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Modelling inter-relationships of barriers to smart construction implementation

    Beiyu You Affiliation
    ; Zhengyi Chen Affiliation
    ; Yulu Xue Affiliation
    ; Yanbo Zhang Affiliation
    ; Keyu Chen Affiliation

Abstract

Smart construction technology offers fresh avenues for advancing the field of civil engineering. It seamlessly integrates across the entire life cycle of civil engineering projects, encompassing planning, design, construction, and maintenance, thereby fundamentally reshaping the landscape of civil engineering development. Nonetheless, it is essential to recognize that, presently, smart construction’s developmental stage remains relatively nascent. Its progression is subject to a myriad of adoption barriers, and the complex dynamics of their interactions remain insufficiently understood. Therefore, this study aims to (1) explore the barriers to the adoption of smart construction; (2) analyze the impact level of each barrier; and the interaction mechanism between the barriers (3) propose effective strategies to promote the development of smart construction. This study commences by identifying 16 major impediments to the adoption of smart construction through a comprehensive synthesis of existing literature and expert interviews. Subsequently, Euclidean similarity analysis is employed to harmonize varying expert assessments. Following this, the Decision-Making Trial and Evaluation Laboratory model is utilized to ascertain the degree of influence associated with each barrier. Further, the Interpretive Structural Model is employed to establish a hierarchical framework that illuminates the interdependencies among these barriers. Additionally, the Matrice d’Impacts Croisés Multiplication Appliqués à un Classement method is invoked to elucidate the roles and statuses of each barrier. Finally, strategies are proposed based on the results of the analysis. This study offers practical strategies for overcoming barriers and driving the adoption of smart construction, filling a critical gap in understanding by identifying key barriers and providing actionable insights, thus significantly advancing the field and empowering stakeholders for successful implementation and dissemination.

Keyword : adoption barriers, decision-making trial and evaluation laboratory model, inner mechanisms, interpretive structural model: smart construction

How to Cite
You, B., Chen, Z., Xue, Y., Zhang, Y., & Chen, K. (2024). Modelling inter-relationships of barriers to smart construction implementation. Journal of Civil Engineering and Management, 30(8), 738–757. https://doi.org/10.3846/jcem.2024.22250
Published in Issue
Oct 15, 2024
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References

Abanda, F. H., Tah, J. H. M., & Cheung, F. K. T. (2017). BIM in off-site manufacturing for buildings. Journal of Building Engineering, 14, 89–102. https://doi.org/10.1016/j.jobe.2017.10.002

Abioye, S. O., Oyedele, L. O., Akanbi, L., Ajayi, A., Davila Delgado, J. M., Bilal, M., Akinade, O. O., & Ahmed, A. (2021). Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges. Journal of Building Engineering, 44, Article 103299. https://doi.org/10.1016/j.jobe.2021.103299

Agarwal, R., Chandrasekaran, S., & Sridhar, M. (2016). Imagining construction’s digital future. McKinsey & Company.

Alaloul, W. S., Liew, M. S., Zawawi, N. A. W. A., & Kennedy, I. B. (2020). Industrial Revolution 4.0 in the construction industry: Challenges and opportunities for stakeholders. Ain Shams Engineering Journal, 11(1), 225–230. https://doi.org/10.1016/j.asej.2019.08.010

Anastasiades, K., Goffin, J., Rinke, M., Buyle, M., Audenaert, A., & Blom, J. (2021). Standardisation: An essential enabler for the circular reuse of construction components? A trajectory for a cleaner European construction industry. Journal of Cleaner Production, 298, Article 126864. https://doi.org/10.1016/j.jclepro.2021.126864

Ansah, M. K., Chen, X., Yang, H., Lu, L., & Lam, P. T. I. (2019). A review and outlook for integrated BIM application in green building assessment. Sustainable Cities and Society, 48, Article 101576. https://doi.org/10.1016/j.scs.2019.101576

Bux, H., Zhang, Z., & Ahmad, N. (2020). Promoting sustainability through corporate social responsibility implementation in the manufacturing industry: An empirical analysis of barriers using the ISM-MICMAC approach. Corporate Social Responsibility and Environmental Management, 27(4), 1729–1748. https://doi.org/10.1002/csr.1920

