Turismo em Cabo Verde : um estudo da competitividade entre os clusters de Santo Antão-São Vicente e Sal-Boa Vista

Abstract

Joint efforts between firms are increasingly common, even when there exists competitive rivalry in the market. Companies tend to group together in (I erased what was written here) clusters, forming critical masses of industries to take advantage of synergies such as increased productivity, innovation and, in essence, the possibility of becoming more competitive. Given that clusters increase the competitiveness of an industry and given that tourism is a powerful instrument of regional development, this study is aimed at examining the determinants of competitive advantage for tourism clusters of Santo Antao - Sao Vicente and Sal - Boavista, which are a set of four islands located in the Republic of Cape Verde, Africa. In order to identify the relevant variables to enhance competitiveness in these regions, a semi-structured model was created in light of the "Diamond of Competitiveness" by Porter (1990). It incorporated the following attributes: (i) factor conditions, (ii) demand conditions, (iii) strategy, structure and rivalry of the companies, (iv) related and supporting industries, and the influence of the government variable. The Government´s role was evaluated from the national level whereas this can influence significantly the determinants of competitive advantage. Thus, the operationalization of this study was through a quantitative survey, with data analysis using the statistical procedure called the Mann Whitney. Data from field research resulted in a sample of 100 businesses, hotels, restaurants, travel agencies, sports and recreation, clubs, lodging and rental car, which was proportionally divided between the two clusters. Results from the application of the model indicate the competitive performance of tourism in each of the clusters thus infer theoretical and empirical implications, and the resulting managerial implications that favor the goals of both public and private sector aimed at improving the competitiveness of the clusters under study . It is still possible through a comparative basis of variables foster learning from one region over another in order to introduce improvements.