{"title":"Strategic collaboration in agro-industrial clusters: territorial dynamics within the dairy industry in Uruguay","authors":"Pablo Galaso, Adrián Rodríguez Miranda","doi":"10.1108/cr-10-2021-0146","DOIUrl":null,"url":null,"abstract":"\nPurpose\nInquiring about the patterns of interaction within clusters can provide a valuable insight into the cooperation and competition strategies followed by firms. However, such internal patterns are difficult to identify using conventional methods. This study aims to apply a social network analysis approach to identify and analyze different sub-groups of firms within a dairy cluster. These sub-groups seem to respond to different forms of productive organization, with different levels of territorial anchorage.\n\n\nDesign/methodology/approach\nThe authors study the dairy cluster in the south-west of Uruguay, where one of the country’s main industries is located. The authors use data from semi-structured interviews applied to managing directors of 40 dairy industrial firms. The authors analyze the collaboration network among firms and industry support organizations. Using a community detection algorithm, the authors identify strategic groups of firms and organizations within the network. The authors analyze information from the interviews to delve deeper into the strategies pursued by actors in each of these sub-groups.\n\n\nFindings\nThe four groups identified by the algorithm respond to particular logics associated not only with collaborative behavior, but also with territorial distribution and competitive strategies pursued by firms. In particular, these communities show a positive association between the centrality of their nodes in the network, the size of their firms, their export orientation and their innovative capacity. These associations indicate the co-existence, within the cluster, of different local productive systems and other forms of productive organization.\n\n\nOriginality/value\nThe paper illustrates how different strategies of firms within a cluster can be understood using social network analysis. This approach is particularly interesting in agri-food clusters, where their wider dispersion in the territory often implies their firms following different collaborative and competitive strategies, and different levels of territorial anchorage.\n","PeriodicalId":46521,"journal":{"name":"Competitiveness Review","volume":" ","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Competitiveness Review","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/cr-10-2021-0146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
Inquiring about the patterns of interaction within clusters can provide a valuable insight into the cooperation and competition strategies followed by firms. However, such internal patterns are difficult to identify using conventional methods. This study aims to apply a social network analysis approach to identify and analyze different sub-groups of firms within a dairy cluster. These sub-groups seem to respond to different forms of productive organization, with different levels of territorial anchorage.
Design/methodology/approach
The authors study the dairy cluster in the south-west of Uruguay, where one of the country’s main industries is located. The authors use data from semi-structured interviews applied to managing directors of 40 dairy industrial firms. The authors analyze the collaboration network among firms and industry support organizations. Using a community detection algorithm, the authors identify strategic groups of firms and organizations within the network. The authors analyze information from the interviews to delve deeper into the strategies pursued by actors in each of these sub-groups.
Findings
The four groups identified by the algorithm respond to particular logics associated not only with collaborative behavior, but also with territorial distribution and competitive strategies pursued by firms. In particular, these communities show a positive association between the centrality of their nodes in the network, the size of their firms, their export orientation and their innovative capacity. These associations indicate the co-existence, within the cluster, of different local productive systems and other forms of productive organization.
Originality/value
The paper illustrates how different strategies of firms within a cluster can be understood using social network analysis. This approach is particularly interesting in agri-food clusters, where their wider dispersion in the territory often implies their firms following different collaborative and competitive strategies, and different levels of territorial anchorage.
期刊介绍:
The following list indicates the key issues in the Competitiveness Review. We invite papers on these and related topics. Special issues of the Review will collect papers on specific topics selected by the editors. Definition/conceptual framework of competitiveness Competitiveness diagnostics and rankings Competitiveness and economic outcomes Specific dimensions of competitiveness Competitiveness and endowments Competitiveness and economic development Location and business strategy International business and the role of MNCs Innovation and innovative capacity Clusters and cluster initiatives Institutions for competitiveness Public policy (e.g., innovation, cluster development, regional development) The Competitiveness Review aims to publish high quality papers directed at scholars, government institutions, businesses and practitioners. It appears in collaboration with key academic and professional groups in the field of competitiveness analysis and policy, including the Microeconomics of Competitiveness (MOC) network and The Competitiveness Institute (TCI) practitioner network for competitiveness, clusters and innovation.