Factors Influencing Adoption of Digital Twin Advanced Technologies for Smart City Development: Evidence from Malaysia

Buildings - Tập 13 Số 3 - Trang 775
Ahsan Waqar1, Idris Othman1, Hamad Almujibah2, Muhammad Basit Khan1, Saleh Alotaibi3, Adil A. M. Elhassan4,2
1Department of Civil and Environmental Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar 32610, Perak, Malaysia
2Department of Civil Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif City, 21974, Saudi Arabia
3Department of Civil Engineering, Faculty of Engineering-Rabigh Branch, King Abdulaziz University, Jeddah 21589, Saudi Arabia
4Department of Architecture Design, College of Architecture and Planning, Sudan University of Science and Technology (SUST), P.O. Box 407, Khartoum 11111, Khartoum, Sudan

Tóm tắt

Digital Twin Technology (DTT) has gained significant attention as a vital technology for the efficient management of smart cities. However, its successful implementation in developing countries is often hindered by several barriers. Despite limited research available on smart city development in Malaysia, there is a need to investigate the possible challenges that could affect the effective implementation of DTT in the country. This study employs a mixed methodology research design, comprising an interview, a pilot survey, and the main survey. Firstly, we identified barriers reported in the literature and excluded insignificant factors through interviews. Next, we conducted an Exploratory Factor Analysis (EFA) on the pilot survey results to further refine the factors. Finally, we performed a Structural Equation Modeling (SEM) analysis on the main survey data to develop a model that identifies barriers to DTT implementation in smart city development in Malaysia. Our findings suggest the presence of 13 highly significant barriers, which are divided into four formative constructs. We found that personalization barriers are highly crucial, while operational barriers were less important for DTT implementation in smart city development in Malaysia.

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Tài liệu tham khảo

Isa, M.N., Hua, T.C., Jazuli, A.R.M., Shaharuddin, S., and Yusof, S.N.M. (June, January 29). Cadastral in Supporting Smart Cities in Malaysia. Proceedings of the FIG Working Week 2017 Surveying the World of Tomorrow—From Digitalisation to Augmented Reality, Helsinki, Finland.

Liu, 2018, Summary and perspective survey on digital twin technology, Yi Qi Yi Biao Xue Bao/Chin. J. Sci. Instrum., 19, 1

White, 2021, A digital twin smart city for citizen feedback, Cities, 110, 103064, 10.1016/j.cities.2020.103064

Ozturk, 2021, Digital Twin Research in the AECO-FM Industry, J. Build. Eng., 40, 102730, 10.1016/j.jobe.2021.102730

Asri, 2019, Designing a model for smart city through digital transformation, Int. J. Adv. Trends Comput. Sci. Eng., 8, 345, 10.30534/ijatcse/2019/6281.32019

Schimanski, C.P., Monizza, G.P., Marcher, C., and Matt, D.T. (2019). Pushing digital automation of configure-to-order services in small and medium enterprises of the construction equipment industry: A design science research approach. Appl. Sci., 9.

Fuller, 2020, Digital Twin: Enabling Technologies, Challenges and Open Research, IEEE Access, 8, 108952, 10.1109/ACCESS.2020.2998358

Olszewski, R., Cegiełka, M., and Wesołowski, J. (2019, January 11–15). The Concept and Development of a Serious Game „Alter Eco” as Part of Creating a Digital Twin of a Smart City. Proceedings of the Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Arequipa, Peru.

Dembski, F., Wössner, U., Letzgus, M., Ruddat, M., and Yamu, C. (2020). Urban digital twins for smart cities and citizens: The case study of herrenberg, germany. Sustainability, 12.

Cheng, 2020, A study of Malaysia’s smart cities initiative progress in comparison of neighbouring countries (Singapore & Indonesia), J. Crit. Rev., 7, 47

2021, Integrating digital twin technology into large panel system estates retrofit projects, Urban Plan., 6, 164, 10.17645/up.v6i4.4464

Xie, R., Chen, M., Liu, W., Jian, H., and Shi, Y. (2021). Digital twin technologies for turbomachinery in a life cycle perspective: A review. Sustainability, 13.

Madni, A.M., Madni, C.C., and Lucero, S.D. (2019). Leveraging digital twin technology in model-based systems engineering. Systems, 7.

