Decision Support Systems For Financial Recovery and Turnaround Management: A Bibliometric Analysis

Economic volatility, complex business environments, and recurring financial crises have increased the need for structured and information-based decision-making. In this context, Decision Support Systems (DSS) play a key role in financial recovery and turnaround management by reducing uncertainty, integrating multiple criteria, and supporting strategic decisions. De-spite growing academic interest, research in this field remains fragmented. This study aims to provide a systematic overview of the scientific literature on DSS applied to financial recovery and turnaround management using a bibliometric approach. Articles indexed in the Scopus database were analysed through performance analysis and science mapping techniques. In ad-dition, keyword co-occurrence analysis using VOSviewer was conducted to identify dominant themes, conceptual clusters, and emerging research trends. The findings show a significant increase in publications over the last decade, mainly within management, economics, and finance. The results highlight the importance of DSS in crisis situations, particularly their integration with multicriteria decision-making methods, bankruptcy prediction models, artificial intelligence, and resilience-oriented approaches. However, important gaps persist, including limited connections between DSS and turnaround strategies and weak integration between failure prediction and strategic decision-making. Overall, this study contributes by offering a con-cise and structured overview of the evolution of research on DSS in financial recovery and turnaround management, supporting the identification of research gaps and future research directions.