This paper explains both capital-structure and debt-maturity choices for SMEs in terms of institutional differences at the local level, making use of regions as the unit of analysis. Specifically, the article considers local financial development and the effectiveness of the local enforcement system, controlling for firm-specific characteristics. The ability of the local financial market to provide funds efficiently is of particular interest to SMEs, due to the fact that large firms can tolerate imperfections in the local financial system by moving to international, more highly integrated financial markets. The main findings of the analysis suggest that capital-structure and debt-maturity choices interact as complementary factors and that corporate financial decisions are not only the result of firm-specific or industry-specific characteristics, but are also based on the institutional climate in which a firm operates. After controlling for heterogeneity in firm characteristics, leverage was found to be positively influenced by local financial development, while the enforcement system was less relevant. Conversely, debt maturity was longer in regions with high levels of law enforcement, whereas local financial development did not play a relevant role.

Purpose: This study focuses on the role of individuals in the innovation management process, by concentrating on leaders and associated behaviors. Specifically, Entrepreneurial Leadership (EL) represent one of the most important fields of innovation management that has become increasingly multifaceted and interdisciplinary with its evolution. Thus, the purpose of this study is to examine a newly emerging research trend with a new lens that is “neuroscience”.Design/methodology/approach: This paper finds an evidence-based roadmap by reviewing the literature with a quantitative Bibliometric Analysis (BA) employing Co-Citation (Co-C) and bibliographic coupling analysis (BcA) to find linkages between the leadership and entrepreneurship literature and the neuroscience literature.Findings: This study identifies five promising groups of research areas such as the organizational approach, the biological approach, the cognitive approach, the emotional approach and it identify five future research topics such as dynamic skills in innovation exploitation process, the human aspect of leadership, the building process of leadership, the biological perspective of leadership and the application of neuroscience in the ecosystem. Moreover, we find an evidence-based roadmap for stimulating focused EL within the broad topic of innovation management research, to move the field forward.Originality/value: Although the past few years have observed the necessity of review studies on the subsets of biological factors, no reviews have sought to bring those different subsets together into a broader biological perspective. This study provides important indications on the interdisciplinary developments between the neuroscience aspects and EL, as a new emerging paradigm within the broad field of innovation management.

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.

The potential conflicts of interest between managers, stockholders and debtholders influence capital structure, corporate governance activities and investment policies, which, in turn, could give rise to inefficient managerial decisions and “suboptimal” investments that generally fall under the categories of problems of underinvestment and overinvestment. This paper intends to discuss these problems by identifying their causes, determining factors and the consequences on the value production processes, as well as to point out possible solutions to them. After having confronted the effects and their implications on firm governance activities by clarifying the relevance of the phenomenon and showing the main empirical data that emerged in the prevailing researches, we summarize the main financial proposals found in literature that can diminish their impact