A SISMW approach for weighting and modeling sustainable supplier selection criteria for biomass energy supply

Purpose To develop an integrated, biomass-specific framework for identifying, weighting and modeling sustainable supplier selection criteria (SSSC) in biomass energy supply chains. The study aims to address gaps in existing supplier-selection research by capturing economic, social and environmental dimensions and the unique technical and seasonal challenges of biomass feedstocks. Design/methodology/approach A three-step approach was used: (1) a meta-synthesis of 56 studies to extract candidate criteria; (2) a two-round fuzzy Delphi method (12 experts from industry, academia, consultancy and policy) to validate and reduce the list to 18 final criteria and (3) application of the SISMW method to simultaneously weight criteria and model their structural interrelationships. ISM and MICMAC analyses were employed to derive hierarchical levels and driving/dependence classifications. Feedstock-specific considerations (e.g. agricultural residues, forestry residues, energy crops, municipal and industrial organic wastes) were incorporated into the framework. Findings The study produced 18 validated SSSC across economic, social and environmental dimensions. Top-ranked and most influential criteria are: organization and management (EC5), corporate social responsibility (SO3), environmental management system (EN4), organizational culture (SO4) and technology/equipment (EC4). SISMW yielded criterion weights and an ISM hierarchy; MICMAC classified EC4, EC5, SO3, SO4, SO6, EN1 and EN4 as primary driving (independent) criteria, while EC2, EC3, EC6, EC7, EN2 and EN5 were primarily dependent. Practical recommendations include biomass-specific certification, supplier technology development programs, carbon accounting and traceability systems and multi-tier supplier engagement. Originality/value This paper is, to our knowledge, the first application of the SISMW technique to biomass supplier selection, offering an integrated simultaneous-weighting-and-modeling approach tailored to biomass feedstock heterogeneity. The study advances theory by revealing causal links among sustainability criteria in the biomass context and provides actionable, feedstock-aware guidance for managers and policymakers.