International Journal of
Advanced Multidisciplinary Application

Volume 3, Issue 10

• Author(s)Ranganathan Radhakrishnan Nair, Mr. Darshit Shah
• AffiliationM.Tech Civil Engineering (Construction Project Management), Assistant Professor Department of Civil Engineering, Parul Institute of Engineering and Technology, Parul University, Vadodara, Gujarat, India.
• Page No.1-6
• Volume, Issue & YearVolume 3 Issue 10 , Oct-2026
• Published On05/10/2026
• JournalInternational Journal of Advanced Multidisciplinary Application (IJAMA)
• ISSN No.3048-9350

Abstract

Labour productivity is a central concern in building construction because the rate at which work is completed affects project time, cost and resource utilisation. Previous studies show that productivity is influenced not only by worker effort but also by material availability, tools, supervision, drawings, communication, planning, site conditions and weather. This paper reviews published research on factors affecting construction labour productivity and develops a practical framework for prioritising improvement actions on building projects. A structured literature assessment was undertaken using peer-reviewed studies, established productivity models and recent reviews covering India and other construction contexts. The evidence was organised into six themes: labour capability, material readiness, equipment and tools, management and supervision, information flow, and site and environmental conditions. The reviewed literature consistently identifies material availability, worker skill and experience, competent supervision, communication, drawing availability, planning and site conditions as recurring influences, although their relative importance varies with project context. Recent research also indicates growing use of digital productivity monitoring, while heat exposure is receiving greater attention because of its effect on workforce output. On the basis of the synthesis, the paper proposes a low-cost Productivity Action Matrix linking each factor group with practical controls and measurable indicators. The contribution is a decision-oriented framework for students, site engineers and project managers and a basis for later empirical validation.

Keywords: labour productivity, building construction, site management, supervision, workforce, construction planning

