A Conceptual Model on Gender Biases and Discrimination in Entrepreneurial Resource Provision

Abstract

The entrepreneurship literature has provided mixed evidence as to whether various resource-providers —such as actual investors or hypothetical providers of financial capital, technology office licensers, consumers, as well as potential employees— discriminate against female-led innovative start-up ventures in their resource-commitment decisions in terms of the likelihood and terms of resource provision. While some studies revealed evidence indicative of negative discrimination against female entrepreneurs, others have provided evidence of positive discrimination. Yet, another set of studies suggested that entrepreneurial resource-providers are “gender-blind” in their evaluations after accounting for differentials in individual, organizational, and industry characteristics of female- and male-led ventures. These divergent findings point to the need for a more nuanced and integrative approach to studying gender biases in entrepreneurial resource provision, with greater attention paid to both moderating contingency factors and mediating mechanisms. We develop a conceptual model and empirically-testable propositions discussing when, how, and why entrepreneurial resource-providers are likely to undervalue, equivalue, and overvalue female-led innovative ventures. Our model discusses the importance of a key contingency that is likely to influence evaluations of female- and male-led innovative ventures by resource providers: the gender-typing of the entrepreneur’s product or service offering. We further discuss the mediating channels through which gender stereotyping is likely to influence the valuation of female- versus male-led ventures. Our model develops a systematic framework and empirically-testable propositions for assessing the occurrence of gender biases in entrepreneurial evaluations and the ensuing resource provision to innovative start-up ventures. We conclude with implications for future entrepreneurship research.