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

  • Construction Management
  • Published:
KSCE Journal of Civil Engineering Aims and scope

Abstract

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.

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References

  • Ahadzie, D. K., Proverbs, D. G., and Olomolaiye, P. O. (2008). “A model for predicting the performance of project managers at the construction phase of mass house building projects.” ASCE J. Constr. Eng. Manage., Vol. 134, No. 8, pp. 618–629, DOI: 10.1061/(ASCE)0733-9364(2008)134:8(618).

    Article  Google Scholar 

  • Alarcon, L. F. and Ashley, D. B. (1996). “Modeling project performance for decision making.” ASCE J. Constr.Eng. Manage., Vol. 122, No. 3, pp. 265–273, DOI: 10.1061/(ASCE)0733-9364(1996)122:3(265).

    Article  Google Scholar 

  • Armentrout, D. R. (1986). “Engineering productivity management and performance measurement.” ASCE J. Manage. Engr., Vol. 2, No. 3, pp.141–147, DOI: 10.1061/(ASCE)9742-597X(1986)2:3(141).

    Article  Google Scholar 

  • Bassioni, H. A. Price, A. D. F., and Hassan, T. M. (2004). “Performance measurement in construction.” ASCE J. Manage. Engr., Vol. 20, No. 2, pp. 42–50, DOI: 10.1061/(ASCE)0742-597X(2004)20:2(42).

    Article  Google Scholar 

  • Cha, H. S. and O’Connor, J. T. (2006). “Characteristics for leveraging value management processes on capital facility projects.” ASCE Journal of Mgmt. Engr., Vol. 22, No. 3, pp. 135–147, DOI: 10.1061/(ASCE)0742-597X(2006)22:3(135).

    Article  Google Scholar 

  • Cha, H. S. and Shin, G. Y. (2011). “Predicting project cost performance level by assessing risk factors of building construction.” Journal of Asian Architecture and Building Engineering, Vol. 10, No. 2, pp. 437–444, DOI: 10.3130/jaabe.10.437.

    Article  Google Scholar 

  • Cha, H. S. and Kim, C. K. (2011). “Quantitative approach for project performance measurement on building construction in South Korea.” KSCE Journal of Civil Engineering, Vol. 15, No. 8, pp. 1319–1328, DOI: 10.3846/13923730.2014.890644.

    Article  Google Scholar 

  • Chan, T. K. (2009). “Measuring performance of the Malaysian construction industry.” Constr. Manage. Econ., Vol. 27, No. 12, pp. 1231–1244, DOI: 10.1080/01446190903233137.

    Article  Google Scholar 

  • Cho, Y. S. and Cha, H. S. (2010). “A Study of project characteristics and project performance level of difficulty.” KICEM Journal of Construction Engineering & Management, Vol. 11, No. 6, pp. 78–88, DOI: 10.6106/KJCEM.2010.11.6.78.

    Article  Google Scholar 

  • Choi, J., Yun, S., and Oliveira, D. P. (2016). “Developing a cost normalization framework for phase-based performance assessment of construction projects.” Canadian Journal of Civil Engineering, Vol. 43, No. 12, pp. 1075–1086, DOI: 10.1139/cjce-2016-0223.

    Article  Google Scholar 

  • Han, S., Kim, D., Kim, H., and Jang, W. (2008). “A web-based integrated system for international project risk management.” Automation in Construction, Vol. 17, pp. 342–356, DOI: 10.1016/j.autcon.2007.05.012.

    Article  Google Scholar 

  • Haponava, T. and Al-Jibouri, S. (2012). “Proposed system for measuring project performance using process-based key performance indicators.” ASCE J. Manage. Engr., Vol. 28, No. 2, pp. 140–149, DOI: 10.1061/(ASCE)ME.1943-5479.0000078.

    Article  Google Scholar 

  • Hwang, B., Thomas., S., Degezelle, D., and Caldas, C. (2008). “Development of a benchmarking framework for pharmaceutical capital projects.” Constr. Manage. Econ., Vol. 26, No. 2, pp. 177–195, DOI: 10.1080/01446190701802398.

    Article  Google Scholar 

  • Kagioglou, M., Cooper, R., and Aouad, G. (2001). “Performance management in construction: A conceptual framework.” J. Constr. Manage. Econ., Vol. 19, No. 1, pp. 85–95, DOI: 10.1080/01446190010003425.

