Risk and Bankruptcy Research: Mapping the State of the Art

Almeida, Luís António Gomes

doi:10.3390/jrfm16080361

Cited by 6 publications

(3 citation statements)

References 72 publications

(107 reference statements)

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“…Applying Zipf's Law to analyze word frequency can benefit indexing in a particular domain. Similar to the works of Almeida (2023) and Almeida and Vieira (2023), we evaluate if the three vital bibliometric laws apply to the study's data.…”

Section: Keyword Frequency Via Zipf's Law Lensmentioning

confidence: 99%

Analyzing Trends in Green Financial Instrument Issuance for Climate Finance in Capital Markets

Maina,

Gyenge,

Fekete-Farkas

et al. 2024

JRFM

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Numerous stakeholders concur that tackling the climate change effect requires massive financial mobilization from the public and private sectors to reduce the climate financing gap. Capital markets are among the key players fostering this mobilization by issuing green financial instruments and facilitating capital flows to green investments. The study aimed to conduct a bibliometric analysis to fill a knowledge gap by evaluating the status and linkages in the literature on capital markets’ green financial instrument issuances. We utilized the Bibliometrix R package and VOS viewer to analyze 314 relevant publications from the Web of Science in 2017–2023 following the Sustainable Stock Exchanges’ green finance voluntary action plan. The analysis entailed mapping the scientific production trends, journal significance, author productivity, keyword linkages, emerging and trending topics, and collaborations within social structures. Further, the study assessed the applicability of Bradford’s, Zipf’s, and Lotka’s bibliometric laws. We highlight six conclusions based on the analysis, their relevance to various stakeholders, and future research directions. The findings are essential in enhancing the decision-making process of policymakers, corporations, responsible investors, and researchers interested in understanding the effectiveness and impact of green financial instruments.

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Section: Keyword Frequency Via Zipf's Law Lensmentioning

confidence: 99%

Analyzing Trends in Green Financial Instrument Issuance for Climate Finance in Capital Markets

Maina,

Gyenge,

Fekete-Farkas

et al. 2024

JRFM

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“…For Tavares et al (2021) and Santos et al (2022), image risks are linked to the company's reputation, which it transfers abroad. On the other hand, these authors consider Risks 2024, 12, 91 2 of 20 that financial risks are associated with the economic and financial capacity of companies and the way they carry out their business, an idea corroborated by Almeida (2023). Financial risks are distinguished between short-term and medium-and long-term risks.…”

Section: Introductionmentioning

confidence: 99%

Determinants of Corporate Indebtedness in Portugal: An Analysis of Financial Behaviour Clusters

Tavares,

Santos,

Oliveira

et al. 2024

Risks

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Corporate indebtedness is a powerful tool in determining a company’s financial health with impacts on its image and reputation. The main objective of this research is to study the determining factors in corporate indebtedness in Portugal. It also has the secondary objectives of creating clusters of companies’ behaviour in relation to the use of credit and verifying their differences in relation to the characteristics of the companies. It uses a quantitative methodology based on a questionnaire survey of 1957 Portuguese companies. The results of the factor analysis show the formation of six determining factors in corporate indebtedness, namely the negotiating relationship with banks, financing, cycle and indebtedness, company operating performance, guarantees used to obtain bank financing and financing risk analysis as well as secondary forms of bank financing. The application of cluster analysis to the six factors formed led to the classification of companies into three clusters: the resilient financial cluster, the operational excellence cluster and the strategic financial cluster. There are several statistically significant differences in the corporate financing factors in relation to the clusters to which they belong. The evidence of the factors and clusters explaining company financing provides insights for improving credit access practices and for implementing public policies that facilitate access to credit and promote economic development.

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“…The data was analyzed using many programs (RStudio, VOSviewer, and Excel), and the most active actors in terms of nations, institutions, sources, documents, and authors were shown. (Almeida, 2023) To identify academic domains that have made substantial research contributions, we summarized 711 bibliometric publications on AI & its sub-sets and BDA that were published in various fields. From the Scopus Q1 and Q2 journal databases, we selected bibliometric review articles from publications between 2012 and 2022.…”

mentioning

confidence: 99%

A Bibliometric Analysis of Corporate Bankruptcy Prediction Research: Trends and Insights

2024

Journal of Informatics Education and Research

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This paper is the outcome of a bibliometric study aimed at providing a worldwide overview of the prediction of corporate bankruptcy. This research paper provides a thorough examination of bibliometric analysis in the field of corporate bankruptcy prediction, specifically emphasising Artificial Intelligence-based models. This study uses rigorous bibliometric methods to identify and analyse the journals with the highest productivity, the papers with the most citations, and the authors with the most citations in this particular field. In addition, the research environment is illuminated by descriptive analysis of authors, countries, journals, and keywords. The study also examines the expansion and patterns in publications, offering significant insights for identifying periods of heightened interest and possible domains for additional investigation. In addition, this study examines country-specific annotations and analyzes individual and country-specific co-authorship to reveal collaboration networks and research contributions in various locations. Co-citation analysis and co-occurrence analysis of journals provide a more profound understanding of how knowledge is spread and the formation of topic clusters within the field. The results of this study have important consequences for research institutions and politicians, providing valuable insights that can lead to future research and influence policy decisions in the field of corporate bankruptcy prediction. It will guide future research and advance the discourse on financial stability and risk management.

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Risk and Bankruptcy Research: Mapping the State of the Art

Cited by 6 publications

References 72 publications

Analyzing Trends in Green Financial Instrument Issuance for Climate Finance in Capital Markets

Analyzing Trends in Green Financial Instrument Issuance for Climate Finance in Capital Markets

Determinants of Corporate Indebtedness in Portugal: An Analysis of Financial Behaviour Clusters

A Bibliometric Analysis of Corporate Bankruptcy Prediction Research: Trends and Insights

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