Share:


A review of agent-based modeling in construction management: an analytical framework based on multiple objectives

    Wenyao Liu Affiliation
    ; Qingfeng Meng Affiliation
    ; Hanhao Zhi Affiliation
    ; Zhen Li Affiliation
    ; Xin Hu Affiliation

Abstract

The increased complexity of construction projects has caused various management challenges. To clarify the mechanism of construction system complexity and improve the ability to manage the complexity of construction projects, the Agent-based modeling (ABM) method has been introduced and used in the construction management field. Nevertheless, a systematic, holistic, and panoramic understanding of the use of the ABM model in the construction management field is still lacking. To address this research gap, this study reviewed 133 historical explorations retrieved from the database of Web of Science. By using the multiple objectives of construction management as the literature classification framework, the study described the research status of the agent-based modeling method in the field of construction management. On this basis, this paper suggested the improvement paths in the application of this method from three aspects. It is expected that this study will provide a theoretical basis for enhancing understanding of the use of the ABM method in construction management, and also provide insights for future explorations in the area.

Keyword : literature review, agent-based modeling, construction management, multiple objectives, bibliometric analysis

How to Cite
Liu, W., Meng, Q., Zhi, H., Li, Z., & Hu, X. (2024). A review of agent-based modeling in construction management: an analytical framework based on multiple objectives. Journal of Civil Engineering and Management, 30(3), 200–219. https://doi.org/10.3846/jcem.2024.20949
Published in Issue
Mar 8, 2024
Abstract Views
1086
PDF Downloads
559
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Agarwal, R., Chandrasekaran, S., & Sridhar, M. (2016). Imagining construction’s digital future. McKinsey & Company. https://www.mckinsey.com/capabilities/operations/our-insights/imagining-constructions-digital-future

Ahn, S., & Lee, S. (2015). Methodology for creating empirically supported agent-based simulation with survey data for studying group behavior of construction workers. Journal of Construction Engineering and Management, 141(1), Article 04014065. https://doi.org/10.1061/(asce)co.1943-7862.0000918

Ahn, S., Lee, S., & Steel, R. P. (2013). Effects of workers’ social learning: Focusing on absence behavior. Journal of Construction Engineering and Management, 139(8), 1015–1025. https://doi.org/10.1061/(asce)co.1943-7862.0000680

Akcay, E. C., & Arditi, D. (2022). Predicting employer and worker responsibilities in accidents that involve falls in building construction sites. Buildings, 12(4), Article 464. https://doi.org/10.3390/buildings12040464

Ali, Q., Thaheem, M. J., Ullah, F., & Sepasgozar, S. M. E. (2020). The performance gap in energy-efficient office buildings: How the occupants can help?. Energies, 13(6), Article 1480. https://doi.org/10.3390/en13061480

AlRyalat, S. A. S., Malkawi, L. W., & Momani, S. M. (2019). Comparing bibliometric analysis using PubMed, Scopus, and Web of Science databases. Journal of Visualized Experiments, 152, Article e58494. https://doi.org/10.3791/58494

Araya, F. (2020). Modelación basada en agentes [Agent based modeling]. Revista Ingeniería de Construcción, 35(2), 111–118. https://doi.org/10.4067/S0718-50732020000200111

Araya, F. (2021). Modeling the spread of COVID-19 on construction workers: An agent-based approach. Safety Science, 133, Article 105022. https://doi.org/10.1016/j.ssci.2020.105022

Araya, F. (2022). Modeling the influence of multiskilled construction workers in the context of the covid-19 pandemic using an agent-based approach. Revista De La Construccion, 21(1), 105–117. https://doi.org/10.7764/rdlc.21.1.105

Arteaga, C., & Park, J. (2020). Building design and its effect on evacuation efficiency and casualty levels during an indoor active shooter incident. Safety Science, 127, Article 104692. https://doi.org/10.1016/j.ssci.2020.104692

Asgari, S., Awwad, R., Kandil, A., & Odeh, I. (2016). Impact of considering need for work and risk on performance of construction contractors: An agent-based approach. Automation in Construction, 65, 9–20. https://doi.org/10.1016/j.autcon.2016.01.004

Awwad, R., & Ammoury, M. (2019). Owner’s perspective on evolution of bid prices under various price-driven bid selection methods. Journal of Computing in Civil Engineering, 33(2), Article 04018061. https://doi.org/10.1061/(asce)cp.1943-5487.0000803

