Digital Twins as Socio-Technical Decision Systems: A Comparative Systematic Review of Supply Chain Management and Healthcare

Yehia Alzoubi; Shahnawaz Muhammed; Atik Kulakli

doi:10.31181/dma412026190

Authors

Yehia Alzoubi College of Business Administration, American University of the Middle East, Egaila 54200, Kuwait https://orcid.org/0000-0003-4329-4072
Shahnawaz Muhammed College of Business Administration, American University of the Middle East, Egaila 54200, Kuwait https://orcid.org/0000-0002-6031-5376
Atik Kulakli College of Business Administration, American University of the Middle East, Egaila 54200, Kuwait https://orcid.org/0000-0002-2368-3225

DOI:

https://doi.org/10.31181/dma412026190

Keywords:

Digital Transformation, Decision Support System, Supply Chain Management, Health Care, Value–complexity, Trade-off

Abstract

Digital Twin (DT) technology is rapidly evolving from a digital representation of physical assets into a decision-support infrastructure that integrates real-time data, analytics, and simulation. However, existing research remains fragmented across application domains, limiting understanding of how DTs enable decision-making under different socio-technical conditions. This study presents a systematic literature review and decision-centric comparative analysis of DT applications in two contrasting decision environments: Supply Chain Management (SCM) and healthcare. Following a Systematic Literature Review (SLR) protocol, 193 peer-reviewed studies (95 SCM and 98 healthcare) were identified, screened, and synthesized across six analytical dimensions: application domains, technological integration, decision-making levels, business value, stakeholder involvement, and implementation challenges. The findings reveal fundamentally different decision logics despite a shared technological foundation based on Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing. SCM-DTs primarily support coordination, optimization, resilience, and organizational scalability, whereas healthcare-DTs emphasize personalization, patient safety, and ethical governance under stringent regulatory constraints. Building on these findings, the study proposes a decision-centric comparative framework and a value–complexity perspective suggesting that value realization is increasingly associated with technological, organizational, and governance complexity as DT ecosystems mature. The paper advances the conceptualization of DTs as socio-technical decision systems and provides practical guidance for researchers, managers, and policymakers seeking responsible and effective digital transformation.

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References

Tabet, W., Benfriha, K., & Bounab, B. (2026). A review on integration of digital twins within Industry 4.0. Journal of Intelligent Manufacturing. Advance online publication. https://doi.org/10.1007/s10845-026-02851-1

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

Mohanraj, R., & Balaji, S. N. (2026). Digital twin technology: A comprehensive review of modeling, applications, challenges and future directions in complex system integration. Archives of Computational Methods in Engineering, 33(3), 3291–3316. https://doi.org/10.1007/s11831-025-10397-3

Gartner. (2026). Gartner top 10 strategic technology trends for 2026. https://www.gartner.com/en/articles/top-technology-trends-2026

Mbabu, A., Underwood, J., Munir, M., & Wildenauer, A. (2026). A digital twin framework for lean strategic facility management in the UK healthcare built environment. International Journal of Building Pathology and Adaptation. Advance online publication, 1-22. https://doi.org/10.1108/IJBPA-12-2024-0276

Zhang, Y., Shi, K., & Li, B. (2026). A brief history of digital twin technology. PET Clinics, 21(1), 143–151. https://doi.org/10.1016/j.cpet.2025.09.006

Zaidi, S. A. H., Khan, S. A., & Chaabane, A. (2024). Unlocking the potential of digital twins in supply chains: A systematic review. Supply Chain Analytics, 7, 100075. https://doi.org/10.1016/j.sca.2024.100075

Ahmad, R. (2026). Developing trustworthy and ethically-based healthcare systems. Applied Computing and Informatics. Advance online publication, 22(3-4), 410-422. https://doi.org/10.1108/ACI-05-2025-0203

Daraio, C., Di Leo, S., & Orsini, J. (2025). An integrated and flexible review framework to evaluate the evolution and barriers of digital-twin technologies in industrial and healthcare domains. Global Journal of Flexible Systems Management, 26(3), 625–648. https://doi.org/10.1007/s40171-025-00447-x

Chrysanthakopoulou, D., & Koutsojannis, C. (2025). Digital twins in medicine: Where we stand? In H. Kondylakis & A. Triantafyllidis (Eds.), Pervasive Computing Technologies for Healthcare. PervasiveHealth 2024 (Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Vol. 611, pp. 221–237). Springer. https://doi.org/10.1007/978-3-031-85572-6_14

Ivanov, D. (2025). Conceptual and formal models for design, adaptation, and control of digital twins in supply chain ecosystems. Omega, 137, 103356. https://doi.org/10.1016/j.omega.2025.103356

Lim, K. Y. H., Dang, L. V., & Chen, C.-H. (2024). Incorporating supply and production digital twins to mitigate demand disruptions in multi-echelon networks. International Journal of Production Economics, 273, 109258. https://doi.org/10.1016/j.ijpe.2024.109258

Saratkar, S. Y., Langote, M., Kumar, P., Gote, P., Weerarathna, I. N., & Mishra, G. V. (2025). Digital twin for personalized medicine development. Frontiers in Digital Health, 7, 1583466. https://doi.org/10.3389/fdgth.2025.1583466

Meng, Y., Rahimian, F., Rodriguez, S., Sun, Y., & Wei, H. (2025). Blockchain-based secure digital twin framework for the smart healthy city. In T. A. Nguyen (Ed.), Digital Twin, Blockchain, and Sensor Networks in the Healthy and Mobile City (pp. 199–226). Elsevier. https://doi.org/10.1016/B978-0-443-34174-8.00013-2

Rankin, R. L. (2017). The comparative method. In B. D. Joseph & R. D. Janda (Eds.), The handbook of historical linguistics (pp. 181–212). Wiley. https://doi.org/10.1002/9781405166201.ch1

Ricci, A., Croatti, A., & Montagna, S. (2021). Pervasive and connected digital twins—A vision for digital health. IEEE Internet Computing, 26(5), 26–32. https://doi.org/10.1109/MIC.2021.3052039

Botín-Sanabria, D. M., Mihaita, A.-S., Peimbert-García, R. E., Ramírez-Moreno, M. A., Ramírez-Mendoza, R. A., & Lozoya-Santos, J. d. J. (2022). Digital twin technology challenges and applications: A comprehensive review. Remote Sensing, 14(6), 1335. https://doi.org/10.3390/rs14061335

Saracco, R. (2019). Digital twins: Bridging physical space and cyberspace. Computer, 52(12), 58–64. https://doi.org/10.1109/MC.2019.2942803

Ahmad, N., Fatima, I., Alam, M., Khan, I. R., & Mahmoud, A. (2025). Digital twin model design for smart village. In S. Iyer, A. Nayyar, A. Paul, & M. Naved (Eds.), Digital Twins for Smart Cities and Villages (pp. 127–148). Elsevier. https://doi.org/10.1016/B978-0-443-28884-5.00006-3

Tiwari, S., & Shukla, A. (2024). Digital twins in industry: Real-world applications and innovations. In A. Mishra, M. E. Barachi, & M. Kumar (Eds.), Transforming Industry using Digital Twin Technology (pp. 1–18). Springer. https://doi.org/10.1007/978-3-031-58523-4_1

Stauss, T., Wawer, M. L., Wurst, J., Hamlaoui, R., Orimi, A. G., & Lachmayer, R. (2025). Digital twin or digital model: An analysis of definitions along the product lifecycle. Procedia CIRP, 136, 230–235. https://doi.org/10.1016/j.procir.2025.08.041

Araghi, S. N., Liu, Z., Sarkar, A., Louge, T., & Karray, M. H. (2025). Digital twin's anatomy: A cross-sector framework with healthcare validation. IEEE Access, 13, 21306–21334. https://doi.org/10.1109/ACCESS.2025.3528736

Taylor, S. J., Johansson, B., Jeon, S., Lee, L. H., Lendermann, P., & Shao, G. (2021). Using simulation and digital twins to innovate: Are we getting smarter? In 2021 Winter Simulation Conference (WSC) (pp. 1–13). IEEE. https://doi.org/10.1109/WSC52266.2021.9715535

Marquardt, T., Cleophas, C., & Morgan, L. (2021). Indolence is fatal: Research opportunities in designing digital shadows and twins for decision support. In 2021 Winter Simulation Conference (WSC) (pp. 1–11). IEEE. https://doi.org/10.1109/WSC52266.2021.9715332

Schulte, S. N., Grunenwald, C.-P., Schulze, P., Breiten, T., & Stark, R. (2025). A systematic description of twinning levels of measured data and models in digital twins. Proceedings of the Design Society, 5, 289–298. https://doi.org/10.1017/pds.2025.10043

Keshvarinia, M., MacKenzie, C. A., & Zhao, Z. (2025). A simulation-based digital twin model for data-driven decision optimization. Decision Analytics Journal, 17, 100646. https://doi.org/10.1016/j.dajour.2025.100646

Yuniarti, R., Suparno, & Arvitrida, N. I. (2025). A scoping review and bibliometric analysis of sustainable and resilient supply chain network design. Supply Chain Analytics, 12, 100162. https://doi.org/10.1016/j.sca.2025.100162

