Advertisement

International Journal of Civil Engineering

, Volume 17, Issue 3, pp 427–442 | Cite as

Critical Success Factors and Dynamic Modeling of Construction Labour Productivity

  • Shraddha Palikhe
  • Sunkuk Kim
  • Joseph J. KimEmail author
Research paper
  • 110 Downloads

Abstract

Poor construction labour productivity is a major issue within the construction industry because it directly contributes to cost and schedule overrun. Although considerable research has been done on labour productivity factors, few studies have researched construction labour productivity in developing countries. Therefore, in consideration of improving productivity, a questionnaire survey was conducted with construction practitioners involved in the Nepalese construction industry to identify critical factors and to examine the underlying relationships among these factors using fuzzy analytical hierarchical process. The results show that the most critical factors for poor labour productivity are lack of monetary incentive, tools unavailability, insufficient periodic meetings, and unsafe working conditions. The top-ranked factors were compared to those obtained from other countries. The causal relationship diagram and system dynamic models were constructed to examine the inter-relationship between the perceived 30 factors and four criteria to identify the root cause of a decrease in productivity. The system dynamic models will help researchers determine the productivity growth rate in terms of cost and time, and policy makers to revise policies so that the decision maker can draw upon the policy process and its implications. The results not only coincide with the existing body of knowledge on the labour productivity improvement, but also contribute to the growing body of the construction labour productivity research by providing an evaluation method for multi-criteria decision making.

Keywords

Labour productivity factors Developing countries Fuzzy analytic hierarchy Residential buildings System dynamics 