Awwad, R., Asgari, S., & Kandil, A. (2015). Developing a virtual laboratory for construction bidding environment using Agent-Based Modeling. Journal of Computing in Civil Engineering, 29(6), Article 04014105. https://doi.org/10.1061/(asce)cp.1943-5487.0000440

Awwad, R., Shdid, C. A., & Tayeh, R. (2017). Agent-based model for simulating construction safety climate in a market environment. Journal of Computing in Civil Engineering, 31(1), Article 05016003. https://doi.org/10.1061/(asce)cp.1943-5487.0000612

Azar, E., & Al Ansari, H. (2017). Multilayer agent-based modeling and social network framework to evaluate energy feedback methods for groups of buildings. Journal of Computing in Civil Engineering, 31(4), Article 04017007. https://doi.org/10.1061/(asce)cp.1943-5487.0000651

Azar, E., Nikolopoulou, C., & Papadopoulos, S. (2016). Integrating and optimizing metrics of sustainable building performance using human-focused agent-based modeling. Applied Energy, 183, 926–937. https://doi.org/10.1016/j.apenergy.2016.09.022

Ben-Alon, L., & Sacks, R. (2017). Simulating the behavior of trade crews in construction using agents and building information modeling. Automation in Construction, 74, 12–27. https://doi.org/10.1016/j.autcon.2016.11.002

Carbo, J., Sanchez-Pi, N., & Molina, J. M. (2018). Agent-based simulation with NetLogo to evaluate ambient intelligence scenarios. Journal of Simulation, 12(1), 42–52. https://doi.org/10.1057/jos.2016.10

Chen, C. (2017). Science mapping: a systematic review of the literature. Journal of Data Information Science, 2(2), 1–40. https://doi.org/10.1515/jdis-2017-0006

Chen, C., Lou, Y., Li, X.-Y., Lv, Z.-T., Zhang, L.-Q., & Mao, W. (2020). Mapping current research and identifying hotspots on mesenchymal stem cells in cardiovascular disease. Stem Cell Research & Therapy, 11(1), Article 498. https://doi.org/10.1186/s13287-020-02009-7

Cheng, L., Guo, H., & Lin, H. (2021). Evolutionary model of coal mine safety system based on multi-agent modeling. Process Safety and Environmental Protection, 147, 1193–1200. https://doi.org/10.1016/j.psep.2021.01.046

Choi, B., & Lee, S. (2018). An empirically based agent-based model of the sociocognitive process of construction workers’ safety behavior. Journal of Construction Engineering and Management, 144(2), Article 04017102. https://doi.org/10.1061/(asce)co.1943-7862.0001421

Dabirian, S., Khanzadi, M., & Moussazadeh, M. (2016). Predicting labor costs in construction projects using agent-based modeling and simulation. Scientia Iranica, 23(1), 91–101. https://doi.org/10.24200/sci.2016.2100

Dang, Q., Luo, Z., Ouyang, C., & Wang, L. (2021). First systematic review on health communication using the CiteSpace Software in China: Exploring its research hotspots and frontiers. International Journal of Environmental Research and Public Health, 18(24), Article 13008. https://doi.org/10.3390/ijerph182413008

Ding, Z., Wang, Y., & Zou, P. X. W. (2016). An agent based environmental impact assessment of building demolition waste management: Conventional versus green management. Journal of Cleaner Production, 133, 1136–1153. https://doi.org/10.1016/j.jclepro.2016.06.054

Ding, Z., Gong, W., Fan, Z., Tam, V. W. Y., & Illankoon, I. M. C. S. (2020). Agent-based modelling for environmental impact of renovation waste in Shenzhen, China. Proceedings of the Institution of Civil Engineers-Engineering Sustainability, 173(8), 397–413. https://doi.org/10.1680/jensu.19.00040

Ding, Z., Liu, R., Wang, Y., Tam, V. W. Y., & Ma, M. (2021). An agent-based model approach for urban demolition waste quantification and a management framework for stakeholders. Journal of Cleaner Production, 285, Article 124897. https://doi.org/10.1016/j.jclepro.2020.124897

Du, J., & El-Gafy, M. (2012). Virtual organizational imitation for construction enterprises: Agent-based simulation framework for exploring human and organizational implications in construction management. Journal of Computing in Civil Engineering, 26(3), 282–297. https://doi.org/10.1061/(asce)cp.1943-5487.0000122

Du, J., & El-Gafy, M. (2015). Using agent-based modeling to investigate goal incongruence issues in proposal development: Case study of an EPC project. Journal of Management in Engineering, 31(6), Article 5014025. https://doi.org/10.1061/(asce)me.1943-5479.0000343

