Quantifying the Impact of Technology Utilization on Schedule and Cost Performance in Construction Projects
Publication: Journal of Construction Engineering and Management
Volume 150, Issue 8
Abstract
There has been a plethora of research on the performance of schedule and cost in construction projects. However, current research falls short in investigating the combined contribution of different construction technologies on project performance metrics. Specifically, none of the previous efforts have used integrated earned value management (EVM) parameters and utilized construction technologies to assess project schedule and cost performance. This paper fills this knowledge gap. To this end, a multistep research methodology was employed to (1) explore the utilization ratings of 13 construction technologies based on data collected from 52 industry experts; (2) rank these technologies in terms of their contribution to schedule and cost savings; (3) map the utilization ratings of construction technologies to schedule and cost variances by leveraging data from 48 construction projects with varying levels and scopes of technology integration to gauge the impact of using these technologies; and (4) develop an associated decision-support model that underwent rigorous verification under extreme conditions and sensitivity analysis. This study makes a noteworthy contribution to the existing body knowledge, revealing that the major drivers for schedule savings are building information modeling (BIM), unmanned aerial vehicles (UAVs), and augmented/virtual reality (AR/VR), while additive manufacturing (AM), digital twin (DT), and Internet of Things (IoT) are the most significant contributors to cost savings. Moreover, the study reveals strong correlations between various technologies, such as UAVs and laser scanning, geographic information system (GIS) and GPS, AR/VR and digital twins, as well as robotics/automation and AR/VR. Furthermore, the study introduces a novel model that enhances the prediction of project performance, specifically in terms of schedule and cost variations resulting from the adoption of various construction technologies. Eventually, it improves the decision-making process related to the deployment of the investigated construction technologies.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or codes generated or used during the study are available from the authors upon reasonable request.
References
Abba, W. F. 1997. “Earned value management-reconciling government and commercial practices.” Program Manager 26 (Jun): 58–63.
Abdul Nabi, M., and I. H. El-adaway. 2021. “Risk-based approach to predict the cost performance of modularization in construction projects.” J. Constr. Eng. Manage. 147 (10): 04021133. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002159.
Abdul Nabi, M., and I. H. El-adaway. 2022. “A proactive risk assessment framework to maximize schedule benefits of modularization in construction projects.” J. Constr. Eng. Manage. 148 (7): 04022052. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002311.
Abioye, S. O., L. O. Oyedele, L. Akanbi, A. Ajayi, J. M. D. Delgado, M. Bilal, O. O. Akinade, and A. Ahmed. 2021. “Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges.” J. Build. Eng. 44 (Dec): 103299. https://doi.org/10.1016/j.jobe.2021.103299.
Akintoye, A. 2000. “Analysis of factors influencing project cost estimating practice.” Construct. Manage. Econ. 18 (1): 77–89. https://doi.org/10.1080/014461900370979.
Assaad, R., I. H. El-adaway, and I. S. Abotaleb. 2020. “Predicting project performance in the construction industry.” J. Constr. Eng. Manage. 146 (5): 04020030. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001797.
Assaad, R. H., I. H. El-adaway, M. Hastak, and K. LaScola Needy. 2023. “Key factors affecting labor productivity in offsite construction projects.” J. Constr. Eng. Manage. 149 (1): 04022158. https://doi.org/10.1061/JCEMD4.COENG-12654.
Babar, S., M. J. Thaheem, and B. Ayub. 2017. “Estimated cost at completion: Integrating risk into earned value management.” J. Constr. Eng. Manage. 143 (3): 04016104. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001245.
Barbosa, F., J. Woetzel, and J. Mischke. 2017. Reinventing construction: A route of higher productivity. New York: McKinsey Global Institute.
Bartlett, J. E., J. W. Kotrlik, and C. C. Higgins. 2001. “Organizational research: Determining appropriate sample size in survey research.” Inf. Technol. Learn. Perform. J. 19 (1): 43.
Blanco, J. L., S. Fuchs, M. Parsons, and M. J. Ribeirinho. 2018. “Artificial intelligence: Construction technology’s next frontier.” Build. Econ. (Sep): 7–13.
Boje, C., A. Guerriero, S. Kubicki, and Y. Rezgui. 2020. “Towards a semantic construction digital twin: Directions for future research.” Autom. Constr. 114 (Jun): 103179. https://doi.org/10.1016/j.autcon.2020.103179.
Bughin, J., E. Hazan, P. Sree Ramaswamy, W. DC, and M. Chu. 2017. Artificial intelligence the next digital frontier. New York: McKinsey.
Camacho, D. D., P. Clayton, W. J. O’Brien, C. Seepersad, M. Juenger, R. Ferron, and S. Salamone. 2018. “Applications of additive manufacturing in the construction industry—A forward-looking review.” Autom. Constr. 89 (May): 110–119. https://doi.org/10.1016/j.autcon.2017.12.031.
Chaphalkar, N. B., K. C. Iyer, and S. K. Patil. 2015. “Prediction of outcome of construction dispute claims using multilayer perceptron neural network model.” Int. J. Project Manage. 33 (8): 1827–1835. https://doi.org/10.1016/j.ijproman.2015.09.002.
