Clusters and the Context for Competitive Advantage: a Strategic Analysis of the Engineering & Tooling Cluster

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Ano de publicação
2019
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ISEG - Lisbon School of Economics and Management
Resumo
This dissertation illustrates an empirical application of Porter’s (1990, 2004) Diamond Model using the Partial Least Squares Structural Equation Modelling (PLS-SEM; Wold, 1975, 1982) method in order to assess the effects of the microeconomic business environment on firms’ competitive advantage and the government’s supportive role in improving such an environment. It follows a concurrent triangulation design and takes firms in the Portuguese Engineering & Tooling cluster as the basic unit of analysis. The findings from the path analysis derive from a total number of 168 questionnaire responses obtained from firms in the cluster, which were subsequently triangulated with secondary data and interviews conducted with several cluster stakeholders. These findings reveal a positive effect of the related and supporting industries, the context for firm strategy and rivalry, and the factor (input) conditions at the cluster level on firms’ competitive advantage. Government action has also been shown to have a positive effect on the four determinants of the Diamond Model. Conversely, respondents’ perceptions do not support a positive effect of the demand conditions at the cluster level on firms’ competitive advantage. The positive and negative effects of the Engineering & Tooling cluster’s environment on the competitive edge of firms highlight the catalytic roles of the government and collective action in cluster upgrading.
Descrição
Cluster, Ventaja Competitiva, Políticas de Clusters, Políticas de Clusterização, Vantagem Competitiva, Modelo do Diamante, Cluster Engineering & Tooling, Investigação por Métodos Mistos, Modelação de Equações Estruturais com base nos Mínimos Quadrados Parciais (PLS-SEM), Cluster Policies, Competitive Advantage, Modelo del Diamante, Modelación de Ecuaciones Estructurales con Mínimos Cuadrados Parciales (PLS-SEM), Investigación de Métodos Mixtos
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