Integrating the gender dimension to disclose the degree of businesses’ articulation of innovation

Giacomo Tollo (), Joseph Andria (), Stoyan Tanev () and Sara Ghilardi ()
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Giacomo Tollo: Università degli Studi Del Sannio
Joseph Andria: Università degli Studi di Palermo
Stoyan Tanev: Carleton University
Sara Ghilardi: Regalgrid Europe Srl

Journal of Computational Social Science, 2024, vol. 7, issue 1, No 4, 87-123

Abstract: Abstract In this contribution, we examine the relationship between the presence of women in companies’ Boards and innovation communication claims: we propose a framework to quantitatively assess the presence of women and the online articulation of innovation, in order to understand whether some correlations hold between these two variables. We also introduce a neural network approach to predict the innovation metric that uses, amongst the predictors, the gender component, and we compare it with a linear regression analysis. Results indicate that neural networks may be used to predict the articulation of innovation by using a predictor set that includes the gender component of the Board of Directors, and also that the use of the gender metric improves previous predictions about the articulation of innovation model’s output.

Keywords: Gender diversity; Board of directors; Innovation metrics; Online communication; Neural networks (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s42001-023-00230-x

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