Measuring Project Performance in Consideration of Optimal Best Management Practices for Building Construction in South Korea

• Published in: KSCE journal of civil engineering Vol. 22; no. 5; pp. 1614 - 1625
• Main Authors: Cha, Hee Sung, Kim, Ki Hyun
• Format: Journal Article
• Language: English
• Published: Seoul Korean Society of Civil Engineers 01.05.2018; Springer Nature B.V; 대한토목학회
• Subjects: Algorithms; Best management practices; Civil Engineering; Construction; Construction industry; Construction Management; Contractors; Decision making; Empirical analysis; Engineering; Feedback; Geotechnical Engineering & Applied Earth Sciences; Industrial Pollution Prevention; Performance measurement; Performance prediction; Vulnerability; 토목공학; South Korea; performance prediction; Best Management Practice (BMP); Performance Measurement System (PMS); quantitative analysis; Project characteristics
• ISSN: 1226-7988; 1976-3808
• DOI: 10.1007/s12205-017-0156-2

A variety of Performance Measurement Systems (PMS) are aimed to provide owners and contractors with sound decision-making by identifying the Best Management Practices (BMP). Most of them, however, are not effectively linked with project characteristics (i.e., project type, owner requirement, and/or project circumstances). Furthermore, a continuous feedback system is necessary in order to pin-point “how-to” solutions for the subject project. Compared to the conventional PMS, this study is focused on; (1) identifying, if any, quantifiable relationships among project characteristics, project performance, and BMP; (2) developing a systematic framework for predicting the performance level of the subject project; and (3) validating the feedback algorithm by detecting the most suitable management practices for a given construction project. Although the proposed system is limited to Korean building construction industry, the main contribution of this research is twofold. First, this study has conducted the first-ever empirical analysis by quantifying the project performance and selecting the optimal BMP in consideration of project characteristics. Second, the continuous feedback approach in the field of PMS is proven by effectively diagnosing the vulnerability of the project in terms of the various types of project performance.