Du, J., Jing, H., Castro-Lacouture, D., & Sugumaran, V. (2020). Multi-agent simulation for managing design changes in prefabricated construction projects. Engineering, Construction and Architectural Management, 27(1), 270–295. https://doi.org/10.1108/ecam-11-2018-0524

Du, H., Han, Q., Sun, J., & Wang, C. C. (2023). Adoptions of prefabrication in residential sector in China: agent-based policy option exploration. Engineering, Construction and Architectural Management, 30(4), 1697–1725. https://doi.org/10.1108/ecam-04-2021-0330

Falcone, R., & Sapienza, A. (2023). An agent-based model to assess citizens’ acceptance of COVID-19 restrictions. Journal of Simulation, 17(1), 105–119. https://doi.org/10.1080/17477778.2021.1965501

Farshchian, M. M., & Heravi, G. (2018). Probabilistic assessment of cost, time, and revenue in a portfolio of projects using stochastic agent-based simulation. Journal of Construction Engineering and Management, 144(5), Article 04018028. https://doi.org/10.1061/(asce)co.1943-7862.0001476

Farshchian, M. M., Heravi, G., & AbouRizk, S. (2017). Optimizing the owner’s scenarios for budget al.ocation in a portfolio of projects using agent-based simulation. Journal of Construction Engineering and Management, 143(7), Article 04017022. https://doi.org/10.1061/(asce)co.1943-7862.0001315

Gan, V. J. L., & Cheng, J. C. P. (2015). Formulation and analysis of dynamic supply chain of backfill in construction waste management using agent-based modeling. Advanced Engineering Informatics, 29(4), 878–888. https://doi.org/10.1016/j.aei.2015.01.004

Geng, Y., Zhu, R., & Maimaituerxun, M. (2022). Bibliometric review of carbon neutrality with CiteSpace: evolution, trends, and framework. Environmental Science and Pollution Research, 29(51), 76668–76686. https://doi.org/10.1007/s11356-022-23283-3

Goh, Y. M., & Ali, M. J. A. (2016). A hybrid simulation approach for integrating safety behavior into construction planning: An earthmoving case study. Accident Analysis and Prevention, 93, 310–318. https://doi.org/10.1016/j.aap.2015.09.015

Ha, V., & Lykotrafitis, G. (2012). Agent-based modeling of a multi-room multi-floor building emergency evacuation. Physica A: Statistical Mechanics and Its Applications, 391(8), 2740–2751. https://doi.org/10.1016/j.physa.2011.12.034

He, C., Jia, G., McCabe, B., Chen, Y., Zhang, P., & Sun, J. (2023). Psychological decision-making process of construction worker safety behavior: an agent-based simulation approach. International Journal of Occupational Safety and Ergonomics, 29(1), 141–153. https://doi.org/10.1080/10803548.2021.2022351

Huang, S., & Liu, H. (2021). Impact of COVID-19 on stock price crash risk: Evidence from Chinese energy firms. Energy Economics, 101, Article 105431. https://doi.org/10.1016/j.eneco.2021.105431

Hussein, M., Darko, A., Eltoukhy, A. E. E., & Zayed, T. (2022). Sustainable logistics planning in modular integrated construction using multimethod simulation and Taguchi approach. Journal of Construction Engineering and Management, 148(6), Article 04022022. https://doi.org/10.1061/(asce)co.1943-7862.0002273

Ji, T., Wei, H.-H., & Cheng, J. (2019). Understanding the effect of co-worker support on construction safety performance from the perspective of risk theory: an agent-based modeling approac. Journal of Civil Engineering and Management, 25(2), 132–144. https://doi.org/10.3846/jcem.2019.7642

Jo, H., Lee, H., Suh, Y., Kim, J., & Park, Y. (2015). A dynamic feasibility analysis of public investment projects: An integrated approach using system dynamics and agent-based modeling. International Journal of Project Management, 33(8), 1863–1876. https://doi.org/10.1016/j.ijproman.2015.07.002

Jung, M., Park, M., Lee, H.-S., & Chi, S. (2018). Multimethod supply chain aimulation model for high-rise building construction projects. Journal of Computing in Civil Engineering, 32(3), Article 04018007. https://doi.org/10.1061/(asce)cp.1943-5487.0000751

