Biodiversity Protection Practices in Supply Chain Management: A Novel Hybrid Grey Best–Worst Method/Axial Distance-Based Aggregated Measurement Multi-Criteria Decision-Making Model

Summary

This paper presents a novel hybrid grey multi-criteria decision-making model that combines the grey Best–Worst Method and grey Axial Distance-based Aggregated Measurement method to evaluate and rank biodiversity protection practices in supply chain management. The application demonstrated that proactive, framework-based practices such as supply chain policies and goal-setting with transparency substantially outperform reactive compliance-only approaches for effective biodiversity conservation. The framework is intended to serve as both a theoretical contribution and a practical tool for organisations seeking to prioritise and integrate biodiversity-focused strategies into supply chains.

UK applicability

The MCDM framework and the identified hierarchy of effective practices (proactive strategy over reactive compliance) are applicable to UK supply chain contexts, where businesses increasingly face regulatory and market pressure to demonstrate genuine biodiversity commitment. The findings support the development of UK-specific biodiversity supply chain standards and governance frameworks that emphasise transparency, goal-setting, and cultural change over minimum legal compliance.

Key measures

Relative weightings and rankings of nine supply chain practices according to seven biodiversity-related criteria; numerical scores for top-ranked practices (e.g. supply chain policies: 0.044; goal setting/monitoring/reporting: 0.039; education/awareness: 0.037; compliance with legislation: 0.006)

Outcomes reported

The study ranked nine biodiversity protection practices across seven criteria using a novel hybrid grey multi-criteria decision-making model. Supply chain policies, biodiversity goal setting with monitoring and transparency, and education and awareness were identified as the most effective practices for biodiversity conservation in supply chains.

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