Competitiveness of clusters

Abstract

Purpose – The purpose of this paper is to deepen the discussion regarding the competitiveness of clusters based on a theoretical and empirical study that compares the level of competitiveness of the Brazilian wine cluster located in Serra Gaúcha with the competitiveness of the Chilean cluster located in Valle del Maule. Design/methodology/approach – A qualitative-descriptive approach was applied to the study, and data collection was conducted through secondary sources. Findings – The analysis employed a competitiveness analysis model consisting of 11 competitiveness factors. The Chilean cluster presented a higher level of competitiveness in four competitiveness factors (“scope of viable and relevant business,” “introduction of new technologies,” “balance with no privileged positions” and “oriented strategy”), while the Brazilian cluster presented a higher level of competitiveness in three competitiveness factors (“concentration,” “cooperation” and “replacement”). For four of the competitiveness factors of the model, both clusters presented similar levels of competitiveness. Practical implications – By comparing the two wine clusters, it was possible to identify aspects that can be improved to increase competitiveness, especially in the Brazilian cluster. These aspects include, first, the need for bottle manufacturers in Serra Gaúcha, which would have a positive impact on production costs; second, the expansion of the geographical indication registration for the entire Serra Gaúcha region, resulting in an enhanced image of Brazilian wine abroad; and third, greater incentives for exports, which would result in an increase in market share. Originality/value – The paper proposes an explanation for the superior level of competitiveness of the Chilean cluster regarding the “scope of viable and relevant business,” “balance with no privileged positions,” “introduction of new technologies” and “strategy focussed on cluster development.” In terms of its contribution, the study developed additional metrics for the model adopted, which can be used for the competitive analysis of other agribusiness clusters.