Karakas, K., Dikmen, I., & Birgonul, M. T. (2013). Multiagent system to simulate risk-allocation and cost-sharing processes in construction projects. Journal of Computing in Civil Engineering, 27(3), 307–319. https://doi.org/10.1061/(asce)cp.1943-5487.0000218

Ke, Y. (2018). Research on the Chinese industrialized construction migrant workers from the perspective of complex adaptive system: Combining the application of SWARM computer simulation technology. Wireless Personal Communications, 102(4), 2469–2481. https://doi.org/10.1007/s11277-018-5266-8

Kedir, N. S., Raoufi, M., & Fayek, A. R. (2020). Fuzzy agent-based multicriteria decision-making model for analyzing construction crew performance. Journal of Management in Engineering, 36(5), Article 04020053. https://doi.org/10.1061/(asce)me.1943-5479.0000815

Khodabandelu, A., Park, J., & Arteaga, C. (2020). Crane operation planning in overlapping areas through dynamic supply selection. Automation in Construction, 117, Article 103253. https://doi.org/10.1016/j.autcon.2020.103253

Kim, K., & Paulson, B. C. (2003). Agent-based compensatory negotiation methodology to facilitate distributed coordination of project schedule changes. Journal of Computing in Civil Engineering, 17(1), 10–18. https://doi.org/10.1061/(asce)0887-3801(2003)17:1(10)

Kiomjian, D., Srour, I., & Srour, F. J. (2020). Knowledge sharing and productivity improvement: An agent-based modeling approach. Journal of Construction Engineering and Management, 146(7), Article 04020076. https://doi.org/10.1061/(asce)co.1943-7862.0001866

Klein, L., Kwak, J.-y., Kavulya, G., Jazizadeh, F., Becerik-Gerber, B., Varakantham, P., & Tambe, M. (2012). Coordinating occupant behavior for building energy and comfort management using multi-agent systems. Automation in Construction, 22, 525–536. https://doi.org/10.1016/j.autcon.2011.11.012

Knight, V. A., Williams, J. E., & Reynolds, I. (2012). Modelling patient choice in healthcare systems: Development and application of a discrete event simulation with agent-based decision making. Journal of Simulation, 6(2), 92–102. https://doi.org/10.1057/jos.2011.21

Korb, S., & Sacks, R. (2021). Agent-based simulation of general contractor-subcontractor interactions in a multiproject environment. Journal of Construction Engineering and Management, 147(1), Article 04020151. https://doi.org/10.1061/(asce)co.1943-7862.0001944

Lee, J., & Bernold, L. E. (2008). Ubiquitous agent-based communication in construction. Journal of Computing in Civil Engineering, 22(1), 31–39. https://doi.org/10.1061/(ASCE)0887-3801(2008)22:1(31))

Li, Z., & Xu, W. (2020). Pedestrian evacuation within limited-space buildings based on different exit design schemes. Safety Science, 124, Article 104575. https://doi.org/10.1016/j.ssci.2019.104575

Li, Z., Lv, X. F., Zhu, H. M., & Sheng, Z. H. (2018). Analysis of complexity of unsafe behavior in construction teams and a multiagent simulation. Complexity, 15, Article 6568719. https://doi.org/10.1155/2018/6568719

Li, Z., Mao, R., Meng, Q. F., Hu, X., & Li, H. X. (2021a). Exploring precursors of construction accidents in China: A grounded theory approach. International Journal of Environmental Research and Public Health, 18(2), Article 410. https://doi.org/10.3390/ijerph18020410

Li, Z., Zhang, S. W., Meng, Q. F., & Hu, X. (2021b). Barriers to the development of prefabricated buildings in China: a news coverage analysis. Engineering, Construction and Architectural Management, 28(10), 2884–2903. https://doi.org/10.1108/ecam-03-2020-0195

Li, Z., Jin, Y., Li, W., Meng, Q., & Hu, X. (2022). Impacts of COVID-19 on construction project management: a life cycle perspective. Engineering, Construction and Architectural Management, 30(8), 3357–3389. https://doi.org/10.1108/ecam-10-2021-0873

Liang, H., & Lin, K.-Y. (2019). A hybrid simulation approach for understanding the social contagion effect of safety violations within the construction crew. In ASCE International Conference on Computing in Civil Engineering (i3CE), Georgia Institute of Technology, Atlanta, Georgia, USA. https://doi.org/10.1061/9780784482421.065