Chen, C., Zhao, Z., Xiao, J., and Tiong, R. (2021). A conceptual framework for estimating building embodied carbon based on digital twin technology and life cycle assessment. Sustainability, 13.

Opoku, D.G.J., Perera, S., Osei-Kyei, R., Rashidi, M., Famakinwa, T., and Bamdad, K. (2022). Drivers for Digital Twin Adoption in the Construction Industry: A Systematic Literature Review. Buildings, 12.

Ramu, 2022, Federated learning enabled digital twins for smart cities: Concepts, recent advances, and future directions, Sustain. Cities Soc., 79, 103663, 10.1016/j.scs.2021.103663

Rutka, 2022, Digital Twin Technology: The Future of Predicting Neurological Complications of Pediatric Cancers and Their Treatment, Front. Oncol., 11, 781499, 10.3389/fonc.2021.781499

2021, Overall introduction to the framework of BIM-based digital twinning in decision-making in safety management in building construction industry, Dir. Organ., 74, 31

Agnusdei, G.P., Elia, V., and Gnoni, M.G. (2021). Is digital twin technology supporting safety management? A bibliometric and systematic review. Appl. Sci., 11.

Lim, S.B., Malek, J.A., and Yigitcanlar, T. (2021). Post-materialist values of smart city societies: International comparison of public values for good enough governance. Future Internet, 13.

Bhatti, 2021, Towards the future of ssmart electric vehicles: Digital twin technology, Renew. Sustain. Energy Rev., 141, 110801, 10.1016/j.rser.2021.110801

Farouk, 2021, Economic analysis of rehabilitation approaches for water distribution networks: Comparative study between Egypt and Malaysia, J. Eng. Des. Technol., 21, 130

Teisserenc, B., and Sepasgozar, S. (2021). Project data categorization, adoption factors, and non-functional requirements for blockchain based digital twins in the construction industry 4.0. Buildings, 11.

Zhu, J., and Wu, P. (2021). Towards effective bim/gis data integration for smart city by integrating computer graphics technique. Remote Sens., 13.

Rafsanjani, 2021, Towards digital architecture, engineering, and construction (AEC) industry through virtual design and construction (VDC) and digital twin, Energy Built Environ., 4, 169, 10.1016/j.enbenv.2021.10.004

Lu, Q., Jiang, H., Chen, S., Gu, Y., Gao, T., and Zhang, J. (August, January 15). Applications of Digital Twin System in a Smart City System with Multi-Energy. Proceedings of the 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence, DTPI 2021, Beijing, China.

Murugan, R., and Palanichamy, N. (2021, January 6–8). Smart City Air Quality Prediction using Machine Learning. Proceedings of the 5th International Conference on Intelligent Computing and Control Systems, ICICCS 2021, Madurai, India.

Li, 2022, Big data analysis of the Internet of Things in the digital twins of smart city based on deep learning, Future Gener. Comput. Syst., 128, 167, 10.1016/j.future.2021.10.006

Rani, 2020, Proposed framework on public and private partnership for smart cities growth in Malaysia, Test Eng. Manag., 82, 5632

Ford, 2020, Smart Cities with Digital Twin Systems for Disaster Management, J. Manag. Eng., 36, 04020027, 10.1061/(ASCE)ME.1943-5479.0000779

Kee, 2020, An assessment of the viability of the smart parking system: The case of a smart city initiative in Malaysia, Glob. Bus. Organ. Excell., 39, 26, 10.1002/joe.22013

Greif, 2020, Peeking into the void: Digital twins for construction site logistics, Comput. Ind., 121, 103264, 10.1016/j.compind.2020.103264

Mohammadi, N., Vimal, A., and Taylor, J.E. (2020, January 7–10). Knowledge Discovery in Smart City Digital Twins. Proceedings of the Annual Hawaii International Conference on System Sciences, Maui, HI, USA.

