Abstract:
The presence of high-productivity labor at each level of a project's development is critical
to its success. No previous work has been able to account for the effects of continuous
variables as well as the interactions between different agents at the same time. The purpose
of this study is to apply an agent-based model in the short and long run of labor productivity
Improvement from a system dynamic (SD) approach on selected building project sites in
Hawassa city. A literature review was conducted, and factors recommended by local
experts were considered to categorize the factors. Sixty factors were studied and ranked
using the relative importance index, which was divided into eight groups. The Independent test was used to determine if the factors were significant or not. Time series analysis was
used to predict short-term labor productivity. Then, using a regression model, the
relationship between various parameters was established, and a quantitative model of
labor productivity was constructed. The labor productivity was approximated using the SD
model, which takes into account the effects of all significant factors. The SD and ABM
simulation was used to measure labor productivity using real world data. The research
findings included the value labor productivity was simulated based on the significant
factors, which included a regression constant of 0.779 and a regression coefficient for each
important element. Lack of construction materials (-0.032), construction manager's lack of
leadership (0.089), amount of salary for workers (-0.020), project management efficiency
(0.098), improper work planning and scheduling (-0.042), work discontinuity (-0.035), and
a lack of clear and daily task assignments (-0.044). It is believed that the SD and ABM
simulation approaches offer sound tools for modeling of construction labor productivity of
building projects because the effects of various continuous influencing factors and the
interactions of agents are taken into account. Project managers were able to predict and
improve the value of labor productivity by taking account of all the influencing factors.
They were able to pinpoint the root cause of a decrease in labor productivity. As a result,
by implementing appropriate solutions, labor productivity can be increased.