Xu, Y., Qamsane, Y., Puchala, S., Januszczak, A., Tilbury, D. M., & Barton, K. (2024). A data-driven approach toward a machine-and system-level performance monitoring digital twin for production lines. Computers in Industry, 157, 104086. https://doi.org/10.1016/j.compind.2024.104086

Ren, X., & Zhao, N. (2023). Research on digital twin framework for customized product manual assembly systems. Journal of Manufacturing Systems, 71, 527–545. https://doi.org/10.1016/j.jmsy.2023.08.018

Battarra, I., Accorsi, R., Lupi, G., Manzini, R., & Sirri, G. (2025). A flow-generator platform to assess a data-driven design of material handling and production systems. IFAC-PapersOnLine, 59(10), 298–303. https://doi.org/10.1016/j.ifacol.2025.09.052

Giel, R., & Dąbrowska, A. (2024). A digital twin framework for cyber-physical waste stream control systems: Towards reverse logistics 4.0. LogForum, 20(3), 297–306. https://doi.org/10.17270/J.LOG.001054

Barbieri, G., et al. (2021). A virtual commissioning based methodology to integrate digital twins into manufacturing systems. Production Engineering, 15(3-4), 397–412. https://doi.org/10.1007/s11740-021-01037-3

Guo, D., Zhong, R. Y., Rong, Y., & Huang, G. G. (2023). Synchronization of shop-floor logistics and manufacturing under IIoT and digital twin-enabled graduation intelligent manufacturing system. IEEE Transactions on Cybernetics, 53(3), 2005–2016. https://doi.org/10.1109/TCYB.2021.3108546

Wang, K.-J., Lee, Y.-H., & Angelica, S. (2021). Digital twin design for real-time monitoring—A case study of die cutting machine. International Journal of Production Research, 59(21), 6471–6485. https://doi.org/10.1080/00207543.2020.1817999

Ghandar, A., Ahmed, A., Zulfiqar, S., Hua, Z., Hanai, M., & Theodoropoulos, G. (2021). A decision support system for urban agriculture using digital twin: A case study with aquaponics. IEEE Access, 9, 35691–35708. https://doi.org/10.1109/ACCESS.2021.3061722

Ichsan, F. A., Noche, B., & Lobeck, F. (2025). A DIKW-based pyramid framework for integrating the Metaverse in supply chain management. IEEE Open Journal on Immersive Displays, 2, 232–250. https://doi.org/10.1109/OJID.2025.3639210

Yu, W., Patros, P., Young, B., Klinac, E., & Walmsley, T. G. (2022). Energy digital twin technology for industrial energy management: Classification, challenges and future. Renewable and Sustainable Energy Reviews, 161, 112407. https://doi.org/10.1016/j.rser.2022.112407

Kaur, M. J., Mishra, V. P., & Maheshwari, P. (2019). The convergence of digital twin, IoT, and machine learning: Transforming data into action. In M. Farsi, A. Daneshkhah, A. Hosseinian-Far, & H. Jahankhani (Eds.), Digital Twin Technologies and Smart Cities. Internet of Things (pp. 3–17). Springer. https://doi.org/10.1007/978-3-030-18732-3_1

Alghamdi, W. Y., et al. (2025). Exploring the synergy between digital twin technology and artificial intelligence: A comprehensive survey. International Journal of Advanced Computer Science & Applications, 16(3). https://doi.org/10.14569/ijacsa.2025.0160399

Farid, F., Bello, A., Jahan, N., & Sultana, R. (2023). A review of the concept, applications, risks and control strategies for digital twin. In R. Silhavy & P. Silhavy (Eds.), Data Analytics in System Engineering. CoMeSySo 2023 (Lecture Notes in Networks and Systems, Vol. 935, pp. 264–282). Springer. https://doi.org/10.1007/978-3-031-54820-8_21

Liu, Y., et al. (2019). A novel cloud-based framework for the elderly healthcare services using digital twin. IEEE Access, 7, 49088–49101. https://doi.org/10.1109/ACCESS.2019.2909828

Mishra, A., Jabar, T. S., Alzoubi, Y. I., & Mishra, K. N. (2023). Enhancing privacy-preserving mechanisms in cloud storage: A novel conceptual framework. Concurrency and Computation: Practice and Experience, 35(26), e7831. https://doi.org/10.1002/cpe.7831

Knebel, F. P., Trevisan, R., do Nascimento, G. S., Abel, M., & Wickboldt, J. A. (2023). A study on cloud and edge computing for the implementation of digital twins in the oil & gas industries. Computers & Industrial Engineering, 182, 109363. https://doi.org/10.1016/j.cie.2023.109363

Lucchi, E. (2025). Digital twins and smart sensors for building performance and maintenance optimization. In E. N. Farsangi, M. Noori, T. Y. Yang, V. Sarhosis, S. Mirjalili, & M. J. Skibniewski (Eds.), Digital Transformation in the Construction Industry (pp. 417–428). Elsevier. https://doi.org/10.1016/B978-0-443-29861-5.00020-2

Liu, W., Wu, M., Wan, G., & Xu, M. (2024). Digital twin of space environment: Development, challenges, applications, and future outlook. Remote Sensing, 16(16), 3023. https://doi.org/10.3390/rs16163023

Wagner, T., Kittl, C., Jakob, J., Hiry, J., & Häger, U. (2024). Digital twins in power systems: A proposal for a definition. IEEE Power and Energy Magazine, 22(1), 16–23. https://doi.org/10.1109/MPE.2023.3328581

Singh, P. D., & Tripathi, V. (2024). Digital twins: A comprehensive study on models, platforms, applications and challenges. In 11th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 1072–1077). IEEE. https://doi.org/10.23919/INDIACom61295.2024.10498975

Vishwakarma, L. P., & Singh, R. K. (2023). Application of digital twin for efficient supply chain: Analysis of opportunities and challenges. In K. E. K. Vimal, S. Rajak, V. Kumar, R. S. Mor, & A. Assayed (Eds.), Industry 4.0 Technologies: Sustainable Manufacturing Supply Chains. Environmental Footprints and Eco-design of Products and Processes (pp. 105–124). Springer. https://doi.org/10.1007/978-981-99-4819-2_8

Sen, S., & Kilic, K. D. (2025). Digital twins in medicine, AI-driven personalized healthcare, and predictive analytics. In B. S & S. Kadry (Eds.), AI-Powered Digital Twins for Predictive Healthcare: Creating Virtual Replicas of Humans (pp. 359–396). IGI. https://doi.org/10.4018/979-8-3373-0538-7.ch011

Iswariya, V. T., Asireddy, S. R., Vallarapu, N. K., & Madhira, J.. (2024). Digital twins in drug discovery: A paradigm shift shaping pharmaceutical innovation. International Journal of Pharmaceutical Sciences and Nanotechnology, 17, 7628–7637. https://doi.org/10.37285/ijpsn.2024.17.5.9

Kanaga Priya, P., & Reethika, A. (2024). A review of digital twin applications in various sectors. In A. Mishra, M. E. Barachi, & M. Kumar (Eds.), Transforming Industry using Digital Twin Technology (pp. 239–258). Springer. https://doi.org/10.1007/978-3-031-58523-4_12

Singh, B., & Nayyar, A. (2025). Exploring diverse use cases of digital twins projecting digital transformation: Unlocking potential, addressing challenges and viable solutions. In S. Iyer, A. Nayyar, A. Paul, & M. Naved (Eds.), Digital Twins for Smart Cities and Villages (pp. 631–655). Elsevier. https://doi.org/10.1016/B978-0-443-28884-5.00027-0

Wilke, D. N. (2022). Digital twins for physical asset lifecycle management. In Z. Lv & E. Fersman (Eds.), Digital Twins: Basics and Applications (pp. 13–26). Springer. https://doi.org/10.1007/978-3-031-11401-4_3

Huang, Z., Shen, Y., Li, J., Fey, M., & Brecher, C. (2021). A survey on AI-driven digital twins in Industry 4.0: Smart manufacturing and advanced robotics. Sensors, 21(19), 6340. https://doi.org/10.3390/s21196340

Göksoy, A., Yalırsu, H. Y., & Vayvay, Ö. (2023). Digital twin: Is it hype? In P. Vardarlıer (Ed.), Multidimensional and Strategic Outlook in Digital Business Transformation. Contributions to Management Science (pp. 81–93). Springer. https://doi.org/10.1007/978-3-031-23432-3_7

Savolainen, J., & Knudsen, M. S. (2022). Contrasting digital twin vision of manufacturing with the industrial reality. International Journal of Computer Integrated Manufacturing, 35(2), 165–182. https://doi.org/10.1080/0951192X.2021.1972471

West, S., Stoll, O., Meierhofer, J., & Züst, S. (2021). Digital twin providing new opportunities for value co-creation through supporting decision-making. Applied Sciences, 11(9), 3750. https://doi.org/10.3390/app11093750

Hickey, B., Gachon, D. C., & Cosgrove, D. J. (2023). Digital twin—A tool for project management in manufacturing. Procedia Computer Science, 217, 720–727. https://doi.org/10.1016/j.procs.2022.12.268

Lumley, D. J., Polesel, F., Refstrup Sørensen, H., & Gustafsson, L.-G. (2024). Connecting digital twins to control collections systems and water resource recovery facilities: From siloed to integrated urban (waste) water management. Water Practice & Technology, 19(6), 2267–2278. https://doi.org/10.2166/wpt.2024.128

