Analysis of Labor Productivity during concreting operation in building construction of Kathmandu Valley


  • Prerana Joshi Department of Civil Engineering, Pulchowk Campus, IOE,TU, Nepal.
  • Santosh Kumar Shrestha Department of Civil Engineering, Pulchowk Campus, IOE,TU, Nepal.


Concreting, Construction Industry, Labor, Productivity, Productivity Rates, Artificial Neural Network (ANN), Relative Importance Index (RII), Sensitivity Analysis


Purpose: Construction productivity is highly dependent upon the overall productivity of labor during the execution of the project. Labor is considered as one of the most flexible factors for successful accomplishment of construction. The purpose of this research is to assess the effects of set of factors on labor productivity during concreting operation using Artificial Neural Network (ANN) model. The factors determined for this research were collected through questionnaire survey from site engineers, supervisors, project managers involved in construction sites. Most common factors affecting labor productivity were identified from Relative Importance Index (RII). Data were collected from active building construction sites during concreting operation of beam and slab. ANN model was used to study the effect of factors on labor productivity during concreting for estimating the production rates. Mean Square Error (MSE) were calculated from the estimated and actual rates which was obtained 0.17 which shows that the model has estimated the productivity rates within acceptable range. The data thus collected were analyzed using sensitivity analysis. The result of this research will enable to estimate labor productivity during concreting under certain variables accurately and provide understanding of the parameters that impact labor productivity in building construction.

How to cite this article: Joshi P, Shrestha SK. Analysis of Labor Productivity During Concreting Operation in Building Construction of Kathmandu Valley. J Adv Res Const Urban Arch 2019; 4(3&4): 1-6.


1. Jergeas G. Improving construction productivity on alberta oil and gas capital projects, a report submitted to alberta finance and enterprise. Alberta, Canada. 2009.
2. Missbauer H, Hauber W. Bid calculation for construction projects: Regulations and incentive effects of unit price
contracts. European journal of operational research 2006; 171(3): 1005-1019.
3. Salem D. Predicting productivity rates of pouring concrete in Egypt using artificial neural networks model, 2006.
4. Bernolak I. Effective measurement and successful elements of company productivity: The basis of competitiveness and world prosperity. International Journal of Production Economics 1997; 52(1-2): 203-213.
5. EnShassi A, Mohamed S, Mayer P et al. Benchmarking masonry labor productivity. International Journal of Productivity and Performance Management 2007; 56(4): 358-368, 2007.
6. Hanna AS, Chang CK, Sullivan T et al. Impact of shift work on labor productivity for labor intensive contractor. Journal of construction engineering and management 2008; 134(3): 197-204.
7. Ameh VO, Odusami KT. Factors affecting labor productivity in the nigerian construction industry-a case study of indigenous contracting organization in lagos. The Quantity Surveyor 2002; 40(3): 14-18.
8. Groover MP. Work systems and the methods, measurement, and management of work. Pearson Prentice Hall Upper Saddle River, NJ. 2007.
9. Dozzi SP, AbouRizk SM. Productivity in construction. Institute for Research in Construction, National Research Council Ottawa. 1993.
10. Varma S, Apte MR. Productivity in building construction. IOSR Journal of Mechanical and Civil Engineering 2014; 10(5): 64-71.
11. Oduba AO. Predicting industrial construction productivity using fuzzy expert systems. 2004.
12. Chan APC, Chan DAW, Yeung JN. Overview of the application of fuzzy techniques in construction management research. Journal of construction engineering and management 2009; 135(11): 12411252.
13. Gunayd?n HM, Dogan SZ. A neural network approach for early cost estimation of structural systems of buildings. International Journal of Project Management 2004; 22(7): 595-602.
14. Maskey A, Mishra AK. Labor productivity assessment of armed police force Nepal building construction projects. International Journal of Current Research, 2018; 10(11): 75315-75324
15. Chilwal K, Mishra AK. Impact of Performance on profitability of small hydropower projects in Nepal, International Journal of Current Research 2018; 10(1): 63918-63925.
16. Mishra AK, Regmi U. Effects of Price Fluctuation on the Financial Capacity of “Class A” Contractors”. International Journal of Creative Research Thoughts (IJCRT) 2017; 5(4). ISSN: 2320-2882.
17. Mishra AK. Assessment of Human Resource Capacity of Construction Companies in Nepal. J Adv Res Jour Mass Comm 2018; 5(4): 14-25.