The digitalization of the construction industry is deemed a crucial element in Construction 4.0’s vision, attainable through the implementation of digital twinning. It is perceived as a virtual strategy to surmount the constraints linked with traditional construction projects, thereby augmenting their productivity and effectiveness. However, the neglect to investigate the causal relationship between implementation and construction project management performance has resulted from a lack of understanding and awareness regarding the consequences of digital twinning implementation, combined with a shortage of expertise among construction professionals. Consequently, this paper extensively explores the relationship between digital twinning implementation and construction project management performance. The Innovation Diffusion Theory (IDT) is employed to investigate this relationship, utilizing a quantitative research approach through document analysis and questionnaire surveys. Additionally, partial least squares structural equation modeling (PLS-SEM) with SmartPLS software is employed to deduce the relationship. The results underscore that digital twinning implementation significantly improves construction project management performance. Despite recognizing various challenges in digital twinning implementation, when regarded as moderating factors, these challenges do not significantly impact the established causal relationship. Therefore, this investigation aligns with the national push toward the digitalization of the construction sector, highlighting the positive impacts of digital twinning implementation on construction project management performance. Moreover, this study details the impacts of implementing digital twinning from the construction industry’s perspective, including positive and negative impacts. Afterwards, this paper addresses the existing research gap, providing a more precise understanding and awareness among construction industry participants, particularly in developing nations.

Adeleke, A. Q., Bamgbade, J. A., Gbadebo Salimon, M., et al. (2019). Project Management Performance and Its Influence on Malaysian Building Projects. KnE Social Sciences. https://doi.org/10.18502/kss.v3i22.5058

Al-Ageeli, H. K., & Alzobaee, A. S. J. A. (2016). Critical Success Factors in Construction Projects (Governmental Projects as a Case Study). Journal of Engineering, 22(3), 129–147. https://doi.org/10.31026/j.eng.2016.03.09

Albtoush, A. M. F., Doh, S. I., Rahman, R. A., et al. (2022). Critical success factors of construction projects in Jordan: an empirical investigation. Asian Journal of Civil Engineering, 23(7), 1087–1099. https://doi.org/10.1007/s42107-022-00470-8

Aljohani, A. (2017). Construction Projects Cost Overrun: What Does the Literature Tell Us? International Journal of Innovation, Management and Technology, 137–143. https://doi.org/10.18178/ijimt.2017.8.2.717

Alzahrani, J. I., & Emsley, M. W. (2013). The impact of contractors’ attributes on construction project success: A post construction evaluation. International Journal of Project Management, 31(2), 313–322. https://doi.org/10.1016/j.ijproman.2012.06.006

Ammar, A., Nassereddine, H., AbdulBaky, N., et al. (2022). Digital Twins in the Construction Industry: A Perspective of Practitioners and Building Authority. Frontiers in Built Environment, 8. https://doi.org/10.3389/fbuil.2022.834671

Andrić, J. M., Mahamadu, A. M., Wang, J., et al. (2019). The cost performance and causes of overruns in infrastructure development projects in Asia. Journal Of Civil Engineering and Management, 25(3), 203–214. https://doi.org/10.3846/jcem.2019.8646

Attaran, M., & Celik, B. G. (2023). Digital Twin: Benefits, use cases, challenges, and opportunities. Decision Analytics Journal, 6, 100165. https://doi.org/10.1016/j.dajour.2023.100165

Baccarini, D. (1999). The Logical Framework Method for Defining Project Success. Project Management Journal, 30(4), 25–32. https://doi.org/10.1177/875697289903000405

Bertoni, M., & Bertoni, A. (2022). Designing solutions with the product-service systems digital twin: What is now and what is next? Computers in Industry, 138, 103629. https://doi.org/10.1016/j.compind.2022.103629

Besklubova, S., Skibniewski, M. J., & Zhang, X. (2021). Factors Affecting 3D Printing Technology Adaptation in Construction. Journal of Construction Engineering and Management, 147(5). https://doi.org/10.1061/(ASCE)CO.1943-7862.0002034

Bi, D., & Huo, Y. (2021). Application analysis of digital twin model in horizontal directional drilling. Journal of Physics: Conference Series, 2030(1), 012066. https://doi.org/10.1088/1742-6596/2030/1/012066

