Debora Anelli

In recent years, research into urban regeneration and property valuation has had to grapple with the growing complexity of decision-making processes. The challenges posed by climate change, the energy transition, resource scarcity and social inequalities have, in fact, highlighted the limitations of sector-specific approaches, making it increasingly involved in environmental, economic, social and governance (ESG) dimensions (Anelli et al. 2026;Morano et al., 2021).In this context, ESG criteria, initially developed within the field of sustainable finance, have gradually broadened their scope to become a benchmark for urban planning, built environment management and property valuation as well. At the same time, the growing availability of spatial data and the development of advanced methodologies -such as artificial intelligence, machine learning, geographic information systems, optimization techniques and life-cycle-based models -have expanded the possibilities for analyzing urban systems. Rather than merely representing new tools, these approaches are helping to transform the way in which complexity is described, interpreted and incorporated into decision-making processes (Guarini et al., 2024;Morano et al., 2025).It is against this backdrop that the Research Topic "AI-driven Multidimensional Approaches for ESGoriented Urban Regeneration and Real Estate Valuation" has been launched, with the aim of promoting an interdisciplinary dialogue on the methodologies and tools capable of putting ESG principles into practice in the fields of urban regeneration and property valuation. The contributions collected explore different perspectives but share a common interest in the development of models, frameworks and decision-support tools capable of integrating heterogeneous data and multiple dimensions of sustainability.This Research Topic brings together seven contributions, comprising original articles and reviews, developed by research groups operating predominantly within the European context. Whilst addressing different themes, scales of analysis and case studies, the papers converge towards a common objective: to develop models and tools capable of integrating data, ESG criteria and quantitative methodologies to support increasingly complex decisions.The first group of contributions focuses on defining conceptual and methodological frameworks to guide decision-making processes towards sustainability objectives. The review by Kim e Yang critically traces the evolution of the ESG paradigm in the construction and real estate sectors: through a systematic review of the literature, the authors identify the challenges that remain in its implementation and outline some research avenues to make it more operational in decision-making processes. From a complementary perspective, Di Liddo et al. propose a systematic review of the literature to identify the main factors (economic, cultural and conservation-related) influencing investment in cultural heritage, organizing them into a decision-support framework for private sector operators. To round off this strand, Senanayake et al. shift the focus from the built environment to corporate reporting, comparing the biodiversity and ESG disclosure practices of Indonesian and Korean companies: despite growing attention to the issue, the analysis shows that biodiversity is still rarely treated as a material issue in sustainability reports.The second group of studies proposes operational methodologies for translating ESG principles into assessment and decision-support tools. Salvo and Tavano develop a framework that integrates Life Cycle Assessment and Life Cycle Costing to incorporate the circular economy into property valuation, demonstrating how the joint analysis of environmental performance and costs across the entire life cycle can provide a more comprehensive estimate of the value generated by sustainable strategies. Anelli et al., on the other hand, propose a two-stage Goal Programming model that integrates the assessment of ESG performance with the selection of intervention strategies, moving beyond a static interpretation of sustainability and transforming it into a tool for prioritizing the most effective actions even in the presence of potentially conflicting economic, environmental and management objectives; its application to two case studies in different industrial contexts confirms its operational validity.The last group of contributions highlights the potential of data-driven approaches in the analysis of complex urban phenomena. Díaz-López et al. use geographic information systems to analyze the evolution of climate zones in Spain under different scenarios, demonstrating how such changes may affect the vulnerability of the building stock and guide strategies for adaptation, regeneration and property valuation -a contribution that highlights the value of geospatial analysis for planning policies that are more resilient to climate change. Finally, Di Ruocco combines econometric models and machine learning techniques to examine the relationship between environmental quality and the residential property market in twelve Italian cities, demonstrating how this relationship is non-linear and strongly depends on the specific characteristics of the urban context.Taken together, the collected contributions show how research into urban regeneration and property valuation is moving beyond standardized valuation approaches. Rather than a single dominant perspective, this Research Topic highlights the value of complementarity between different points of view: systematic reviews, decision-support tools, optimization models, geospatial analyses and data-driven methodologies each contribute, in their own way, to understand specific aspects of urban regeneration processes and property markets.However, some interesting challenges remain, for example: ESG indicators and measures that are more standardized and comparable across different geographical...

