This paper investigates gender dimensions in the relationship between CEO duality and firm performance, combining feminist theories and stewardship arguments. Using a large sample of listed firms from 23 European countries in the 2014–2020 period, we have found that CEO duality has a positive effect on corporate performance when a woman holds both the roles of CEO and board chair. These findings highlight the ‘bright side’ of women in governance, suggesting the presence of women in double leadership positions can amplify benefits and/or limits costs related to CEO duality. Having a woman in CEO-chair leadership could optimize a firm’s use of its resources and more effectively contribute to improving performance. Directions for future research could include a better understanding of women in leadership in the organizational domain. Our results have a number of managerial and political implications.

In this article, we investigate the effect of local financial development on cash holdings of Italian small and medium-sized enterprises (SMEs). Consistent with the hypothesis that local financial development reduces the need to hold precautionary cash because it facilitates access to bank debt, we find that local financial development measured by the density of bank branches in Italian provinces has a negative effect on corporate cash holdings. This effect is driven by SMEs with bank debt. Furthermore, the negative effect of local financial development on cash holdings only exists for younger and smaller SMEs, which are more likely to benefit from increased local financial development. Our work highlights that local financial development is an important driver of policies on holding cash by SMEs and is particularly relevant during crisis periods, such as the recent COVID-19 crisis.

Noteworthy contributions have highlighted that human contact is a considerable factor in bank-firm relationships. It allows the acquisition of soft information, which alleviates information asymmetries and increases the use of bank debt. The advent of digital technologies in the information collection process open new horizons and change the role of personal contacts in bank-firm interactions, as entrepreneurs visit bank branches less frequently. This study uses a large sample of Italian SMEs from 2011 to 2020 and finds that the rapid increase and use of digital instruments have reduced the positive influence of physical closeness between banks and SMEs on the indebtedness levels. Interestingly, our study has also found that the COVID-19 crisis did not amplify this moderating effect. Results support theories that human contact is an important factor in bank-firm relationships because it allows the acquisition of soft information, which alleviates information asymmetries and increases the use of bank debt. Our study suggests that close human ties are still extremely relevant and digitalization should be exploited to support the collection of the kind of qualitative soft information that is crucial in debt negotiations.

Purpose: Our aim is to develop a highly precise corporate crisis prediction model that surpasses previous versions, rooted in the forefront of technological advancements. Design/methodology/approach: Artificial Intelligence (AI) for corporate default prediction with a novel approach based on a mix of techniques, enabling it to achieve a higher accuracy. We investigated models with sequence lengths that were both fixed and variable, and we chose the best variable sequence length model. Findings: Our findings demonstrate that the artificial techniques implemented lead to very high accuracy in predicting business crises compared to previous research efforts, even those utilising long-time sequences or a high volume of observations. Research limitations/implications: We highlight the key variables with a higher predictive power that need monitoring to prevent business crises. We also aim to open a new avenue of research that, starting from the use of these techniques and our results, can implement models incorporating non-accounting variables to prevent business crises. Practical implications: We provide a model/tool that assesses a possible business crisis in advance through a monitoring and alert system. Policymakers can use our research’s output as a tool to combine with current credit-scoring systems and to assess the effectiveness of the new corporate crisis reforms that are upcoming in many European countries. The results of our research can be useful also to banks, public entities, and consulting firms that interact with companies and are interested in the evaluation of a firm’s financial health and stability. Originality/value: Our innovative work leverages cutting-edge methodologies such as deep Recurrent Neural Networks and explainable AI. This choice is driven by the rapid evolution of AI techniques in practical application.