Do clusters create shared value? A social network analysis of the motor valley case
| Autor: | Fernando Alberti, Federica Belfanti |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Operationalization
Variables Computer science media_common.quotation_subject Context (language use) Creating shared value General Business Management and Accounting Data science Cluster development Business and International Management Empirical evidence Social network analysis Research question media_common |
| Zdroj: | Competitiveness Review: An International Business Journal. 31:326-350 |
| ISSN: | 1059-5422 |
| DOI: | 10.1108/cr-05-2020-0077 |
| Popis: | Purpose This paper aims to contribute to the debate about creating shared value (CSV) and clusters, by shedding light on how clusters might generate shared value, i.e. cause social and business benefits, hence focusing on the following research question “do clusters create shared value?” Design/methodology/approach The study relied on social network analysis methods and techniques. Data have been collected from both primary and secondary sources, in the empirical context of the Motor Valley cluster in Emilia-Romagna. The authors computed three independent and four dependent variables to operationalize the concept of cluster development and shared value creation. A multiple regression quadratic assignment procedure and, more specifically, the most accurate model of that procedure, that is the double semi-partialling method, has been carried out to answer the research question. Finally, empirical evidence has been complemented with other cluster-level data recently collected by the Italian Cluster Mapping project. Findings The findings confirm how the development of the Motor Valley cluster in Emilia-Romagna contributed to the creation of economic and social growth opportunities for all the actors. The study shows that clusters do create shared value and the chosen cluster development variables do explain much of the business and social impact variables at a very high statistical significance level. Originality/value The paper contributes to the under-explored research on clusters and CSV with a very first attempt in providing quantitative evidence of the phenomenon. |
| Databáze: | OpenAIRE |
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