Bin Seddeeq, A., Assaf, S., Abdallah, A., et al. (2019). Time and Cost Overrun in the Saudi Arabian Oil and Gas Construction Industry. Buildings, 9(2), 41. https://doi.org/10.3390/buildings9020041

Cakmak, E., & Cakmak, P. I. (2014). An Analysis of Causes of Disputes in the Construction Industry Using Analytical Network Process. Procedia—Social and Behavioral Sciences, 109, 183–187. https://doi.org/10.1016/j.sbspro.2013.12.441

Cheung, S. O., Suen, H. C. H., & Cheung, K. K. W. (2004). PPMS: a Web-based construction Project Performance Monitoring System. Automation in Construction, 13(3), 361–376. https://doi.org/10.1016/j.autcon.2003.12.001

Darko, A., Chan, A. P. C., Adabre, M. A., et al. (2020). Artificial intelligence in the AEC industry: Scientometric analysis and visualization of research activities. Automation in Construction, 112, 103081. https://doi.org/10.1016/j.autcon.2020.103081

Demirkesen, S., & Ozorhon, B. (2017). Impact of integration management on construction project management performance. International Journal of Project Management, 35(8), 1639–1654. https://doi.org/10.1016/j.ijproman.2017.09.008

Douglass, B. P. (2014). High-Fidelity Modeling. Real-Time UML Workshop for Embedded Systems, 179–217. https://doi.org/10.1016/b978-0-12-407781-2.00007-6

Edirisinghe, R. (2018). Digital skin of the construction site. Engineering, Construction and Architectural Management, 26(2), 184–223. https://doi.org/10.1108/ecam-04-2017-0066

Famiyeh, S., Amoatey, C. T., Adaku, E., et al. (2017). Major causes of construction time and cost overruns. Journal of Engineering, Design and Technology, 15(2), 181–198. https://doi.org/10.1108/jedt-11-2015-0075

Fathi, E., & Stevovic, S. (2016). Measurement the efficiency of building project management. Ekonomika, 62(4), 129–140. https://doi.org/10.5937/ekonomika1604129e

Forcael, E., Ferrari, I., Opazo-Vega, A., et al. (2020). Construction 4.0: A Literature Review. Sustainability, 12(22), 9755. https://doi.org/10.3390/su12229755

Francis, A., & Thomas, A. (2020). Exploring the relationship between lean construction and environmental sustainability: A review of existing literature to decipher broader dimensions. Journal of Cleaner Production, 252, 119913. https://doi.org/10.1016/j.jclepro.2019.119913

Gil, J. (2020). City Information Modelling: A Conceptual Framework for Research and Practice in Digital Urban Planning. Built Environment, 46(4), 501–527. https://doi.org/10.2148/benv.46.4.501

Gledson, B. J., Williams, D. N., & Littlemore, M. (2018). Construction Planning Efficiency and Delivery Time Performance: Analysing Failure in Task-Level ‘Hit Rates’. In: Proceedings of the ARCOM 2018: 34th Annual Conference—A Productive Relationship: Balancing Fragmentation and Integration; Belfast, UK.

Greif, T., Stein, N., & Flath, C. M. (2020). Peeking into the void: Digital twins for construction site logistics. Computers in Industry, 121, 103264. https://doi.org/10.1016/j.compind.2020.103264

Grieves, M., & Vickers, J. (2017). Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems (Excerpt). In: Kahlen, J., Flumerfelt, S., Alves, A. (editors). Transdisciplinary Perspectives on Complex Systems. Springer. pp. 85-113. https://doi.org/10.1007/978-3-319-38756-7_4

Gudienė, N., Banaitis, A., Banaitienė, N., et al. (2013). Development of a Conceptual Critical Success Factors Model for Construction Projects: A Case of Lithuania. Procedia Engineering, 57, 392–397. https://doi.org/10.1016/j.proeng.2013.04.051

Gunduz, M., & Almuajebh, M. (2020). Critical Success Factors for Sustainable Construction Project Management. Sustainability, 12(5), 1990. https://doi.org/10.3390/su12051990

Gurevich, U., & Sacks, R. (2020). Longitudinal Study of BIM Adoption by Public Construction Clients. Journal of Management in Engineering, 36(4). https://doi.org/10.1061/(ASCE)ME.1943-5479.0000797

Gurgun, A. P., & Koc, K. (2022). The role of contract incompleteness factors in project disputes: a hybrid fuzzy multi-criteria decision approach. Engineering, Construction and Architectural Management, 30(9), 3895–3926. https://doi.org/10.1108/ecam-11-2021-1020

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis, 8th ed. Annabel Ainscow.

