Multi-Criteria Decision-Making and Digital Twins for Sustainable Environmental Planning and Management: Methods, Applications, and Limitations: A Review

This is the authors' abstract. We don't add key points for this paper.

Environmental planning and management must reconcile multiple sustainability objectives, uncertain impacts, and diverse stakeholder priorities, often under data-rich but fragmented information environments. Multi-criteria decision-making (MCDM) offers structured approaches for comparing alternatives, while digital twins and related smart tools (e.g., GIS, BIM, IoT monitoring, and decision support platforms) can represent system behaviour and support scenario testing. This article is a comprehensive narrative review (not a registered systematic review or meta-analysis). It synthesises a documented evidence base of 68 sources identified through Scopus/Web of Science-style Boolean strings, citation chasing, and a reproducible OpenAlex retrieval executed on 2 September 2026. Coding of that evidence base shows AHP/ANP as the most frequent MCDM family emphasis, GIS as the most frequent digital layer, and GIS/spatial MCDM (Pattern A) as the most frequent explicit coupling path; fully operational bidirectional twins and closed adaptive ranking loops remain uncommon. The typology contribution is an organising lens that jointly classifies (i) decision structure, (ii) digital representation class (conventional smart tool, partial twin, or fully operational twin), and (iii) coupling Patterns A–D; this differs from method-only MCDM surveys and architecture-only twin reviews by making coupling the unit of synthesis. Recurring limitations include uneven uncertainty treatment and validation, interoperability and cost barriers, governance and equity gaps, and rare monitoring-to-ranking loops. Priorities are transparent data lineage, uncertainty-aware and equity-conscious coupling, interoperable decision layers, and post-implementation learning.