    Article  Google Scholar 

  • Kaplan R. S. (1984). “The evolution of management accounting.” Account. Res., Vol. 59, No. 3, pp. 390–418, DOI: 10.1007/978-1-4899-7138-8_27.

    Google Scholar 

  • Ko, Y. and Cha, H. (2011). “Development of project performance predicting system considering construction project characteristics.” KICEM Journal of Construction Engineering & Management, Vol. 12, No. 1, pp. 62–72, DOI: 10.6106/KJCEM.2011.12.1.62.

    Article  Google Scholar 

  • Ko, Y. J., Cha, H., Shin, D., and Kim, K. (2012). “Selecting optimum management practices according to project characteristics for improving project performance.” KICEM Journal of Construction Engineering & Management, Vol. 13, No. 1, pp. 3–13, DOI: 10.6106/KJCEM.2012.13.1.003.

    Article  Google Scholar 

  • Lee, S., Thomas, S., and Tucker, R. (2005). “Web-Based Benchmarking System for the Construction Industry.” ASCE J. of Construction & Management, pp. 790–798, DOI: 10.1061/(ASCE)0733-9364(2005)131:7(790).

    Google Scholar 

  • Lema, N. M. and Price, A. D. F. (1995). “Benchmarking: Performance improvement toward competitive advantage.” ASCE J. Manage. Eng., Vol. 11, No. 1, pp. 28–37, DOI: 10.1061/(ASCE)0742-597X (1995)11:1(28).

    Article  Google Scholar 

  • Leu, S. and Lin. Y. (2008). “Project performance evaluation based on statistical process control techniques.” ASCE J. Constr. Eng. Manage., Vol. 134, No. 10, pp. 813–819, DOI: 10.1061/(ASCE)0733-9364 (2008)134:10(813).

    Article  Google Scholar 

  • Olumide, A., Walewski, J., and Anderson, S. (2012). “Assessing CII best practices applicability.” Construction Research Congress, pp. 2439–2448, DOI: 10.1061/9780784412329.245.

    Google Scholar 

  • Ozorhon, B., Arditi, D., Dikmen, I., and Birgonul, M. (2011). “Toward a multidimensional performance measure for international joint ventures in construction.” ASCE J. of Construction Engineering & Management, pp. 403–411, DOI: 10.1061/(ASCE)CO.1943-7862.0000314.

    Google Scholar 

  • Ramirez, R. R., Alarcon, L. F., and Knight, P. (2004). “Benchmarking system for evaluating management practices in the construction industry.” ASCE J. Manage. Engr., Vol. 20, No. 3, pp. 110–117, DOI: 10.1061/(ASCE)0742-597X(2004)20:3(110).

    Article  Google Scholar 

  • Sheskin, D. (2003). Handbook of parametric and nonparametric statistical procedures, 3rd edition, CRC Press, Boca Raton, Florida.

    Book  MATH  Google Scholar 

  • Yeung, J. F. Y., Chan, A. P. C., Chan, D. W. M. Chiang, Y. H., and Yang, H. (2013). “Developing a benchmarking model for construction projects in Hong Kong.” ASCE J. Constr. Eng. Manage., Vol. 139, No. 6, pp. 705–716, DOI: 10.1061/(ASCE)CO.1943-7862.0000622.

    Article  Google Scholar 

  • Yu, I., Kim, K., Jung, Y., and Chin, S. (2007). “Comparable performance measurement system for construction companies.” ASCE J. Manage. Engr., Vol. 23, No. 3, pp. 131–139, DOI: 10.1061/(ASCE)0742-597X(2007)23:3(131).

    Article  Google Scholar 

  • Yun, S., Choi, J., Oliveira, D., and Mulva, S. (2015). “Development of performance metrics for phase-based capital project benchmarking.” International Journal of Project Management, Vol. 34, No. 3, pp. 389–402, DOI: 10.1016/j.ijproman.2015.12.004.

    Article  Google Scholar 

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Authors and Affiliations

  1. Dept. of Architectural Engineering, Ajou University, Suwon, 16499, Korea

    Hee Sung Cha & Ki Hyun Kim

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  1. Hee Sung Cha
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  2. Ki Hyun Kim
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Correspondence to Hee Sung Cha.

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Cha, H.S., Kim, K.H. Measuring Project Performance in Consideration of Optimal Best Management Practices for Building Construction in South Korea. KSCE J Civ Eng 22, 1614–1625 (2018). https://doi.org/10.1007/s12205-017-0156-2

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  • DOI: https://doi.org/10.1007/s12205-017-0156-2

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