TY - JOUR
T1 - System dynamics modeling for construction management research: Critical review and future trends
AU - Liu, Mingqiang
AU - Le, Yun
AU - Hu, Yi
AU - Xia, Bo
AU - Skitmore, Martin
AU - Gao, Xianyi
N1 - Funding Information:
This paper is a redevelopment of an earlier conference paper presented to the 2017 Conference on Innovation in Production and Construction (IPC) at Curtin University, Perth, Australia. The work described was funded by the National Natural Science Foundation of China (Grant Nos. 71871164, 71841023, 71390523, 71501142), Australian Research Council (ARC) Discovery Project (Grant No. DP170101208), the China Scholarship Council (Grant No. 201706260214), International Cooperation Program for Postgraduates, Tongji University (Grant No. 2019GJX-SLT-009), Fundamental Research Funds for the Central University (Grant Nos. 3151910514, 22120180227) and the Shanghai Pujiang Program (Grant No. 16PJ1432400).
Funding Information:
This paper is a redevelopment of an earlier conference paper presented to the 2017 Conference on Innovation in Production and Construction (IPC) at Curtin University, Perth, Australia. The work described was funded by the National Natural Science Foundation of China (Grant Nos. 71871164, 71841023, 71390523, 71501142), Australian Research Council (ARC) Discovery Project (Grant No. DP170101208), the China Scholarship Council (Grant No. 201706260214), International Cooperation Program for Postgraduates, Tongji University (Grant No. 2019GJXSLT- 009), Fundamental Research Funds for the Central University (Grant Nos. 3151910514, 22120180227) and the Shanghai Pujiang Program (Grant No. 16PJ1432400).
Publisher Copyright:
© 2019 The Author(s). Published by VGTU Press.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2019/8/22
Y1 - 2019/8/22
N2 - As a result of growing complexities in the construction industry, system dynamics modeling (SDM) has been increasingly used in construction management (CM) research to explore complicated causal relationships at the various levels of construction and management processes. Given the rapid growth of SDM applications over the past two decades, a systematic review is needed to ascertain the state of the art and further trends in the area. This paper provides the results of a systematic analysis of 103 papers from 41 selected peer-reviewed journals from 1997 to 2016. The contributions of the papers are first analyzed, structured and formulated in terms of the year of publication, software involved, the combined use with other methods, and research design. With the assistance of the a keyword co-occurrence network analysis, eight research topics involving different internal and external complexities are identified, including: (1) sustainability, (2) project planning and control, (3) performance and effectiveness, (4) strategic management, (5) site and resource management, (6) risk analysis and management, (7) knowledge management, and (8) organization and stakeholder management. The analysis results reveal the pivotal role of SDM in streamlining different complicated casual relationships at the activity, project, and industry levels across the eight topics and its significant potential in uncovering the impact of complicated contextual conditions on project planning and control, effectiveness and performance, strategic management, and sustainability at the project and industry levels. Lastly, trends and recommendations for SDM applications are provided for future CM research. This paper provides a state of the art of SDM in CM applications and insights into opportunities and useful references for the future.
AB - As a result of growing complexities in the construction industry, system dynamics modeling (SDM) has been increasingly used in construction management (CM) research to explore complicated causal relationships at the various levels of construction and management processes. Given the rapid growth of SDM applications over the past two decades, a systematic review is needed to ascertain the state of the art and further trends in the area. This paper provides the results of a systematic analysis of 103 papers from 41 selected peer-reviewed journals from 1997 to 2016. The contributions of the papers are first analyzed, structured and formulated in terms of the year of publication, software involved, the combined use with other methods, and research design. With the assistance of the a keyword co-occurrence network analysis, eight research topics involving different internal and external complexities are identified, including: (1) sustainability, (2) project planning and control, (3) performance and effectiveness, (4) strategic management, (5) site and resource management, (6) risk analysis and management, (7) knowledge management, and (8) organization and stakeholder management. The analysis results reveal the pivotal role of SDM in streamlining different complicated casual relationships at the activity, project, and industry levels across the eight topics and its significant potential in uncovering the impact of complicated contextual conditions on project planning and control, effectiveness and performance, strategic management, and sustainability at the project and industry levels. Lastly, trends and recommendations for SDM applications are provided for future CM research. This paper provides a state of the art of SDM in CM applications and insights into opportunities and useful references for the future.
UR - http://www.scopus.com/inward/record.url?scp=85084696453&partnerID=8YFLogxK
U2 - 10.3846/jcem.2019.10518
DO - 10.3846/jcem.2019.10518
M3 - Article
AN - SCOPUS:85084696453
SN - 1392-3730
VL - 25
SP - 730
EP - 741
JO - Journal of Civil Engineering and Management
JF - Journal of Civil Engineering and Management
IS - 8
ER -