Chegu Badrinath, A., Chang, Y. T., & Hsieh, S. H. (2016). A review of tertiary BIM education for advanced engineering communication with visualization. Visualization in Engineering, 4, Article 9. https://doi.org/10.1186/s40327-016-0038-6

Chen, C., Chen, C., Wang, Y., Zhao, J., Wu, Y., Sheng, H., & Li, Y. (2021). I3City: An interoperated, intelligent, and integrated platform for smart city ecosystem. IT Professional, 23(4), 88–94. https://doi.org/10.1109/MITP.2020.3036740

Chen, Y., Cai, X., Li, J., Zhang, W., & Liu, Z. (2022). The values and barriers of Building Information Modeling (BIM) implementation combination evaluation in smart building energy and efficiency. Energy Reports, 8(Supplement 6), 96–111. https://doi.org/10.1016/j.egyr.2022.03.075

Chen, R., Tsay, Y.-S., & Zhang, T. (2023a). A multi-objective optimization strategy for building carbon emission from the whole life cycle perspective. Energy, 262, Article 125373. https://doi.org/10.1016/j.energy.2022.125373

Chen, Z.-S., Zhou, M.-D., Chin, K.-S., Darko, A., Wang, X.-J., & Pedrycz, W. (2023b). Optimized decision support for BIM maturity assessment. Automation in Construction, 149, Article 104808. https://doi.org/10.1016/j.autcon.2023.104808

Chen, Z., Chen, K., & Cheng, J. C. P. (2023c). ISM-based analysis of VR-AEC adoption barriers and their inner mechanisms. Engineering, Construction and Architectural Management, 30(9), 4271–4293. https://doi.org/10.1108/ECAM-01-2022-0085

Chen, Z.-S., Wang, Z.-R., Deveci, M., Ding, W., Pedrycz, W., & Skibniewski, M. J. (2024). Optimization-based probabilistic decision support for assessing building information modelling (BIM) maturity considering multiple objectives. Information Fusion, 102, Article 102026. https://doi.org/10.1016/j.inffus.2023.102026

Cheng, Y.-M. (2014). An exploration into cost-influencing factors on construction projects. International Journal of Project Management, 32(5), 850–860. https://doi.org/10.1016/j.ijproman.2013.10.003

Cheng, J. C. P., Chen, K., & Chen, W. (2020). State-of-the-art review on mixed reality applications in the AECO industry. Journal of Construction Engineering and Management, 146(2), Article 03119009. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001749

Chiarelli, A., Al-Mohammedawi, A., Dawson, A. R., & García, A. (2017). Construction and configuration of convection-powered asphalt solar collectors for the reduction of urban temperatures. International Journal of Thermal Sciences, 112, 242–251. https://doi.org/10.1016/j.ijthermalsci.2016.10.012

Das, D., Datta, A., Kumar, P., Kazancoglu, Y., & Ram, M. (2022). Building supply chain resilience in the era of COVID-19: An AHP-DEMATEL approach. Operations Management Research, 15, 249–267. https://doi.org/10.1007/s12063-021-00200-4

Ding, Z., Wang, X., & Zou, P. X. W. (2023). Barriers and countermeasures of construction and demolition waste recycling enterprises under circular economy. Journal of Cleaner Production, 420, Article 138235. https://doi.org/10.1016/j.jclepro.2023.138235

Dong, R.-R. (2017). The application of BIM technology in building construction quality management and talent training. Eurasia Journal of Mathematics, Science and Technology Education, 13(7), 4311–4317. https://doi.org/10.12973/eurasia.2017.00860a

Dong, R. R., & Martin, A. (2017). Research on barriers and government driving force in technological innovation of architecture based on BIM. Eurasia Journal of Mathematics, Science and Technology Education, 13(8), 5757–5763. https://doi.org/10.12973/eurasia.2017.01025a

García De Soto, B., Agustí-Juan, I., Hunhevicz, J., Joss, S., Graser, K., Habert, G., & Adey, B. T. (2018). Productivity of digital fabrication in construction: Cost and time analysis of a robotically built wall. Automation in Construction, 92, 297–311. https://doi.org/10.1016/j.autcon.2018.04.004