Ham, Y., Lee, S. J., & Chowdhury, A. G. (2017). Imaging-to-Simulation Framework for Improving Disaster Preparedness of Construction Projects and Neighboring Communities. Computing in Civil Engineering. https://doi.org/10.1061/9780784480830.029

Han, S. H., Kim, D. Y., Kim, H., et al. (2006). Fully Integrated Web-Based Risk Management Systems for Highly Uncertain Global Projects. In: Proceedings of the 23rd International Symposium on Automation and Robotics in Construction. https://doi.org/10.22260/isarc2006/0052

Hassani, H., Huang, X., & MacFeely, S. (2022). Impactful Digital Twin in the Healthcare Revolution. Big Data and Cognitive Computing, 6(3), 83. https://doi.org/10.3390/bdcc6030083

Hussain, C. M., Paulraj, M. S., & Nuzhat, S. (2022). Source reduction and waste minimization in construction industry. Source Reduction and Waste Minimization, 111–126. https://doi.org/10.1016/b978-0-12-824320-6.00005-8

Hwang, B. G., Ngo, J., & Her, P. W. Y. (2020). Integrated Digital Delivery: Implementation status and project performance in the Singapore construction industry. Journal of Cleaner Production, 262, 121396. https://doi.org/10.1016/j.jclepro.2020.121396

Jazzar, M. E., Piskernik, M., & Nassereddine, H. (2020). Digital Twin in Construction: An Empirical Analysis, EG-ICE 2020 Workshop on Intelligent Computing in Engineering. Universitätsverlag der TU Berlin.

Jiang, F., Ma, L., Broyd, T., et al. (2021). Digital twin and its implementations in the civil engineering sector. Automation in Construction, 130, 103838. https://doi.org/10.1016/j.autcon.2021.103838

Jiang, Y., Li, M., Guo, D., et al. (2022). Digital twin-enabled smart modular integrated construction system for on-site assembly. Computers in Industry, 136, 103594. https://doi.org/10.1016/j.compind.2021.103594

Kamari, M., & Ham, Y. (2022). AI-based risk assessment for construction site disaster preparedness through deep learning-based digital twinning. Automation in Construction, 134, 104091. https://doi.org/10.1016/j.autcon.2021.104091

Kock, N., & Hadaya, P. (2016). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information Systems Journal, 28(1), 227–261. https://doi.org/10.1111/isj.12131

Larsen, J. K., Shen, G. Q., Lindhard, S. M., & Brunoe, T. D. (2015). Factors Affecting Schedule Delay, Cost Overrun, and Quality Level in Public Construction Projects. Journal of Management in Engineering, 32(1), 04015032. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000391

Lee, J., Lapira, E., Bagheri, B., et al. (2013). Recent advances and trends in predictive manufacturing systems in big data environment. Manufacturing Letters, 1(1), 38–41. https://doi.org/10.1016/j.mfglet.2013.09.005

Lei, B., Janssen, P., Stoter, J., et al. (2023). Challenges of urban digital twins: A systematic review and a Delphi expert survey. Automation in Construction, 147, 104716. https://doi.org/10.1016/j.autcon.2022.104716

Lim, K. Y. H., Zheng, P., Chen, C. H., et al. (2020). A digital twin-enhanced system for engineering product family design and optimization. Journal of Manufacturing Systems, 57, 82–93. https://doi.org/10.1016/j.jmsy.2020.08.011