Chen, L., and H. Luo. 2014. “A BIM-based construction quality management model and its applications.” Autom. Constr. 46 (Apr): 64–73. https://doi.org/10.1016/j.autcon.2014.05.009.
Choudhry, R. M., M. A. Aslam, J. W. Hinze, and F. M. Arain. 2014. “Cost and schedule risk analysis of bridge construction in Pakistan: Establishing risk guidelines.” J. Constr. Eng. Manage. 140 (7): 04014020. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000857.
Christmann, A., and S. Van Aelst. 2006. “Robust estimation of Cronbach’s alpha.” J. Multivar. Anal. 97 (7): 1660–1674. https://doi.org/10.1016/j.jmva.2005.05.012.
Cochran, W. G. 1977. Sampling techniques. 3rd ed. New York: Wiley.
Converse, J. M., and S. Presser. 1986. Vol. 63 of Survey questions: Handcrafting the standardized questionnaire. Thousand Oaks, CA: SAGE.
Davila Delgado, J. M., L. Oyedele, T. Beach, and P. Demian. 2020. “Augmented and virtual reality in construction: Drivers and limitations for industry adoption.” J. Constr. Eng. Manage. 146 (7): 04020079. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001844.
DBIA (Design–Build Institute of America). 2018 “Projects database.” Accessed September 28, 2023. https://dbia.org/projects-database.
Doloi, H., A. Sawhney, K. C. Iyer, and S. Rentala. 2012. “Analysing factors affecting delays in Indian construction projects.” Int. J. Project Manage. 30 (4): 479–489. https://doi.org/10.1016/j.ijproman.2011.10.004.
Du, J., B.-C. Kim, and D. Zhao. 2016. “Cost performance as a stochastic process: EAC projection by Markov chain simulation.” J. Constr. Eng. Manage. 142 (6): 04016009. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001115.
Fellows, R. F., and A. M. Liu. 2015. Research methods for construction. New York: Wiley.
Firouzi, A., W. Yang, and C.-Q. Li. 2016. “Prediction of total cost of construction project with dependent cost items.” J. Constr. Eng. Manage. 142 (12): 04016072. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001194.
Fowler, F. J. 1995. Improving survey questions: Design and evaluation. Thousand Oaks, CA: SAGE.
Franz, B., K. R. Molenaar, and B. A. M. Roberts. 2020. “Revisiting project delivery system performance from 1998 to 2018.” J. Constr. Eng. Manage. 146 (9): 04020100. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001896.
Gao, N., and A. Touran. 2020. “Cost overruns and formal risk assessment program in US rail transit projects.” J. Constr. Eng. Manage. 146 (5): 05020004. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001827.
Geisser, S., and W. O. Johnson. 2006. Modes of parametric statistical inference. Thousand Oaks, CA: Wiley.
Grau, D., and W. E. Back. 2015. “Predictability index: Novel metric to assess cost and schedule performance.” J. Constr. Eng. Manage. 141 (12): 04015043. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000994.
Haas, C., P. Goodrum, and C. Caldas. 2008. Leveraging technology to improve construction productivity. Austin, TX: Univ. of Texas at Austin.
Hwang, B. G., and W. J. Ng. 2013. “Project management knowledge and skills for green construction: Overcoming challenges.” Int. J. Project Manage. 31 (2): 272–284. https://doi.org/10.1016/j.ijproman.2012.05.004.
Hwang, B.-G., X. Zhao, and S. Y. Ong. 2015. “Value management in Singaporean building projects: Implementation status, critical success factors, and risk factors.” J. Manage. Eng. 31 (6): 04014094. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000342.
IPRA (Integrated Project Risk Assessment). 2013. “Integrated project risk assessment (IPRA), version 2.0.” Accessed January 12, 2024. https://www.construction-institute.org/integrated-project-risk-assessment-ipra-version-2-0.
Irizarry, J., E. P. Karan, and F. Jalaei. 2013. “Integrating BIM and GIS to improve the visual monitoring of construction supply chain management.” Autom. Constr. 31 (Apr): 241–254. https://doi.org/10.1016/j.autcon.2012.12.005.
Jang, Y., K. Kim, F. Leite, S. Ayer, and Y. K. Cho. 2021. “Identifying the perception differences of emerging construction-related technologies between industry and academia to enable high levels of collaboration.” J. Constr. Eng. Manage. 147 (10): 06021004. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002156.
Khun-anod, K., C. Limsawasd, and N. Athigakunagorn. 2023. “Predicting cost and schedule performance of green building projects based on preproject planning efforts using multiple linear regression analysis.” J. Archit. Eng. 29 (3): 04023025. https://doi.org/10.1061/JAEIED.AEENG-1424.
Kim, D. Y., S. H. Han, and H. Kim. 2008. “Discriminant analysis for predicting ranges of cost variance in international construction projects.” J. Constr. Eng. Manage. 134 (6): 398–410. https://doi.org/10.1061/(ASCE)0733-9364(2008)134:6(398).
