Studying the effect of learning curve on labor productivity using agent-based modeling -

Abstract

The labor-intensive nature of construction projects requires proper management and efficient utilization of labor resources. Improvement of labor productivity can enhance project performance and thereby lead to substantial time and cost savings. Several studies focused on identifying the effect of different factors on labor productivity, whereby the learning curve factor proved of paramount importance. Previous research efforts developed models to analyze the effect of learning curve on labor productivity but failed to capture all the complexities of this mechanism and its dynamics. This paper presents an agent-based construction learning model that models a construction site as an active environment in which construction personnel or agents interact with each other and their surroundings thereby creating an adaptive environment open for learning and improvement. More specifically, the developed work illustrates many scenarios representing different learning levels and typical interactions between workers on construction sites. The components of the proposed model were created and results highlighted the potential of using the agent-based modeling paradigm to better simulate the effect of learning on labor productivity in the construction industry.