Venture Creation Speed and Subsequent Growth: Evidence from South America

Abstract

Though time is an important dimension of the venture creation process, our understanding of why some entrepreneurs are able to act more quickly than others is limited. Equally, not much is known about the relationship between venture creation speed and the subsequent venture growth. In this paper, we use a resource‐based perspective to provide insights into the factors that quicken or retard venture creation and to explore how speed impacts on subsequent growth. This is important because the topic remains generally underresearched and because even less is understood about venture creation speed in the context of South American economies. Data were collected from face‐to‐face interviews with 647 entrepreneurs in Argentina, Brazil, Chile, and Peru. Using a multivariate regression framework, we find that entrepreneurs make use of their human and social capital resources to shape the speed by which their venture is created. Moreover, their perceptions of unfavorable environmental conditions seem to retard venture creation. Findings also suggest that entrepreneurs who take more time to create a more solid resource base tend to receive better growth outcomes. Implications from the findings are discussed.

Notes

¹ De Soto (1989) found that setting up a new venture in Peru cost the equivalent of three years wages and suggested that such costs drive the poor toward the illegality. Djankov et al (2002) identified the costs and time associated with establishing a new formally registered firm in 85 countries and showed that, for example, it takes 83 days for a Peruvian entrepreneur to set up a new venture, 63 in Brazil, and 48 in Argentina. This compares with two days for Canada, four for the United States, and five for the United Kingdom. Using similar objective measures, the expanded results from the World Bank (2006) suggest that the situation in South America has not improved.

² We are grateful to an anonymous referee for this suggestion.

³ See Kantis (2004) for a description of the methodology.

⁴ Buenos Aires city and urban areas of Buenos Aires in Argentina, Lima in Peru, São Paulo and Campinas in Brazil, and Federal District and Guadalajara in Mexico.

⁵ Subsequent statistical analyses are based on pooled data since the number of observations in each national subsample is relatively small and the number of variables is relatively high. However, we included three dummy variables in the regression equations to control for any country‐specific effects.

Additional information

Notes on contributors

Joan‐lluis Capelleras

Joan‐Lluis Capelleras is lecturer in the Department of Business Economics at the Universitat Autònoma de Barcelona.

Francis J. Greene

Francis J. Greene is associate professor at Warwick Business School, University of Warwick.

Hugo Kantis

Hugo Kantis is professor in the Institute of Industry at the Universidad Nacional de General Sarmiento, Argentina.

Rodrigo Rabetino

Rodrigo Rabetino is lecturer in the Department of Business Economics at the Universitat Autònoma de Barcelona, Spain.