Research article Special Issues

Factors influencing the Supply Chain Management in e-Health using UTAUT model

  • Received: 27 January 2023 Revised: 20 February 2023 Accepted: 27 February 2023 Published: 15 March 2023
  • Logistics in the healthcare industry involves coordinating the distribution of medical supplies and equipment across various departments and organizations. Supply Chain Management can help healthcare facilities identify weaknesses and devise strategies to address them. Using the Unified Theory of Acceptance and Use of Technology (UTAUT), the study investigates the motivations behind the individuals’ desire to use Internet of Things (IoT) solutions in healthcare. In order to better understand the factors that influence the use of IoT for e-HMS, a survey was administered to 210 healthcare IoT users. The study focuses on the potential medicinal applications of IoT technologies and incorporates the concepts of performance expectations, healthcare hazard, and trust (PHT) and perceived enabling circumstances (PFC) to complement past findings in the field. Overall, the study appears to be focused on contributing to the existing knowledge about the factors that influence the adoption of IoT technologies in healthcare, and it emphasizes the importance of considering theoretical constructs such as PHT and PFC in this context. The findings of the study can be used by IoT creators, medical experts, and vendors to optimize e-HMS and provide insight into the potential and limitations of UTAUT simulation to improve the logistic of Supply Chain Management in healthcare 4.0. The results have been analyzed by applying machine learning classifiers and have been visualized using different metrics.

    Citation: Moteeb Al Moteri, Mohammed Alojail. Factors influencing the Supply Chain Management in e-Health using UTAUT model[J]. Electronic Research Archive, 2023, 31(5): 2855-2877. doi: 10.3934/era.2023144

    Related Papers:

  • Logistics in the healthcare industry involves coordinating the distribution of medical supplies and equipment across various departments and organizations. Supply Chain Management can help healthcare facilities identify weaknesses and devise strategies to address them. Using the Unified Theory of Acceptance and Use of Technology (UTAUT), the study investigates the motivations behind the individuals’ desire to use Internet of Things (IoT) solutions in healthcare. In order to better understand the factors that influence the use of IoT for e-HMS, a survey was administered to 210 healthcare IoT users. The study focuses on the potential medicinal applications of IoT technologies and incorporates the concepts of performance expectations, healthcare hazard, and trust (PHT) and perceived enabling circumstances (PFC) to complement past findings in the field. Overall, the study appears to be focused on contributing to the existing knowledge about the factors that influence the adoption of IoT technologies in healthcare, and it emphasizes the importance of considering theoretical constructs such as PHT and PFC in this context. The findings of the study can be used by IoT creators, medical experts, and vendors to optimize e-HMS and provide insight into the potential and limitations of UTAUT simulation to improve the logistic of Supply Chain Management in healthcare 4.0. The results have been analyzed by applying machine learning classifiers and have been visualized using different metrics.



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    [1] I. Ali, D. Kannan, Mapping research on healthcare operations and supply chain management: a topic modelling-based literature review, Ann. Oper. Res., 315 (2022), 29–55. https://doi.org/10.1007/s10479-022-04596-5 doi: 10.1007/s10479-022-04596-5
