Key points are not available for this paper at this time.
Biodiversity, from genes to entire ecosystems, is crucial for a healthy planet. However, human activities, including business practices, are causing rapid biodiversity loss. This study focuses on selecting and integrating biodiversity protection practices into the supply chain, offering a chance to make positive changes for the environment and future generations. A new hybrid grey multi-criteria decision-making (MCDM) model is proposed in this paper, which combines the grey Best–Worst Method (BWM) for obtaining criteria weights and the grey Axial Distance-based Aggregated Measurement (ADAM) method for ranking alternatives (practices). The applicability of the proposed model for solving the defined problem was demonstrated by ranking nine practices according to seven criteria. The most effective supply chain management practices in the context of biodiversity conservation were supply chain policies (with a score of 0.044), biodiversity goal setting, monitoring, reporting, and transparency (0.039), and education and awareness raising (0.037). These practices are the best because they combine clear frameworks, measurable goals, and long-term cultural change for effective biodiversity conservation. The lowest ranked practice is compliance with legislation (0.006) since it represents a baseline, reactive approach rather than a proactive or innovative strategy for biodiversity conservation. This study provides a comprehensive framework and hybrid MCDM model that enhances theoretical knowledge and can serve as a basis for developing a practical tool for integrating, assessing, and prioritizing biodiversity-focused practices in supply chains. The main novelties of this paper are the extension of the ADAM method in the grey environment, the development of a new hybrid MCDM model that combines the grey BWM and grey ADAM method, the identification of biodiversity-oriented business strategies in supply chains and the criteria for their evaluation, and a framework for practice evaluation and selection.
Krstić et al. (Tue,) studied this question.