System Dynamics Modeling for Construction Management Research: Critical Review and Future Trends

Liu, Mingqiang; Le, Yun; Hu, Yi; Xia, Bo; Skitmore, Martin; Gao, Xuexu

doi:10.3846/jcem.2019.10518

Cited by 18 publications

(22 citation statements)

References 87 publications

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“…The first round of selection checked the articles' title, abstract and keywords information, followed by a second round of selection conducted by reading and analyzing the whole article to double-check articles. The following criteria were used [41]: ANN was studied as the main technology or played an important role rather than a comparison. Finally, 112 articles were selected and used in this study (Table 2).…”

Section: Article Selectionmentioning

confidence: 99%

Application of Artificial Neural Networks in Construction Management: Current Status and Future Directions

et al. 2021

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Artificial neural networks (ANN) exhibit excellent performance in complex problems and have been increasingly applied in the research field of construction management (CM) over the last few decades. However, few papers draw up a systematic review to evaluate the state-of-the-art research on ANN in CM. In this paper, content analysis is performed to comprehensively analyze 112 related bibliographic records retrieved from seven selected top journals published between 2000 and 2020. The results indicate that the applications of ANN of interest in CM research have been significantly increasing since 2015. Back-propagation was the most widely used algorithm in training ANN. Integrated ANN with fuzzy logic/genetic algorithm was the most commonly employed way of addressing the CM problem. In addition, 11 application fields and 31 research topics were identified, with the primary research interests focusing on cost, performance, and safety. Lastly, challenges and future directions for ANN in CM were put forward from four main areas of input data, modeling, application fields, and emerging technologies. This paper provides a comprehensive understanding of the application of ANN in CM research and useful reference for the future.

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Section: Article Selectionmentioning

confidence: 99%

Application of Artificial Neural Networks in Construction Management: Current Status and Future Directions

et al. 2021

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“…The SD method was proposed by Professor J. W. Forrester in the United States. In recent years, it has become a pivotal approach to modeling the interrelationships and feedbacks that exist within complex systems [ 63 ]. It has reached maturity in applications to risk management in construction projects.…”

Section: Literature Reviewmentioning

confidence: 99%

Risk Assessment of High-Speed Rail Projects: A Risk Coupling Model Based on System Dynamics

Xue

Pan

Jia

et al. 2020

IJERPH

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Due to their characteristics and multiple objectives, high-speed rail (HSR) projects carry more complex risks than conventional projects and high correlation and conductivity are among the associated risk factors. Previous risk assessment frameworks for rail infrastructure have ignored the effects of risk interactions that inflate risk levels, namely, risk coupling effects. Based on a system dynamics method, this paper develops a risk coupling model for HSR project risk assessments. A risk factor list is established from a literature review, and relationships analysed using a case study and expert interviews. System dynamics equations are constructed and their parameters obtained by expert evaluations of risk factors. The proposed model is applied to a real-world HSR project to demonstrate it in detail. The model can evaluate the risk levels of HSR projects during a simulation period. In particular, it can identify the key coupling effects that are the main increased risk. It provides a significant resource, using which HSR project managers can identify and mitigate risks.

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“…At the same time, the plans of construction management constantly change with time [8]. Therefore, SD is very suitable for simulating and analyzing construction projects to maximize the positive impact of complex and dynamic factors [9].…”

Section: Introductionmentioning

confidence: 99%

A Scientometric Review of System Dynamics Applications in Construction Management Research

Yang

Lai

et al. 2020

Sustainability

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Construction management can be regarded as a complex and dynamic system. In recent years, system dynamics (SD) has been widely applied to solve the complex and dynamic problems in the construction management. However, there is a lack of a scientometric analysis to investigate SD applications in construction management from an objective perspective. To fill out this research gap, this study retrieved a total of 222 relevant articles from the Scopus database. Then, VOSviewer was employed to analyze the collected literature from five aspects (i.e., co-authorship, published journals, co-occurring keywords, article citations, and regions). Based on the analysis results, four mainstream research themes were identified and discussed, including “risk management”, “waste management”, “energy management”, and “construction productivity”. In addition, future research directions, such as “construction risk allocation in PPP projects”, “evaluating the economic feasibility of construction waste landfilling centers”, “identifying the variables affecting lighting infrastructure energy consumption”, and “assessing construction productivity for technology-intensive activities”, were proposed. The contribution of this study lies in that it helps both scholars and practitioners to solve the complex and dynamic problems in construction management.

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System Dynamics Modeling for Construction Management Research: Critical Review and Future Trends

Cited by 18 publications

References 87 publications

Application of Artificial Neural Networks in Construction Management: Current Status and Future Directions

Application of Artificial Neural Networks in Construction Management: Current Status and Future Directions

Risk Assessment of High-Speed Rail Projects: A Risk Coupling Model Based on System Dynamics

A Scientometric Review of System Dynamics Applications in Construction Management Research

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