Topolsky, D., Beliakova, V., & Patrakhina, T. (2025). The use of digital twin technology in the development of intelligent equipment. In 2025 International Russian Smart Industry Conference (SmartIndustryCon) (pp. 805–810). IEEE. https://doi.org/10.1109/SmartIndustryCon65166.2025.10986107

Soleymanizadeh, H., Qu, Q., Bamakan, S. M. H., & Zanjirchi, S. M. (2023). Digital twin empowering manufacturing paradigms: Lean, agile, just-in-time (JIT), flexible, resilience, sustainable. Procedia Computer Science, 221, 1258–1267. https://doi.org/10.1016/j.procs.2023.08.114

Zaland, A., Ali, Z., Haris, M., Saad, S., & Rasheed, K. (2025). Integrating digital twins and robotics. In S. Saad, K. Rasheed, & S. Ammad (Eds.), Applications of Digital Twins and Robotics in the Construction Sector (pp. 152–173). CRC Press. https://doi.org/10.1201/9781003518747-7

Kastner, M., Saporiti, N., Lange, A. K., & Rossi, T. (2024). Insights into how to enhance container terminal operations with digital twins. Computers, 13(6), 138. https://doi.org/10.3390/computers13060138

Sahal, R., Alsamhi, S. H., Breslin, J. G., Brown, K. N., & Ali, M. I. (2021). Digital twins collaboration for automatic erratic operational data detection in Industry 4.0. Applied Sciences, 11(7), 3186. https://doi.org/10.3390/app11073186

Hémono, P., Chabane, A. N., & Sahnoun, M. (2025). Leveraging digital twin and dynamic scheduling for enhanced human-robot collaboration. International Journal of Production Economics, 293, 109823. https://doi.org/10.1016/j.ijpe.2025.109823

Sousa, B., Arieiro, M., Pereira, V., Correia, J., Lourenço, N., & Cruz, T. (2021). ELEGANT: Security of critical infrastructures with digital twins. IEEE Access, 9, 107574–107588. https://doi.org/10.1109/ACCESS.2021.3100708

Bucaioni, A., Axelsson, J., Behnam, M., & Ferko, E. (2025). Digital twins for essential services. Future Generation Computer Systems, 176, 108147. https://doi.org/10.1016/j.future.2025.108147

Loginovsky, O., Beliakov, A., & Zvereva, E. (2025). The application of digital twin technology in information support systems. In 2025 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM) (pp. 902–906). IEEE. https://doi.org/10.1109/ICIEAM65163.2025.11028358

Agarwal, V., Sahai, S., & Sahay, N. (2024). Navigating the digital landscape: Prioritizing challenges in supply chain management of digital twin implementation. International Journal of System Assurance Engineering and Management, 2024. https://doi.org/10.1007/s13198-024-02553-y

Al-Sehrawy, R., Kumar, B., & Watson, R. (2023). The pluralism of digital twins for urban management: Bridging theory and practice. Journal of Urban Management, 12(1), 16–32. https://doi.org/10.1016/j.jum.2023.01.002

Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039

Xia, Y., Wang, K., Huang, Y., Lin, T., Shi, L., & Wu, F. (2026). Bounded rational decision-making modeling and analysis in local energy markets: A state-of-the-art review. Renewable and Sustainable Energy Reviews, 226, 116310. https://doi.org/10.1016/j.rser.2025.116310

Peldon, D., Banihashemi, S., LeNguyen, K., & Derrible, S. (2024). Navigating urban complexity: The transformative role of digital twins in smart city development. Sustainable Cities and Society, 111, 105583. https://doi.org/10.1016/j.scs.2024.105583

Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222. https://doi.org/10.1111/1467-8551.00375

Thomas, J., & Harden, A. (2008). Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Medical Research Methodology, 8(1), 45. https://doi.org/10.1186/1471-2288-8-45

Alzoubi, Y. I., Gill, A. Q., & Al-Ani, A. (2016). Empirical studies of geographically distributed agile development communication challenges: A systematic review. Information & Management, 53(1), 22–37. https://doi.org/10.1016/j.im.2015.08.003

Arai, L., Britten, N., Popay, J., Roberts, H., Petticrew, M., Rodgers, M., & Sowden, A. (2007). Testing methodological developments in the conduct of narrative synthesis: a demonstration review of research on the implementation of smoke alarm interventions. Evidence & Policy, 3(3), 361-383. https://doi.org/10.1332/174426407781738029

Booth, A., Sutton, A., Clowes, M., & Martyn-St James, M. (2016). Systematic approaches to a successful literature review (3rd ed.). London, UK: SAGE Publications. https://doi.org/10.4135/9781036232009

Alzoubi, Y. I., & Mishra, A. (2024). Blockchain consensus mechanisms comparison in fog computing: A systematic review. ICT Express, 10(2), 342–373. https://doi.org/10.1016/j.icte.2024.02.008

McHugh, M. L. (2012). Interrater reliability: The kappa statistic. Biochemia Medica, 22(3), 276–282. https://hrcak.srce.hr/89395

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372. https://doi.org/10.1136/bmj.n71

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., & Moher, D. (2022). A declaração PRISMA 2020: uma diretriz atualizada para relatar revisões sistemáticas. BMJ, 372. https://doi.org/10.26633/RPSP.2022.112

Sarkar, A., & Goswami, S. S. (2026). A systematic review of MCDM techniques for decision-making in smart manufacturing systems under Industry 4.0. Management Science Advances, 3(1), 290–306. https://doi.org/10.31181/msa31202649

Sahoo, S. K., Goswami, S. S., Božanić, D., & Mitra, S. (2025). Evaluating green economy strategies through multi-criteria decision analysis: A systematic review. International Journal of Economic Sciences, 14(1), 385–407. https://doi.org/10.31181/ijes1412025245

Aluvalu, R., Mudrakola, S., V. U. M., Kaladevi, A. C., Sandhya, M. V. S, & Bhat, C. R. (2023). The novel emergency hospital services for patients using digital twins. Microprocessors and Microsystems, 98, 104794. https://doi.org/10.1016/j.micpro.2023.104794

Arya, S., Aggarwal, S., & Ansar, S. A. (2025). Transforming healthcare with blockchain and digital twins: Innovations in IoMT for smart hospitals. In T. A. Nguyen (Ed.), Blockchain and Digital Twin for Smart Hospitals (pp. 497–510). Elsevier. https://doi.org/10.1016/B978-0-443-34226-4.00025-3

Bhatia, M. (2025). Digital twin-inspired anxiety detection for smart office healthcare. IEEE Internet of Things Journal, 12(15), 32237–32244. https://doi.org/10.1109/JIOT.2025.3576325

Chauhan, D., & Bahad, P. (2025). Improving the operational efficiency of healthcare operations using digital twins. In B. S & S. Kadry (Eds.), AI-Powered Digital Twins for Predictive Healthcare: Creating Virtual Replicas of Humans (pp. 139–168). IGI. https://doi.org/10.4018/979-8-3373-0538-7.ch005

MAMTA, & Karri, S. R. (2025). Toward smart healthcare in the digital twin ecosystem: Architecture, challenges and implementation. In A. Taneja, A. Kumar, S. V. Limkar, M. Ouaissa, & M. Ouaissa (Eds.), Driving Innovation through AI and Digital Twin for 6G Powered Sustainable Ultra Smart Cities (pp. 237–263). Wiley. https://doi.org/10.1002/9781394411320.ch10

Manocha, A., Sood, S. K., & Bhatia, M. (2023). Digital-twin-assisted academic environment monitoring for anxiety disorder. IEEE Internet of Things Journal, 11(8), 13563–13570. https://doi.org/10.1109/JIOT.2023.3337846

Palraj, R., Sarkar, S., Kakade, K., & Vajravelu, A. (2025). Using blockchain-enabled digital twins to optimize healthcare workflows and improve efficiency. In M. Gahlawat & S. Tanwar (Eds.), Digital Twin and Blockchain for Sustainable Healthcare 5.0 (pp. 19–32). Chapman and Hall/CRC. https://doi.org/10.1201/9781003532286-2

Palvadi, S. K., Pradeep, K. G. M., & Kadiravan, G. (2025). Exploring the advantages and security aspects of digital twin technology in healthcare. In R. Agrawal, P. S. Rathore, G. G. Devarajan, & R. R. Divivedi (Eds.), Artificial Intelligence and Cybersecurity in Healthcare (pp. 173–205). Wiley. https://doi.org/10.1002/9781394229826.ch7

Rani, S., & Hasanpuri, V. (2025). Data security and ethical considerations in healthcare digital twins. In M. Dixit, K. R. Bhatele, & D. Tiwari (Eds.), Digital Twin Technology for Better Health: A Healthcare Odyssey. CRC Press. https://doi.org/10.1201/9781003498117-6

Roopa, M. S., & Venugopal, K. R. (2025). Digital twins for cyber-physical healthcare systems: Architecture, requirements, systematic analysis and future prospects. IEEE Access, 13, 44963–44996. https://doi.org/10.1109/ACCESS.2025.3547991

Sengupta, S., Sharma, L., Kumar, A., & Goyal, S. B. (2025). A digital twinning for advanced precision medicine and patient care: Tools and technologies. In L. Sharma & P. K. Garg (Eds.), Digital Twins and Simulation Technology: Concepts and Applications (pp. 40–54). Chapman and Hall/CRC. https://doi.org/10.1201/9781003582489-4