Ling, F. Y. Y., Chan, S. L., Chong, E., & Ee, L. P. (2004). Predicting Performance of Design-Build and Design-Bid-Build Projects. Journal of Construction Engineering and Management, 130(1), 75-83. https://doi.org/10.1061/(ASCE)0733-9364(2004)130:1(75)

Liu, M., Fang, S., Dong, H., et al. (2021). Review of digital twin about concepts, technologies, and industrial applications. Journal of Manufacturing Systems, 58, 346–361. https://doi.org/10.1016/j.jmsy.2020.06.017

Liyanage, C., & Villalba-Romero, F. (2015). Measuring Success of PPP Transport Projects: A Cross-Case Analysis of Toll Roads. Transport Reviews, 35(2), 140–161. https://doi.org/10.1080/01441647.2014.994583

Lu, Q., Parlikad, A. K., Woodall, P., et al. (2020). Developing a Digital Twin at Building and City Levels: Case Study of West Cambridge Campus. Journal of Management in Engineering, 36(3), 05020004. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000763

Mahamid, I. (2016). Factors contributing to poor performance in construction projects: studies of Saudi Arabia. Australian Journal of Multi-Disciplinary Engineering, 12(1), 27–38. https://doi.org/10.1080/14488388.2016.1243034

Matthews, J., Love, P. E. D., Heinemann, S., et al. (2015). Real time progress management: Re-engineering processes for cloud-based BIM in construction. Automation in Construction, 58, 38–47. https://doi.org/10.1016/j.autcon.2015.07.004

Nabi, M. A., & El-adaway, I. H. (2021). Understanding the Key Risks Affecting Cost and Schedule Performance of Modular Construction Projects. Journal of Management in Engineering, 37(4), 04021023. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000917

Neyestani, B. (2016). Effectiveness of Quality Management System (QMS) on Construction Projects. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2947712

Nnaji, C., & Karakhan, A. A. (2020). Technologies for safety and health management in construction: Current use, implementation benefits and limitations, and adoption barriers. Journal of Building Engineering, 29, 101212. https://doi.org/10.1016/j.jobe.2020.101212

Nolling, K. (2016). THINK ACT—Digitization in the Construction Industry (Building Europe’s Road to “Construction 4.0”: A comprehensive guide to reinventing companies). Available online: https://www.rolandberger.com/en/Media/Digitization-in-the-construction-sector.html (accessed on 3 March 2023).

Oke, A., Aigbavboa, C., & Dlamini, E. (2017). Factors Affecting Quality of Construction Projects in Swazilland. In: Proceedings of the Ninth International Conference on Construction in the 21st Century (CITC-9); Dubai, United Arab Emirates.

Olsson, N. O. E., Arica, E., Woods, R., et al. (2021). Industry 4.0 in a project context: Introducing 3D printing in construction projects. Project Leadership and Society, 2, 100033. https://doi.org/10.1016/j.plas.2021.100033

Olsson, N. O. E., Shafqat, A., Arica, E., et al. (2019). 3D-Printing Technology in Construction: Results from a Survey. Emerald Reach Proceedings Series, 349–356. https://doi.org/10.1108/s2516-285320190000002044

Opoku, D. G. J., Perera, S., Osei-Kyei, R., et al. (2021). Digital twin application in the construction industry: A literature review. Journal of Building Engineering, 40, 102726. https://doi.org/10.1016/j.jobe.2021.102726

Oraee, M., Hosseini, M. R., Edwards, D. J., et al. (2019). Collaboration barriers in BIM-based construction networks: A conceptual model. International Journal of Project Management, 37(6), 839–854. https://doi.org/10.1016/j.ijproman.2019.05.004

Paz, D. H. F., Lafayette, K. P. V., & Sobral, M. C. M. (2020). Management of construction and demolition waste using GIS tools. Advances in Construction and Demolition Waste Recycling. Woodhead Publishing. pp. 121–156. https://doi.org/10.1016/b978-0-12-819055-5.00008-5

Pereira, A. P., Buzzo, M., Zimermann, I., et al. (2021). A Descriptive 3D City Information Model Built from Infrastructure BIM. International Journal of E-Planning Research, 10(4), 138–151. https://doi.org/10.4018/ijepr.20211001.oa9

Puan, Z. A. (2019). Focus Group Discussion (FGD) for the Proposed Development of Solid Waste Transfer Station, on 12.474 Acres of Land on Lots 1336 & 1337, Pekan Nenas, Mukim Jeram Batu, Daerah Pontian, Johor Darul Takzim for Jabatan Pengurusan Sisa Pepejal Negara (JPSPN). IKTISAS ENVIRONMENT SDN BHD.

