Predicting construction company insolvent failure: A scientometric analysis and qualitative review of research trends

Jun Wang*, Mao Li, Martin Skitmore, Jianli Chen

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

Abstract

The construction industry is infamous for its high insolvent failure rate because construction pro-jects 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 varia-bles, balancing model predictability and interpretability, and quantifying the causality and inter-correlation of variables. This study provides a big picture of existing research on predicting con-struction company insolvent failure and presents outcomes that can help researchers to compre-hend relevant literature, directing research policy-makers and editorial boards to adopt the promising themes for further research and development.
Original languageEnglish
Article number2290
JournalSustainability
Volume16
Issue number6
DOIs
Publication statusPublished - 2024

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