Dynamic Modeling of Multifactor Construction Productivity for Equipment-Intensive Activities

Construction productivity is a major research interest within the construction domain. Because construction is a labor-intensive industry, previous research has often focused on construction labor productivity (CLP). However, equipment is the main driver of productivity for some construction activities, so-called equipment-intensive activities. Existing models of activity-level productivity often predict a single-factor productivity measure - namely CLP - yet determining multifactor productivity, including labor, material, and equipment, provides more comprehensive predictions of productivity. Construction productivity models are often static in nature, or incapable of capturing the subjective uncertainty of some factors influencing productivity. Fuzzy system dynamics is an appropriate technique for modeling construction productivity because it captures the dynamism of construction projects and addresses the subjective and probabilistic uncertainty of factors influencing productivity. The contributions of this paper are threefold: identifying the key factors influencing the productivity of equipment-intensive activities, developing a predictive model of multifactor productivity for equipment-intensive activities using fuzzy system dynamics technique, and developing an approach to reduce uncertainty overestimation in the simulation results of fuzzy system dynamics models.