Gardas, B. B., Mangla, S. K., Raut, R. D., Narkhede, B. & Luthra, S. (2019). Green talent management to unlock sustainability in the oil and gas sector. Journal of Cleaner Production, 229, 850–862. https://doi.org/10.1016/j.jclepro.2019.05.018

Ghansah, F. A., Owusu-Manu, D.-G., Ayarkwa, J., Edwards, D. J., & Hosseini, M. R. (2021). Exploration of latent barriers inhibiting project management processes in adopting smart building technologies (SBTs) in the developing countries. Construction Innovation, 21(4), 685–707. https://doi.org/10.1108/CI-07-2020-0116

Gong, J., & Caldas, C. H. (2011). An object recognition, tracking, and contextual reasoning-based video interpretation method for rapid productivity analysis of construction operations. Automation in Construction, 20(8), 1211–1226. https://doi.org/10.1016/j.autcon.2011.05.005

He, R., Li, M., Gan, V. J. L., & Ma, J. (2021a). BIM-enabled computerized design and digital fabrication of industrialized buildings: A case study. Journal of Cleaner Production, 278, Article 123505. https://doi.org/10.1016/j.jclepro.2020.123505

He, Y., Kang, J., Pei, Y., Ran, B., & Song, Y. (2021b). Research on influencing factors of fuel consumption on superhighway based on DEMATEL-ISM model. Energy Policy, 158, Article 112545. https://doi.org/10.1016/j.enpol.2021.112545

Hong, J., Shen, G. Q., Li, Z., Zhang, B., & Zhang, W. (2018). Barriers to promoting prefabricated construction in China: A cost–benefit analysis. Journal of Cleaner Production, 172, 649–660. https://doi.org/10.1016/j.jclepro.2017.10.171

Hu, Z.-Z., Tian, P.-L., Li, S.-W., & Zhang, J.-P. (2018). BIM-based integrated delivery technologies for intelligent MEP management in the operation and maintenance phase. Advances in Engineering Software, 115, 1–16. https://doi.org/10.1016/j.advengsoft.2017.08.007

Huang, B., Lei, J., Ren, F., Chen, Y., Zhao, Q., Li, S., & Lin, Y. (2021). Contribution and obstacle analysis of applying BIM in promoting green buildings. Journal of Cleaner Production, 278, Article 123946. https://doi.org/10.1016/j.jclepro.2020.123946

Huh, S.-H., Ham, N., Kim, J.-H., & Kim, J.-J. (2023). Quantitative impact analysis of priority policy applied to BIM-based design validation. Automation in Construction, 154, Article 105031. https://doi.org/10.1016/j.autcon.2023.105031

Huo, T., Cong, X., Cheng, C., Cai, W., & Zuo, J. (2023). What is the driving mechanism for the carbon emissions in the building sector? An integrated DEMATEL-ISM model. Energy, 274, Article 127399. https://doi.org/10.1016/j.energy.2023.127399

Hwang, B.-G., Ngo, J., & Teo, J. Z. K. (2022). Challenges and strategies for the adoption of smart technologies in the construction industry: The case of Singapore. Journal of Management in Engineering, 38(1), Article 05021014. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000986

Iyer, K. C., & Jha, K. N. (2005). Factors affecting cost performance: evidence from Indian construction projects. International Journal of Project Management, 23(4), 283–295. https://doi.org/10.1016/j.ijproman.2004.10.003

Jahanger, Q. K., Trejo, D., & Louis, J. (2023). Evaluation of field labor and management productivity in the USA construction industry. Engineering, Construction and Architectural Management. https://doi.org/10.1108/ECAM-09-2022-0918

Jalaei, F., Masoudi, R., & Guest, G. (2022). A framework for specifying low-carbon construction materials in government procurement: A case study for concrete in a new building investment. Journal of Cleaner Production, 345, Article 131056. https://doi.org/10.1016/j.jclepro.2022.131056

