Advancements in Bankruptcy Prediction Models and Bibliometric Analysis

被引:0
作者
de Abreu Gomes, Amanda Zetzsche [1 ]
Lopes, Cristina [1 ]
Pereira Bertuzi da Silva, Rui Filipe [1 ]
机构
[1] Inst Politecn Porto, ISCAP, CEOS PP, Porto, Portugal
来源
PROCEEDINGS OF THE 23RD EUROPEAN CONFERENCE ON RESEARCH METHODOLOGY FOR BUSINESS AND MANAGEMENT STUDIES, ECRM 2024 | 2024年 / 23卷
关键词
Bankruptcy prediction; Predictive models; Financial distress; Bibliometric analysis; Risk; FINANCIAL RATIOS; MACHINE; RISK;
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
Since the economic downturn of the 1930s, there has been a growing interest in predicting company bankruptcies. Though not a new topic, the prospect of business bankruptcy has gained increasing relevance due to globalisation. This study explores various methodologies employed in predicting bankruptcy. Preventing bankruptcies also bolsters economic stability by averting the adverse effects of insolvency on the community. Companies with a solid and flexible economic foundation are more likely to succeed. This article reviews existing literature, discusses prevalent predictive models, and presents a statistical analysis of bibliometric data associated with bankruptcy prediction. This work aims to answer the research question of identifying the trends over time in the econometric models used to predict bankruptcy. This article may be useful for finance and business students in providing an overview of the subject and for business managers to identify the key determinants of financial distress. Exploring the R package, Bibliometrix (R) demonstrates its efficacy as a powerful tool for science mapping.
引用
收藏
页码:82 / 91
页数:10
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