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Business Failure Prediction Models: A Bibliometric Analysis

In: Mindful Topics on Risk Analysis and Design of Experiments

Author

Listed:
  • Giuseppe Giordano

    (University of Salerno)

  • Marialuisa Restaino

    (University of Salerno)

Abstract

The business failure prediction (BFP) research area is attracting renewed attention due to increasing complexity and uncertainty of modern markets, as witnessed by financial crisis in last decade. Since many predictive models have been developed using various analytical tools, it should be important to capture the development of the BFP models, underlying their limitations and strengths. Using the Web of Science database, the purpose of this paper is to investigate the evolution of the scientific studies in the field of BFP within a bibliometric analysis. The research production from 1990 to 2019 is analyzed, and the most relevant research products in the field are identified and classified by papers, authors, institutions and countries. Moreover, the most influential key-words are clustered according to similarity and visualized in a network. Finally, the social structure between countries and affiliations are investigated in order to capture the relationship between authors.

Suggested Citation

  • Giuseppe Giordano & Marialuisa Restaino, 2022. "Business Failure Prediction Models: A Bibliometric Analysis," Springer Books, in: Jürgen Pilz & Teresa A. Oliveira & Karl Moder & Christos P. Kitsos (ed.), Mindful Topics on Risk Analysis and Design of Experiments, pages 62-77, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-06685-6_5
    DOI: 10.1007/978-3-031-06685-6_5
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