Session
Innovations in Decision-Support and AI-driven Valuation for Urban Energy Transition
Track 5 - Economics and Valuation of the Urban Energy Transition
Achieving a just energy transition in cities requires decision-making processes that are evidence-based and optimized, capable of addressing environmental, economic, and social dimensions. This special session invites contributions that explore how decision-support tools, also backed by AI-driven applications, can enhance the multidimensional evaluation of urban and territorial transformations. AI plays an increasingly pivotal role by enabling the identification of spatial patterns, predictive modeling, and the comparison of alternative scenarios, helping to navigate the complexity and assess the multiple benefits and impacts at different scales.
The session focuses on evaluation methodologies that support (energy) transition strategies at urban and regional scales, including their impacts on property values, mass appraisal techniques, machine learning applications, spatial data analysis, and participatory decision-making frameworks. Particular emphasis is placed on data-driven approaches that integrate geographic information systems (GIS), multi-criteria decision analysis (MCDA), and advanced spatial analytics to model urban dynamics, assess intervention scenarios, and align decisions with sustainability and equity goals.
We welcome contributions presenting methodological innovations, case studies, and critical reflections on such evaluation practices. The session aims to advance decision-support tools and evaluation frameworks that bridge technical potential with societal needs, empowering decision-makers to design and prioritize interventions that foster energy-efficient, resilient, and inclusive cities.
The topics of interest include, but are not limited to:
Decision-support systems and data-driven approaches
Impacts of energy transition on property values and real estate dynamics
AI, GIS, and advanced spatial analytics for urban and regional planning
Machine learning, mass appraisal, and predictive modeling techniques
Multi-criteria and multi-stakeholder evaluation methods and scenario analysis
Financial and economic analyses for transition strategies
Methodological innovations bridging technical potential and societal needs