    [2] M. K. Anser, M. A. Khan, A. A. Nassani, M. M. Q. Abro, K. Zaman, A. Kabbani, Does COVID-19 pandemic disrupt sustainable supply chain process? Covering some new global facts, Environ. Sci. Pollut. Res., 28 (2021), 59792–59804. https://doi.org/10.1007/s11356-021-14817-2 doi: 10.1007/s11356-021-14817-2
    [3] M. Alojail, S. Bhatia, A novel technique for behavioral analytics using ensemble learning algorithms in E-commerce, IEEE Access, 8 (2020), 150072–150080. https://doi.org/10.1109/ACCESS.2020.3016419 doi: 10.1109/ACCESS.2020.3016419
    [4] M. Shuaib, N. H. Hassan, S. Usman, S. Alam, S. Bhatia, A. Mashat, et al., Self-sovereign identity solution for blockchain-based land registry system: A comparison, Mobile Inf. Syst., (2022), 8930472. https://doi.org/10.1155/2022/8930472 doi: 10.1155/2022/8930472
    [5] B. B. Tefera, G. T. Anbessa, P Anbessa, Pharmaceutical supply chain practices and its associated factors in public health facilities, West Gojjam Zone, Ethiopia: Cross-Sectional Study, Hosp. Pharm., 57 (2022), 622–632. https://doi.org/10.1177/00185787211067375 doi: 10.1177/00185787211067375
    [6] R. Bala, K. R. Sarangee, S. He, G. Jin, Get Us PPE: A self-organizing platform ecosystem for supply chain optimization during COVID-19, Sustainability, 14 (2022), 3175. https://doi.org/10.3390/su14063175 doi: 10.3390/su14063175
    [7] M. Beaulieu, O. Bentahar, Digitalization of the healthcare supply chain: A roadmap to generate benefits and effectively support healthcare delivery, Technol. Forecast. Soc. Change, 167 (2021). https://doi.org/10.1016/j.techfore.2021.120717 doi: 10.1016/j.techfore.2021.120717
    [8] O. Bentahar, S. Benzidia, M. Bourlakis, A green supply chain taxonomy in healthcare: critical factors for a proactive approach, Int. J. Logist. Manage., 1 (2022). https://doi.org/10.1108/IJLM-04-2021-0240 doi: 10.1108/IJLM-04-2021-0240
    [9] S. Benzidia, N. Makaoui, O. Bentahar, The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance, Technol. Forecast. Soc. Change, 165 (2021), 120557. https://doi.org/10.1016/j.techfore.2020.120557 doi: 10.1016/j.techfore.2020.120557
    [10] W. Bian, X. Yang, S. Li, X. Yang, G. Hua, Advantages of 3PLs as healthcare supply chain orchestrators, Comput. Ind. Eng., 161 (2021), 107628. https://doi.org/10.1016/j.cie.2021.107628 doi: 10.1016/j.cie.2021.107628
    [11] J. D. Borrero, Agri-food supply chain traceability for fruit and vegetable cooperatives using blockchain technology, Ciriec-Espana Rev. Econ. Publ. Soc. Coop., 95 (2019), 71–94. https://doi.org/10.7203/ciriec-e.95.13123 doi: 10.7203/ciriec-e.95.13123
    [12] H. Çolak, C. H. Kaǧnicioǧlu, Acceptance of blockchain technology in supply chains: A model proposal, Oper. Supply Chain Manage., 15 (2022), 17–26. https://doi.org/10.31387/oscm0480327 doi: 10.31387/oscm0480327
    [13] H. Cole, The organ supply chain: Geography and the inequalities of transplant logistics, Trans. Inst. Br. Geogr., 46 (2021), 1008–1021. https://doi.org/10.1111/tran.12458 doi: 10.1111/tran.12458
    [14] K. Dorgham, I. Nouaouri, J. C. Nicolas, G. Goncalves, Fuzzy programming approach for collaborative supply chain under uncertain demand, in 2022 IEEE 6th International Conference on Logistics Operations Management GOL, (2022), 1–7. https://doi.org/10.1109/GOL53975.2022.9820247
    [15] S. Duarte, M. D. R. Cabrita, V. Cruz-Machado, Lean and green modelling in healthcare supply chains: The case of massive COVID-19 vaccine distribution, in Proceedings of the International Conference on Industrial Engineering and Operations Management, (2021), 912–921.