Kim, E., W. G. Wells Jr., and M. R. Duffey. 2003. “A model for effective implementation of earned value management methodology.” Int. J. Project Manage. 21 (5): 375–382. https://doi.org/10.1016/S0263-7863(02)00049-2.
Li, Y., K. Lu, and Y. Lu. 2017. “Project schedule forecasting for skyscrapers.” J. Manage. Eng. 33 (3): 05016023. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000498.
Lipke, W., O. Zwikael, K. Henderson, and F. Anbari. 2009. “Prediction of project outcome: The application of statistical methods to earned value management and earned schedule performance indexes.” Int. J. Project Manage. 27 (4): 400–407. https://doi.org/10.1016/j.ijproman.2008.02.009.
Nasir, M. K., and B. H. W. Hadikusumo. 2019. “System dynamics model of contractual relationships between owner and contractor in construction projects.” J. Manage. Eng. 35 (1): 04018052. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000666.
Naughton, J. 1994. “What is technology.” In Teaching technology, 7–12. London: Routledge.
Pan, Y., and L. Zhang. 2021. “Roles of artificial intelligence in construction engineering and management: A critical review and future trends.” Autom. Constr. 122 (May): 103517. https://doi.org/10.1016/j.autcon.2020.103517.
Paolini, A., S. Kollmannsberger, and E. Rank. 2019. “Additive manufacturing in construction: A review on processes, applications, and digital planning methods.” Addit. Manuf. 30 (Aug): 100894. https://doi.org/10.1016/j.addma.2019.100894.
Peng, Y., Y. Shi, H. Yan, and J. Zhang. 2020. “Multivariate frequency analysis of annual maxima suspended sediment concentrations and floods in the Jinsha River, China.” J. Hydrol. Eng. 25 (9): 05020029. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001977.
Rudeli, N., A. Santilli, I. Puente, and E. Viles. 2017. “Statistical model for schedule prediction: Validation in a housing-cooperative construction database.” J. Constr. Eng. Manage. 143 (11): 04017083. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001396.
Sacks, R., L. Koskela, B. A. Dave, and R. Owen. 2010. “Interaction of lean and building information modeling in construction.” J. Constr. Eng. Manage. 136 (9): 968–980. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000203.
Salih, F., and I. El-adaway. 2024. “Achieving project objectives and improving functions: The benefits of AI and construction technologies.” In Construction Research Congress 2024, 1–11. Reston, VA: ASCE.
Smith, N. J., T. Merna, and P. Jobling. 2014. Managing risk in construction projects. New York: Wiley.
Son, J., and E. M. Rojas. 2011. “Impact of optimism bias regarding organizational dynamics on project planning and control.” J. Constr. Eng. Manage. 137 (2): 147–157. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000260.
Stephens, M. A. 2017. “Tests based on EDF statistics.” In Goodness-of-fit-techniques, 97–194. New York: Routledge.
Sterman, J. 2010. Business dynamics. New York: McGraw-Hill.
Sudman, S. 1976. Applied sampling. New York: Academic Press.
Tan, Y., L. Shen, C. Langston, W. Lu, and M. C. H. Yam. 2014. “Critical success factors for building maintenance business: A Hong Kong case study.” Facilities 32 (5–6): 208–225. https://doi.org/10.1108/F-08-2012-0062.
Touran, A., and L. Suphot. 1997. “Rank correlations in simulating construction costs.” J. Constr. Eng. Manage. 123 (3): 297–301. https://doi.org/10.1061/(ASCE)0733-9364(1997)123:3(297).
Wasserman, L. 2006. All of nonparametric statistics. New York: Springer.
Wuni, I. Y., G. Q. Shen, A. J. Ogungbile, and J. Z. Ayitey. 2022. “Four-pronged decision support framework for implementing industrialized construction projects.” Constr. Innovation 22 (2): 263–283. https://doi.org/10.1108/CI-11-2020-0184.
Zahrizan, Z., N. M. Ali, A. T. Haron, A. Marshall-Ponting, and Z. A. Hamid. 2013. “Exploring the adoption of building information modelling (BIM) in the Malaysian construction industry: A qualitative approach.” Int. J. Res. Eng. Technol. 2 (8): 384–395. https://doi.org/10.15623/ijret.2013.0208060.
Zhu, H., B.-G. Hwang, J. Ngo, and J. P. S. Tan. 2022. “Applications of smart technologies in construction project management.” J. Constr. Eng. Manage. 148 (4): 04022010. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002260.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 150 • Issue 8 • August 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Oct 23, 2023
Accepted: Feb 20, 2024
Published online: May 21, 2024
Published in print: Aug 1, 2024
Discussion open until: Oct 21, 2024
ASCE Technical Topics:
- Architectural engineering
- Building information modeling
- Building management
- Business management
- Construction costs
- Construction engineering
- Construction management
- Construction methods
- Data analysis
- Engineering fundamentals
- Management methods
- Methodology (by type)
- Practice and Profession
- Project management
- Research methods (by type)
- Scheduling
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.