Jia, Y., Lu, L., Wu, G., Liu, Y., & Mo, X. (2022). Spatial nonlinear simulation analysis on the temperature shrinkage effect of a super-long frame structure considering the construction process. Processes, 10(9), Article 1874. https://doi.org/10.3390/pr10091874

Jiang, D. (2020). The construction of smart city information system based on the Internet of Things and cloud computing. Computer Communications, 150, 158–166. https://doi.org/10.1016/j.comcom.2019.10.035

Jiang, R., Wu, C., Lei, X., Shemery, A., & Wu, P. (2021). Government efforts and roadmaps for building information modeling implementation: lessons from Singapore, the UK and the US. Engineering Construction and Architectural Management, 29(2), 782–818. https://doi.org/10.1108/ECAM-08-2019-0438

Jiang, Y., Li, M., Li, M., Liu, X., Zhong, R. Y., Pan, W., & Huang, G. Q. (2022). Digital twin-enabled real-time synchronization for planning, scheduling, and execution in precast on-site assembly. Automation in Construction, 141, Article 104397. https://doi.org/10.1016/j.autcon.2022.104397

Jiang, Y., Yang, G., Li, H., & Zhang, T. (2023). Knowledge driven approach for smart bridge maintenance using big data mining. Automation in Construction, 146, Article 104673. https://doi.org/10.1016/j.autcon.2022.104673

Jin, G. (2023). Selection of virtual team members for smart port development projects through the application of the direct and indirect uncertain TOPSIS method. Expert Systems with Applications, 217, Article 119555. https://doi.org/10.1016/j.eswa.2023.119555

Karim, R., & Karmaker, C. L. (2016). Machine selection by AHP and TOPSIS methods. American Journal of Industrial Engineering, 4(1), 7–13.

Karthick, S., Kermanshachi, S., Pamidimukkala, A., & Namian, M. (2023). A review of construction workforce health challenges and strategies in extreme weather conditions. International Journal of Occupational Safety and Ergonomics, 29(2), 773–784. https://doi.org/10.1080/10803548.2022.2082138

Karthik, D., & Rao, C. B. K. (2019). Influence of human parameters on labor productivity in the construction industry. Human Factors, 61, 1086–1098. https://doi.org/10.1177/0018720819829944

Kim, J. H., & Ahn, B. S. (2019). Extended VIKOR method using incomplete criteria weights. Expert Systems with Applications, 126, 124–132. https://doi.org/10.1016/j.eswa.2019.02.019

Kumar, A., Srivastava, V., Singh, M. K., & Hancke, G. P. (2015). Current status of the IEEE 1451 standard-based sensor applications. IEEE Sensors Journal, 15(5), 2505–2513. https://doi.org/10.1109/JSEN.2014.2359794

Kumar, A., Singh, A., Kumar, A., Singh, M. K., Mahanta, P., & Mukhopadhyay, S. C. (2018). Sensing technologies for monitoring intelligent buildings: A review. IEEE Sensors Journal, 18(12), 4847–4860. https://doi.org/10.1109/JSEN.2018.2829268

Lee, H.-S., Tzeng, G.-H., Yeih, W., Wang, Y.-J., & Yang, S.-C. (2013). Revised DEMATEL: Resolving the infeasibility of DEMATEL. Applied Mathematical Modelling, 37(10–11), 6746–6757. https://doi.org/10.1016/j.apm.2013.01.016

Lee, J., Park, Y.-J., Choi, C.-H., & Han, C.-H. (2017). BIM-assisted labor productivity measurement method for structural formwork. Automation in Construction, 84, 121–132. https://doi.org/10.1016/j.autcon.2017.08.009

Leśniak, A., Górka, M., & Skrzypczak, I. (2021). Barriers to BIM implementation in architecture, construction, and engineering projects – The Polish study. Energies, 14, Article 2090. https://doi.org/10.3390/en14082090

Li, J., Greenwood, D., & Kassem, M. (2019). Blockchain in the built environment and construction industry: A systematic review, conceptual models and practical use cases. Automation in Construction, 102, 288–307. https://doi.org/10.1016/j.autcon.2019.02.005