    [16] A. E. Mokrini. T. Aouam, A decision-support tool for policy makers in healthcare supply chains to balance between perceived risk in logistics outsourcing and cost-efficiency, Expert Syst. Appl., 201 (2022), 116999. https://doi.org/10.1016/j.eswa.2022.116999 doi: 10.1016/j.eswa.2022.116999
    [17] M. Falasca, S. Dellana, W. J. Rowe, J. F. Kros, The impact of counterfeit risk management on healthcare supply chain performance: an empirical analysis, Int. J. Prod. Perform. Manage., 71 (2022), 3078–3099. https://doi.org/10.1108/IJPPM-08-2020-0426 doi: 10.1108/IJPPM-08-2020-0426
    [18] D. Feyisa, A. Jemal, T. Aferu, F. Ejeta, A. Endeshaw, Evaluation of cold chain management performance for temperature-sensitive pharmaceuticals at public health facilities supplied by the jimma pharmaceuticals supply agency hub, southwest ethiopia: Pharmaceuticals logistic management perspective using a multicentered, mixed-method approach, Adv. Pharmacol. Pharm. Sci., 2021 (2021), 5167858. https://doi.org/10.1155/2021/5167858 doi: 10.1155/2021/5167858
    [19] D. J. Finkenstadt, R. Handfield, The influence of supply chain immunity perceptions on COVID-19 vaccine willingness in supply chain professionals, Int. J. Logist. Manage., 34 (2023), 84–105. https://doi.org/10.1108/IJLM-03-2022-0111 doi: 10.1108/IJLM-03-2022-0111
    [20] D. J. Finkenstadt, R. B. Handfield, Tuning value chains for better signals in the post-COVID era: vaccine supply chain concerns, Int. J. Oper. Prod. Manage., 41 (2021), 1302–1317. https://doi.org/10.1108/IJOPM-01-2021-0039 doi: 10.1108/IJOPM-01-2021-0039
    [21] D. Friday, D. A. Savage, S. A. Melnyk, N. Harrison, S. Ryan, H. Wechtler, A collaborative approach to maintaining optimal inventory and mitigating stockout risks during a pandemic: capabilities for enabling health-care supply chain resilience, J. Humanitarian Logist. Supply Chain Manage., 11 (2021), 248–271. https://doi.org/10.1108/JHLSCM-07-2020-0061 doi: 10.1108/JHLSCM-07-2020-0061
    [22] K. Gunaratne, A. Thibbotuwawa, A. E. Vasegaard, P. Nielsen, H. N. Perera, Unmanned aerial aehicle adaptation to facilitate healthcare supply chains in low-income countries, Drones, 6 (2022), 321. https://doi.org/10.3390/drones6110321 doi: 10.3390/drones6110321
    [23] A. Jain, D. S. Jat, Supply Chain Management Using Blockchain, IoT and Edge Computing Technology, Springer, Singapore, 2022. https://doi.org/10.1007/978-981-19-0240-6_6
    [24] R. Katoch, IoT research in supply chain management and logistics: A bibliometric analysis using vosviewer software, Mater. Today: Proc., 56 (2022), 2505–2515. https://doi.org/10.1016/j.matpr.2021.08.272 doi: 10.1016/j.matpr.2021.08.272
    [25] N. Koshta, Y. Devi, S. Patra, Aerial bots in the supply chain: A new ally to combat COVID-19, Technol. Soc., 66 (2021), 101646. https://doi.org/10.1016/j.techsoc.2021.101646 doi: 10.1016/j.techsoc.2021.101646
    [26] M. Kouhizadeh, S. Saberi, J. Sarkis, Blockchain technology and the sustainable supply chain: Theoretically exploring adoption barriers, Int. J. Prod. Econ., 231 (2021), 107831. https://doi.org/10.1016/j.ijpe.2020.107831 doi: 10.1016/j.ijpe.2020.107831
    [27] Y. Y. Lau, M. A. Dulebenets, H. T. Yip, Y. M. Tang, Healthcare supply chain management under COVID-19 Settings: The existing practices in Hong Kong and the United States, Healthcare, 10 (2022), 1549. https://doi.org/10.3390/healthcare10081549 doi: 10.3390/healthcare10081549
    [28] E. Lugada, H. Komakech, I. Ochola, S. Mwebaze, M. O. Oteba, D. O. Ladwar, Health supply chain system in Uganda: current issues, structure, performance, and implications for systems strengthening, J. Pharm. Policy Pract., 15 (2022), 14. https://doi.org/10.1186/s40545-022-00412-4 doi: 10.1186/s40545-022-00412-4
    [29] E. Lugada, I. Ochola, A. Kirunda, M. Sembatya, S. Mwebaze, M. Olowo, et al., Health supply chain system in uganda: Assessment of status and of performance of health facilities, J. Pharm. Policy Pract., 15 (2022), 58. https://doi.org/10.1186/s40545-022-00452-w doi: 10.1186/s40545-022-00452-w
    [30] S. Mazumder, A. Bhaumik, Blockchain: Transforming supply chain management amidst Covid-19, Int. J. Eng. Trends Technol., 70 (2022), 100–105. https://doi.org/10.14445/22315381/IJETT-V70I6P212 doi: 10.14445/22315381/IJETT-V70I6P212
    [31] H. Min, Assessing the impact of a COVID-19 pandemic on supply chain transformation: an exploratory analysis, Benchmarking: Int. J., 1 (2022). https://doi.org/10.1108/BIJ-04-2022-0260 doi: 10.1108/BIJ-04-2022-0260
    [32] L. I. O. Montilla, H. M. C. Carretero, Collaborative logistics in healthcare. A case study of the supply chain of medicines and medical devices for hospitals in Colombia, in Proceedings of the International Conference on Industrial Engineering and Operations Management, (2021), 348–349.