References

1. 1. Jian, F., Liu, Q., Feng, C., Hu, Q., Yu, Q. and Guo, Q. 2025. Critical Factors Affecting Construction Labor Productivity: A Systematic Review and Meta-Analysis. Buildings 15(14): 2463. https://doi.org/10.3390/buildings15142463.
2. 2. Thomas, A.V. and Sudhakumar, J. 2014. Factors Influencing Construction Labour Productivity: An Indian Case Study. Journal of Construction in Developing Countries 19(1): 53–68.
3. 3. Thomas, A.V. and Sudhakumar, J. 2013. Critical Analysis of the Key Factors Affecting Construction Labour Productivity – An Indian Perspective. International Journal of Construction Management 13(4): 103–125. https://doi.org/10.1080/15623599.2013.10878231.
4. 4. Hasan, A., Baroudi, B., Elmualim, A. and Rameezdeen, R. 2018. Factors Affecting Construction Productivity: A 30 Year Systematic Review. Engineering, Construction and Architectural Management 25(7): 916–937. https://doi.org/10.1108/ECAM-02-2017-0035.
5. 5. Naoum, S.G. 2016. Factors Influencing Labor Productivity on Construction Sites. International Journal of Productivity and Performance Management 65(3): 401–421.
6. 6. Dai, J., Goodrum, P.M., Maloney, W.F. and Srinivasan, C. 2009. Latent Structures of the Factors Affecting Construction Labor Productivity. Journal of Construction Engineering and Management 135(5): 397–406.
7. 7. Thomas, H.R. and Yiakoumis, I. 1987. Factor Model of Construction Productivity. Journal of Construction Engineering and Management 113(4): 623–639.
8. 8. Thomas, H.R., Maloney, W.F., Horner, R.M.W., Smith, G.R., Handa, V.K. and Sanders, S.R. 1990. Modeling Construction Labor Productivity. Journal of Construction Engineering and Management 116(4): 705–726.
9. 9. Kaming, P.F., Holt, G.D., Kometa, S.T. and Olomolaiye, P.O. 1998. Severity Diagnosis of Productivity Problems: A Reliability Analysis. International Journal of Project Management 16(2): 107–113. https://doi.org/10.1016/S0263-7863(97)00036-7.
10. 10. Zakeri, M., Olomolaiye, P.O., Holt, G.D. and Harris, F.C. 1996. A Survey of Constraints on Iranian Construction Operatives’ Productivity. Construction Management and Economics 14(5): 417–426.
11. 11. Lim, E.C. and Alum, J. 1995. Construction Productivity: Issues Encountered by Contractors in Singapore. International Journal of Project Management 13(1): 51–58.
12. 12. Abdul Kadir, M.R., Lee, W.P., Jaafar, M.S., Sapuan, S.M. and Ali, A.A.A. 2005. Factors Affecting Construction Labour Productivity for Malaysian Residential Projects. Structural Survey 23(1): 42–54. https://doi.org/10.1108/02630800510586907.
13. 13. Hiyassat, M.A., Hiyari, M.A. and Sweis, G.J. 2016. Factors Affecting Construction Labour Productivity: A Case Study of Jordan. International Journal of Construction Management 16(2): 138–149. https://doi.org/10.1080/15623599.2016.1142266.
14. 14. Enshassi, A., Mohamed, S., Abu Mustafa, Z. and Mayer, P.E. 2007. Factors Affecting Labour Productivity in Building Projects in the Gaza Strip. Journal of Civil Engineering and Management 13(4): 245–254. https://doi.org/10.3846/13923730.2007.9636444.
15. 15. El-Gohary, K.M. and Aziz, R.F. 2014. Factors Influencing Construction Labor Productivity in Egypt. Journal of Management in Engineering 30(1): 1–9. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000168.
16. 16. Odesola, I.A. and Idoro, G.I. 2014. Influence of Labour-Related Factors on Construction Labour Productivity in the South-South Geo-Political Zone of Nigeria. Journal of Construction in Developing Countries 19(1): 93–109.
17. 17. Gurmu, A.T. 2019. Identifying and Prioritizing Safety Practices Affecting Construction Labour Productivity: An Empirical Study. International Journal of Productivity and Performance Management 68(8): 1457–1474. https://doi.org/10.1108/IJPPM-10-2018-0349.
18. 18. Adebowale, O.J. and Agumba, J.N. 2023. A Meta-Analysis of Factors Affecting Construction Labour Productivity in the Middle East. Journal of Construction in Developing Countries 28(1): 193–220. https://doi.org/10.21315/jcdc-12-21-0192.
19. 19. Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al-Salaheen, M. and Musarat, M.A. 2021. Productivity Monitoring in Building Construction Projects: A Systematic Review. Engineering, Construction and Architectural Management 29(7): 2760–2785. https://doi.org/10.1108/ECAM-03-2021-0211.
20. 20. Lim, Y.T., Yi, W. and Wang, H. 2024. Application of Machine Learning in Construction Productivity at Activity Level: A Critical Review. Applied Sciences 14(22): 10605. https://doi.org/10.3390/app142210605.
21. 21. Han, S., Dong, L., Weng, Y. and Xiang, J. 2024. Heat Exposure and Productivity Loss Among Construction Workers: A Meta-Analysis. BMC Public Health 24: 3252. https://doi.org/10.1186/s12889-024-20744-x.
22. 22. Alahmad, B., Lung, S.-C.C., Makar, A., Alwadi, Y., Chiu, C.-H., Hu, S.-C., Chen, L.-J., Chen, H.H. and Chen, C.Y. 2025. Heat Stress and Productivity Losses in Urban Construction Workforces. Nature Cities 2: 703–707. https://doi.org/10.1038/s44284-025-00283-1.
23. 23. Dey, S., Prabhu, S.M. and Subramani, G.S. 2017. Identification and Mitigation of Factors Affecting Human Resource Productivity in Construction. International Journal of Civil Engineering and Technology 8(1): 123–131.
24. 24. Durdyev, S. and Mbachu, J. 2011. On-site Labour Productivity of New Zealand Construction Industry: Key Constraints and Improvement Measures. Construction Economics and Building 11(3): 18–33. https://doi.org/10.5130/AJCEB.v11i3.2120.
25. 25. Ghoddousi, P. and Hosseini, M.R. 2012. A Survey of the Factors Affecting the Productivity of Construction Projects in Iran. Technological and Economic Development of Economy 18(1): 99–116. https://doi.org/10.3846/20294913.2012.661203.

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