Analysis of construction productivity based on construction duration per floor and per gross area, with identification of influential factors
Abstract
This study analyzes construction productivity based on the construction duration per floor and per gross area over 20 years (1996–2015) and compares the results among the United States, United Kingdom, South Korea, and Japan, which have similar sizes of total construction investment and market risk. Although construction labor productivity is widely used to analyze and compare construction productivity among countries, it does not consider the changed construction duration caused by levels of investment and technology. Therefore, construction duration per floor and gross area was selected analyze and compare construction productivity in this paper. Regular and non-modular buildings with a total of five or more floors and a basement are collected during the analysis period (1996–2015). The total number of collected buildings is 800 and it includes buildings in the United States (194), the United Kingdom (186), South Korea (322) and Japan (98). Construction duration, increase rate and standard deviation are then compared between each country. Finally, factors that influence construction duration are derived and additionally considered to explain and adjust the trends and changes of construction productivity related to construction duration in the four countries. The productivity of the United States is the highest, but the difference between it and other countries decreases steadily because the increase rate of the construction duration in the United stated is larger than those of other countries. Then, the factors influencing the construction duration are derived as a learning effect by the number of ground floors and gross area, as well as the rate of constructed buildings with a first basement floor for efficient productivity management. The rate of the first basement floor influences both the construction duration per floor and per gross area. This study contributes to the field by explaining the productivity change based on the construction duration and proposing the key management point of the productivity by deriving the influence factors.
Keyword : construction duration, increase rate of construction duration, influence factors, learning effect by the number of floors and gross area, rate of the first basement floor
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Alinaitwe, H. M., Mwakali, J. A., & Hansson, B. (2007). Factors affecting the productivity of building craftsmen – studies of Uganda. Journal of Civil Engineering and Management, 13(3), 169–176. https://doi.org/10.3846/13923730.2007.9636434
Allmon, E., Haas, C. T., Borcherding, J. D.; & Goodrum, P. M. (2000). U.S. construction labor productivity trends, 19701998. Journal of Construction Engineering and Management, 119(2), 97–104. https://doi.org/10.1061/(ASCE)0733-9364(2000)126:2(97)
Banaitienė, N., Banaitis, A., & Laučys, M. (2015). Foreign direct investment and growth: analysis of the construction sector in the Baltic States. Journal of Civil Engineering and Management, 21(6), 813–826. https://doi.org/10.3846/13923730.2015.1046478
BLS. (2016). Current employment statistics – CES (National). http://www.bls.gov/ces/#data
Bughin, J., Manyika, J., & Woetzel, J. (2017). Reinventing construction: A route to higher productivity. McKinsey Global Institute.
Burke, R. D., Parrish, K., & Asmar, M. E. (2018). Environmental product declarations: Use in the architectural and engineering design process to support sustainable construction. Journal of Construction Engineering and Management, 144(5), 04018026. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001481
Chan, D. (1998). Modelling construction durations for public housing projects in Hong Kong. University of Hong Kong, Hong Kong. https://doi.org/10.1016/S0360-1323(98)00040-7
Chan, D. W. M., & Kumaraswamy, M. M. (2002). Compressing construction durations: lessens learned from Hong Kong building projects. International Journal of Project Management, 20, 23–35. https://doi.org/10.1016/S0263-7863(00)00032-6
Chia, F. C., Skitmore, M., Gray, J., & Bridge, A. (2018). International comparisons of nominal and real construction labour productivity. Engineering, Construction and Architectural Management, 25(7), 896–915. https://doi.org/10.1108/ECAM-12-2016-0255
Choy, C. F. (2011). Revisiting the ‘Bon curve’. Construction Management and Economics, 29(7), 695–712. https://doi.org/10.1080/01446193.2011.578959
Couto, J. P., & Teixeira, J. C. (2005). Using linear model for learning curve effect on highrise floor construction. Construction Management and Economics, 23(4), 355–364. https://doi.org/10.1080/01446190500040505
Durdyev, S., Ismail, S., & Kandymov, N. (2018). Structural equation model of the factors affecting construction labor productivity. Journal of Construction Engineering and Management, 144(4), 04018007. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001452
El-Gohary, K. M., & 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
Enshassi, A., Mohamed, S., Mustafa, Z. A., & 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
Forsythe, P. J., & Sepasgozar, S. M. E. (2018). Measuring installation productivity in prefabricated timber construction. Engineering, Construction and Architectural Management, 26(4), 578–598. https://doi.org/10.1108/ECAM-09-2017-0205
Freeman, R. (2008). Labour productivity indicators - Comparison of two OECD databases productivity differentials & the Balassa-Samuelson effect. Division of Structural Economic Statistics, OECD.