Shamanna, P., et al. (2024). One-year outcomes of a digital twin intervention for type 2 diabetes: A retrospective real-world study. Scientific Reports, 14(1), 25478. https://doi.org/10.1038/s41598-024-76584-7

Sharma, A. K., Srivastava, M. K., & Sharma, R. (2025). Barriers and challenges for digital twin adoption in healthcare supply chain and operations management. Global Business Review, 2025, 1-20. https://doi.org/10.1177/09721509251314795

Sharma, H., & Kaur, S. (2025). Patient-specific digital twins for personalized healthcare: A hybrid AI and simulation-based framework. IEEE Access, 13, 143277–143290. https://doi.org/10.1109/ACCESS.2025.3598130

Thirupathi, L., SrihaReddy, E., & Deepika, J. V. P. U. (2024). Challenges and innovations in the creation of digital twins in healthcare. In A. Dubey, C. K. K. Reddy, S. Doss, & M. M. Hanafiah (Eds.), Exploring the Advancements and Future Directions of Digital Twins in Healthcare 6.0 (pp. 69–85). IGI. https://doi.org/10.4018/979-8-3693-5893-1.ch004

Tyagi, A. K., & Richa. (2025). Digital twin–based healthcare facilities management. In T. A. Nguyen (Ed.), Blockchain and Digital Twin for Smart Hospitals (pp. 47–65). Elsevier. https://doi.org/10.1016/B978-0-443-34226-4.00004-6

Binsfeld, T., & Gerlach, B. (2022). Quantifying the benefits of digital supply chain twins—A simulation study in organic food supply chains. Logistics, 6(3), 46. https://doi.org/10.3390/logistics6030046

Borowski, P. F. (2021). Digitization, digital twins, blockchain, and Industry 4.0 as elements of management process in enterprises in the energy sector. Energies, 14(7), 1885. https://doi.org/10.3390/en14071885

Burgos, D., & Ivanov, D. (2021). Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions. Transportation Research Part E: Logistics and Transportation Review, 152, 102412. https://doi.org/10.1016/j.tre.2021.102412

Busse, A., Gerlach, B., Lengeling, J. C., Poschmann, P., Werner, J., & Zarnitz, S. (2021). Towards digital twins of multimodal supply chains. Logistics, 5(2), 25. https://doi.org/10.3390/logistics5020025

Damtew, A. W. (2024). Roles of digital twins on material performances and utilization on upstream industry (the case of automotive industry). The International Journal of Advanced Manufacturing Technology, 130(7-8), 3525–3536. https://doi.org/10.1007/s00170-023-12706-1

Ivanov, D. (2023). Intelligent digital twin (iDT) for supply chain stress-testing, resilience, and viability. International Journal of Production Economics, 263, 108938. https://doi.org/10.1016/j.ijpe.2023.108938

Janecki, L., Antons, O., Reh, D., & Arlinghaus, J. C. (2024). Comparing digital twins and virtual engineering in buyer supplier relationships for complex production facilities. In M. Thürer, R. Riedel, G. von Cieminski, & D. Romero (Eds.), Advances in Production Management Systems. Production Management Systems for Volatile, Uncertain, Complex, and Ambiguous Environments. APMS 2024 (IFIP Advances in Information and Communication Technology, Vol. 733, pp. 180–193). Springer. https://doi.org/10.1007/978-3-031-71645-4_13

Oehlschläger, D., Glas, A. H., & Eßig, M. (2024). Acceptance of digital twins of customer demands for supply chain optimisation: An analysis of three hierarchical digital twin levels. Industrial Management & Data Systems, 124(3), 1050–1075. https://doi.org/10.1108/IMDS-07-2023-0467

Pehlken, A., Davila R, M. F., Dawel, L., & Meyer, O. (2024). Digital twins: Enhancing circular economy through digital tools. Procedia CIRP, 122, 563–568. https://doi.org/10.1016/j.procir.2024.01.082

Preut, A., Kopka, J.-P., & Clausen, U. (2021). Digital twins for the circular economy. Sustainability, 13(18), 10467. https://doi.org/10.3390/su131810467

Stadtfeld, G. M., Lienemann, R., & Gruchmann, T. (2025). An analysis of digital twin technologies enhancing supply chain viability: Empirical evidence from multiple cases. Production Planning & Control, 36(13), 1792–1808. https://doi.org/10.1080/09537287.2024.2415418

Winkler, P., Gallego-García, S., & Groten, M. (2022). Design and simulation of a digital twin mobility concept: An electric aviation system dynamics case study with capacity constraints. Applied Sciences, 12(2), 848. https://doi.org/10.3390/app12020848

Zarnitz, S., & Straube, F. (2023). Digital twins in logistics: Requirements, application and potentials. In F. Schupp & H. Wöhner (Eds.), Digitalisierung im Einkauf (pp. 189–201). Springer Gabler. https://doi.org/10.1007/978-3-658-40570-0_12

Cui, J., & Cao, S. (2025). Virtual reality medical technology in the metaverse: A digital twin approach and cybersecurity considerations. In F. Hu, S. Cao, & X. S. Hei (Eds.), Metaverse Platform Implementation: AI, Security, and Applications (pp. 249–264). CRC Press. https://doi.org/10.1201/9781032663609-17

Guo, S., et al. (2025). Ten years of the digital twin brain: Perspectives and challenges. Europhysics Letters, 149(4), 47001. https://doi.org/10.1209/0295-5075/adb3c9

Han, Y., Li, Y., Li, Y., Yang, B., & Cao, L. (2023). Digital twinning for smart hospital operations: Framework and proof of concept. Technology in Society, 74, 102317. https://doi.org/10.1016/j.techsoc.2023.102317

Li, T., Shen, Y., Li, Y., Zhang, Y., & Wu, S. (2024). The status quo and future prospects of digital twins for healthcare. EngMedicine, 1(3), 100042. https://doi.org/10.1016/j.engmed.2024.100042

Ning, Y., Wu, Z., & Ye, Q. (2025). Utilizing AI-driven 6G medical informatics and consumer electronics for early injury classification and response with a self-learning healthcare digital twin. IEEE Transactions on Consumer Electronics. Advance online publication. https://doi.org/10.1109/TCE.2025.3632401

Shen, S., et al. (2025). From virtual to reality: Innovative practices of digital twins in tumor therapy. Journal of Translational Medicine, 23(1), 348. https://doi.org/10.1186/s12967-025-06371-z

Sun, T., He, X., & Li, Z. (2023). Digital twin in healthcare: Recent updates and challenges. Digital Health, 9, 20552076221149651. https://doi.org/10.1177/20552076221149651

Sun, T., He, X., Song, X., Shu, L., & Li, Z. (2022). The digital twin in medicine: A key to the future of healthcare? Frontiers in Medicine, 9, 907066. https://doi.org/10.3389/fmed.2022.907066

Tang, X., Zhou, L., Mo, Y., Yin, G., Li, J., & Wei, S. (2025). A task lifecycle-driven digital twin framework for dynamic human-robot collaboration in healthcare. IFAC-PapersOnLine, 59(35), 567–572. https://doi.org/10.1016/j.ifacol.2025.12.538

Wang, M., Hu, H., & Wu, S. (2023). Opportunities and challenges of digital twin technology in healthcare. Chinese Medical Journal, 136(23), 2895–2896. https://doi.org/10.1097/CM9.0000000000002896

Zhao, F., et al. (2025). Current progress of digital twin construction using medical imaging. Journal of Applied Clinical Medical Physics, 26(9), e70226. https://doi.org/10.1002/acm2.70226

Bargavi, R., & Mathivathanan, D. (2024). Digital twins an enabler of digitalization in supply chain. In V. K. E. K., S. Rajak, V. Kumar, R. S. Mor, & A. Assayed (Eds.), Technologies: Sustainable Manufacturing Supply Chains. Environmental Footprints and Eco-design of Products and Processes (pp. 169–183). Springer. https://doi.org/10.1007/978-981-99-4894-9_11

Bhaskarkumar, M. S & Sivakumar, B. (2025). Advanced predictive maintenance of Phoenix Contact relays: A digital twin and machine learning approach. Procedia Computer Science, 260, 576–584. https://doi.org/10.1016/j.procs.2025.03.236

Goel, V., Arora, A., Rani, R., Goel, N., Thakar, P., & Arora, H. (2024). Machine learning model for a digital twin for predictive maintenance and optimization in a fruit supply chain. In 2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA) (pp. 1–8). IEEE. https://doi.org/10.1109/ICAIQSA64000.2024.10882378

Guo, D., & Mantravadi, S. (2025). The role of digital twins in lean supply chain management: Review and research directions. International Journal of Production Research, 63(5), 1851–1872. https://doi.org/10.1080/00207543.2024.2372655

Javaid, M., & Haleem, A. (2025). Role of digital twin and blockchain in logistics and supply chain management. In T. A. Nguyen (Ed.), Digital Twin and Blockchain for Sensor Networks in Smart Cities (pp. 243–264). Elsevier. https://doi.org/10.1016/B978-0-443-30076-9.00012-1