Qi, Q., Tao, F., Hu, T., et al. (2021). Enabling technologies and tools for digital twin. Journal of Manufacturing Systems, 58, 3–21. https://doi.org/10.1016/j.jmsy.2019.10.001

Qiang, M., Wen, Q., Jiang, H., et al. (2015). Factors governing construction project delivery selection: A content analysis. International Journal of Project Management, 33(8), 1780–1794. https://doi.org/10.1016/j.ijproman.2015.07.001

Ramu, S. P., Boopalan, P., Pham, Q. V., et al. (2022). Federated learning enabled digital twins for smart cities: Concepts, recent advances, and future directions. Sustainable Cities and Society, 79, 103663. https://doi.org/10.1016/j.scs.2021.103663

Rasheed, A., San, O., & Kvamsdal, T. (2020). Digital Twin: Values, Challenges and Enablers from a Modeling Perspective. IEEE Access, 8, 21980–22012. https://doi.org/10.1109/access.2020.2970143

Redmond, A., Hore, A., Alshawi, M., et al. (2012). Exploring how information exchanges can be enhanced through Cloud BIM. Automation in Construction, 24, 175–183. https://doi.org/10.1016/j.autcon.2012.02.003

Riaz, H., Iqbal Ahmad Khan, K., Ullah, F., et al. (2023). Key factors for implementation of total quality management in construction Sector: A system dynamics approach. Ain Shams Engineering Journal, 14(3), 101903. https://doi.org/10.1016/j.asej.2022.101903

Sacks, R., Brilakis, I., Pikas, E., et al. (2020). Construction with digital twin information systems. Data-Centric Engineering, 1. https://doi.org/10.1017/dce.2020.16

Sai, Y., Zhang, T., Huang, X., & Ding, C. (2020). Analysis of Digital Twins and Application Value of Power Engineering Based on BIM. In: Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2019). Springer, Singapore.

Schleich, B., Anwer, N., Mathieu, L., et al. (2017). Shaping the digital twin for design and production engineering. CIRP Annals, 66(1), 141–144. https://doi.org/10.1016/j.cirp.2017.04.040

Semeraro, C., Lezoche, M., Panetto, H., et al. (2021). Digital twin paradigm: A systematic literature review. Computers in Industry, 130, 103469. https://doi.org/10.1016/j.compind.2021.103469

Shahat, E., Hyun, C. T., & Yeom, C. (2021). City Digital Twin Potentials: A Review and Research Agenda. Sustainability, 13(6), 3386. https://doi.org/10.3390/su13063386

Shanbari, H. A., Blinn, N. M., & Issa, R. R. (2016). Laser scanning technology and BIM in construction management education. Journal of Information Technology in Construction, 21, 204-217.

Soori, M., Arezoo, B., & Dastres, R. (2023). Digital twin for smart manufacturing, A review. Sustainable Manufacturing and Service Economics, 2, 100017. https://doi.org/10.1016/j.smse.2023.100017

Sun, K., & Liu, R. (2014). Inheritance and Innovation of Engineering Management Informatization. Frontiers of Engineering Management, 1(1), 76. https://doi.org/10.15302/j-fem-2014014

Tan, Y., Yang, W., Yoshida, K., et al. (2019). Application of IoT-Aided Simulation to Manufacturing Systems in Cyber-Physical System. Machines, 7(1), 2. https://doi.org/10.3390/machines7010002

Tao, F., Cheng, J., Qi, Q., et al. (2017). Digital twin-driven product design, manufacturing and service with big data. The International Journal of Advanced Manufacturing Technology, 94(9–12), 3563–3576. https://doi.org/10.1007/s00170-017-0233-1

Tao, F., Sui, F., Liu, A., et al. (2018). Digital twin-driven product design framework. International Journal of Production Research, 57(12), 3935–3953. https://doi.org/10.1080/00207543.2018.1443229