References

  1. 1.
    David WH, Laura AD, James DB (1994) Action response model and loss of productivity in construction. J Constr Eng Manag 1(47):47–64.  https://doi.org/10.1061/(ASCE)0733-9364(1994)120:1(47) Google Scholar
  2. 2.
    Jorge EG, Carl TH, David PM (2002) Assignment and allocation optimization of partially multi skilled workforce. J Constr Eng Manag 2(103):103–109.  https://doi.org/10.1061/(ASCE)0733-9364(2002)128:2(103) Google Scholar
  3. 3.
    Awad SH, Pehr P, Lee MJ (2002) Benchmarking productivity indicators for electrical/mechanical projects. J Constr Eng Manag 128(4):331–337.  https://doi.org/10.1061/(ASCE)0733-9364(2002)128:4(331) Google Scholar
  4. 4.
    Ronie N (2005) Automated project performance control of construction projects. Autom Constr 14(4):467–476.  https://doi.org/10.1016/j.autcon.2004.09.006 Google Scholar
  5. 5.
    Asian Productivity Organisation, APO (2016) Keio University, Japan. ISBN 978–92-833-2472-0Google Scholar
  6. 6.
    Fah CC (2014) Construction and economic development: the case of Malaysia. Constr Manag Econ 12(1):23–35.  https://doi.org/10.1080/15623599.2012.10773182 Google Scholar
  7. 7.
    Kadir MRA, Lee WP, Jaafar MS, Sapuan SM, Ali AAA (2005) Factors affecting construction labour productivity for Malaysian residential projects. Struct Surv 23(1):42–54.  https://doi.org/10.1108/02630800510586907 Google Scholar
  8. 8.
    Anu VT (2014) Critical analysis of the key factors affecting construction labour productivity-an Indian perspective. Int J Constr Manag 13(4):103–125.  https://doi.org/10.1080/15623599.2013.10878231 Google Scholar
  9. 9.
    Abdulaziz MJ (2015) Factors influencing labour productivity in Bahrain’s construction industry. Int J Constr Manag 15(1):94–108.  https://doi.org/10.1080/15623599.2015.1012143 Google Scholar
  10. 10.
    Mohammed AH, Montaser AH, Ghaleb JS (2016) Factors affecting construction labour productivity: a case study of Jordan. Int J Constr Manag 16(2):138–149.  https://doi.org/10.1080/15623599.2016.1142266 Google Scholar
  11. 11.
    Peter FK, Paul OO, Gary DH, Frank CH (1997) Factors influencing construction time and cost overruns on high–rise projects in Indonesia. Constr Manag Econ 15(1):83–94.  https://doi.org/10.1080/014461997373132 Google Scholar
  12. 12.
    Henry MA, Jackson AM, Bengt H (2007) Factors affecting the productivity of building craftsmen studies of Uganda. J Civ Eng Manag 13(3):169–176Google Scholar
  13. 13.
    Adnan E, Sherif M, Ziad AM, Peter EM (2007) Factors affecting labour productivity in building projects in the Gaza Strip. J Civ Eng Manag 15(3):269–280.  https://doi.org/10.1080/13923730.2007.9636444 Google Scholar
  14. 14.
    Rodrigo AR, John DB, Vicente G, Luis FA (2011) Analysis of factors influencing productivity using craftsmen questionnaires: case study in a Chilean construction company. J Constr Eng Manag 137(4):312–320.  https://doi.org/10.1061/(ASCE)CO.1943-7862.0000274 Google Scholar
  15. 15.
    Abdulaziz MJ, Camille GB (2012) Factors affecting construction labour productivity in Kuwait. J Constr Eng Manag 138(7):811–820.  https://doi.org/10.1061/(ASCE)CO.1943-7862.0000501 Google Scholar
  16. 16.
    Anisul I, Mohammad K (2013) Productivity determinants in Oman construction industry. Int J Product Qual Manag 12(4):426–448.  https://doi.org/10.1504/IJPQM.2013.056736 Google Scholar
  17. 17.
    Khaled ME, Remon FA (2014) Factors influencing construction labour productivity in Egypt. J Manag Eng 30(1):1–9.  https://doi.org/10.1061/(ASCE)ME.1943-5479.0000168 Google Scholar
  18. 18.
    Abdulaziz MJ, Charles YK, Jamal HY (2012) A survey of factors influencing the productivity of construction operatives in the state of Qatar. Int J Constr Manag 12(3):1–23.  https://doi.org/10.1080/15623599.2012.10773192 Google Scholar
  19. 19.
    Parviz G, Mohammad RH (2012) A survey of the factors affecting the productivity of construction projects in Iran. Technol Econ Dev Econ 18(1):99–116.  https://doi.org/10.3846/20294913.2012.661203 Google Scholar
  20. 20.
    Zakeri M, Paul O, Gary DH, Frank CH (1997) Factors affecting the motivation of Iranian construction operatives. Build Environ 32(2):161–166.  https://doi.org/10.1016/S0360-1323(96)00044-3 Google Scholar
  21. 21.
    Rangika H (2015) Critical factors which govern labour productivity in building construction industry in Sri Lanka. PM World J 5(5):1–13Google Scholar
  22. 22.
    Nirmal KA, Lee YD, Kim JK (2006) Critical construction conflicting factors identification using analytical hierarchy process. KSCE J Civ Eng 10(3):165–174.  https://doi.org/10.1007/BF02824057 Google Scholar
  23. 23.
    Zohar H, Raplh E (1990) Research of factors influencing construction productivity. Constr Manag Econ 8(1):49–61.  https://doi.org/10.1080/01446199000000005 Google Scholar
  24. 24.
    Krishna PK, Nirajan M, Eddy MR, Terence F (2017) Optimal productivity in labour-intensive construction operations: pilot study. J Constr Eng Manag.  https://doi.org/10.1061/(ASCE)CO.1943-7862.0001257 Google Scholar
  25. 25.
    Somik G, Matt R, Anthony P, Malcolm C (2017) Increasing the productivity of a construction project using collaborative pull planning. Archit Eng Inst.  https://doi.org/10.1061/9780784480502.069 Google Scholar
  26. 26.
    Kazaz A, Acikara T, Er B (2016) Evaluation of factors affecting labor productivity in Turkey by using Herzberg motivation-Hygiene theory. In: Proceedings of the World Congress on Engineering 2016 Vol II, WCE 2016, June 29–July 1, 2016, London, UKGoogle Scholar
  27. 27.
    Barbosa AAR (2017) Productivity and innovation as a support in project management: a study through construction industry in Brazil. PM World J 6(9):1–11.  https://doi.org/10.1002/pmj.21466 Google Scholar
  28. 28.
    Ferber R (1980) Readings in the analysis of survey data. American Marketing Association, New YorkGoogle Scholar
  29. 29.
    George JK, Bo Y (1995) Fuzzy sets and fuzzy logic: theory and applications. Prentice Hall, Upper Saddle RiverzbMATHGoogle Scholar
  30. 30.
    Polit DF, Beck CT (2006) The content validity index: are you sure you know what’s being reported? Critique and recommendations. Res Nurs Health 29:489–497.  https://doi.org/10.1002/nur.20147 Google Scholar
  31. 31.
    Koehn E, Ahmed MU (1999) Production rates for international projects in Asia. Cost Eng 41(8):38–44Google Scholar
  32. 32.
    Buckley JJ (1998) Fuzzy hierarchical analysis. Fuzzy Sets Syst 17(3):233–247MathSciNetzbMATHGoogle Scholar
  33. 33.
    Da YC (1996) Applications of the extent analysis method on Fuzzy AHP. Eur J Oper Res 95:649–655.  https://doi.org/10.1016/0377-2217(95)00300-2 zbMATHGoogle Scholar
  34. 34.
    Michael JM, Saad AJ (2010) Modelling construction project productivity using system dynamics approach. Int J Product Perform Manag 59(1):18–36.  https://doi.org/10.1108/17410401011006095 Google Scholar

Copyright information

© Iran University of Science and Technology 2018

Authors and Affiliations

  1. 1.Department of Architectural EngineeringKyung Hee UniversityYonginSouth Korea
  2. 2.Department of Civil Engineering and Construction Engineering ManagementCalifornia State UniversityLong BeachUSA
  3. 3.International Scholar of Department of Architectural EngineeringKyung Hee UniversityYonginSouth Korea

Personalised recommendations