decision variables. We employ the Normalised Weighted Sum Method with fuzzy AHP weights and test robustness through sensitivity analyses. Findings Social thresholds are the most binding constraint, highlighting employee trust and well-being as central to sustainable performance. The model gives managers actionable guidance for budget allocation, investment prioritisation and system design. Economic performance remains stable across weighting scenarios, providing strategic flexibility. Originality/value This study fills a gap by being the first to encode stakeholder conflicts directly into HRM practice-based optimisation. It offers a practical decision-support tool that simultaneously delivers economic, social and environmental outcomes. Limitations include the single-industry case, cross-sectional data and deterministic parameters; future research should test transferability and incorporate uncertainties.