Kapil, D., Raut, R., Nayal, K., Kumar, M., & Akarte, M. M. (2024). A multisectoral systematic literature review of digital twins in supply chain management. Benchmarking: An International Journal, 32(10), 3793–3824. https://doi.org/10.1108/BIJ-04-2024-0286

Rashed, M. S., Fakhry, S., Satour, R., Abdelkarim, E. A., Sobhy, M., & Pathania, S. (2025). IoT and digital twins for smart food supply chains. In P. K. Dutta, A. Hamad, A. K. Haghi, & P. K. Prabhakar (Eds.), Food and Industry 5.0: Transforming the Food System for a Sustainable Future (pp. 249–273). Springer. https://doi.org/10.1007/978-3-031-76758-6_16

Samayamantri, S., & Vaddy, R. K. (2025). Sustainable development through digital twin technology: Optimizing the supply chain. In P. Whig, N. Silva, A. A. Elngar, N. Aneja, & P. Sharma (Eds.), Sustainable Development through Machine Learning, AI and IoT. ICSD 2024 (Communications in Computer and Information Science, pp. 92–101). Springer. https://doi.org/10.1007/978-3-031-71729-1_9

Singh, R. K. (2025). Transforming humanitarian supply chains with digital twin technology: A study on resilience and agility. The International Journal of Logistics Management, 36(4), 1119–1135. https://doi.org/10.1108/IJLM-08-2024-0504

Srinivasarao, L. B. (2025). Role of technological innovation in supply chain: AI and digital twins as tools for improving supply chain efficiency. In S. D. Bukhari & I. Zafar (Eds.), Supply Chain Disruptions and Impact on Global Inflation (pp. 137–164). IGI. https://doi.org/10.4018/979-8-3373-1982-7.ch006

Tyagi, A. K., & Richa. (2023). Digital twin technology: Opportunities and challenges for smart era's applications. In 15th International Conference on Contemporary Computing (IC3) (pp. 328–336). ACM. https://doi.org/10.1145/3607947.3608015

Vedashree, R., Ashok, P., & Pillai, S. (2024). Transforming cold chain management: The role of digital twins in post-harvest logistics. In 2nd World Conference on Communication and Computing (WCONF) (pp. 1–6). IEEE. https://doi.org/10.1109/WCONF61366.2024.10691976

Yalla, R. K. M. K., Ganesan, T., Devarajan, M. V., Yallamelli, A. R. G., Mamidala, V., & Sambas, A. (2025). Optimizing digital twin supply chains leveraging genetic algorithms Markov decision processes. In U. Mamodiya, A. Kalam, & D. Goyal (Eds.), Accelerating Product Development Cycles With Digital Twins and IoT Integration (pp. 99–130). IGI. https://doi.org/10.4018/979-8-3373-2028-1.ch006

Baker, G. H., & Davis, M. (2024). Digital twin in cardiovascular medicine and surgery. In A. C. Chang & A. Limon (Eds.), Intelligence-Based Cardiology and Cardiac Surgery (pp. 357–361). Elsevier. https://doi.org/10.1016/B978-0-323-90534-3.00032-9

Chaudhuri, A., et al. (2023). Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas. Frontiers in Artificial Intelligence, 6, 1222612. https://doi.org/10.3389/frai.2023.1222612

Kabir, M. R., Shishir, F. S., Shomaji, S., & Ray, S. (2025). Digital twins in healthcare IoT: A systematic review. High-Confidence Computing, 5(3), 100340. https://doi.org/10.1016/j.hcc.2025.100340

Katsoulakis, E., et al. (2024). Digital twins for health: A scoping review. NPJ Digital Medicine, 7(1), 77. https://doi.org/10.1038/s41746-024-01073-0

Li, X., et al. (2025). Digital twins as global learning health and disease models for preventive and personalized medicine. Genome Medicine, 17(1), 11. https://doi.org/10.1186/s13073-025-01435-7

Rahim, M., Lalouani, W., Toubal, E., & Emokpae, L. (2024). A digital twin-based platform for medical cyber-physical systems. IEEE Access, 12, 174591–174607. https://doi.org/10.1109/ACCESS.2024.3502077

Rahimi, S. A., Baradaran, A., Khameneifar, F., Gore, G., & Issa, A. M. (2024). DECIDE-twin: A framework for AI-enabled digital twins in clinical decision-making. IEEE Journal of Biomedical and Health Informatics, 29(9), 6332–6341. https://doi.org/10.1109/JBHI.2024.3521717

Rovati, L., et al. (2024). Development and usability testing of a patient digital twin for critical care education: A mixed methods study. Frontiers in Medicine, 10, 1336897. https://doi.org/10.3389/fmed.2023.1336897

Sadée, C., et al. (2025). Medical digital twins: Enabling precision medicine and medical artificial intelligence. The Lancet Digital Health, 7(7), 100864. https://doi.org/10.1016/j.landig.2025.02.004

Sel, K., et al. (2025). Survey and perspective on verification, validation, and uncertainty quantification of digital twins for precision medicine. NPJ Digital Medicine, 8(1), 40. https://doi.org/10.1038/s41746-025-01447-y

Zhang, K., et al. (2024). Concepts and applications of digital twins in healthcare and medicine. Patterns, 5(8), 101028. https://doi.org/10.1016/j.patter.2024.101028

Chen, H., Chu, T., Yang, L., Wang, Z., & Xue, L. (2024). Digital twin warehouse management platform developed based on Unity3D. In 4th International Conference on Internet of Things and Machine Learning (IoTML) (pp. 303–310). ACM. https://doi.org/10.1145/3697467.3697667

Chen, Z., & Huang, L. (2021). Digital twins for information-sharing in remanufacturing supply chain: A review. Energy, 220, 119712. https://doi.org/10.1016/j.energy.2020.119712

Liu, J., Yeoh, W., Gao, S., Qu, Y., & Gao, L. (2025). Blockchain-based digital twin for supply chain management: A survey. In S. Iyer, A. Nayyar, A. Paul, & M. Naved (Ed.), Digital Twins for Smart Cities and Villages (pp. 581–600). Elsevier. https://doi.org/10.1016/B978-0-443-28884-5.00025-7

Lv, Z., Qiao, L., Mardani, A., & Lv, H. (2022). Digital twins on the resilience of supply chain under COVID-19 pandemic. IEEE Transactions on Engineering Management, 71, 10522–10533. https://doi.org/10.1109/TEM.2022.3195903

Shang, W., et al. (2025). DigiPyramid: A multiresolution digital twin framework for reliable logistics management—Conceptualization, implementation, and intelligentization. IEEE Access, 13. https://doi.org/10.1109/ACCESS.2025.3606168

Wang, L., Deng, T., Shen, Z. J. M., Hu, H., & Qi, Y. (2022). Digital twin-driven smart supply chain. Frontiers of Engineering Management, 9(1), 56–70. https://doi.org/10.1007/s42524-021-0186-9

Wu, Y., Zhang, J., Li, Q., & Tan, H. (2023). Research on real-time robust optimization of perishable supply-chain systems based on digital twins. Sensors, 23(4), 1850. https://doi.org/10.3390/s23041850

Yin, Y., Zheng, P., Li, C., & Wang, L. (2023). A state-of-the-art survey on augmented reality-assisted digital twin for futuristic human-centric industry transformation. Robotics and Computer-Integrated Manufacturing, 81, 102515. https://doi.org/10.1016/j.rcim.2022.102515

Zhao, Y., Yang, Y.-J., & Luo, B. (2025). An evolutionary game approach to multi-technology synergy in logistics information sharing for smart supply chains. IEEE Access, 13, 161320–161343. https://doi.org/10.1109/ACCESS.2025.3610030

Zhen, Z., & Yao, Y. (2025). The confluence of digital twin and blockchain technologies in Industry 5.0: Transforming supply chain management for innovation and sustainability. Journal of the Knowledge Economy, 16(1), 5295–5321. https://doi.org/10.1007/s13132-024-02151-0

Zhong, D., Xia, Z., Zhu, Y., & Duan, J. (2023). Overview of predictive maintenance based on digital twin technology. Heliyon, 9(4), e14534. https://doi.org/10.1016/j.heliyon.2023.e14534

Araniti, G., et al. (2025). Medical digital twin and IoT devices: Monitoring patients through human-centered technologies. IEEE Internet of Things Magazine, 8(6), 107–114. https://doi.org/10.1109/MIOT.2025.3591039

Armeni, P., Polat, I., De Rossi, L. M., Diaferia, L., Meregalli, S., & Gatti, A. (2022). Digital twins in healthcare: Is it the beginning of a new era of evidence-based medicine? A critical review. Journal of Personalized Medicine, 12(8), 1255. https://doi.org/10.3390/jpm12081255

Cellina, M., et al. (2023). Digital twins: The new frontier for personalized medicine? Applied Sciences, 13(13), 7940. https://doi.org/10.3390/app13137940

De Domenico, M., et al. (2025). Challenges and opportunities for digital twins in precision medicine from a complex systems perspective. NPJ Digital Medicine, 8(1), 37. https://doi.org/10.1038/s41746-024-01402-3

Faiella, E., Pileri, M., Ragone, R., Grasso, R. F., Zobel, B. B., & Santucci, D. (2025). Digital twins in radiology: A systematic review of applications, challenges, and future perspectives. European Journal of Radiology, 189, 112166. https://doi.org/10.1016/j.ejrad.2025.112166

