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Predicting Construction Company Insolvent Failure: A Scientometric Analysis and Qualitative Review of Research Trends

Author

Listed:
  • Jun Wang

    (School of Management Engineering, Qingdao University of Technology, Qingdao 266520, China)

  • Mao Li

    (School of Management Engineering, Qingdao University of Technology, Qingdao 266520, China
    PetroChina Huabei Oilfield Company, Cangzhou 062552, China)

  • Martin Skitmore

    (Faculty of Society and Design, Bond University, Robina, QLD 4226, Australia)

  • Jianli Chen

    (Department of Civil Engineering, University of Utah, Salt Lake City, UT 84112, USA)

Abstract

The construction industry is infamous for its high insolvent failure rate because construction projects require complex processes, heavy investment, and long durations. However, there is a lack of a comprehensive framework and a requirement for such a framework in predicting the financial distress of construction firms. This paper reviews relevant literature to summarize the existing knowledge, identify current problems, and point out future research directions needed in this area using a scientometric analysis approach. Based on a total of 93 journal articles relating to predicting construction company failure extracted from multiple databases, this study conducts a holistic review in terms of chronological trends, journal sources, active researchers, frequent keywords, and most cited documents. Qualitative analysis is also provided to explore the data collection and processing procedures, model selection and development process, and detailed performance evaluation metrics. Four research gaps and future directions for predicting construction company failure are presented: selecting a broader data sample, incorporating more heterogeneous variables, balancing model predictability and interpretability, and quantifying the causality and intercorrelation of variables. This study provides a big picture of existing research on predicting construction company insolvent failure and presents outcomes that can help researchers to comprehend relevant literature, directing research policy-makers and editorial boards to adopt the promising themes for further research and development.

Suggested Citation

  • Jun Wang & Mao Li & Martin Skitmore & Jianli Chen, 2024. "Predicting Construction Company Insolvent Failure: A Scientometric Analysis and Qualitative Review of Research Trends," Sustainability, MDPI, vol. 16(6), pages 1-22, March.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:6:p:2290-:d:1354263
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    References listed on IDEAS

    as
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