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

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

doi:10.3390/su16062290

Cited by 3 publications

(1 citation statement)

References 131 publications

(232 reference statements)

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“…The review's second stage includes scientometric analysis, a popular method for domain analysis and visualization [42]. This has been widely used to support systematic literature reviews in various aspects of building construction research (e.g., [43][44][45][46][47]). VOSViewer is a text-mining tool that generates network-based visualizations using distance metrics.…”

Section: Scientometric Analysismentioning

confidence: 99%

Structural Equation Modeling in Technology Adoption and Use in the Construction Industry: A Scientometric Analysis and Qualitative Review

Fu,

Wang,

et al. 2024

Sustainability

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Considering the emergence and adoption of various innovative technologies, the construction industry has undergone transformation into a more secure, highly efficient, and ecologically sustainable landscape. An increasing number of studies uses the structural equation modeling (SEM) method to explore the dynamics of technology adoption and use within the construction sector. Previous studies have mainly focused on qualitative analysis using the SEM method to analyze technology adoption and usage in the construction industry. This study, however, distinguishes itself from previous research by focusing on the SEM method itself and conducting a systematic analysis using scientometric methods. Based on a total of 140 relevant journal articles, this study adopts a scientometric analysis approach to conduct a holistic review encompassing sources, researchers, keywords, and highly cited documents. The research findings are as follows: (1) the primary focus of the current research topics is on BIM technology; (2) most studies employ cross-sectional SEM instead of longitudinal SEM; (3) there is a deficiency in the theoretical foundation for designing SEM in current research; and (4) the selection of either reflective or formative measures lacks sufficient rigor. Qualitative analysis is used to examine prevailing issues in research design and address the intricate technicalities and potential challenges inherent in the SEM method. Three research gaps and future directions are presented: diversifying regions of study and research topics, incorporating theoretical support for research design, and carefully choosing reflective or formative measures. The findings provide a comprehensive roadmap and valuable reference for future research in this field.

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Section: Scientometric Analysismentioning

confidence: 99%

Structural Equation Modeling in Technology Adoption and Use in the Construction Industry: A Scientometric Analysis and Qualitative Review

Fu,

Wang,

et al. 2024

Sustainability

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Using firm-level intellectual capital to achieve strategic sustainability: examination of phenomenon of business failure in terms of the critical events

Pereira,

Jayawardena,

Sindhwani

et al. 2024

JIC

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PurposeThe purpose of this study is twofold. Firstly, the authors have conducted a systematic investigation considering the historical pandemic periods (1991–2021) over 30 years to identify critical factors and business failure phenomenon during pandemics to explore “what”, “why” and “how” factors contributing to business failure during the COVID-19 pandemic and secondly identified interlinks of these factors to explain the phenomenon of business failure strategically through various quantitative models.Design/methodology/approachFirstly, the critical factors were identified through previous literature and systematically reported in accordance with the PRISMA guidelines. To remove any bias in critical factor selection, Delphi method was employed. In the second phase, m-TISM approach was adopted to understand the interrelationships of the factors to develop the hierarchy levels. Lastly, MICMAC analysis was also done to evaluate the driving and dependence powers of the critical factors. For implementation of the stated methodology, expert opinion was collected to assess the critical factors based on their knowledge and experience. A total of seven experts were involved in this study.FindingsTwo major takeaways from the results of phase one were that “external environmental changes” was at the highest level and had the highest driving power as well as the lowest dependence power, while “inappropriate marketing techniques” was at the lowest level and had the highest dependence and lowest driving powers.Practical implicationsThe ever-developing digital technologies act as a synonym to innovation and are shaping up to be the key to future-proofing any industry. However, before one can move towards developing effective strategies to mitigate any business disruptions, there is a need to assess the causes of business failures in the first place which is a major managerial implication identified through this study.Originality/valueThis paper can be considered as the first few studies to conduct a systematic investigation considering the historical pandemic periods (1991–2021) over 30 years to identify critical factors and business failure phenomenon during pandemics to explore “what”, “why” and “how” factors contributing to business failure during the COVID-19 pandemic and secondly identified interlinks of these factors to explain the phenomenon of business failure strategically through various quantitative models.

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The Application of Machine Learning and Deep Learning in Intelligent Transportation: A Scientometric Analysis and Qualitative Review of Research Trends

Zhang,

Wang,

Zang

et al. 2024

Sustainability

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Machine learning (ML) and deep learning (DL) have become very popular in the research community for addressing complex issues in intelligent transportation. This has resulted in many scientific papers being published across various transportation topics over the past decade. This paper conducts a systematic review of the intelligent transportation literature using a scientometric analysis, aiming to summarize what is already known, identify current research trends, evaluate academic impacts, and suggest future research directions. The study provides a detailed review by analyzing 113 journal articles from the Web of Science (WoS) database. It examines the growth of publications over time, explores the collaboration patterns of key contributors, such as researchers, countries, and organizations, and employs techniques such as co-authorship analysis and keyword co-occurrence analysis to delve into the publication clusters and identify emerging research topics. Nine emerging sub-topics are identified and qualitatively discussed. The outcomes include recognizing pioneering researchers in intelligent transportation for potential collaboration opportunities, identifying reliable sources of information for publishing new work, and aiding researchers in selecting the best solutions for specific problems. These findings help researchers better understand the application of ML and DL in the intelligent transportation literature and guide research policymakers and editorial boards in selecting promising research topics for further research and development.

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

Cited by 3 publications

References 131 publications

Structural Equation Modeling in Technology Adoption and Use in the Construction Industry: A Scientometric Analysis and Qualitative Review

Structural Equation Modeling in Technology Adoption and Use in the Construction Industry: A Scientometric Analysis and Qualitative Review

Using firm-level intellectual capital to achieve strategic sustainability: examination of phenomenon of business failure in terms of the critical events

The Application of Machine Learning and Deep Learning in Intelligent Transportation: A Scientometric Analysis and Qualitative Review of Research Trends

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