Gender aspects of management, innovation and entrepreneurship are gaining more and more importance as cross-cutting issues for researchers, practitioners and decision makers. Extant literature pays a growing attention to the hypothesis that there exists a correlation between the gender diversity of corporate boards of directors and the business attitude to innovation. In this paper we introduce a working framework to test the aforementioned hypothesis and to examine the correlation between board diversity and innovation perception of a business. This framework is based on correlation computation and feed-forward neural networks, and it is used to evaluate whether the gender component may be used to predict the innovation perception of a business. First results about three different economic scenarios are reported and discussed.

di Tollo, G., Andria, J., Tanev, S. (2021). Neural Networks to Determine the Relationships Between Business Innovation and Gender Aspects. In Mathematical and Statistical Methods for Actuarial Sciences and Finance (pp. 193-199) [10.1007/978-3-030-78965-7_29].

Neural Networks to Determine the Relationships Between Business Innovation and Gender Aspects

Andria, Joseph;
2021-01-01

Abstract

Gender aspects of management, innovation and entrepreneurship are gaining more and more importance as cross-cutting issues for researchers, practitioners and decision makers. Extant literature pays a growing attention to the hypothesis that there exists a correlation between the gender diversity of corporate boards of directors and the business attitude to innovation. In this paper we introduce a working framework to test the aforementioned hypothesis and to examine the correlation between board diversity and innovation perception of a business. This framework is based on correlation computation and feed-forward neural networks, and it is used to evaluate whether the gender component may be used to predict the innovation perception of a business. First results about three different economic scenarios are reported and discussed.
2021
di Tollo, G., Andria, J., Tanev, S. (2021). Neural Networks to Determine the Relationships Between Business Innovation and Gender Aspects. In Mathematical and Statistical Methods for Actuarial Sciences and Finance (pp. 193-199) [10.1007/978-3-030-78965-7_29].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/535044
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