Liang, H., Lin, K.-Y., & Zhang, S. (2018). Understanding the social contagion effect of safety violations within a construction crew: A hybrid approach using system dynamics and agent-based modeling. International Journal of Environmental Research and Public Health, 15(12), Article 2696. https://doi.org/10.3390/ijerph15122696

Liang, X., Yu, T., Hong, J., & Shen, G. Q. (2019). Making incentive policies more effective: An agent-based model for energy-efficiency retrofit in China. Energy Policy, 126, 177–189. https://doi.org/10.1016/j.enpol.2018.11.029

Liang, H., Zhang, S., & Su, Y. (2020). The structure and emerging trends of construction safety management research: a bibliometric review. International Journal of Occupational Safety and Ergonomics, 26(3), 469–488. https://doi.org/10.1080/10803548.2018.1444565

Lin, J., Ling, F., Huang, P., Chen, M., Song, M., Lu, K., & Wang, W. (2022). The development of GABAergic network in depression in recent 17 years: A visual analysis based on CiteSpace and VOSviewer. Frontiers in Psychiatry, 13, Article 874137. https://doi.org/10.3389/fpsyt.2022.874137

Liu, J. K., Yi, Y. Q., & Wang, X. T. (2020a). Exploring factors influencing construction waste reduction: A structural equation modeling approach. Journal of Cleaner Production, 276, Article 123185. https://doi.org/10.1016/j.jclepro.2020.123185

Liu, Y., Li, Q., Li, W., Li, H., & Pei, X. (2020b). Safety assessment of all-steel-type attached lifting scaffold based on grey Euclidean theory. Plos One, 15(8), Article e0238074. https://doi.org/10.1371/journal.pone.0238074

Liu, W. Y., Meng, Q. F., Li, Z., & Hu, X. (2021). Applications of computer vision in monitoring the unsafe behavior of construction workers: Current status and challenges. Buildings, 11(9), Article 409. https://doi.org/10.3390/buildings11090409

Lu, M., Cheung, C. M., Li, H., & Hsu, S.-C. (2016). Understanding the relationship between safety investment and safety performance of construction projects through agent-based modeling. Accident Analysis and Prevention, 94, 8–17. https://doi.org/10.1016/j.aap.2016.05.014

Lu, H., Qi, J., Li, J., Xie, Y., Xu, G., & Wang, H. (2020). Multi-agent based safety computational experiment system for shield tunneling projects. Engineering, Construction and Architectural Management, 27(8), 1963–1991. https://doi.org/10.1108/ecam-12-2019-0726

Mahjoubpour, B., Nasirzadeh, F., Golabchi, M. M. H. Z., Khajehghiasi, M. R., & Mir, M. (2018). Modeling of workers’ learning behavior in construction projects using agent-based approach: The case study of a steel structure project. Engineering, Construction and Architectural Management, 25(4), 559–573. https://doi.org/10.1108/ECAM-07-2016-0166

Manley, M., & Kim, Y. S. (2012). Modeling emergency evacuation of individuals with disabilities (exitus): An agent-based public decision support system. Expert Systems with Applications, 39(9), 8300–8311. https://doi.org/10.1016/j.eswa.2012.01.169

Marzouk, M., & Ali, H. (2013). Modeling safety considerations and space limitations in piling operations using agent based simulation. Expert Systems with Applications, 40(12), 4848–4857. https://doi.org/10.1016/j.eswa.2013.02.021

Matejevic, B., Zlatanovic, M., & Cvetkovic, D. (2018). The simulation model for predicting the productivity of the reinforced concrete slabs concreting process. Tehnicki Vjesnik-Technical Gazette, 25(6), 1672–1679. https://doi.org/10.17559/tv-20170627195003

Meng, Q., Chen, J., & Qian, K. (2018a). The complexity and simulation of revenue sharing negotiation based on construction stakeholders. Complexity, Article 5698170. https://doi.org/10.1155/2018/5698170

Meng, Q., Zhu, H., Li, Z., Du, J., Wang, X., & Kim, M. J. (2018b). How green building product decisions from customers can be transitioned to manufacturers: An agent-based model. Sustainability, 10(11), Article 3977. https://doi.org/10.3390/su10113977

Meng, Q., Li, Z., Du, J., Liu, H., & Ding, X. (2019). Negotiation for time optimization in construction projects with competitive and social welfare preferences. Complexity, 2019, Article 3269025. https://doi.org/10.1155/2019/3269025