Ferro, D., et al. (2025). Making the case for digital twins: Italian healthcare needs AI-driven predictive modeling for personalized medicine. Recenti Progressi in Medicina, 116(10), 561–566. https://doi.org/10.1701/4573.45777

Giansanti, D., & Morelli, S. (2025). Exploring the potential of digital twins in cancer treatment: A narrative review of reviews. Journal of Clinical Medicine, 14(10), 3574. https://doi.org/10.3390/jcm14103574

Tortora, M., et al. (2025). Medical digital twin: A review on technical principles and clinical applications. Journal of Clinical Medicine, 14(2), 324. https://doi.org/10.3390/jcm14020324

Badakhshan, E., & Ball, P. (2023). Applying digital twins for inventory and cash management in supply chains under physical and financial disruptions. International Journal of Production Research, 61(15), 5094–5116. https://doi.org/10.1080/00207543.2022.2093682

Huang, Y., Ghadge, A., & Yates, N. (2024). Implementation of digital twins in the food supply chain: A review and conceptual framework. International Journal of Production Research, 62(17), 6400–6426. https://doi.org/10.1080/00207543.2024.2305804

Jesus, V., Kalaitzi, D., Batista, L., & Lopez, N. L. (2024). Digital twins of supply chains: A systems approach. IEEE Transactions on Engineering Management, 71, 14915–14932. https://doi.org/10.1109/TEM.2024.3468177

Okimi, T. O. (2025). Human centric digital twins for sustainable supply chain in construction. Smart Construction and Sustainable Cities, 3(1), 31. https://doi.org/10.1007/s44268-025-00078-2

Sani, S., Zarifnia, A., Salonitis, K., & Milisavljevic-Syed, J. (2024). Supply chain 4.0 and the digital twin approach: A framework for improving supply chain visibility. Procedia CIRP, 128, 321–326. https://doi.org/10.1016/j.procir.2024.03.014

Singh, G., Rajesh, R., Daultani, Y., & Misra, S. C. (2023). Resilience and sustainability enhancements in food supply chains using Digital Twin technology: A grey causal modelling (GCM) approach. Computers & Industrial Engineering, 179, 109172. https://doi.org/10.1016/j.cie.2023.109172

Singh, G., Singh, S., Daultani, Y., & Chouhan, M. (2023). Measuring the influence of digital twins on the sustainability of manufacturing supply chain: A mediating role of supply chain resilience and performance. Computers & Industrial Engineering, 186, 109711. https://doi.org/10.1016/j.cie.2023.109711

Zhang, G., MacCarthy, B. L., & Ivanov, D. (2022). The cloud, platforms, and digital twins—Enablers of the digital supply chain. In B. L. MacCarthy & D. Ivanov (Eds.), The Digital Supply Chain (pp. 77–91). Elsevier. https://doi.org/10.1016/B978-0-323-91614-1.00005-8

Onaji, I., Tiwari, D., Soulatiantork, P., Song, B., & Tiwari, A. (2022). Digital twin in manufacturing: Conceptual framework and case studies. International Journal of Computer Integrated Manufacturing, 35(8), 831–858. https://doi.org/10.1080/0951192X.2022.2027014

Kamel Boulos, M. N., & Zhang, P. (2021). Digital twins: From personalised medicine to precision public health. Journal of Personalized Medicine, 11(8), 745. https://doi.org/10.3390/jpm11080745

Brand, D., & Devlin, S. (2025). Ethical, legal, and technical considerations for the development of digital twins in healthcare. In 9th Forum on Research and Technologies for Society and Industry (RTSI) (pp. 308–313). IEEE. https://doi.org/10.1109/RTSI64020.2025.11212607

Hassani, H., & MacFeely, S. (2025). Integration of digital twin and blockchain for smart hospitals. In T. A. Nguyen (Ed.), Sensor Networks for Smart Hospitals (pp. 603–616). Elsevier. https://doi.org/10.1016/B978-0-443-36370-2.00030-X

Jameil, A. K., & Al-Raweshidy, H. (2024). Implementation and evaluation of digital twin framework for Internet of Things based healthcare systems. IET Wireless Sensor Systems, 14(6), 507–527. https://doi.org/10.1049/wss2.12101

Khan, S., Alzaabi, A., Iqbal, Z., Ratnarajah, T., & Arslan, T. (2023). A novel digital twin (DT) model based on WiFi CSI, signal processing and machine learning for patient respiration monitoring and decision-support. IEEE Access, 11, 103554–103568. https://doi.org/10.1109/ACCESS.2023.3316508

Koul, S., Mishra, V., & Taylor, I. W. (2025). Enhancing hospital operations efficiency through digital twin technology. In T. A. Nguyen (Ed.), Blockchain and Digital Twin for Smart Hospitals (pp. 511–528). Elsevier. https://doi.org/10.1016/B978-0-443-34226-4.00026-5

Madubuike, O. C., & Anumba, C. J. (2023). Digital twin–based health care facilities management. Journal of Computing in Civil Engineering, 37(2), 04022057. https://doi.org/10.1061/JCCEE5.CPENG-4842

Sasitharasarma, S., Alani, N. H. S., & Wisker, Z. L. (2025). Is the healthcare industry ready for digital twins? Examining the opportunities and challenges. Future Internet, 17(9), 386. https://doi.org/10.3390/fi17090386

Alguirat, I., Lehyani, F., & Zouari, A. (2025). Digital twins in supply chain management: A review of their role in boosting operational efficiency. Business Process Management Journal, 2025, 1–28. https://doi.org/10.1108/BPMJ-02-2025-0147

Kamble, S. S., Gunasekaran, A., Parekh, H., Mani, V., Belhadi, A., & Sharma, R. (2022). Digital twin for sustainable manufacturing supply chains: Current trends, future perspectives, and an implementation framework. Technological Forecasting and Social Change, 176, 121448. https://doi.org/10.1016/j.techfore.2021.121448

Maheshwari, P., & Kamble, S. (2022). The application of supply chain digital twin to measure optimal inventory policy. IFAC-PapersOnLine, 55(10), 2324–2329. https://doi.org/10.1016/j.ifacol.2022.10.055

Nakache, L., Féniès, P., & Ren, L. (2025). Digital twins to improve supply chain efficiency and resilience: Literature review and research potential. IFAC-PapersOnLine, 59(10), 2046–2051. https://doi.org/10.1016/j.ifacol.2025.09.344

Coorey, G., et al. (2022). The health digital twin to tackle cardiovascular disease—A review of an emerging interdisciplinary field. NPJ Digital Medicine, 5(1), 126. https://doi.org/10.1038/s41746-022-00640-7

Kaul, R., et al. (2023). The role of AI for developing digital twins in healthcare: The case of cancer care. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 13(1), e1480. https://doi.org/10.1002/widm.1480

Primiero, C. A., Janda, M., & Soyer, H. P. (2025). Skin 2.0: How cutaneous digital twins could reshape dermatology. Journal of Investigative Dermatology, 145(1), 18–21. https://doi.org/10.1016/j.jid.2024.07.011

Wickramasinghe, N., & Ulapane, N. (2025). A solution for the health data sharing dilemma: Data-less and identity-less model sharing through federated learning and digital twin-assisted clinical decision making. Electronics, 14(4), 682. https://doi.org/10.3390/electronics14040682

Melesse, T. Y., Franciosi, C., Di Pasquale, V., & Riemma, S. (2023). Analyzing the implementation of digital twins in the agri-food supply chain. Logistics, 7(2), 33. https://doi.org/10.3390/logistics7020033

Zenezini, G., Lagorio, A., Mangano, G., Pinto, R., & Rafele, C. (2025). Implementing digital twins in supply chain management: A maturity model. IFAC-PapersOnLine, 59(10), 1516–1521. https://doi.org/10.1016/j.ifacol.2025.09.255

Oulefki, A., Amira, A., & Foufou, S. (2025). Digital twins and AI transforming healthcare systems through innovation and data-driven decision making. Health and Technology, 15(2), 299–321. https://doi.org/10.1007/s12553-025-00947-x

Vallée, A. (2023). Digital twin for healthcare systems. Frontiers in Digital Health, 5, 1253050. https://doi.org/10.3389/fdgth.2023.1253050

Vallée, A. (2024a). Challenges and directions for digital twin implementation in otorhinolaryngology. European Archives of Oto-Rhino-Laryngology, 281(11), 6155–6159. https://doi.org/10.1007/s00405-024-08662-5

Vallée, A. (2024b). Envisioning the future of personalized medicine: Role and realities of digital twins. Journal of Medical Internet Research, 26, e50204. https://doi.org/10.2196/50204

Kalaiarasan, R., Olhager, J., Agrawal, T. K., & Wiktorsson, M. (2022). The ABCDE of supply chain visibility: A systematic literature review and framework. International Journal of Production Economics, 248, 108464. https://doi.org/10.1016/j.ijpe.2022.108464

Klar, R., Fredriksson, A., & Angelakis, V. (2023). Digital twins for ports: Derived from smart city and supply chain twinning experience. IEEE Access, 11, 71777–71799. https://doi.org/10.1109/ACCESS.2023.3295495

Morganti, L., et al. (2025). Wood-for-construction supply chain digital twin to drive circular economy and actor-based LCA information. Journal of Cleaner Production, 520, 146074. https://doi.org/10.1016/j.jclepro.2025.146074

