Influence Factors of Learning-Curve Effect in High-Rise Building Constructions

Learning-curve theory has been applied to construction activities due to their labor-intensive and repetitive features. However, previous research argued that the effect of the learning curve does not exist in construction because it is not recognizable by the amount of repetition in construction labor. Although prior research implied that there is a need for the modified learning curve specifically tailored to construction, the studies may not fully investigate the reasons for the gap between theory and practice or fully consider the factors that affect the manifestation process of learning development. Moreover, they tend to underestimate the applicability of the learning-curve theory in construction. To address these issues, this paper clarifies factors that impact the manifestation process to suggest a more suitable learning-curve model for high-rise building construction activities as a subject. Specifically, three influence factors are selected-(1) task change, (2) work adaptation, and (3) vertical transportation time-and a hypothetical learning curve is proposed for the high-rise building construction. A case project in Korea is tested to validate the suggested factors. The quantitative data including labor performance (e.g., work hours, quantity, and number of workers) per floor are converted to the proposed learning curve and compared with actual data. The results show that the suggested learning curve is more suitable for representing the development of learning in high-rise construction than that of previous research. The proposed learning curve can also extend its applicability toward labor productivity issues for the high-rise building because its accuracy was improved considering the influence factors. Based on the results of this research, a project manager can improve labor productivity from the learning-curve effect by controlling influence factors in the construction phase. Further, this research may have implications for investigating hidden phenomenon through a quantitative approach, which is shown as tangible. (C) 2015 American Society of Civil Engineers.