Meng, Q., Zhang, Y., Li, Z., Shi, W., Wang, J., Sun, Y., Xu, L., & Wang, X. (2020). A review of integrated applications of BIM and related technologies in whole building life cycle. Engineering, Construction and Architectural Management, 27(8), 1647–1677. https://doi.org/10.1108/ecam-09-2019-0511

Meng, Q., Li, M., Liu, W., Li, Z., & Zhang, J. (2021a). Pricing policies of dual-channel green supply chain: Considering government subsidies and consumers’ dual preferences. Sustainable Production and Consumption, 26, 1021–1030. https://doi.org/10.1016/j.spc.2021.01.012

Meng, Q. F., Liu, W. Y., Li, Z., & Hu, X. (2021b). Influencing factors, mechanism and prevention of construction workers’ unsafe behaviors: A systematic literature review. International Journal of Environmental Research and Public Health, 18(5), Article 2644. https://doi.org/10.3390/ijerph18052644

Min, J. U., & Bjomsson, H. C. (2008). Agent-based construction supply chain simulator (CS2) for measuring the value of real-time information sharing in construction. Journal of Management in Engineering, 24(4), 245–254. https://doi.org/10.1061/(asce)0742-597x(2008)24:4(245)

Mirahadi, F., McCabe, B., & Shahi, A. (2019). IFC-centric performance-based evaluation of building evacuations using fire dynamics simulation and agent-based modeling. Automation in Construction, 101, 1–16. https://doi.org/10.1016/j.autcon.2019.01.007

Mohan, D. I., Verma, A., & Rao, S. (2023). Modelling prejudice and its effect on societal prosperity. Journal of Simulation, 17(6), 647–657. https://doi.org/10.1080/17477778.2022.2039570

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Grp, P. (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. British Medical Journal, 339, Article b2535. https://doi.org/10.1136/bmj.b2535

Monks, T., Currie, C. S. M., Onggo, B. S., Robinson, S., Kunc, M., & Taylor, S. J. E. (2019). Strengthening the reporting of empirical simulation studies: Introducing the STRESS guidelines. Journal of Simulation, 13(1), 55–67. https://doi.org/10.1080/17477778.2018.1442155

Mostafavi, A., Abraham, D., DeLaurentis, D., Sinfield, J., Kandil, A., & Queiroz, C. (2016). Agent-based simulation model for assessment of financing scenarios in highway transportation infrastructure systems. Journal of Computing in Civil Engineering, 30(2), Article 04015012. https://doi.org/10.1061/(asce)cp.1943-5487.0000482

Mukherjee, A., & Muga, H. (2010). An integrative framework for studying sustainable practices and its adoption in the AEC industry: A case study. Journal of Engineering and Technology Management, 27(3–4), 197–214. https://doi.org/10.1016/j.jengtecman.2010.06.006

Naili, M., Bourahla, M., & Naili, M. (2019). Stability-based model for evacuation system using agent-based social simulation and Monte Carlo method. International Journal of Simulation Process Modelling, 14(1), 1–16. https://doi.org/10.1504/IJSPM.2019.097702

Naticchia, B., Carbonari, A., Vaccarini, M., & Giorgi, R. (2019). Holonic execution system for real-time construction management. Automation in Construction, 104, 179–196. https://doi.org/10.1016/j.autcon.2019.04.018

Norouziasl, S., Jafari, A., & Wang, C. (2020). An agent-based simulation of occupancy schedule in office buildings. Building and Environment, 186, Article 107352. https://doi.org/10.1016/j.buildenv.2020.107352

Obonyo, E., Anumba, C., & Thorpe, T. (2005). APRON: an agent‐based specification and procurement system for construction products. Engineering, Construction and Architectural Management, 12(4), 329–350. https://doi.org/10.1108/09699980510608802

Ogunmakinde, O. E., Egbelakin, T., & Sher, W. (2022). Contributions of the circular economy to the UN sustainable development goals through sustainable construction. Resources Conservation and Recycling, 178, Article 106023. https://doi.org/10.1016/j.resconrec.2021.106023

Olawumi, T. O., Chan, D. W. M., & Wong, J. K. W. (2017). Evolution in the intellectual structure of BIM research: a bibliometric analysis. Journal of Civil Engineering and Management, 23(8), 1060–1081. https://doi.org/10.3846/13923730.2017.1374301

Qiu, Y., Liao, K., Zou, Y., & Huang, G. (2022). A bibliometric analysis on research regarding residential segregation and health based on CiteSpace. International Journal of Environmental Research and Public Health, 19(16), Article 10069. https://doi.org/10.3390/ijerph191610069