    [33] A. Nguyen, S. Lamouri, R. Pellerin, S. Tamayo, B. Lekens, Data analytics in pharmaceutical supply chains: state of the art, opportunities, and challenges, Int. J. Prod. Res., 66 (2022), 6888–6907. https://doi.org/10.1080/00207543.2021.1950937 doi: 10.1080/00207543.2021.1950937
    [34] J. Nsikan, E. A. Affiah, I. Briggs, N. Koko, Sustainable supplier selection factors and supply chain performance in the Nigerian healthcare industry, J. Transp. Supply Chain Manage., 16 (2022), 633. https://doi.org/10.4102/jtscm.v16i0.633 doi: 10.4102/jtscm.v16i0.633
    [35] W. Prosser, O. Folorunso, J. McCord, G. Roche, M. Tien, B. Hatch, et al., Redesigning immunization supply chains: Results from three country analyses, Vaccine, 39 (2021), 2246–2254. https://doi.org/10.1016/j.vaccine.2021.03.037 doi: 10.1016/j.vaccine.2021.03.037
    [36] S. Romdhani, I. Nouaouri, J. Tounsi, S. Gattoufi, H. Allaoui, Two-echelon inventory management for sustainable pharmaceutical supply chain through waste reduction, IFAC-PapersOnLine, 55 (2022), 1380–1385. https://doi.org/10.1016/j.ifacol.2022.09.583 doi: 10.1016/j.ifacol.2022.09.583
    [37] Y. Sabri, S. Harchi, N. E. Kamoun, Managing health supply chain using blockchain technology: State of art challenges and solution, Int. J. Reconfigurable Embedded Syst., 11 (2022), 258–264. https://doi.org/10.11591/ijres.v11.i3.pp258-264 doi: 10.11591/ijres.v11.i3.pp258-264
    [38] K. Z. Sholpanbaeva, A. A. Apysheva, N. K. Shaikhanova, A. K. Modenov, An integrated optimization model for medicine order distribution and delivery problem of online pharmacy based on the optimal supply chain strategy, Ind. Eng. Manage. Syst., 20 (2021), 555–562. https://doi.org/10.7232/iems.2021.20.4.555 doi: 10.7232/iems.2021.20.4.555
    [39] B. Skowron-Grabowska, M. Wincewicz-Bosy, M. Dymyt, A. Sadowski, T. Dymyt, K. Wąsowska, Healthcare supply chain reliability: The case of medical air transport, Int. J. Environ. Res. Public Health, 19 (2022), 4336. https://doi.org/10.3390/ijerph19074336 doi: 10.3390/ijerph19074336
    [40] S. Sriyanto, M. S. Lodhi, H. Salamun, S. Sardin, C. F. Pasani, G. Muneer, et al., The role of healthcare supply chain management in the wake of COVID-19 pandemic: Hot off the press, Foresight, 24 (2022), 429–444. https://doi.org/10.1108/FS-07-2021-0136 doi: 10.1108/FS-07-2021-0136
    [41] A. S. Suresh, M. Vasudevan, S. Vinod, Factors Influencing Association of Intermediaries in the Supply Chain of Consumer Healthcare Brands, J. Distrib. Sci., 19 (2021), 105–113. https://doi.org/10.15722/jds.19.1.202101.1.105 doi: 10.15722/jds.19.1.202101.1.105
    [42] M. L. Tseng, H. M. Ha, K. J. Wu, B. Xue, Healthcare industry circular supply chain collaboration in Vietnam: vision and learning influences on connection in a circular supply chain and circularity business model, Int. J. Logist. Res. Appl., 25 (2022), 743–768. https://doi.org/10.1080/13675567.2021.1923671 doi: 10.1080/13675567.2021.1923671