Li, C. Z., Chen, Z., Xue, F., Kong, X. T. R., Xiao, B., Lai, X., & Zhao, Y. (2021). A blockchain- and IoT-based smart product-service system for the sustainability of prefabricated housing construction. Journal of Cleaner Production, 286, Article 125391. https://doi.org/10.1016/j.jclepro.2020.125391

Liu, L., Li, Z., Cai, G., Liu, X., & Yan, S. (2020). Humidity field characteristics in road embankment constructed with recycled construction wastes. Journal of Cleaner Production, 259, Article 120977. https://doi.org/10.1016/j.jclepro.2020.120977

Liu, X., Dou, Z., & Yang, W. (2021). Research on influencing factors of cross border e-commerce supply chain resilience based on integrated fuzzy DEMATEL-ISM. IEEE Access, 9, 36140–36153. https://doi.org/10.1109/ACCESS.2021.3059867

Liu, Q., Ma, J., Zhao, X., Zhang, K., Xiangli, K., & Meng, D. (2024). A novel method for fault diagnosis and type identification of cell voltage inconsistency in electric vehicles using weighted Euclidean distance evaluation and statistical analysis. Energy, 293, Article 130575. https://doi.org/10.1016/j.energy.2024.130575

Lyu, H.-M., Zhou, W.-H., Shen, S.-L., & Zhou, A.-N. (2020). Inundation risk assessment of metro system using AHP and TFN-AHP in Shenzhen. Sustainable Cities and Society, 56, Article 102103. https://doi.org/10.1016/j.scs.2020.102103

Ma, L., Liu, C., & Mills, A. (2016). Construction labor productivity convergence: A conditional frontier approach. Engineering, Construction and Architectural Management, 23(3), 283–301. https://doi.org/10.1108/ECAM-03-2015-0040

Masood, R., & Roy, K. (2022). Review on prefabricated building technology. In Scope: Contemporary research topics. Otago Polytechnic Press. https://doi.org/10.34074/scop.6004002

Masood, R., Lim, J. B. P., González, V. A., Roy, K., & Khan, K. I. A. (2022). A systematic review on supply chain management in prefabricated house-building research. Buildings, 12(1), Article 40. https://doi.org/10.3390/buildings12010040

Masood, R., Roy, K., Gonzalez, V. A., Lim, J. B. P., & Nasir, A. R. (2023). Modeling relational performance of the supply chains for prefabricated housebuilding in New Zealand. Smart and Sustainable Built Environment. https://doi.org/10.1108/SASBE-01-2023-0006

Mehmood, M. U., Chun, D., Zeeshan, Han, H., Jeon, G., & Chen, K. (2019). A review of the applications of artificial intelligence and big data to buildings for energy-efficiency and a comfortable indoor living environment. Energy and Buildings, 202, Article 109383. https://doi.org/10.1016/j.enbuild.2019.109383

Navaratnam, S., Satheeskumar, A., Zhang, G., Nguyen, K., Venkatesan, S., & Poologanathan, K. (2022). The challenges confronting the growth of sustainable prefabricated building construction in Australia: Construction industry views. Journal of Building Engineering, 48, Article 103935. https://doi.org/10.1016/j.jobe.2021.103935

Olanrewaju, O. I., Kineber, A. F., Chileshe, N., & Edwards, D. J. (2022). Modelling the relationship between Building Information Modelling (BIM) implementation barriers, usage and awareness on building project lifecycle. Building and Environment, 207, Article 108556. https://doi.org/10.1016/j.buildenv.2021.108556

Olofsson Hallén, K., Forsman, M., & Eriksson, A. (2023). Interactions between Human, Technology and Organization in Building Information Modelling (BIM) – A scoping review of critical factors for the individual user. International Journal of Industrial Ergonomics, 97, Article 103480. https://doi.org/10.1016/j.ergon.2023.103480

Oluleye, B. I., Chan, D. W. M., Antwi-Afari, P., & Olawumi, T. O. (2023). Modeling the principal success factors for attaining systemic circularity in the building construction industry: An international survey of circular economy experts. Sustainable Production and Consumption, 37, 268–283. https://doi.org/10.1016/j.spc.2023.03.008

