A Network-Based Fuzzy Clustering Approach to classify delphi outputs
- Posted by Mara Di Berardo
- On 15 November 2025
- 0 Comments
- delphi, delphi scenarios, fuzzy clustering, Italy Node
A new study titled “A network-based fuzzy clustering approach to classify Delphi outputs in scenario development”, authored by Yuri Calleo, Mario Bolzan (Italy Node members), and Simone Di Zio (Italy Node Co-Chair), has been published open access in Quality & Quantity on November 13, 2025.
The article presents an innovative statistical methodology for analyzing Delphi study results in scenario development by integrating network-based fuzzy clustering with centrality measures. This approach models Delphi outputs as interconnected nodes, allowing items to belong to multiple clusters with different intensities—better reflecting the complexity and overlapping nature of future scenarios.
The study also incorporates community detection algorithms such as Louvain’s method, providing richer insights into the structural properties of expert assessments. The methodology is demonstrated through a case study on future family dynamics in northeast Italy, highlighting how social and demographic trends can inform more robust scenario narratives.
By overcoming the limitations of traditional clustering methods, this framework significantly enhances the rigor, interpretability, and practical value of scenario planning, offering decision-makers a powerful tool for exploring complex and uncertain futures.
