Modelagem do potencial de mercado dos municípios paulistas

Os indicadores de potencial de consumo são medidas indiretas da capacidade de uma região absorver uma determinada categoria de produto. O método de regressão linear simples pode ser utilizado na elaboração de índices simples e robustos que geralmente produzem resultados comparáveis ou superiores aos que podem ser obtidos pela utilização de índices vendidos por empresas de consultoria. Este fato passa despercebido pela maioria dos usuários porque habitualmente não são feitos esforços de comparar os índices com a realidade que estes se propõem a descrever (o que tem uma certa lógica, porque se conhecêssemos a realidade não precisaríamos do índice de potencial). Para estabelecer a metodologia e demonstrar a tese acima, são coletados dados a respeito da área de loja de supermercados dos municípios do Estado de São Paulo; um índice é construído, e em seguida comparado com outros indicadores. Os resultados confirmam a suposição inicial.

The failure of early-stage technology startups in Brazil: a study about the contributing factors to the early-death of startups between 2009 and 2014 in Southeastern Brazil

This research aimed to find out which are the main factors that lead technology startups to fail. The study focused on companies located in the Southeast region of Brazil that operated between 2009 and 2014. In the beginning, a review of the literature was done to have a better understanding of basic concepts of entrepreneurship as well as modern techniques for developing entrepreneurship. Furthermore, an analysis of the entrepreneurial scenario in Brazil, with a focus on the Southeast, was also done. After this phase, the qualitative study began, in which 24 specialists from startups were interviewed and asked about which factors were crucial in leading a technology startup to fail. After analyzing the results, four main factors were identified and these factors were validated through a quantitative survey. A questionnaire was then formulated based on the answers from the respondents and distributed to founders and executives of startups, which both failed and succeeded. The questionnaire was answered by 56 companies and their answers were treated with the factor analysis statistical method to check the validity of the questionnaire. Finally, the logistical regression method was used to know the extent to which the factors led to the startups’ failure. In the end, the results obtained suggest that the most significant factor that leads technology startups in southeastern Brazil to fail are problems with interpersonal relationship between partners or investors.