Strategic Assessment of IoT Technologies in Healthcare: Grey MCDM Approach
DOI:
https://doi.org/10.31181/sdmap21202528Keywords:
IoT, Healthcare, Grey DEMATEL, Multi-Criteria Decision Making, Security, Scalability, Data PrivacyAbstract
The integration of Internet of Things (IoT) technologies in healthcare has revolutionized patient monitoring, data analytics, and remote medical device management, significantly improving healthcare delivery. However, selecting the most appropriate IoT technologies in the healthcare sector involves evaluating multiple criteria under conditions of uncertainty. This study addresses this challenge by utilizing the Grey Decision-Making Trial and Evaluation Laboratory (Grey DEMATEL) method to analyze the key criteria influencing IoT technology selection in healthcare. Eight critical criteria, including security, data privacy, technical performance, usability, scalability, and economic factors, were identified and examined for their causal relationships. The results show that security and data privacy are the most influential factors, followed by technical performance and usability. The findings offer valuable insights for decision-makers, assisting them in prioritizing crucial aspects for successful IoT implementation in healthcare. This research contributes to the field by providing a structured decision-making framework that enhances the effective integration of IoT technologies while addressing security, efficiency, and regulatory concerns.
Downloads
References
Krishankumar, R., Dhruva, S., Ravichandran, K. S., & Kar, S. (2024). Selection of a viable blockchain service provider for data management within the internet of medical things: An MCDM approach to Indian healthcare. Information Sciences, 657, 119890. https://doi.org/10.1016/j.ins.2023.119890
Wang, L., Ali, Y., Nazir, S., & Niazi, M. (2020). ISA evaluation framework for security of internet of health things system using AHP-TOPSIS methods. IEEE Access, 8, 152316–152332. https://doi.org/10.1109/ACCESS.2020.3017221
Tariq, M. I., Mian, N. A., Sohail, A., Alyas, T., & Ahmad, R. (2020). Evaluation of the challenges in the internet of medical things with multicriteria decision making (AHP and TOPSIS) to overcome its obstruction under fuzzy environment. Mobile Information Systems, 1, 8815651. https://doi.org/10.1155/2020/8815651
Yeşılyurt, B., Karakuş, K., Gür, Ş., & Eren, T. (2020). Evaluation of the potential of the internet of things in health services with multi criteria decision-making methods. Sigma Journal of Engineering and Natural Sciences, 38(3), 1595–1606.
Pant, S., Garg, P., Kumar, A., Sharma, H. K., & Klochkov, Y. (2024). AHP-based multi-criteria decision-making approach for monitoring health management practices in smart healthcare system. International Journal of System Assurance Engineering and Management, 15(4), 1444–1455. https://doi.org/10.1007/s13198-023-01904-5
Zaidan, A. A., Alsattar, H. A., Qahtan, S., Pamučar, D., & Gupta, B. B. (2023). Secure decision approach for internet of healthcare things smart-system-based blockchain. IEEE Internet of Things Journal, 10(24), 21647–21655. https://doi.org/10.1109/JIOT.2023.3308953
Wahab, S. N., Singh, J., & Subramaniam, N. (2023). Telemedicine implementation framework for Malaysia: An integrated SWOT-MCDM approach. Health Policy and Technology, 12(4), 100818. https://doi.org/10.1016/j.hlpt.2023.100818
Alamoodi, A. H., Albahri, O. S., Zaidan, A. A., Zaidan, B. B., & Albahri, A. S. (2023). Hospital selection framework for remote MCD patients based on fuzzy q-rung orthopair environment. Neural Computing and Applications, 35(8), 6185–6196. https://doi.org/10.1007/s00521-022-07998-5
Khan, H. U., Ali, Y., & Khan, F. (2023). A features-based privacy preserving assessment model for authentication of internet of medical things (IoMT) devices in healthcare. Mathematics, 11(5), 1197. https://doi.org/10.3390/math11051197
Narang, D., Madaan, J., Chan, F. T. S., & Chungcharoen, E. (2024). Managing open loop water resource value chain through IoT focused decision and information integration (DII) modelling using fuzzy MCDM approach. Journal of Environmental Management, 350, 119609. https://doi.org/10.1016/j.jenvman.2023.119609