Paiho, S., Wessberg, N., Dubovik, M., Lavikka, R., & Naumer, S. (2023). Twin transition in the built environment – Policy mechanisms, technologies and market views from a cold climate perspective. Sustainable Cities and Society, 98, Article 104870. https://doi.org/10.1016/j.scs.2023.104870

Raut, R. D., Narkhede, B., & Gardas, B. B. (2017). To identify the critical success factors of sustainable supply chain management practices in the context of oil and gas industries: ISM approach. Renewable and Sustainable Energy Reviews, 68(Part 1), 33–47. https://doi.org/10.1016/j.rser.2016.09.067

Regona, M., Yigitcanlar, T., Xia, B., & Li, R. Y. M. (2022). Opportunities and Adoption Challenges of AI in the Construction Industry: A PRISMA Review. Journal of Open Innovation: Technology, Market, and Complexity, 8(1), Article 45. https://doi.org/10.3390/joitmc8010045

Rostamzadeh, R., Govindan, K., Esmaeili, A., & Sabaghi, M. (2015). Application of fuzzy VIKOR for evaluation of green supply chain management practices. Ecological Indicators, 49, 188–203. https://doi.org/10.1016/j.ecolind.2014.09.045

Saaty, T. L. (1996). Decision making with dependence and feedback: The Analytic Network Process. The organization and prioritization of complexity. RWS Publications.

Safari, H., Faraji, Z., & Majidian, S. (2016). Identifying and evaluating enterprise architecture risks using FMEA and fuzzy VIKOR. Journal of Intelligent Manufacturing, 27, 475–486. https://doi.org/10.1007/s10845-014-0880-0

Sevkli, M., Lenny Koh, S. C., Zaim, S., Demirbag, M., & Tatoglu, E. (2007). An application of data envelopment analytic hierarchy process for supplier selection: A case study of BEKO in Turkey. International Journal of Production Research, 45(9), 1973–2003. https://doi.org/10.1080/00207540600957399

Shanker, S., & Barve, A. (2021). Analysing sustainable concerns in diamond supply chain: a fuzzy ISM-MICMAC and DEMATEL approach. International Journal of Sustainable Engineering, 14(5), 1269–1285. https://doi.org/10.1080/19397038.2020.1862351

Si, S.-L., You, X.-Y., Liu, H.-C., & Zhang, P. (2018). DEMATEL technique: A systematic review of the state-of-the-art literature on methodologies and applications. Mathematical Problems in Engineering, 2018, Article 3696457. https://doi.org/10.1155/2018/3696457

Sindhu, S., Nehra, V., & Luthra, S. (2016). Identification and analysis of barriers in implementation of solar energy in Indian rural sector using integrated ISM and fuzzy MICMAC approach. Renewable and Sustainable Energy Reviews, 62, 70–88. https://doi.org/10.1016/j.rser.2016.04.033

Singh, R. K., & Gupta, A. (2020). Framework for sustainable maintenance system: ISM–fuzzy MICMAC and TOPSIS approach. Annals of Operations Research, 290, 643–676. https://doi.org/10.1007/s10479-019-03162-w

Solangi, Y. A., Longsheng, C., & Shah, S. A. A. (2021). Assessing and overcoming the renewable energy barriers for sustainable development in Pakistan: An integrated AHP and fuzzy TOPSIS approach. Renewable Energy, 173, 209–222. https://doi.org/10.1016/j.renene.2021.03.141

Song, C., & Wu, X. (2022). Smart city + IoT standardization application practice model and realization of key technologies. Computational Intelligence and Neuroscience, 2022, Article 8070939. https://doi.org/10.1155/2022/8070939

Song, M. (2022). Construction of intelligent building integrated evaluation system based on BIM technology. Advances in Multimedia, 2022, Article 3807681. https://doi.org/10.1155/2022/3807681

Štefanič, M., & Stankovski, V. (2019). A review of technologies and applications for smart construction. Proceedings of the Institution of Civil Engineers – Civil Engineering, 172(4), 83–87. https://doi.org/10.1680/jcien.17.00050

