Browsing by Author "Pisoni, Galena"

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Editorial Boards of Finance Journals: The Gender Gap and Social Networks
(Springer, 2025) Bedowska-Sojka, Barbara; Tarantola, Claudia; Mare, Codruta; Paccagnini, Alessia; Ozturkkal, Belma; Pisoni, Galena; Skaftadotti, Hanna Kristin
We investigate gender disparities and network linkages among editors of Finance journals at the end of 2022. The role of journal editors in shaping academic disciplines is crucial, yet gender imbalances and the geographic concentration of editors remain poorly understood. Ethical considerations arise when examining the representation of women on editorial boards, as these imbalances can impact academic equity and the diversity of perspectives. We examine the gender composition of editorial boards and uncover the network structures among editors, seeking to shed light on the concentration of editorial power and its implications for diversity and inclusion. Our findings reveal that women account for an average of 20% of all editors, with notable variations across countries. Additionally, editorial affiliations are heavily concentrated in the United States and the United Kingdom. Through typological metrics, we identify highly connected editors with significant board memberships. While gender ratios remain consistent in substructures involving highly central editors or those serving on multiple boards, men consistently outnumber women.
Investigating Gender Gap in Editorial Boards of Finance Journals: A Social Network Perspective
(Springer International Publishing AG, 2025) Tarantola, Claudia; Bedowska-Sojka, Barbara; Mare, Codruta; Paccagnini, Alessia; Ozturkkal, Belma; Pisoni, Galena; Skaftadottir, Hanna Kristin; International Trade and Finance; 03. Faculty of Economics, Administrative and Social Sciences; 01. Kadir Has University
This study explores gender disparities and network connections among Finance journal editors worldwide, focusing on the crucial role these editors play in shaping academic fields and promoting diversity and equity in publishing. Despite efforts by publishers to present gender profiles and maintain balance in reviewer selection, significant gender imbalances persist, particularly affecting women's representation on editorial boards. Utilizing network analysis, the study documents the prevalence of a few highly connected editors and underscores the gender disparity in editorial roles, highlighting the need for policy interventions to enhance diversity and inclusion. Utilizing various typological metrics, we identify a core group of highly interconnected editors who hold positions on multiple boards. The gender distribution remains skewed towards men, even among editors with central roles or those serving on numerous boards. This research underscores the persistent gender gaps within academic publishing networks and calls for a deeper understanding and remediation of these disparities to foster diversity and equity in the academic landscape.
The Synergy of Statistical and Fuzzy Logic Approaches in Mining Patterns from the Peer-to-Peer Lending Data
(Pergamon-Elsevier Science Ltd, 2026) Hudec, Miroslav; Molnar, Balint; Pisoni, Galena; Vucetic, Miljan; Barcakova, Nina; Bedowska-Sojka, Barbara; Iannario, Maria; 01. Kadir Has University
Statistical measures, such as correlation, compute numeric values. However, it is not always the best option for domain experts. A promising way is to augment these measures linguistically. Therefore, the main objective of this work is the synergy of statistical and fuzzy logic approaches in mining and interpreting valuable information from financial lending data. The correlation reveals whether attributes are related while exhibiting relatively low computational costs. Fuzzy functional dependencies recognize the direction of influence but are demanding in terms of computational cost. Finally, linguistic summaries explore and interpret dependencies between the subdomains of the considered attributes. These two approaches are less influenced by a smaller vagueness in the data. In addition, the support for decision making validated by diverse approaches and explained from different points of view is more reliable. These approaches are integrated and applied to peer-to-peer (P2P) anonymized lending data consisting of 266,483 loans. Among other things, a significant correlation between loan amount and loan duration (r = 0.25) is explained further, indicating that the direction of influence is slightly stronger from loan duration to loan amount than the opposite case. At the same time, the dependency is very strong from low duration to low amount, but relatively weak from high duration to high amount. Finally, further research and application directions are outlined.