Fulford, R., & Standing, C. (2014). Construction industry productivity and the potential for collaborative practice. International Journal of Project Management, 32, 315–326. https://doi.org/10.1016/j.ijproman.2013.05.007
Goodrum, P., Haas, C., & Glover, R. (2002). The divergence in aggregate and activity estimates of U.S. construction productivity. Construction Management and Economics, 20(5), 415–423. https://doi.org/10.1080/01446190210145868
Goodrum, P. M., Zhai, D., & Yasin, M. F. (2009). Relationship between changes in material technology and construction productivity. Jornal of Construction Engineering and Management, 135(4), 278–287. https://doi.org/10.1061/(ASCE)0733-9364(2009)135:4(278)
Gregori, T., & Pietroforte, R. (2015). An input-output analysis of the construction sector in emerging markets. Construction Management and Economics, 33(2), 134–145. https://doi.org/10.1080/01446193.2015.1021704
Han, S., Ko, Y.-H., Hong, T., Koo, C., Lee, S. (2017). Framework for the validation of simulation-based productivity analysis: focused on curtain wall construction process. Journal of Civil Engineering and Management, 23(2), 163–172. https://doi.org/10.3846/13923730.2014.992468
Harrison, P. (2007). Can measurement error explain the weakness of productivity growth in the Canadian construction industry? Centre for the Study of Living Standards (CSLS), Ottawa, Canada.
Hu, X., & Liu, C. (2017). Total factor productivity measurement with carbon reduction. Engineering, Construction and Architectural Management, 24(4), 575–592. https://doi.org/10.1108/ECAM-06-2015-0097
Jarkas, A. M. (2010a). The impacts of buildability factors on formwork labour productivity of columns. Journal of Civil Engineering and Management, 16(4), 471–483. https://doi.org/10.3846/jcem.2010.53
Jarkas, A. (2010b). Critical investigation into the applicability of the learning curve theory to rebar fixing labor productivity. Journal of Construction Engineering and Management, 136(12), 1279–1288. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000236
IHS. (2013). Global construction outlook. IHS Economics, CO, USA.
Liao, P.-C., O’Brien, W. J., Thomas, S. R., Dai, J., & Mulva, S. P. (2011). Factors affecting engineering productivity. Journal of Management in Engineering, 27(4), 229–235. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000059
MOLIT. (2016). Building code. http://www.law.go.kr/%EB%B2%95%EB%A0%B9/%EA%B1%B4%EC%B6%95%EB%B2%95
Nasir, H., Ahmed, H., Haas, C., & Goodrum, P. M. (2014). An analysis of construction productivity differences between Canada and the United States. Construction Management and Economics, 32(6), 595–607. https://doi.org/10.1080/01446193.2013.848995
Nguyen, L. D., & Nguyen, H. T. (2013). Relationship between building floor and construction labor productivity – A case of structural work. Engineering, Construction and Architectural Management, 20(6), 563–575. https://doi.org/10.1108/ECAM-03-2012-0034
Nguyen, L. D., Phan, D. H., & Tang, L. C. M. (2013). Simulating construction duration for multistory buildings with controlling activities. Journal of Construction Engineering and Management, 139(8), 951–959. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000677
Organisation for Economic Co-operation and Development. (2001). Measuring productivity – OECD Manual: measurement of aggregate and industry-level productivity growth. OECD Publications.
Robles, G., Stifi, A., Ponz-Tienda, J. L., & Gentes, S. (2014). Labor productivity in the construction industry – Factors influencing the Spanish construction labor productivity. International Journal of Civil, Architectural, Structural and Construction Engineering, 8(10), 999–1008.
Rojas, E. M., & Aramvareekul, P. (2003). Is construction labor productivity really declining? Journal of Construction Engineering and Management, 129(1), 41–46. https://doi.org/10.1061/(ASCE)0733-9364(2003)129:1(41)
Sacks, R., & Barak, R. (2005). A methodology for assessment of the impact of 3D modeling of buildings on structural engineering productivity. In International Conference on Computing in Civil Engineering 2005. https://doi.org/10.1061/40794(179)41
Shoar, S., & Banaitis, A. (2019). Application of fuzzy fault tree analysis to identify factors influencing construction labor productivity: a high-rise building case study. Journal of Civil Engineering and Management, 25(1), 41–52. https://doi.org/10.3846/jcem.2019.7785
Vereen, S. C., Rasdorf, W., & Hummer, J. E. (2016). Development and comparative analysis of construction industry labor productivity metrics. Journal of Construction Engineering and Management, 142(7), 04016020. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001112
Vogl, B., & Abdel-Wahab, M. (2015). Measuring the construction industry’s productivity performance: Critique of international productivity comparisons at industry level. Journal of Construction Engineering and Management, 141(4), 04014085. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000944
Wideman, R. M. (1994). A pragmatic approach to using resource loading, production, and learining curves on construction projects. Canadian Journal of Civil Engineering, 21(6), 939– 953. https://doi.org/10.1139/l94-100
Won, J., & Lee, G. (2008). An analysis of the international competitiveness of productivity in the Korean construction industry. Korea Journal of Construction Engineering and Management, 9(4), 136–146.
Zhi, M., Hua, G. B., Wang, S. Q., & Ofori, G. 2003. Total factor productivity growth accounting in the construction industry of Singapore. Construction Management and Economics, 21(7), 707–718. https://doi.org/10.1080/0144619032000056126