Rafiquee, A., & Shabbiruddin. (2024). Optimal selection and challenges of municipal waste management system using an integrated approach: A case study. Energy Sources, Part A: Recovery, Utilization and Environmental Effects, 46(1), 1996–2023. https://doi.org/10.1080/15567036.2023.2298285
He, Y., He, J., & Wen, N. (2023). The challenges of IoT-based applications in high-risk environments, health and safety industries in the Industry 4.0 era using decision-making approach. Journal of Innovation and Knowledge, 8(2), 100347. https://doi.org/10.1016/j.jik.2023.100347
Hsu, C.-H., Liu, J.-C., Cai, X.-Q., Zhang, T.-Y., & Lv, W.-Y. (2024). Enabling sustainable diffusion in supply chains through Industry 5.0: An impact analysis of key enablers for SMEs in emerging economies. Mathematics, 12(24), 3938. https://doi.org/10.3390/math12243938
Orfanidou, V. S., Dimitriou, D. J., Rachaniotis, N. P., & Tsoulfas, G. T. (2024). Critical factors for green public procurement: The case of Greece. Logistics, 8(4), 127. https://doi.org/10.3390/logistics8040127
Anand, S., Barua, M. K., Katiyar, R., & Meet, R. K. (2024). Minimizing waste, maximizing sustainability: Analyzing collaborative practices implementation barriers in the agri-fresh produce industry. Sustainable Futures, 8, 100398. https://doi.org/10.1016/j.sftr.2024.100398
Zekhnini, K., Tarei, P. K., Benabdellah, A. C., & Oktari, R. S. (2024). Analyzing the dyadic relationship between the performance enablers to achieve the humanitarian supply chain 4.0. International Journal of Disaster Risk Reduction, 115, 105046. https://doi.org/10.1016/j.ijdrr.2024.105046
Gautam, A., Shankar, R., & Vrat, P. (2024). Circular economy-based operational strategies in the management of solar photovoltaics e-waste: A multi-stakeholder perspective. Business Strategy and the Environment, 33(8), 9040–9058. https://doi.org/10.1002/bse.3963
Dwivedi, A., Ganguly, A., & Paul, S. K. (2024). Critical success factors for linking digital technologies and circular supply chains. Business Strategy and the Environment, 33(8), 8332–8360. https://doi.org/10.1002/bse.3907
Yan, M., Jia, J., & Chen, Y. (2024). Research on accident early warning of metallurgical enterprises based on grey DEMATEL/ISM and Bayesian network. Scientific Reports, 14(1), 18312. https://doi.org/10.1038/s41598-024-68855-0
Li, J., Huang, Z., Wang, H., Jameel, D., & Wang, P. (2024). Multi-index comprehensive evaluation model for assessing risk to trainees in an emergency rescue training base for building collapse. Scientific Reports, 14(1), 4792. https://doi.org/10.1038/s41598-024-55368-z
Aria, A., Jafari, P., & Behifar, M. (2024). Identification of factors affecting student academic burnout in online education during the COVID-19 pandemic using grey Delphi and grey-DEMATEL techniques. Scientific Reports, 14(1), 3989. https://doi.org/10.1038/s41598-024-53233-7
Li, X., Li, J., He, J., Dai, J., & Shen, Q. (2024). What are the key factors of enterprises' greenwashing behaviors under multi-agent interaction? A grey-DEMATEL analysis from Chinese construction materials enterprises. Engineering, Construction and Architectural Management, 31(11), 4659–4676. https://doi.org/10.1108/ECAM-01-2023-0027
Deng, J. L. (1982). Control problems of grey systems. Systems and Control Letters, 1(5), 288–294. https://doi.org/10.1016/S0167-6911(82)80025-X
Deng, J. L. (1989). Introduction to grey system theory. Journal of Grey Systems, 1(1), 1–24.
Bai, C., & Sarkis, J. (2013). Grey-based DEMATEL model for evaluating business process management critical success factors. International Journal of Production Economics, 146(1), 281–292. https://doi.org/10.1016/j.ijpe.2013.07.011
Gupta, H., & Barua, M. K. (2018). A grey DEMATEL-based approach for modeling enablers of green innovation in manufacturing organizations. Environmental Science and Pollution Research, 25, 9556–9578. https://doi.org/10.1007/s11356-018-1261-6
Tseng, M. L. (2009). A causal and effect decision making model of service quality expectation using grey-fuzzy DEMATEL approach. Expert Systems with Applications, 36, 7738–7748. https://doi.org/10.1016/j.eswa.2008.09.011
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Gülay Demir (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.