A sustainability and digitalization maturity model for supply chains: bridging Industry 5.0, operational excellence and the SDGs

Abstract

Existing sustainable supply chain management (SSCM) maturity models remain fragmented and predominantly diagnostic, offering limited guidance for prioritizing improvements across interdependent sustainability dimensions. This study aims to develop an integrated diagnostic–prescriptive maturity model to support the sustainable and digital path (twin transition) in supply chains by combining sustainability assessment, Industry 5.0-oriented human-centric digitalization, operational excellence and the Sustainable Development Goals (SDGs). The model is particularly relevant to Ibero-American supply chains operating under resource constraints, institutional heterogeneity and increasing pressure to align digital transformation with sustainability priorities. Following design science research, a systematic literature review identified 26 maturity models, which were examined through qualitative content analysis to reveal structural gaps and derive the artifact’s design requirements. The model integrates 187 variables across 4 dimensions and 13 subdimensions. It was refined and validated through a two-round Fuzzy Delphi process involving 15 experts from five Ibero-American countries. A group-based ordinal multicriteria method was embedded to aggregate stakeholders’ linguistic judgments into a consensus ranking of improvement priorities. An illustrative application demonstrated its use. The model assesses environmental, social, economic and transversal maturity while translating identified gaps into ranked improvement priorities and a strategic roadmap. Digital technologies, including the Internet of Things, cyber-physical systems and big data analytics, are framed as sociotechnical enablers of transparency, traceability and responsiveness. The model therefore supports the assessment of Industry 5.0, Operational Excellence 5.0 and SDG-oriented improvement efforts. This study combines sustainability assessment, human-centric digitalization and multicriteria prioritization within a single maturity artifact. By moving beyond diagnosis toward collective, context-sensitive prioritization, it provides decision support for the twin transition, while large-scale applications remain necessary to confirm usability and performance benefits.