Agent-Based Modeling and Simulation of Multidimensional Impacts of Construction Labor Productivity Factors

Despite numerous attempts to quantify the impacts of factors influencing productivity in the construction industry, such factors are still perceived as static and independent, resulting in unrealistic productivity estimates. The objective is to highlight the necessity of perceiving the already heavily researched factors affecting productivity as dynamic and interdependent through a multidimensional lens.

Two generic agent-based models were built to simulate the outcomes of a project through varying levels of detail, each investigating a certain set of impacts. The first model includes the quantified impacts of the factors on productivity (the traditional approach), while the second encompasses all the quantified impacts of the factors on productivity and on each other (the comprehensive approach). Findings proved the accuracy of the proposed comprehensive approach in estimating durations compared to planned durations and to those obtained from the traditional approach.

Individual task durations and total project duration results were obtained. By implementing a case study for model validation, an average 8.8% increase in task duration was detected among all tasks between the two models, and an average increase of 9.8% was observed between the total project durations. These values highlight the significant changes observed in duration results after considering the impacts of the factors on each other.

Additionally, results showed that considering the impacts of the factors on each other resulted in a more accurate and reliable duration estimation process for task and project durations, with only 8.9% and 3.3% relative changes, respectively, compared to actual durations. Such an approach allows for more reliable planning, where enhancing the planning process can help refine the overall project performance by providing more realistic and achievable plans while also reducing wastes in time, cost, and resources. Practicing reliable planning also ensures a more efficient project monitoring and control process by allowing for more accurate calculations of control metrics.


Statechart and attributes for the Task and Worker agents illustrated
Statechart and attributes for the (a) Task agent and (b) Worker agents

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