Tao, F., Zhang, H., Liu, A., et al. (2019). Digital Twin in Industry: State-of-the-Art. IEEE Transactions on Industrial Informatics, 15(4), 2405–2415. https://doi.org/10.1109/tii.2018.2873186

Tao, F., Zhang, M., & Nee, A. Y. C. (2019). Digital Twin Driven Smart Manufacturing. Academic Press. https://doi.org/10.1016/C2018-0-02206-9

Thomas, S. N., Palaneeswaran, E., & Kumaraswamy, M. M. (2002). A dynamic e-Reporting system for contractor’s performance appraisal. Advances in Engineering Software, 33(6), 339-349. https://doi.org/10.1016/S0965-9978(02)00042-X

Tiew, S. Y. (2022). Factors affecting performance of graduate architects in contract implementation management: a case study on housing projects in Malaysia. Engineering, Construction and Architectural Management, 31(5), 1789–1806. https://doi.org/10.1108/ecam-11-2021-1010

Tsiga, Z., Emes, M., & Smith, A. (2016). Critical Success Factors for the Construction Industry. PM World Journal, 5(8).

Venkateswaran, C. B., & Murugasan, R. (2017). Time Delay and Cost Overrun of Road over Bridge (ROB) Construction Projects in India. Journal of Construction in Developing Countries, 22(suppl. 1), 79–96. https://doi.org/10.21315/jcdc2017.22.supp1.5

Wang, Z., Jiang, H., Zhang, W., et al. (2020). The Problem Analysis and Solution Suggestion in the Process of City Information Model Construction. In: Proceedings of the 2020 4th International Conference on Smart Grid and Smart Cities (ICSGSC). https://doi.org/10.1109/icsgsc50906.2020.9248544

Wawak, S., Ljevo, Ž., & Vukomanović, M. (2020). Understanding the Key Quality Factors in Construction Projects—A Systematic Literature Review. Sustainability, 12(24), 10376. https://doi.org/10.3390/su122410376

Wu, G., Liu, C., Zhao, X., et al. (2017). Investigating the relationship between communication-conflict interaction and project success among construction project teams. International Journal of Project Management, 35(8), 1466–1482. https://doi.org/10.1016/j.ijproman.2017.08.006

Xu, Z., Zhang, L., Li, H., et al. (2020). Combining IFC and 3D tiles to create 3D visualization for building information modeling. Automation in Construction, 109, 102995. https://doi.org/10.1016/j.autcon.2019.102995

Yu, T., Man, Q., Wang, Y., et al. (2019). Evaluating different stakeholder impacts on the occurrence of quality defects in offsite construction projects: A Bayesian-network-based model. Journal of Cleaner Production, 241, 118390. https://doi.org/10.1016/j.jclepro.2019.118390

Zaccaria, V., Stenfelt, M., Aslanidou, I., et al. (2018). Fleet Monitoring and Diagnostics Framework Based on Digital Twin of Aero-Engines. In: Proceedings of the ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition. https://doi.org/10.1115/gt2018-76414

Zhai, Y., Chen, K., Zhou, J. X., et al. (2019). An Internet of Things-enabled BIM platform for modular integrated construction: A case study in Hong Kong. Advanced Engineering Informatics, 42, 100997. https://doi.org/10.1016/j.aei.2019.100997

Zheng, P., Lin, T. J., Chen, C. H., et al. (2018). A systematic design approach for service innovation of smart product-service systems. Journal of Cleaner Production, 201, 657–667. https://doi.org/10.1016/j.jclepro.2018.08.101

Zhuang, C., Miao, T., Liu, J., et al. (2021). The connotation of digital twin, and the construction and application method of shop-floor digital twin. Robotics and Computer-Integrated Manufacturing, 68, 102075. https://doi.org/10.1016/j.rcim.2020.102075

Zuhairi, A. H., Razuki, B. I., & Rohaizi, M. J. (2020). Construction 4.0 Strategic Plan (2021-2025)—Next Revolution of the Malaysian Construction Industry. Malaysia: Construction Industry Development Board Malaysia (CIDB).