Sun, H., & Liu, Z. (2022). Research on intelligent dispatching system management platform for construction projects based on digital twin and BIM technology. Advances in Civil Engineering, 2022, Article 8273451. https://doi.org/10.1155/2022/8273451

Tan, T., Chen, K., Xue, F., & Lu, W. (2019). Barriers to Building Information Modeling (BIM) implementation in China’s prefabricated construction: An interpretive structural modeling (ISM) approach. Journal of Cleaner Production, 219, 949–959. https://doi.org/10.1016/j.jclepro.2019.02.141

Tian, D., Li, M., Shi, J., Shen, Y., & Han, S. (2021). On-site text classification and knowledge mining for large-scale projects construction by integrated intelligent approach. Advanced Engineering Informatics, 49, Article 101355. https://doi.org/10.1016/j.aei.2021.101355

Too, J., Ejohwomu, O. A., Hui, F. K. P., Duffield, C., Bukoye, O. T., & Edwards, D. J. (2022). Framework for standardising carbon neutrality in building projects. Journal of Cleaner Production, 373, Article 133858. https://doi.org/10.1016/j.jclepro.2022.133858

Turner, C. J., Oyekan, J., Stergioulas, L., & Griffin, D. (2021). Utilizing Industry 4.0 on the construction site: Challenges and opportunities. IEEE Transactions on Industrial Informatics, 17(2), 746–756. https://doi.org/10.1109/TII.2020.3002197

Tushar, W., Wijerathne, N., Li, W. T., Yuen, C., Poor, H. V., Saha, T. K., & Wood, K. L. (2018). Internet of Things for green building management: Disruptive innovations through low-cost sensor technology and artificial intelligence. IEEE Signal Processing Magazine, 35(5), 100–110. https://doi.org/10.1109/MSP.2018.2842096

Vishwakarma, A., Dangayach, G. S., Meena, M. L., & Gupta, S. (2022). Analysing barriers of sustainable supply chain in apparel & textile sector: A hybrid ISM-MICMAC and DEMATEL approach. Cleaner Logistics and Supply Chain, 5, Article 100073. https://doi.org/10.1016/j.clscn.2022.100073

Wang, X., Chen, Q., Tao, J., Han, R., Ding, X., Xing, F., & Han, N. (2019). Concrete thermal stress analysis during tunnel construction. Advances in Mechanical Engineering, 11, Article 1687814019852232. https://doi.org/10.1177/1687814019852232

Wang, Z., Wang, K., Wang, Y., & Wen, Z. (2022). A data management model for intelligent water project construction based on blockchain. Wireless Communications and Mobile Computing, 2022, Article 8482415. https://doi.org/10.1155/2022/8482415

Wu, Y., & Lu, P. (2022). Comparative analysis and evaluation of bridge construction risk with multiple intelligent algorithms. Mathematical Problems in Engineering, 2022, Article 2638273. https://doi.org/10.1155/2022/2638273

Xiahou, X., Wu, Y., Duan, T., Lin, P., Li, F., Qu, X., Liu, L., Li, Q., & Liu, J. (2022). Analyzing critical factors for the smart construction site development: A DEMATEL-ISM based approach. Buildings, 12(2), Article 116. https://doi.org/10.3390/buildings12020116

Xu, X., & Zou, P. X. W. (2020). Analysis of factors and their hierarchical relationships influencing building energy performance using interpretive structural modelling (ISM) approach. Journal of Cleaner Production, 272, Article 122650. https://doi.org/10.1016/j.jclepro.2020.122650

Yan, K., Zhou, X., & Yang, B. (2023a). Editorial: AI and IoT applications of smart buildings and smart environment design, construction and maintenance. Building and Environment, 229, Article 109968. https://doi.org/10.1016/j.buildenv.2022.109968

Yan, X., Zhang, H., & Zhang, W. (2023b). Intelligent monitoring and evaluation for the prefabricated construction schedule. Computer-Aided Civil and Infrastructure Engineering, 38(3), 391–407. https://doi.org/10.1111/mice.12838

Yang, J.-B., & Chou, H.-Y. (2018). Mixed approach to government BIM implementation policy: An empirical study of Taiwan. Journal of Building Engineering, 20, 337–343. https://doi.org/10.1016/j.jobe.2018.08.007