Regenerating fragile historical contexts requires choices of repurposing that combine heritage protection, continuity of use and managerial feasibility, in the presence of multiple objectives and stakeholders with different preferences. This study develops and tests an MCDA-based decision-support framework for the ex-ante selection of adaptive reuse scenario applied to Craco (Italy) and Palazzo Carbone-Rigirone. Craco and Palazzo Carbone-Rigirone were selected as a critical case because they combine heritage abandonment, geomorphological fragility, cultural visibility, weak local services and the need for a feasible management model. The methodology involves: (i) defining four adaptive reuse scenarios; (ii) constructing nine criteria that integrate socio-economic impacts, safety/security, cultural attractiveness, compatibility with the property and economic–financial feasibility; (iii) elicitation of weights using a hybrid approach, combining the decision-maker’s macro priorities and the social quota derived from questionnaires using normalised indicators of satisfaction/dissatisfaction and priorities for improvement; (iv) classification using the Weighted Sum Model and TOPSIS under two normalizations (distributive and ideal) and two variants (relative and absolute). The results show convergence between methods and stability of the ranking, with a preference for the multifunctional scenario oriented towards cultural services and socialising. In the case of Craco, adaptive reuse offers advantages compared with purely conservative, passive musealization or tourism-only strategies. The study concludes that MCDA is useful as a transparent pre-selection tool and supports the alignment of local needs and institutional priorities; its robustness can be strengthened with sensitivity analyses and policy scenarios.

Introduction: Eco-industrial parks (EIPs) are key infrastructures in the transition toward circular and low-carbon production systems, yet their Environmental, Social and Governance (ESG) performance is still commonly assessed through static metrics that offer limited support for improvement strategies. Methods: This study proposes a two-phase decision-support framework: a passive goal-programming assessment that measures gaps to regulatory targets and best practices, and an active phase that identifies cost-effective portfolios of improvement measures under budgetary and technical constraints. The framework is applied to two European EIPs, Envipark (Italy) and Kalundborg (Denmark). Results: In the passive phase, Envipark shows criticalities mainly in the environmental dimension, while Kalundborg achieves higher performance levels, with residual weaknesses in social indicators related to welfare and community engagement. The active phase confirms distinct strategic trajectories: Envipark tends toward incremental and demonstrative measures, whereas Kalundborg prioritises transformative, large-scale initiatives. Discussion: The framework provides a transparent tool for policymakers and EIP managers to align investment decisions with ESG and decarbonization goals. Overall, it advances methodological practice by operationalizing goal programming for dual passive/active ESG assessment, offering a replicable framework for EIPs, and bridging the gap between assessment and decision-making in sustainability governance.

The selection of the most economically advantageous tender (MEAT) in public procurement procedures requires transparent evaluation systems capable of integrating heterogeneous criteria, including qualitative ones, to reconcile quality and cost. This systematic review analyzes 74 studies published between 1998 and 2023 to explore the application of multi-criteria decision analysis (MCDA) methods in public construction procurement. The vast majority of MCDA applications focus on the award phase, with constant growth over the last 10 years. However, applications in the prequalification and verification phases are much less frequent and remain under-represented. Geographically, Europe is the most active area in terms of publications, followed by China and some countries in the Asia-Pacific area. In these regions, MCDA has been employed more systematically over time, while in other areas (e.g., Africa, Latin America), applications are sporadic or absent. Analytic Hierarchy Process (AHP) is confirmed as the most widely used technique. Emerging techniques (such as BWM, MABAC, EDAS, VIKOR, advanced TOPSIS) show greater computational rigor and in some cases better theoretical properties, but are less used due to complexity, less practical familiarity and the lack of accessible software tools. The operationalization of environmental and social criteria is still poorly standardized: clear indications on metrics, measurement scales and data sources are often lacking. In most cases, the criteria are treated in a generic or qualitative way, without common standards. Furthermore, the use of sensitivity analyses and procedures for aggregating judgments between evaluators is limited, with a consequent risk of poor robustness and transparency in the evaluation. In order to consider proposing a framework or guidelines based on the review findings, a six-step operational framework that connects selection of criteria and their operationalization, choice of method based on the context, robustness checks and standard minimum reporting, with clear assignment of roles and deliverables, is provided. The framework summarizes and makes the review evidence applicable.