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Explainable credit risk modeling with hybrid tabular deep learning and adaptive feature routing

R. John Martin, Ahmad Khawaji, S. Sujatha

Well defined and transparent credit risk evaluation continues to be a fundamental issue in financial decision-making, particularly when dealing with intricate borrower profiles in the forms of organized tabular data. While traditional machine learning models often lack interpretability for predictive accuracy, recent deep learning approaches struggle to generalize across such data formats. We propose an innovative hybrid Tabular Deep Learning system that combines feature tokenizer transformer … more

Environmental innovation and green low-carbon transitions: The moderating role of green regulatory pressure

Tingqian Pu

Environmental innovation is widely recognized as a key driver of sustainability, reducing greenhouse gas emissions and enhancing resource efficiency. However, the mechanisms through which it contributes to green low-carbon transitions remain underexplored, particularly in the context of varying regulatory environments. This study examines the relationship between environmental innovation and green low-carbon transitions, focusing on the moderating role of green regulátory pressure. Using panel… more

Changing times, changing drives: Entrepreneurial motivation across generations

Dominik Salat, Jarmila Duhacek Sebestova

Entrepreneurs from generation to generation play a significant role in the business environment. Understanding this issue, especially by policymakers, is crucial for development. Misunderstanding or lack of interest often leads to inaction or incorrect decisions, creating barriers for current and potential entrepreneurs. Each generation evolves in its own era, and over time, each will fade and be replaced by a new, undefined generation. Policymakers would be interested in understanding these… more

The organizational innovation climate on affecting individuals’ innovative work behavior: The roles of knowledge sharing and creative self-efficacy

Yu Li, Yang Chen, Changfeng Wang

Technological advancement promotes social changes and brings both opportunities and challenges to organizations. For high-tech enterprises in great demand of innovation and knowledge management, exploring what factors affect employees’ innovative work behavior becomes emergent. This study investigates the impact of organizational innovation climate on employees’ innovative work behavior, with knowledge sharing and creative self-efficacy as mediators. The structural model was tested using sample… more

Reporting practices in Romania: Propelling corporate sustainability forward through firm performance

Dorina Nita, Lia Alexandra Baltador, Codruta Cornelia Dura, Elias Appiah-Kubi

In the context of growing global emphasis on sustainable business practices, understanding the financial drivers of corporate sustainability has become increasingly important. This study examines key financial and market indicators to understand their influence on corporate sustainability disclosure. Focusing on Romanian companies, it investigates how market share, financial ratings, probability of insolvency, and market value shape sustainability outcomes. The dataset was sourced from Azores… more

Banks in smart cities. A bibliometric and thematic review

Zbigniew Korzeb, Danuta Szpilko, Filippo di Pietro

This article aims to systematize scientific research on the role of banks in the context of the smart city concept. A bibliometric study of papers obtained from the Scopus and Web of Science databases between 2011 and 2025. Following the application of restricting criteria throughout the search procedure, 110 records were retrieved from Web of Science and 312 from the Scopus database. This study highlights the possible gaps found and provides an appraisal of the current state and future… more

Analyzing user perceptions and adoption of urban public transport applications through natural language processing

Juan Antonio Aguilar-Moreno, Pedro R. Palos-Sanchez, Rafael Pozo-Barajas, Teresa Duarte-Atoche

An enhanced understanding of urban public transport app adoption has been achieved by applying innovative data mining and sentiment analysis techniques to large user review datasets from Google Play Store and Apple App Store, covering major European metropolitan areas. Natural language processing (NLP) methods were employed to perform sentiment analysis, emotion analysis, and topic modeling (LDA), extracting valuable insights from unstructured text. The results highlight the importance of… more