Shamanna, 2020, Reducing HbA1c in Type 2 Diabetes Using Digital Twin Technology-Enabled Precision Nutrition: A Retrospective Analysis, Diabetes Ther., 11, 2703, 10.1007/s13300-020-00931-w

Laamarti, 2020, El An ISO/IEEE 11073 Standardized Digital Twin Framework for Health and Well-Being in Smart Cities, IEEE Access, 8, 105950, 10.1109/ACCESS.2020.2999871

Du, 2020, Cognition Digital Twins for Personalized Information Systems of Smart Cities: Proof of Concept, J. Manag. Eng., 36, 04019052, 10.1061/(ASCE)ME.1943-5479.0000740

Francisco, 2020, Smart City Digital Twin–Enabled Energy Management: Toward Real-Time Urban Building Energy Benchmarking, J. Manag. Eng., 36, 04019045, 10.1061/(ASCE)ME.1943-5479.0000741

Austin, 2020, Architecting Smart City Digital Twins: Combined Semantic Model and Machine Learning Approach, J. Manag. Eng., 36, 04020026, 10.1061/(ASCE)ME.1943-5479.0000774

Dave, R., Dave, S., and Thakkar, H. (2020). Digital Twins: Current problems in Smart City and Recommendations for future technology. Int. Res. J. Eng. Technolgy, 7.

Shirowzhan, S., Tan, W., and Sepasgozar, S.M.E. (2020). Digital twin and CyberGIS for improving connectivity and measuring the impact of infrastructure construction planning in smart cities. ISPRS Int. J. Geo-Inf., 9.

Kwak, 2020, 2019 Journal of Management in Engineering End-of-Year Review, J. Manag. Eng., 36, 01620001, 10.1061/(ASCE)ME.1943-5479.0000801

Opoku, 2021, Digital twin application in the construction industry: A literature review, J. Build. Eng., 40, 102726, 10.1016/j.jobe.2021.102726

Deren, 2021, Smart city based on digital twins, Comput. Urban Sci., 1, 4, 10.1007/s43762-021-00005-y

Teisserenc, B., and Sepasgozar, S. (2021). Adoption of blockchain technology through digital twins in the construction industry 4.0: A PESTELS approach. Buildings, 11.

Mylonas, 2021, Digital Twins from Smart Manufacturing to Smart Cities: A Survey, IEEE Access, 9, 143222, 10.1109/ACCESS.2021.3120843

Qi, 2021, Enabling technologies and tools for digital twin, J. Manuf. Syst., 58, 3, 10.1016/j.jmsy.2019.10.001

Waqar, A., and Othman, I. (2023). Impact of 3D Printing on the Overall Project Success of Residential Construction Projects Using Structural Equation Modelling. Int. J. Environ. Res. Public Health, 20.

Waqar, A., Qureshi, A.H., and Alaloul, W.S. (2023). Barriers to Building Information Modeling (BIM) Deployment in Small Construction Projects: Malaysian Construction Industry. Sustainability, 15.

Anderl, 2021, Digital twin technology-An approach for Industrie 4.0 vertical and horizontal lifecycle integration, It-Inf. Technol., 60, 125

Taylor, 2021, Engineering Smarter Cities with Smart City Digital Twins, J. Manag. Eng., 37, 02021001, 10.1061/(ASCE)ME.1943-5479.0000974

Akanmu, 2021, Towards next generation cyber-physical systems and digital twins for construction, J. Inf. Technol. Constr., 26, 505

Mashaly, 2021, Connecting the twins: A review on digital twin technology & its networking requirements, Procedia Comput. Sci., 184, 299, 10.1016/j.procs.2021.03.039

Turner, 2021, Utilizing Industry 4.0 on the Construction Site: Challenges and Opportunities, IEEE Trans. Ind. Inform., 17, 746, 10.1109/TII.2020.3002197

Lim, S.B., Malek, J.A., Yussoff, M.F.Y.M., and Yigitcanlar, T. (2021). Understanding and acceptance of smart city policies: Practitioners’ perspectives on the malaysian smart city framework. Sustainability, 17.

Liu, 2021, Digital twin modeling method for construction process of assembled building, Jianzhu Jiegou Xuebao/J. Build. Struct., 42, 213

Sepasgozar, S.M.E. (2021). Differentiating digital twin from digital shadow: Elucidating a paradigm shift to expedite a smart, sustainable built environment. Buildings, 11.

Zhang, Z., Zou, Y., Zhou, T., Zhang, X., and Xu, Z. (2021). Energy consumption prediction of electric vehicles based on digital twin technology. World Electr. Veh. J., 12.

Petrova-Antonova, D., and Ilieva, S. (2021). Advances in Intelligent Systems and Computing, Springer.

Lee, D., and Lee, S. (2021). Digital twin for supply chain coordination in modular construction. Appl. Sci., 11.

Hämäläinen, M. (2021). Smart City Development with Digital Twin Technology, University of Maribor.