Yang, Z., Wang, Y., & Sun, C. (2018). Emerging information technology acceptance model for the development of smart construction system. Journal of Civil Engineering and Management, 24(6), 457–468. https://doi.org/10.3846/jcem.2018.5186

Yang, X., Yu, Y., Shirowzhan, S., Sepasgozar, S., & Li, H. (2020). Automated PPE-Tool pair check system for construction safety using smart IoT. Journal of Building Engineering, 32, Article 101721. https://doi.org/10.1016/j.jobe.2020.101721

Yevu, S. K., Owusu, E. K., Chan, A. P. C., Sepasgozar, S. M. E., & Kamat, V. R. (2023). Digital twin-enabled prefabrication supply chain for smart construction and carbon emissions evaluation in building projects. Journal of Building Engineering, 78, Article 107598. https://doi.org/10.1016/j.jobe.2023.107598

Yi, W., Chan, A. P. C., Wang, X., & Wang, J. (2016). Development of an early-warning system for site work in hot and humid environments: A case study. Automation in Construction, 62, 101–113. https://doi.org/10.1016/j.autcon.2015.11.003

Yilmaz, G., Akcamete, A., & Demirors, O. (2023). BIM-CAREM: Assessing the BIM capabilities of design, construction and facilities management processes in the construction industry. Computers in Industry, 147, Article 103861. https://doi.org/10.1016/j.compind.2023.103861

You, Z., & Feng, L. (2020). Integration of Industry 4.0 related technologies in construction industry: A framework of cyber-physical system. IEEE Access, 8, 122908–122922. https://doi.org/10.1109/ACCESS.2020.3007206

Yu, X., & Zuo, H. (2022). Intelligent construction optimization control of construction project schedule based on the fuzzy logic neural network algorithm. Mathematical Problems in Engineering, 2022, Article 8111504. https://doi.org/10.1155/2022/8111504

Zabin, A., González, V. A., Zou, Y., & Amor, R. (2022). Applications of machine learning to BIM: A systematic literature review. Advanced Engineering Informatics, 51, Article 101474. https://doi.org/10.1016/j.aei.2021.101474

Zhang, G., Sandanayake, M., Setunge, S., Li, C., & Fang, J. (2017). Selection of emission factor standards for estimating emissions from diesel construction equipment in building construction in the Australian context. Journal of Environmental Management, 187, 527–536. https://doi.org/10.1016/j.jenvman.2016.10.068

Zhang, X., Skitmore, M., & Peng, Y. (2014). Exploring the challenges to industrialized residential building in China. Habitat International, 41, 176–184. https://doi.org/10.1016/j.habitatint.2013.08.005

Zhang, F., Li, D., Ahrentzen, S., & Feng, H. (2020). Exploring the inner relationship among neighborhood environmental factors affecting quality of life of older adults based on SLR–ISM method. Journal of Housing and the Built Environment, 35, 215–242. https://doi.org/10.1007/s10901-019-09674-y

Zhao, H. (2022). Application of BIM technology in data collection of large-scale engineering intelligent construction. Wireless Communications and Mobile Computing, 2022, Article 1168579. http://doi.org/10.1155/2022/1168579

Zhao, Y., Genovese, P. V., & Li, Z. (2020). Intelligent thermal comfort controlling system for buildings based on IoT and AI. Future Internet, 12(2), Article 30. https://doi.org/10.3390/fi12020030

Zheng, Z., Wang, F., Gong, G., Yang, H., & Han, D. (2023). Intelligent technologies for construction machinery using data-driven methods. Automation in Construction, 147, Article 104711. https://doi.org/10.1016/j.autcon.2022.104711

Zhu, A., Pauwels, P., & De Vries, B. (2021). Smart component-oriented method of construction robot coordination for prefabricated housing. Automation in Construction, 129, Article 103778. https://doi.org/10.1016/j.autcon.2021.103778

Zuo, J., & Zhao, Z.-Y. (2014). Green building research–current status and future agenda: A review. Renewable and Sustainable Energy Reviews, 30, 271–281. https://doi.org/10.1016/j.rser.2013.10.021