An interactive tool designed to support policymakers in planning circular economy transitions for Historical Small Towns
The H-SMA-CE Decision Support System is the primary output of our research project. It translates extensive analytical and methodological work into a single, integrated, and operational tool designed to bridge the gap between academic modeling and real-world decision-making.
Built on three core principles — accessibility, interactivity, and practical utility — the DSS empowers local administrators to assess their town's current circularity status, simulate different policy scenarios, and identify optimal strategies for sustainable development.
The system addresses five key domains essential for circular economy assessment: Green Enterprise (GE), Sustainable Mobility (SM), Biodiversity Resource Saving (BRS), Water Management (WM), and Digitalization/Efficiency/Competition/Innovation (DECI).
Designed to answer three fundamental questions central to the policy cycle
Evaluate your town's current circularity performance across five key domains with comprehensive indicators and benchmarks.
Test different policy interventions and immediately visualize their projected impact on circularity performance and budget.
Discover the best course of action with multi-objective optimization that balances circularity goals with budget constraints.
Visualize results through charts, summary tables, and real-time feedback as you explore different scenarios.
Estimate implementation costs and expected benefits for each intervention to support economic justification of investments.
Designed as a "boundary object" providing common language for discussing complex sustainability issues among different groups.
A structured approach to guide your circular economy planning process
The Current State module provides a comprehensive assessment of your town's existing circularity levels across all key performance indicators.
The Scenario Simulation module allows you to explore different policy interventions and visualize their potential impacts in real-time.
The Optimal Strategy Finder uses multi-objective optimization to identify the most effective combination of interventions within your constraints.
Experience the DSS through our interactive web application based on the Taurasi case study
We have developed a web-based preview of the H-SMA-CE Decision Support System, specifically configured with data from our primary case study: the historic town of Taurasi in Campania, Italy.
This streamlined version allows you to explore the DSS methodology and interface without any installation. While the full Excel-based tool offers complete customization for any Historical Small Town, this web app provides an immediate, hands-on experience with real data from our research.