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Abstract

Personal bankruptcy is a pertinent topic to discuss due to the surge in personal bankruptcy cases around the world and it is an important indicator of household financial problems nationally. However, only few comprehensive reviews have been conducted to date. Hence, this study provides a bibliometric review of 210 studies on personal bankruptcy authored by 496 scholars. Bibliographical data were extracted from the Scopus database and analyzed it using the Bibliometrix-R software. Based on the citation analysis metrics, we revealed the most influential articles, journals, authors, and institutions. Using the network and conceptual structure analysis, we identified three underlying research clusters: (1) student loan default, (2) financial psychology, and (3) personal bankruptcy law; and three emerging research clusters: (1) credit scoring, (2) machine learning, and (3) data mining. The results of our study provide valuable insights to readers, in gleaning a general overview of the research landscape, including the historical evolution, potential collaboration partners, and the future research direction of the personal bankruptcy study. The implications of the study include further exploration of under-researched areas, especially the integration of advanced technologies like artificial intelligence and data analytics in managing personal bankruptcy issues. By uncovering trends and emerging technologies (e.g., machine learning and data mining), the study may guide policymakers, financial institutions, and other stakeholders in addressing household financial problems and improving bankruptcy-related processes.

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