Allam, 2021, Future (post-COVID) digital, smart and sustainable cities in the wake of 6G: Digital twins, immersive realities and new urban economies, Land Use Policy, 101, 105201, 10.1016/j.landusepol.2020.105201

Yang, 2021, Developments of digital twin technologies in industrial, smart city and healthcare sectors: A survey, Complex Eng. Syst., 1, 3

Yang, 2021, Urban digital twin applications as a virtual platform of smart city, Int. J. Sustain. Build. Technol. Urban Dev., 12, 363

Major, 2021, The use of a data-driven digital twin of a smart city: A case study of ålesund, norway, IEEE Instrum. Meas. Mag., 24, 39, 10.1109/MIM.2021.9549127

Liu, Y., Folz, P., Pan, S., Ramparany, F., Bolle, S., Ballot, E., and Coupaye, T. (2021, January 17–20). Digital Twin-Driven Approach for Smart City Logistics: The Case of Freight Parking Management. Proceedings of the IFIP Advances in Information and Communication Technology, Tampere, Finland.

Mavrokapnidis, D., Mohammadi, N., and Taylor, J.E. (2021, January 5–8). Community Dynamics in Smart City Digital Twins: A Computer Vision-Based Approach for Monitoring and Forecasting Collective Urban Hazard Exposure. Proceedings of the Annual Hawaii International Conference on System Sciences, Maui, HI, USA.

Alshammari, 2021, Cybersecurity for digital twins in the built environment: Current research and future directions, J. Inf. Technol. Constr., 26, 159

Zhang, 2022, Digital Twins for Construction Sites: Concepts, LoD Definition, and Applications, J. Manag. Eng., 38, 04021094, 10.1061/(ASCE)ME.1943-5479.0000948

Deng, 2021, (Max) A systematic review of a digital twin city: A new pattern of urban governance toward smart cities, J. Manag. Sci. Eng., 6, 125

Kaewunruen, S., Sresakoolchai, J., Ma, W., and Phil-Ebosie, O. (2021). Digital twin aided vulnerability assessment and risk-based maintenance planning of bridge infrastructures exposed to extreme conditions. Sustainability, 13.

Amin, 2021, Real Time Water Quality Monitoring System for Smart City in Malaysia, ASEAN J. Sci. Eng., 2, 47, 10.17509/ajse.v2i1.37515

Yu, 2021, Job Shop Scheduling Based on Digital Twin Technology: A Survey and an Intelligent Platform, Complexity, 2021, 8823273, 10.1155/2021/8823273

Narayanan, 2021, Technology Focus: Intelligent Operations (May 2021), J. Pet. Technol., 73, 51, 10.2118/0521-0051-JPT

Ibrahim, R., Asri, N.A.M., and Jamel, S. (2019, January 7). Utilization of IOTs in Developing the Architecture of Smart City in Malaysia. Proceedings of the 2019 IEEE 9th International Conference on System Engineering and Technology, ICSET 2019—Proceeding, Shah Alam, Malaysia.

Sepasgozar, S.M.E., Karimi, R., Shirowzhan, S., Mojtahedi, M., Ebrahimzadeh, S., and McCarthy, D. (2019). Delay causes and emerging digital tools: A novel model of delay analysis, including integrated project delivery and PMBOK. Buildings, 9.

Waqar, A., Othman, I., and Skrzypkowski, K. (2023). Evaluation of Success of Superhydrophobic Coatings in the Oil and Gas Construction Industry Using Structural. Coatings, 13.

Waqar, A., Khan, M.B., Shafiq, N., and Skrzypkowski, K. (2023). Assessment of Challenges to the Adoption of IOT for the Safety Management of Small Construction Projects in Malaysia: Structural Equation Modeling Applied Sciences Assessment of Challenges to the Adoption of IOT for the Safety Management of Small Construction Projects in Malaysia: Structural Equation Modeling Approach. Appl. Sci., 13.

Simonofski, 2021, Engaging citizens in the smart city through participation platforms: A framework for public servants and developers, Comput. Hum. Behav., 124, 106901, 10.1016/j.chb.2021.106901

Heng, 2022, Understanding AI ecosystems in the Global South: The cases of Senegal and Cambodia, Int. J. Inf. Manag., 64, 102454, 10.1016/j.ijinfomgt.2021.102454