Reim, W., Andersson, E., & Eckerwall, K. (2023). Enabling collaboration on digital platforms: A study of digital twins. International Journal of Production Research, 61(12), 3926–3942. https://doi.org/10.1080/00207543.2022.2116499

Fatouros, P., Tsirmpas, C., Andrikopoulos, D., Kaplow, S., Kontoangelos, K., & Papageorgiou, C. (2025). Randomized controlled study of a digital data driven intervention for depressive and generalized anxiety symptoms. NPJ Digital Medicine, 8(1), 113. https://doi.org/10.1038/s41746-025-01511-7

Tsianaka, E., & Peramatzis, K. (2025). Application of digital twin technology for building sustainable strategic business models in healthcare. In A. Naim & A. Kumar (Eds.), Digital technologies and transformations in public administration, engineering, and sustainable business (pp. 333–358). IGI. https://doi.org/10.4018/979-8-3373-1534-8.ch015

Chatterjee, P., Das, D., Rawat, D. B., Ghosh, U., Banerjee, S., & Al-Numay, M. S. (2024). Digital twins and blockchain fusion for security in metaverse-driven consumer supply chains. IEEE Transactions on Consumer Electronics, 70(3). https://doi.org/10.1109/TCE.2024.3477297

Yoon, J., Alkhudary, R., Talluri, S., & Féniès, P. (2025). Risk management and macroeconomic disruptions in supply chains: The role of blockchain, digital twins, generative AI, and quantum computing. IEEE Transactions on Engineering Management, 72, 2995–3009. https://doi.org/10.1109/TEM.2025.3585433

Akash, S. S., & Ferdous, M. S. (2022). A blockchain based system for healthcare digital twin. IEEE Access, 10, 50523–50547. https://doi.org/10.1109/ACCESS.2022.3173617

Das, C., et al. (2022). Toward IORT collaborative digital twin technology enabled future surgical sector: Technical innovations, opportunities and challenges. IEEE Access, 10, 129079–129104. https://doi.org/10.1109/ACCESS.2022.3227644

Voipio, V., Elfvengren, K., Korpela, J., & Vilko, J. (2023). Driving competitiveness with RFID-enabled digital twin: Case study from a global manufacturing firm's supply chain. Measuring Business Excellence, 27(1), 40–53. https://doi.org/10.1108/MBE-06-2021-0084

De Oliveira El-Warrak, L., & Miceli de Farias, C. (2025). TWINVAX: Conceptual model of a digital twin for immunisation services in primary health care. Frontiers in Public Health, 13, 1568123. https://doi.org/10.3389/fpubh.2025.1568123

El-Warrak, L. D. O., Miceli de Farias, C., & De Azevedo Costa, V. H. D. M. (2025). Simulation-based assessment of digital twin systems for immunisation. Frontiers in Digital Health, 7, 1603550. https://doi.org/10.3389/fdgth.2025.1603550

Kalaboukas, K., Kiritsis, D., & Arampatzis, G. (2023). Governance framework for autonomous and cognitive digital twins in agile supply chains. Computers in Industry, 146, 103857. https://doi.org/10.1016/j.compind.2023.103857

Roumeliotis, C., Dasygenis, M., Lazaridis, V., & Dossis, M. (2024). Blockchain and digital twins in smart Industry 4.0: The use case of supply chain—A review of integration techniques and applications. Designs, 8(6), 105. https://doi.org/10.3390/designs8060105

John, A., Alhajj, R., & Rokne, J. (2025). A systematic review of AI as a digital twin for prostate cancer care. Computer Methods and Programs in Biomedicine, 268, 108804. https://doi.org/10.1016/j.cmpb.2025.108804

Ringeval, M., Etindele Sosso, F. A., Cousineau, M., & Paré, G. (2025). Advancing health care with digital twins: Meta-review of applications and implementation challenges. Journal of Medical Internet Research, 27, e69544. https://doi.org/10.2196/69544

Liu, Z., Hansen, D. W., & Chen, Z. (2023). Leveraging digital twins to support industrial symbiosis networks: A case study in the Norwegian wood supply chain collaboration. Sustainability, 15(3), 2647. https://doi.org/10.3390/su15032647

Sun, X., Yu, H., Solvang, W. D., & Gan, M. (2025). Distribution and logistics network design using digital twin: Concepts, methods, and applications. In H. Yu (Ed.), Smart Logistics in Industry 5.0 (pp. 31–56). CRC Press. https://doi.org/10.1201/9781003466451-2

Chaparro-Cárdenas, S. L., et al. (2025). A technological review of digital twins and artificial intelligence for personalized and predictive healthcare. Healthcare, 13(14), 1763. https://doi.org/10.3390/healthcare13141763

Rodríguez-Aguilar, R., Marmolejo-Suacedo, J.-A., Rodríguez-Aguilar, M., & Marmolejo-Saucedo, L. (2024). Machine learning for digital shadow design in health insurance sector. Mobile Networks and Applications, 29(1), 221–234. https://doi.org/10.1007/s11036-023-02289-2

Defraeye, T., et al. (2021). Digital twins are coming: Will we need them in supply chains of fresh horticultural produce? Trends in Food Science & Technology, 109, 245–258. https://doi.org/10.1016/j.tifs.2021.01.025

Shoji, K., Schudel, S., Shrivastava, C., Onwude, D., & Defraeye, T. (2022). Optimizing the postharvest supply chain of imported fresh produce with physics-based digital twins. Journal of Food Engineering, 329, 111077. https://doi.org/10.1016/j.jfoodeng.2022.111077

Meijer, C., Uh, H.-W., & El Bouhaddani, S. (2023). Digital twins in healthcare: Methodological challenges and opportunities. Journal of Personalized Medicine, 13(10), 1522. https://doi.org/10.3390/jpm13101522

Mulder, S. T., et al. (2022). Dynamic digital twin: Diagnosis, treatment, prediction, and prevention of disease during the life course. Journal of Medical Internet Research, 24(9), e35675. https://doi.org/10.2196/35675

Lo, H.-W., Chi, C.-Y., Pai, C.-J., & Deveci, M. (2025). A data-driven two-stage decision-making model for supplier selection and negotiation-based procurement planning. International Journal of Production Research, 64(1), 39–62. https://doi.org/10.1080/00207543.2025.2539305

Jørgensen, C. S., Shukla, A., & Katt, B. (2023). Digital twins in healthcare: Security, privacy, trust and safety challenges. In S. Katsikas et al. (Eds.), Computer Security. ESORICS 2023 International Workshops (Lecture Notes in Computer Science, Vol. 14399, pp. 140–153). Springer. https://doi.org/10.1007/978-3-031-54129-2_9

Sieve, R., Kobialka, P., Slaughter, L., Schlatte, R., Johnsen, E. B., & Tarifa, S. L. T. (2025). BedreFlyt: Improving patient flows through hospital wards with digital twins. In 1st International Workshop on Autonomous Systems Quality Assurance and Prediction with Digital Twins (ASQAP) (pp. 1–15). EPTCS. https://doi.org/10.4204/EPTCS.418.1

Rahmanzadeh, S., Pishvaee, M. S., & Govindan, K. (2023). Emergence of open supply chain management: The role of open innovation in the future smart industry using digital twin network. Annals of Operations Research, 329(1), 979–1007. https://doi.org/10.1007/s10479-021-04254-2

Ziari, M., & Taleizadeh, A. A. (2025). Integrated data-driven and artificial intelligence framework to develop digital twins in distribution system of supply chains: A real industrial case. International Journal of Production Economics, 289, 109743. https://doi.org/10.1016/j.ijpe.2025.109743

Shehadeh, A. (2025). Optimizing construction supply chain efficiency: A blockchain and digital twins approach to automating cost management and contract administration. Engineering, Construction and Architectural Management. Advance online publication, 1-33. https://doi.org/10.1108/ECAM-06-2025-1025

Abideen, A. Z., Sundram, V. P. K., Pyeman, J., Othman, A. K., & Sorooshian, S. (2021). Digital twin integrated reinforced learning in supply chain and logistics. Logistics, 5(4), 84. https://doi.org/10.3390/logistics5040084

Xie, Y., Fang, Z., Korolija, I., & Rovas, D. (2025). Review of digital twins—Enabled applications for demand response. Proceedings of the Institution of Civil Engineers - Smart Infrastructure and Construction, 178(3), 158–166. https://doi.org/10.1680/jsmic.24.00013

Khan, M., Khan, S., & Rahman, I. U. (2025). Supply-chain digitization and non-intrusive load monitoring with digital twins: The impact of energy policies on carbon pricing and renewable energy deployment. Energy Economics, 144, 108400. https://doi.org/10.1016/j.eneco.2025.108400

Santos, R., Piqueiro, H., Dias, R., & Rocha, C. D. (2024). Transitioning trends into action: A simulation-based digital twin architecture for enhanced strategic and operational decision-making. Computers & Industrial Engineering, 198, 110616. https://doi.org/10.1016/j.cie.2024.110616

Abdullahi, I., Longo, S., & Samie, M. (2024). An enabling architecture for computational cost efficiency in predictive maintenance digital twins. In 2024 International Conference on Cyber-Physical Social Intelligence (ICCSI) (pp. 1–6). IEEE. https://doi.org/10.1109/ICCSI62669.2024.10799418

