https://hdl.handle.net/10807/214 Fri, 11 Sep 2026 23:49:56 GMT 2026-09-11T23:49:56Z https://hdl.handle.net/10807/344316 Titolo: Tensioni nei Processi Decisionali: Come Gestire l’Impatto delle Comunità Energetiche Rinnovabili? Autori: Michele Cipriano; Francesco Virili Abstract: Obiettivo dell’articolo: Il lavoro affronta la mancanza di modelli capaci di rappresentare congiuntamente gli impatti economici e sociali delle comunità Energetiche Rinnovabili (CER), proponendo un modello per la progettazione di un DSS che renda trasparente e gestibile la tensione tra sostenibilità economica e finalità sociali. Metodologia: Attraverso un approccio di Design Science Research, integrato con la paradox theory, vengono analizzate le esigenze informative e le dinamiche decisionali delle CER, definendo un meta-requisito, requisiti informativi e principi di progettazione. Risultati: Emerge un meta-requisito centrale, bilanciare in modo esplicito e negoziabile obiettivi economici e sociali, da cui derivano un insieme coerente di requisiti e principi che strutturano l’architettura concettuale del DSS e permettono di rappresentare, misurare e valutare in modo integrato diverse dimensioni di impatto. Implicazioni manageriali: Il modello guida la progettazione di strumenti digitali che supportano decisioni più consapevoli, la distribuzione equa dei benefici e una governance trasparente delle ricadute socio-economiche delle CER. Limiti della ricerca: Il lavoro si colloca nella fase concettuale del ciclo DSR e non include ancora implementazione e validazione empirica. Originalità: Il contributo integra paradox theory, DSS e architetture informative multidimensionali, proponendo una cornice di design innovativa per gestire le tensioni decisionali nelle CER. Thu, 01 Jan 2026 00:00:00 GMT https://hdl.handle.net/10807/344316 2026-01-01T00:00:00Z https://hdl.handle.net/10807/343678 Titolo: Strategizing in the entrepreneurial process during periods of chaos Autori: chiara cantu Abstract: The main aim of this paper is to investigate the key changes affecting the strategies configuration in the entrepreneurial process of SMEs, in order to address the main challenges characterizing periods of chaos. In particular, the paper investigates the changes affecting strategies characterizing an Italian SME, considering the challenges of Twin Transition and globalization process. Findings highlight the relevance of networking for opportunities identification and management, that sustain the growth of SMEs. Thu, 01 Jan 2026 00:00:00 GMT https://hdl.handle.net/10807/343678 2026-01-01T00:00:00Z https://hdl.handle.net/10807/343677 Titolo: Innovation Ecosystem towards sustainability: the role of innovation intermediaries Autori: Chiara Cantu Abstract: Green and digital transitions are affecting the current situation and will affect the future of several industries. Over the years a growing attention has been recognized to collaborative strategies that foster Twin transition and its development. Among the collaborative strategies, scholars have emphasized the importance of relationships characterizing the Innovation Ecosystem. This latter supports the innovation development on the basis of interactions between firms, institutions, universities, and various organization belonging mainly to the same geographical area. In a wider perspective, Innovation Network, based on IMP perspective, recognizes the key role of relationships belonging to various geographic areas and characterized by the same relational proximity. In this contex, the aim of this research is to investigate the potentialities of Innovation Network on the value configuration of technology start-ups, sopporting their growth to become scale- ups and their orientation towards sustainability. In particular, the research analysis the role of Innovation Intermediaries in this process of transition. Thu, 01 Jan 2026 00:00:00 GMT https://hdl.handle.net/10807/343677 2026-01-01T00:00:00Z https://hdl.handle.net/10807/341563 Titolo: Comparison of different similarity measures in hierarchical clustering Autori: Vagni, Marica; Giordano, Noemi; Balestra, Gabriella; Rosati, Samanta Abstract: The management of datasets containing heterogeneous types of data is a crucial point in the context of precision medicine, where genetic, environmental, and life-style information of each individual has to be analyzed simultaneously. Clustering represents a powerful method, used in data mining, for extracting new useful knowledge from unlabeled datasets. Clustering methods are essentially distance-based, since they measure the similarity (or the distance) between two elements or one element and the cluster centroid. However, the selection of the distance metric is not a trivial task: it could influence the clustering results and, thus, the extracted information. In this study we analyze the impact of four similarity measures (Manhattan or L1 distance, Euclidean or L2 distance, Chebyshev or L∞ distance and Gower distance) on the clustering results obtained for datasets containing different types of variables. We applied hierarchical clustering combined with an automatic cut point selection method to six datasets publicly available on the UCI Repository. Four different clusterizations were obtained for every dataset (one for each distance) and were analyzed in terms of number of clusters, number of elements in each cluster, and cluster centroids. Our results showed that changing the distance metric produces substantial modifications in the obtained clusters. This behavior is particularly evident for datasets containing heterogeneous variables. Thus, the choice of the distance measure should not be done a-priori but evaluated according to the set of data to be analyzed and the task to be accomplished. Fri, 01 Jan 2021 00:00:00 GMT https://hdl.handle.net/10807/341563 2021-01-01T00:00:00Z