Ahn, SeungjunChettupuzha, A. J. AntonyEkyalimpa, RonaldHague, StephenAbouRizk, Simaan M.Stylios, Chrysostomos D.2022-09-152022-09-152015Ahn, S., Chettupuzha, A. A., Ekyalimpa, R., Hague, S., AbouRizk, S. M., & Stylios, C. D. (2015, August). Fuzzy Cognitive Maps as a tool for modeling construction labor productivity. In 2015 Annual Conference of the North American Fuzzy Information Processing Society (NAFIPS) held jointly with 2015 5th World Conference on Soft Computing (WConSC) (pp. 1-7). IEEE.https://doi.org/10.1109/NAFIPS-WConSC.2015.7284150https://nru.uncst.go.ug/handle/123456789/4747Labor productivity is a fundamental building block of planning and controlling in construction, and therefore, predicting labor productivity levels for a given condition is very important in construction management. However, predicting labor productivity is extremely difficult due to a large number of factors that can affect productivity in perplexing ways. Another obstacle to predicting labor productivity is the qualitative nature and subjectivity of productivity factors. To address these issues, a soft computing technique called Fuzzy Cognitive Maps (FCMs) is proposed as a tool to model the complex inter-relationships between productivity factors based on expert knowledge, and for assessing the impact of the productivity factors on labor productivity. In this paper, the methodology for creating and using FCMs for this purpose is introduced, and then an exercise is presented for demonstration purposes. Additionally, issues identified from this exercise are described, and the way that FCMs can be practically used in the field for predicting labor productivity is also discussed in the paper.enConstruction Labor Productivity; Fuzzy Cognitive Map (FCM); Knowledge representation; Soft computingArticle