Alsharari, N. M. (2025). Integration of blockchain and digital twin in logistics accounting and supply chain management. In T. A. Nguyen (Ed.), Digital Twin and Blockchain for Sensor Networks in Smart Cities (pp. 351–359). Elsevier. https://doi.org/10.1016/B978-0-443-30076-9.00018-2

Resman, M., Debevec, M., & Herakovič, N. (2025). Using digital twin technology to improve the organization of the supply chain in piece type of production. Systems, 13(7), 505. https://doi.org/10.3390/systems13070505

Kim, D. H., Kim, G. Y., & Noh, S. D. (2025). Digital twin-based prediction and optimization for dynamic supply chain management. Machines, 13(2), 109. https://doi.org/10.3390/machines13020109

Gallego-García, S., Gallego-García, D., & García-García, M. (2023). Sustainability in the agri-food supply chain: A combined digital twin and simulation approach for farmers. Procedia Computer Science, 217, 1280–1295. https://doi.org/10.1016/j.procs.2022.12.326

Bozkaya-Aras, E., Onel, T., Eriskin, L., & Karatas, M. (2025). Intelligent human activity recognition for healthcare digital twin. Internet of Things, 30, 101497. https://doi.org/10.1016/j.iot.2025.101497

Xames, M. D., & Topcu, T. G. (2024). A systematic literature review of digital twin research for healthcare systems: Research trends, gaps, and realization challenges. IEEE Access, 12, 4099–4126. https://doi.org/10.1109/ACCESS.2023.3349379

Pusparum, M., Thas, O., Beck, S., Ecker, S., & Ertaylan, G. (2025). From ageing clocks to human digital twins in personalising healthcare through biological age analysis. NPJ Digital Medicine, 8(1), 537. https://doi.org/10.1038/s41746-025-01911-9

Lauer-Schmaltz, M. W., Cash, P., & Rivera, D. G. T. (2024). ETHICA: Designing human digital twins—A systematic review and proposed methodology. IEEE Access, 12, 86947–86973. https://doi.org/10.1109/ACCESS.2024.3416517

Hemdan, E. E. D., & Sayed, A. (2025). Smart and secure healthcare with digital twins: A deep dive into blockchain, federated learning, and future innovations. Algorithms, 18(7), 401. https://doi.org/10.3390/a18070401

Böhler, D., & Friebe, M. (2022). (Digital) patient journey and empowerment: Digital twin. In M. Friebe (Ed.), Novel Innovation Design for the Future of Health: Entrepreneurial Concepts for Patient Empowerment and Health Democratization (pp. 169–178). Springer. https://doi.org/10.1007/978-3-031-08191-0_17

Sahal, R., Alsamhi, S. H., & Brown, K. N. (2022). Personal digital twin: A close look into the present and a step towards the future of personalised healthcare industry. Sensors, 22(15), 5918. https://doi.org/10.3390/s22155918

Zhang, L., Bullen, C., & Chen, J. (2025). Digital health innovations to catalyze the transition to value-based health care. JMIR Medical Informatics, 13, e57385. https://doi.org/10.2196/57385

Manzoor, B., & Riaz, A. (2025). Revolutionizing healthcare: Harnessing the power of integrated blockchain and digital twins in smart hospitals. In T. A. Nguyen (Ed.), Blockchain and Digital Twin for Smart Hospitals (pp. 283–294). Elsevier. https://doi.org/10.1016/B978-0-443-34226-4.00015-0

Falkowski, P., et al. (2023). Study on the applicability of digital twins for home remote motor rehabilitation. Sensors, 23(2), 911. https://doi.org/10.3390/s23020911

Barr, N., Cucul, C., & Moutinho, J. (2025). How can decentralized technologies, digital twins, and ethical AI empower rare diseases patients? In A. Pesqueira & A. de Bem Machado (Eds.), Navigating Privacy, Innovation, and Patient Empowerment Through Ethical Healthcare Technology (pp. 83–106). IGI. https://doi.org/10.4018/979-8-3693-7630-0.ch004

Aloqaily, M., Bouachir, O., & Karray, F. (2023). Digital twin for healthcare immersive services: Fundamentals, architectures, and open issues. In A. E. Saddik (Ed.), Digital Twin for Healthcare (pp. 39–71). Elsevier. https://doi.org/10.1016/B978-0-32-399163-6.00008-1

Fernando, X., & Lăzăroiu, G. (2025). Medical sensor network, blockchain and digital twin as the backbones of a connected ecosystem of smart hospitals. In T. A. Nguyen (Ed.), Sensor Networks for Smart Hospitals (pp. 109–128). Elsevier. https://doi.org/10.1016/B978-0-443-36370-2.00007-4

Subasi, A., & Subasi, M. E. (2024). Digital twins in healthcare and biomedicine. In P. O. de Pablos & X. Zhang (Eds.), Artificial Intelligence, Big Data, Blockchain and 5G for the Digital Transformation of the Healthcare Industry (pp. 365–401). Academic Press. https://doi.org/10.1016/B978-0-443-21598-8.00011-7

Hwang, T., et al. (2024). Clinical usefulness of digital twin guided virtual amiodarone test in patients with atrial fibrillation ablation. NPJ Digital Medicine, 7(1), 297. https://doi.org/10.1038/s41746-024-01298-z

Momand, Z., Mongkolnam, P., Chan, J. H., Charoenkitkarn, N., & Pal, D. (2025). Building digital twins for elderly care: An end-to-end framework from data acquisition to modeling. IEEE Access, 13, 169415–169445. https://doi.org/10.1109/ACCESS.2025.3607603

Singh, B., Chandra, S., Wongmahesak, K., & Shrivastava, D. (2025). Mobilizing urban planning and resource management: Emerging trends in digital twin-driven healthcare. In U. Mamodiya, A. Kalam, & D. Goyal (Eds.), Accelerating Product Development Cycles With Digital Twins and IoT Integration (pp. 155–174). IGI. https://doi.org/10.4018/979-8-3373-2028-1.ch008

Roy, P., Sherazi, S. H. T., Delda, M. J. M., Maqsood, M., & Ahmad, M. (2025). Secure data sharing in healthcare: A blockchain and digital twins approach. In R. R., S. Chowdhury, S. Kardy, & R. Damaševičius (Eds.), Digital Twins for Sustainable Healthcare in the Metaverse (pp. 255–286). IGI. https://doi.org/10.4018/979-8-3693-4199-5.ch011

Goel, P. K., Verma, S., & Jain, S. (2026). Cloud and edge integration for scalable disease prediction frameworks. In A. Muniasamy (Ed.), AI Model Design and Data Management for Disease Prediction (pp. 323–352). IGI. https://doi.org/10.4018/979-8-3373-5137-7.ch011

Portilla, F., Gerdes, M. W., Reichert, F., & Chaltikyan, G. (2024). Reference information model and interoperable architecture for digital health twins: A position paper. In J. Mantas et al. (Eds.), Digital Health and Informatics Innovations for Sustainable Health Care Systems (Vol. 316, pp. 344–345). IOS Press. https://doi.org/10.3233/SHTI240414

Pariso, P., Picariello, M., & Marino, A. (2025). Digital twins in industry and healthcare: Policy regulation and future prospects in Europe. In L. T. De Paolis, P. Arpaia, & M. Sacco (Eds.), Extended Reality. XR Salento 2025 (Lecture Notes in Computer Science, Vol. 15740, pp. 3–13). Springer. https://doi.org/10.1007/978-3-031-97772-5_1

Radanliev, P., De Roure, D., Nicolescu, R., Huth, M., & Santos, O. (2022). Digital twins: Artificial intelligence and the IoT cyber-physical systems in Industry 4.0. International Journal of Intelligent Robotics and Applications, 6(1), 171–185. https://doi.org/10.1007/s41315-021-00180-5

Tripathi, N., Hietala, H., Xu, Y., & Liyanage, R. (2024). Stakeholders collaborations, challenges and emerging concepts in digital twin ecosystems. Information and Software Technology, 169, 107424. https://doi.org/10.1016/j.infsof.2024.107424

David, I., Shao, G., Gomes, C., Tilbury, D., & Zarkout, B. (2024). Interoperability of digital twins: Challenges, success factors, and future research directions. In T. Margaria & B. Steffen (Eds.), Leveraging Applications of Formal Methods, Verification and Validation. Application Areas. ISoLA 2024 (Lecture Notes in Computer Science, Vol. 15223, pp. 27–46). Springer. https://doi.org/10.1007/978-3-031-75390-9_3

Bhandal, R., Meriton, R., Kavanagh, R. E., & Brown, A. (2022). The application of digital twin technology in operations and supply chain management: A bibliometric review. Supply Chain Management: An International Journal, 27(2), 182–206. https://doi.org/10.1108/SCM-01-2021-0053

Gai, K., Zhang, Y., Qiu, M., & Thuraisingham, B. (2022). Blockchain-enabled service optimizations in supply chain digital twin. IEEE Transactions on Services Computing, 16(3), 1-12. https://doi.org/10.1109/TSC.2022.3192166

Wakili, A., Bakkali, S., & Ibrahim, I. A. (2025). A digital twin-enhanced cybersecurity framework for IoT in healthcare: Applications in Industry 4.0. Telematics and Informatics Reports, 20, 100254. https://doi.org/10.1016/j.teler.2025.100254