Combining multifaceted aspects of technology innovations through fuzzy clustering of multilayer networks

This study advances a novel multilayer network model to explore the connection between different aspects of Technological Innovation in European Union (EU) countries. We follow a fuzzy clustering approach and consider three variables: Research and Development (R&D), High-Tech Exports (HTE), and Human Resources in Science and Technology (HRST). We consider Eurostat data from 2018 to 2023. The variables form the layers, the EU countries are the nodes of the layers, and the weighted intra-layer links are assumed to increase with respect to the similarity of the countries in terms of the related variable. Interlayer connections are modeled probabilistically using a fuzzy clustering approach: two countries in different layers are strongly connected if they belong more probably to the same cluster in the related layers. The analysis offers insights into the patterns of EU countries in terms of Technological Innovation (TI) processes. The proposed framework allows its applicability to a wide set of real-world contexts.

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Publication Details

Journal
PLoS ONE
Published
2025-10-14
DOI
https://doi.org/10.1371/journal.pone.0334138
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Combining multifaceted aspects of technology innovations through fuzzy clustering of multilayer networks

Saverio Storani, Giovanna Ferraro, Raffaele Mattera, Roy Cerqueti
PLoS ONE
Complex Network Analysis Techniques
article

Combining multifaceted aspects of technology innovations through fuzzy clustering of multilayer networks

Saverio Storani, Giovanna Ferraro, Raffaele Mattera, Roy Cerqueti
article en

Abstract

This study advances a novel multilayer network model to explore the connection between different aspects of Technological Innovation in European Union (EU) countries. We follow a fuzzy clustering approach and consider three variables: Research and Development (R&D), High-Tech Exports (HTE), and Human Resources in Science and Technology (HRST). We consider Eurostat data from 2018 to 2023. The variables form the layers, the EU countries are the nodes of the layers, and the weighted intra-layer links are assumed to increase with respect to the similarity of the countries in terms of the related variable. Interlayer connections are modeled probabilistically using a fuzzy clustering approach: two countries in different layers are strongly connected if they belong more probably to the same cluster in the related layers. The analysis offers insights into the patterns of EU countries in terms of Technological Innovation (TI) processes. The proposed framework allows its applicability to a wide set of real-world contexts.

PLoS ONEVol. 20(10)
University of Rome Tor Vergata (IT), University of Campania "Luigi Vanvitelli" (IT), Unitelma Sapienza University (IT), Université d'Angers (FR), Sapienza University of Rome (IT)
Openalex Percentile: Top 77%
Complex Network Analysis Techniques
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