Raoufi, M., & Fayek, A. R. (2018). Fuzzy agent-based modeling of construction crew motivation and performance. Journal of Computing in Civil Engineering, 32(5), Article 04018035. https://doi.org/10.1061/(asce)cp.1943-5487.0000777

Rosales-Carreon, J., & Garcia-Diaz, C. (2015). Exploring transitions towards sustainable construction: The case of near-zero energy buildings in the Netherlands. Journal of Artificial Societies and Social Simulation, 18(1), Article 10. https://doi.org/10.18564/jasss.2625

Sabe, M., Pillinger, T., Kaiser, S., Chen, C., Taipale, H., Tanskanen, A., Tiihonen, J., Leucht, S., Correll, C. U., & Solmi, M. (2022). Half a century of research on antipsychotics and schizophrenia: A scientometric study of hotspots, nodes, bursts, and trends. Neuroscience and Biobehavioral Reviews, 136, Article 104608. https://doi.org/10.1016/j.neubiorev.2022.104608

Shen, W., Hao, Q., & Xue, Y. (2012). A loosely coupled system integration approach for decision support in facility management and maintenance. Automation in Construction, 25, 41–48. https://doi.org/10.1016/j.autcon.2012.04.003

Sheng, Z. (2018). Mega infrastructure construction management. In Fundamental theories of mega infrastructure construction management: Theoretical considerations from Chinese practices (pp. 13–14). Springer. https://doi.org/10.1007/978-3-319-61974-3_2

Singto, C., de Vries, M., Hofstede, G. J., & Fleskens, L. (2021). Ex ante impact assessment of reservoir construction projects for different stakeholders using agent-based modeling. Water Resources Management, 35(3), 1047–1064. https://doi.org/10.1007/s11269-021-02771-0

Son, J., & Rojas, E. M. (2011). Evolution of collaboration in temporary project teams: An agent-based modeling and simulation approach. Journal of Construction Engineering and Management, 137(8), 619–628. https://doi.org/10.1061/(asce)co.1943-7862.0000331

Stephan, K., & Menassa, C. C. (2015). Modeling the effect of building stakeholder interactions on value perception of sustainable retrofits. Journal of Computing in Civil Engineering, 29(4), Article B4014006. https://doi.org/10.1061/(asce)cp.1943-5487.0000409

Su, Y. (2020). Multi-agent evolutionary game in the recycling utilization of construction waste. Science of the Total Environment, 738, Article 139826. https://doi.org/10.1016/j.scitotenv.2020.139826

Tah, J. H. M. (2005). Towards an agent-based construction supply network modelling and simulation platform. Automation in Construction, 14(3), 353–359. https://doi.org/10.1016/j.autcon.2004.08.003

Taillandier, F., Taillandier, P., Tepeli, E., Breysse, D., Mehdizadeh, R., & Khartabil, F. (2015). A multi-agent model to manage risks in construction project (SMACC). Automation in Construction, 58, 1–18. https://doi.org/10.1016/j.autcon.2015.06.005

Taillandier, F., Taillandier, P., Hamzaoui, F., & Breysse, D. (2016). A new agent-based model to manage construction project risks – application to the crossroad of Bab El Karmadine at Tlemcen. European Journal of Environmental and Civil Engineering, 20(10), 1197–1213. https://doi.org/10.1080/19648189.2015.1134675

Tho, S. W., Yeung, Y. Y., Wei, R., Chan, K. W., & So, W. W.-m. (2017). A systematic review of remote laboratory work in science education with the support of visualizing its structure through the HistCite and CiteSpace software. International Journal of Science and Mathematics Education, 15(7), 1217–1236. https://doi.org/10.1007/s10763-016-9740-z

Trappey, A. J. C., Trappey, C. V., & Ni, W.-C. (2013). A multi-agent collaborative maintenance platform applying game theory negotiation strategies. Journal of Intelligent Manufacturing, 24(3), 613–623. https://doi.org/10.1007/s10845-011-0606-5

Vandatikhaki, F., Langari, S. M., Taher, A., El Ammari, K., & Hammad, A. (2017). Enhancing coordination and safety of earthwork equipment operations using Multi-Agent System. Automation in Construction, 81, 267–285. https://doi.org/10.1016/j.autcon.2017.04.008

Wang, N., Xu, Z., & Liu, Z. (2023). Innovation in the construction sector: Bibliometric analysis and research agenda. Journal of Engineering and Technology Management, 68, Article 101747. https://doi.org/10.1016/j.jengtecman.2023.101747