    [43] I. J. Umoren, U. E. Etuk, A. P. Ekong, K. C. Udonyah, Healthcare logistics optimization framework for efficient supply chain management in Niger Delta Region of Nigeria, Int. J. Adv. Comput. Sci. Appl., 12 (2021), 593–604. https://doi.org/10.14569/IJACSA.2021.0120475 doi: 10.14569/IJACSA.2021.0120475
    [44] A. Velayutham, A. R. Rahman, A. Narayan, M. Wang, Pandemic turned into pandemonium: the effect on supply chains and the role of accounting information, Account., Audit. Accoun. J., 34 (2021), 1404–1415. https://doi.org/10.1108/AAAJ-08-2020-4800 doi: 10.1108/AAAJ-08-2020-4800
    [45] Y. Yin, Y. Zeng, X. Chen, Y. Fan, The IoT in healthcare: An overview, J. Ind. Inf. Integr., 1 (2016), 3–13. https://doi.org/10.1016/j.jii.2016.03.004 doi: 10.1016/j.jii.2016.03.004
    [46] P. Singh, Z. Elmi, V. K. Meriga, J. Pasha, M. A. Dulebenets, IoT for sustainable railway transportation: Past, present, and future, Cleaner Logist. Supply Chain, 4 (2022), 100065. https://doi.org/10.1016/j.clscn.2022.100065 doi: 10.1016/j.clscn.2022.100065
    [47] P. Singh, Z. Elmi, Y. Lau, M. Borowska-Stefańska, S. Wiśniewski, M. A. Dulebenets, Blockchain and AI technology convergence: Applications in transportation systems, Veh. Commun., 38 (2022), 100521. https://doi.org/10.1016/j.vehcom.2022.100521 doi: 10.1016/j.vehcom.2022.100521
    [48] B. Dave, S. Kubler, K. Främling, L. Koskela, Opportunities for enhanced lean construction management using IoT standards, Autom. Constr., 61 (2016), 86–97. https://doi.org/10.1016/j.autcon.2015.10.009 doi: 10.1016/j.autcon.2015.10.009
    [49] H. Zhao, C. Zhang, An online-learning-based evolutionary many-objective algorithm, Inf. Sci., 509 (2020), 1–21. https://doi.org/10.1016/j.ins.2019.08.069 doi: 10.1016/j.ins.2019.08.069
    [50] M. A. Dulebenets, An Adaptive Polyploid Memetic Algorithm for scheduling trucks at a cross-docking terminal, Inf. Sci., 565 (2021), 390–421. https://doi.org/10.1016/j.ins.2021.02.039 doi: 10.1016/j.ins.2021.02.039
    [51] M. Kavoosi, M. A. Dulebenets, O. Abioye, J. Pasha, O. Theophilus, H. Wang, et al., Berth scheduling at marine container terminals: A universal island-based metaheuristic approach, Marit. Bus. Rev., 5 (2019), 30–66. https://doi.org/10.1108/MABR-08-2019-0032 doi: 10.1108/MABR-08-2019-0032
    [52] J. Pasha, A. L. Nwodu, A. M. Fathollahi-Fard, G. Tian, Z. Li, H. Wang, et al., Exact and metaheuristic algorithms for the vehicle routing problem with a factory-in-a-box in multi-objective settings, Adv. Eng. Inf., 52 (2022), 101623. https://doi.org/10.1016/j.aei.2022.101623 doi: 10.1016/j.aei.2022.101623
    [53] M. Kavoosi, M. A. Dulebenets, O. F. Abioye, J. Pasha, H. Wang, H. Chi, An augmented self-adaptive parameter control in evolutionary computation: A case study for the berth scheduling problem, Adv. Eng. Inf., 42 (2019), 100972. https://doi.org/10.1016/j.aei.2019.100972 doi: 10.1016/j.aei.2019.100972
    [54] M. Rabbani, N. Oladzad-Abbasabady, N. Akbarian-Saravi, Ambulance routing in disaster response considering variable patient condition: NSGA-Ⅱ and MOPSO algorithms, J. Ind. Manage. Optim., 18 (2022), 1035–1062. https://doi.org/10.3934/jimo.2021007 doi: 10.3934/jimo.2021007
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