Power law distributions in entrepreneurship : implications for theory and research
Data(s) |
2015
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Resumo |
A long-held assumption in entrepreneurship research is that normal (i.e., Gaussian) distributions characterize variables of interest for both theory and practice. We challenge this assumption by examining more than 12,000 nascent, young, and hyper-growth firms. Results reveal that variables which play central roles in resource-, cognition-, action-, and environment-based entrepreneurship theories exhibit highly skewed power law distributions, where a few outliers account for a disproportionate amount of the distribution's total output. Our results call for the development of new theory to explain and predict the mechanisms that generate these distributions and the outliers therein. We offer a research agenda, including a description of non-traditional methodological approaches, to answer this call. |
Formato |
application/pdf |
Identificador | |
Publicador |
Elsevier |
Relação |
http://eprints.qut.edu.au/81245/3/81245.pdf DOI:10.1016/j.jbusvent.2015.01.001 Crawford, G. Christopher, Aguinis, Herman, Lichtenstein, Benyamin, Davidsson, Per, & McKelvey, Bill (2015) Power law distributions in entrepreneurship : implications for theory and research. Journal of Business Venturing, 30(5), pp. 696-713. |
Direitos |
Copyright 2015 Elsevier This is the author’s version of a work that was accepted for publication in Journal of Business Venturing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Business Venturing, [in press] DOI: 10.1016/j.jbusvent.2015.01.001 |
Fonte |
Australian Centre for Entrepreneurship; QUT Business School; School of Management |
Palavras-Chave | #150304 Entrepreneurship #Entrepreneurship #Generative Mechanisms #Growth #Outliers #Power Law Distribution #Theory Development |
Tipo |
Journal Article |