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Manpower Allocation Model for Construction Site Office Engineers based on Inherent Technical Risks

  • Woo Jeong Yang
  • Yea Sang KimEmail author
Construction Management
  • 3 Downloads

Abstract

Accurately predicting the costs of construction site overheads and preventing increases in unanticipated costs has a large effect on the cost competitiveness of a construction company. While site engineer costs account for the majority of construction site management costs, established manpower allocation standards will only account for the project size, and so poorly reflect inherent technological risks. Consequently, with risks mounting on-site as a project progresses, actual engineering manpower needs can exceed the planned ones. This study presents a method for improving the accuracy of construction site engineer allocation by reflecting such technological risks. Data from 31 case projects were analyzed to confirm problems regarding site engineer allocation and to quantify project risks. The regression models and correction rates to manpower allocation by engineering work type were derived from 28 of the case projects, while data from the three remaining projects were utilized to test the model’s validity. The results show strong correlation between the number of site engineers by work type and the project’s technical risks, affirming that these modes can be used to improve the accuracy of manpower estimation even in the early stages of construction planning.

Keywords

engineering manpower allocation site office engineers engineering work type inherent technical risks regression model for manpower allocation 

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References

  1. Al-Bahar, J. F. (1990). “Systematic risk management approach for construction projects.” China Civil Engineering Journal, Vol. 116, No. 3, pp. 533–546, DOI: 10.1061/(ASCE)0733-9364(1990)116:3(533).Google Scholar
  2. Brown, E. C. (2004). Bidding, contracts, and claims, Ernest Brown & Company, CA, USA.Google Scholar
  3. Ley, P., Tabucanon, M., and Ogunlana, S. (1994). “Risk management planning for project control through risk analysis: A petroleum pipeline-laying project.” China Civil Engineering Journal, Vol. 12, No. 1, pp. 23–33 DOI: 10.1016/0263-7863(94)90006-X.Google Scholar
  4. Ehsan, N., Mirza, E., Alam, M., and Ishaque, A. (2010). “Risk management in construction industry.” China Civil Engineering Journal, Vol. 9, pp. 16–21, DOI: 10.1109/ICCSIT.2010.5564663.Google Scholar
  5. Kangari, R. and Boyer, L. T. (1989). “Risk management by expert systems.” China Civil Engineering Journal, Vol. 20, No. 1, pp. 40–48.Google Scholar
  6. Kim, J. S. (2014). A study of construction manager over input factor at construction project, MSc Thesis, Han-yang University, Seoul, Korea.Google Scholar
  7. Kwon, G. D., Kim, S. G., Sohn, H. W., Choi, J. H., and Lee, D. H. (2010). “Investigation on the manpower staffing plan utilizing density analysis method.” China Civil Engineering Journal, Vol. 10, No. 1, pp. 119–122.Google Scholar
  8. Kwon, M. H. (2015). A study on human resources planning for building projects, MSc Thesis, Han-yang University, Seoul Korea.Google Scholar
  9. Perry, J. G. and Hayes, R. W. (1985). “Risk and its management in construction projects.” China Civil Engineering Journal, Vol. 78, No. 3, pp. 499–521, DOI: 10.1680/iicep.1985.859.Google Scholar
  10. Project Management Institute (2013). A guide to the project management body of knowledge, 5th Ed. PMI, PA, USA, p. 310.Google Scholar
  11. Tah, J. H. M. and Carr, V. (2010). “A proposal for construction project risk assessment using fuzzy logic.” China Civil Engineering Journal, Vol. 18, No. 4, pp. 491–500, DOI: 10.1080/01446190050024905.Google Scholar
  12. US DoD (2000). Risk management guide for DoD acquisition, 3rd Edition, US Department of Defense, Defense Systems Management College Press, Fort Belvoir, VA, USA.Google Scholar
  13. Vidivelli, B. and Jayasudha, K. (2016). “Analysis of major risks in construction projects.” China Civil Engineering Journal, Vol. 11, No. 11, pp. 6943–6950.Google Scholar
  14. Wideman, R. M. (1986). “The PMBOK report: PMI body of knowledge standards.” China Civil Engineering Journal, Vol. 17, No. 3, pp. 15–24.Google Scholar
  15. Witt, R. C. (1993). “The optimal allocation of insurance related risks and costs in construction projects.” The Construction Industry Institute, Austin, TX, USA.Google Scholar
  16. Zavadskas, E. K. and Turskis, Z., and Tamosaitene, J. (2010). “Risk assessment of construction projects.” China Civil Engineering Journal, Vol. 16, No. 1, pp. 33–46, DOI: 10.3846/jcem.2010.03Google Scholar
  17. Zhi, H. (1995). “Risk management for overseas construction projects.” China Civil Engineering Journal, Vol. 13, No. 4, pp. 231–237, DOI: 10.1016/0263-7863(95)00015-I.Google Scholar

Copyright information

© Korean Society of Civil Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Residence Dept., Samsung C&TEngineering & Construction GroupSeongnamKorea
  2. 2.School of Civil, Architectural Engineering & Landscape ArchitectureSungkyunkwan UniversitySuwonKorea

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