Framework for Simulating Crew Motivation Impact on Productivity—A Hybrid Modeling Approach
Publication: Construction Research Congress 2022
ABSTRACT
Previous studies have identified motivation as one of the most important factors affecting the efficiency of labor utilization in construction processes. However, there is a lack of research on simulating the impact of motivation on labor productivity to track and devise productivity improvement strategies. Fuzzy system dynamics (FSD) has been used to model labor productivity, because it captures subjective uncertainties and the dynamism of construction systems. However, FSD fails to capture complexity arising from individual components (e.g., crew members) that lead to emerging behaviors in crew motivation modeling. The main contributions of this paper are: (1) proposing a framework for combining FSD and fuzzy agent-based modeling, leading to a more comprehensive method for studying the impact of crew motivation on productivity; and (2) facilitating identification of more effective productivity improvement strategies by allowing construction stakeholders to track the dynamic relationships between motivation and labor productivity.
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REFERENCES
CII (Construction Industry Institute). (2006). Work Force View of Construction Labor Productivity. Univ. of Texas at Austin, Austin, Texas, US.
Eid, M. S., and El-Adaway, I. H. (2018). “Decision-making Framework for Holistic Sustainable Disaster Recovery: Agent-based Approach for Decreasing Vulnerabilities of the Associated Communities.” J. Infrastruct. Syst., 24(3), 04018009.
Gerami Seresht, N., and Fayek, A. R. (2018). “Dynamic Modeling of Multifactor Construction Productivity for Equipment-intensive Activities.” J. Constr. Eng. Manage., 144(9), 04018091.
Gerami Seresht, N., and Fayek, A. R. (2020). “Neuro-fuzzy System Dynamics Technique for Modeling Construction Systems. Appl. Soft Comput., 93, 106400.
Ghodrati, N., Wing Yiu, T., Wilkinson, S., and Shahbazpour, M. (2018). “Role of Management Strategies in Improving Labor Productivity in General Construction Projects in New Zealand: Managerial Perspective.” J. Manage. Eng., 34(6), 04018035.
Gurmu, A. T., and Ongkowijoyo, C. S. (2020). “Predicting Construction Labor Productivity Based on Implementation Levels of Human Resource Management Practices.” J. Constr. Eng. Manag., 146(3), 04019115.
Heravi, G., and Eslamdoost, E. (2015). “Applying Artificial Neural Networks for Measuring and Predicting Construction-labor Productivity.” J. Constr. Eng. Manag., 141(10), 04015032.
Jabri, A., and Zayed, T. (2017). “Agent-based Modeling and Simulation of Earthmoving Operations.” Autom. Constr., 81, 210–223.
Johari, S., and Jha, K. N. (2020). “Impact of Work Motivation on Construction Labor Productivity.” J. Manage. Eng., 36(5), 04020052.
Kedir, N. S., Raoufi, M., and Fayek, A. R. (2020). “Fuzzy Agent-Based Multicriteria Decision-Making Model for Analyzing Construction Crew Performance.” J. Manage. Eng., 36(5).
Khanh, H. D., and Kim, S. Y. (2020). “Exploring Productivity of Concrete Truck for Multistory Building Projects Using Discrete Event Simulation.” KSCE J. Civ. Eng., 24(12), 3531–3545.
Kisi, K. P., Mani, N., Rojas, E. M., and Foster, E. T. (2018). “Estimation of Optimal Productivity in Labor-intensive Construction Operations: Advanced Study.” J. Constr. Eng. Manage., 144(10), 04018097.
Liao, P. C., O’Brien, W. J., Thomas, S. R., Dai, J., and Mulva, S. P. (2011). “Factors Affecting Engineering Productivity.” J. Manage. Eng., 27(4), 229–235.
Nasirzadeh, F., Afshar, A., Khanzadi, M., and Howick, S. (2008). Integrating System Dynamics and Fuzzy Logic Modeling for Construction Risk Management. Const. Manag. Econ., 26, 1197–1212.
Nasirzadeh, F., Khanzadi, M., and Mir, M. (2018). A Hybrid Simulation Framework for Modelling Construction Projects Using Agent-based Modelling and System Dynamics: An Application to Model Construction Workers’ Safety Behavior.” Int. J. Constr. Manag., 18(2), 132–143.
Palaniappan, S., Sawhney, A., Janssen, M. A., and Walsh, K. D. (2007). “Modeling Construction Safety as an Agent-based Emergent Phenomenon.” In Proc., 24th International Symposium on Automation and Robotics in Construction, Kochi, India, 375–382.
Raoufi, M., and Fayek, A. R. (2018). “Fuzzy Agent-based Modeling of Construction Crew Motivation and Performance.” J. Comput. Civ. Eng., 32(5), 04018035.
Raoufi, M., and Fayek, A. R. (2020). “Fuzzy Monte Carlo Agent-based Simulation of Construction Crew Performance.” J. Constr. Eng. Manage., 146(5), 04020041.
Raoufi, M., Gerami Seresht, N., and Fayek, A. R. (2016). “Overview of Fuzzy Simulation Techniques in Construction Engineering and Management.” 2016 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS), IEEE, 1–6.
Rashedi, R., and Hegazy, T. (2015). “Holistic Analysis of Infrastructure Deterioration and Rehabilitation Using System Dynamics.” J. Infrastruct. Syst., 22(1), 04015016.
Siraj, N. B., and Fayek, A. R. (2020). “Hybrid Fuzzy System Dynamics Model for Analyzing the Impacts of Interrelated Risk and Opportunity Events on Project Contingencies.” Can. J. Civ. Eng., Just-IN. https://doi.org/10.1139/cjce-2020-0032.
Swinerd, C., and McNaught, K. R. (2012). “Design Classes for Hybrid Simulations Involving Agent-based and System Dynamics Models.” Simul. Model. Pract. Theory, 25, 118–133.
Tsehayae, A. A., and Fayek, A. R. (2016). “Developing and Optimizing Context-specific Fuzzy Inference System-based Construction Labor Productivity Models. J. Constr. Eng. Manag., 142(7), 04016017.
Yi, W., and Chan, A. P. (2014). “Critical Review of Labor Productivity Research in Construction Journals.” J. Manage. Eng., 30(2), 214–225.
Zadeh, L. (1965). Fuzzy sets. Inf. Control, 8(3), 338–353.
Zhang, D., Nasir, H., and Haas, C. T. (2017). “Development of an Internal Benchmarking and Metrics Model for Industrial Construction Enterprises for Productivity Improvement. Can. J. Civ. Eng., 44(7), 518–529.
Zhao, T., and Dungan, J. M. (2019). “Loss of Productivity Analysis Using Project-specific Curves.” J. Leg. Aff. Disput. Resolut. Eng. Constr., 11(4), 04519027.
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Construction Research Congress 2022
Pages: 880 - 888
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Published online: Mar 7, 2022
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