Watkins, M., Mukherjee, A., Onder, N., & Mattila, K. (2009). Using agent-based modeling to study construction labor productivity as an emergent property of individual and crew interactions. Journal of Construction Engineering and Management, 135(7), 657–667. https://doi.org/10.1061/(asce)co.1943-7862.0000022

Wehbe, F., Al Hattab, M., & Hamzeh, F. (2016). Exploring associations between resilience and construction safety performance in safety networks. Safety Science, 82, 338–351. https://doi.org/10.1016/j.ssci.2015.10.006

Wu, Z. Z., Yu, A. T. W., & Shen, L. Y. (2017). Investigating the determinants of contractor’s construction and demolition waste management behavior in Mainland China. Waste Management, 60, 290–300. https://doi.org/10.1016/j.wasman.2016.09.001

Wu, C., Chen, C., Jiang, R., Wu, P., Xu, B., & Wang, J. (2019). Understanding laborers’ behavioral diversities in multinational construction projects using integrated simulation approach. Engineering, Construction and Architectural Management, 26(9), 2120–2146. https://doi.org/10.1108/ecam-07-2018-0281

Xu, L., Liu, X., Tong, D., Liu, Z., Yin, L., & Zheng, W. (2022). Forecasting urban land use change based on cellular automata and the PLUS Model. Land, 11(5), Article 652. https://doi.org/10.3390/land11050652

Ye, G., Yue, H. Z., Yang, J. J., Li, H. Y., Xiang, Q. T., Fu, Y., & Cui, C. (2020). Understanding the sociocognitive process of construction workers’ unsafe behaviors: An agent-based modeling approach. International Journal of Environmental Research and Public Health, 17(5), Article 1588. https://doi.org/10.3390/ijerph17051588

Yu, Y., Yazan, D. M., Bhochhibhoya, S., & Volker, L. (2021). Towards circular economy through industrial symbiosis in the Dutch construction industry: A case of recycled concrete aggregates. Journal of Cleaner Production, 293, Article 126083. https://doi.org/10.1016/j.jclepro.2021.126083

Zang, X., Zhu, Y., Zhong, Y., & Chu, T. (2022). CiteSpace-based bibliometric review of pickup and delivery problem from 1995 to 2021. Applied Sciences, 12(9), Article 4607. https://doi.org/10.3390/app12094607

Zhang, C., & Hammad, A. (2012). Multiagent approach for real-time collision avoidance and path replanning for cranes. Journal of Computing in Civil Engineering, 26(6), 782–794. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000181

Zhang, P. Y., Li, N., Jiang, Z. M., Fang, D. P., & Anumba, C. J. (2019). An agent-based modeling approach for understanding the effect of worker-management interactions on construction workers’ safety-related behaviors. Automation in Construction, 97, 29–43. https://doi.org/10.1016/j.autcon.2018.10.015

Zhang, M., Shi, R., & Yang, Z. (2020a). A critical review of vision-based occupational health and safety monitoring of construction site workers. Safety Science, 126, Article 104658. https://doi.org/10.1016/j.ssci.2020.104658

Zhang, M. Y., Cao, Z. Y., Yang, Z., & Zhao, X. F. (2020b). Utilizing computer vision and fuzzy inference to evaluate level of collision safety for workers and equipment in a dynamic environment. Journal of Construction Engineering and Management, 146(6), Article 04020051. https://doi.org/10.1061/(asce)co.1943-7862.0001802

Zhao, X. (2017). A scientometric review of global BIM research: Analysis and visualization. Automation in Construction, 80, 37–47. https://doi.org/10.1016/j.autcon.2017.04.002

Zhong, B. T., Wu, H. T., Ding, L. Y., Love, P. E. D., Li, H., Luo, H. B., & Jiao, L. (2019). Mapping computer vision research in construction: Developments, knowledge gaps and implications for research. Automation in Construction, 107, Article 102919. https://doi.org/10.1016/j.autcon.2019.102919

Zhou, J., Jia, X., & Jia, J. (2020). Effects of different staircase design factors on evacuation of children from kindergarten buildings analyzed via agent-based simulation. Healthcare, 8(1), Article 56. https://doi.org/10.3390/healthcare8010056

Zhu, J.-W., Zhou, L.-N., Li, L., & Ali, W. (2020). Decision simulation of construction project delivery system under the sustainable construction project management. Sustainability, 12(6), Article 2202. https://doi.org/10.3390/su12062202