{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T21:18:34Z","timestamp":1776374314123,"version":"3.51.2"},"publisher-location":"Cham","reference-count":79,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032061638","type":"print"},{"value":"9783032061645","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,28]],"date-time":"2025-09-28T00:00:00Z","timestamp":1759017600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,28]],"date-time":"2025-09-28T00:00:00Z","timestamp":1759017600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-06164-5_30","type":"book-chapter","created":{"date-parts":[[2025,9,27]],"date-time":"2025-09-27T05:16:25Z","timestamp":1758950185000},"page":"425-438","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["The Role of Data-Driven Supply Chain Systems in Healthcare\u2013Systematic Review"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3634-4660","authenticated-orcid":false,"given":"George","family":"Maramba","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7120-7787","authenticated-orcid":false,"given":"Hanlie","family":"Smuts","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,28]]},"reference":[{"key":"30_CR1","doi-asserted-by":"publisher","first-page":"43","DOI":"10.4324\/9780429461897-3","volume-title":"The anthropology of epidemics","author":"C Caduff","year":"2019","unstructured":"Caduff, C.: Great anticipations. In: The anthropology of epidemics, pp. 43\u201358. Routledge (2019)"},{"issue":"5","key":"30_CR2","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1177\/0967010614530072","volume":"45","author":"S Elbe","year":"2014","unstructured":"Elbe, S., Roemer-Mahler, A., Long, C.: Securing circulation pharmaceutically: antiviral stockpiling and pandemic preparedness in the European union. Secur. Dialogue 45(5), 440\u2013457 (2014)","journal-title":"Secur. Dialogue"},{"issue":"1","key":"30_CR3","doi-asserted-by":"publisher","first-page":"1341225","DOI":"10.1080\/16549716.2017.1341225","volume":"10","author":"EZ Sambala","year":"2017","unstructured":"Sambala, E.Z., Manderson, L.: Anticipation and response: pandemic influenza in Malawi, 2009. Glob. Health Action 10(1), 1341225 (2017)","journal-title":"Glob. Health Action"},{"key":"30_CR4","doi-asserted-by":"crossref","unstructured":"Kelly, A.H., Keck, F., Lynteris, C.: The anthropology of epidemics. Taylor & Francis (2019)","DOI":"10.4324\/9780429461897"},{"key":"30_CR5","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1007\/s40592-015-0038-7","volume":"33","author":"MJ Smith","year":"2015","unstructured":"Smith, M.J., Silva, D.S.: Ethics for pandemics beyond influenza: ebola, drug-resistant tuberculosis, and anticipating future ethical challenges in pandemic preparedness and response. Monash Bioeth. Rev. 33, 130\u2013147 (2015)","journal-title":"Monash Bioeth. Rev."},{"issue":"4","key":"30_CR6","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1007\/s10654-020-00634-3","volume":"35","author":"EA Harrison","year":"2020","unstructured":"Harrison, E.A., Wu, J.W.: Vaccine confidence in the time of COVID-19. Eur. J. Epidemiol. 35(4), 325\u2013330 (2020)","journal-title":"Eur. J. Epidemiol."},{"key":"30_CR7","unstructured":"Park, C.-Y., Kim, K., Roth, S.: Global shortage of personal protective equipment amid COVID-19: supply chains, bottlenecks, and policy implications. Asian Dev. Bank (2020)"},{"key":"30_CR8","doi-asserted-by":"crossref","unstructured":"Lopes de Sousa, A.B., et al.: Sustainability of supply chains in the wake of the coronavirus (COVID-19\/SARS-CoV-2) pandemic: lessons and trends. Mod. Supply Chain Res. Appl. 2(3), 117\u2013122 (2020)","DOI":"10.1108\/MSCRA-05-2020-0011"},{"key":"30_CR9","unstructured":"Ling, X., et al.: A data-driven network model for the emerging COVID-19 epidemics in Wuhan, Toronto and Italy. Math. Biosci. (2020)"},{"key":"30_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.healthplace.2022.102867","volume":"77","author":"F Li","year":"2022","unstructured":"Li, F.: Disconnected in a pandemic: COVID-19 outcomes and the digital divide in the United States. Health Place 77, 102867 (2022)","journal-title":"Health Place"},{"issue":"3","key":"30_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.14488\/BJOPM.2020.033","volume":"17","author":"CAS Pinto","year":"2020","unstructured":"Pinto, C.A.S.: Knowledge management as a support for supply chain logistics planning in pandemic cases. Braz. J. Oper. Prod. Manage. 17(3), 1\u201311 (2020)","journal-title":"Braz. J. Oper. Prod. Manage."},{"key":"30_CR12","unstructured":"Harris, J.: Confronting legacies and charting a new course? The politics of coronavirus response in South Africa. Coronavirus Politics: The Comparative Politics and Policy of COVID-19, pp. 580\u2013599 (2021)"},{"key":"30_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2020.138532","volume":"725","author":"NJ Rowan","year":"2020","unstructured":"Rowan, N.J., Laffey, J.G.: Challenges and solutions for addressing critical shortage of supply chain for personal and protective equipment (PPE) arising from Coronavirus disease (COVID19) pandemic\u2013Case study from the republic of Ireland. Sci. Total Environ. 725, 138532 (2020)","journal-title":"Sci. Total Environ."},{"issue":"1","key":"30_CR14","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1017\/S1049023X00007718","volume":"25","author":"RM Zoraster","year":"2010","unstructured":"Zoraster, R.M.: Vulnerable populations: Hurricane Katrina as a case study. Prehosp. Disaster Med. 25(1), 74\u201378 (2010)","journal-title":"Prehosp. Disaster Med."},{"issue":"4","key":"30_CR15","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1007\/s40664-014-0041-5","volume":"64","author":"M Bundschuh","year":"2014","unstructured":"Bundschuh, M., Gerber, A.: Zentralblatt f\u00fcr Arbeitsmedizin, Arbeitsschutz und Ergonomie 64(4), 279\u2013280 (2014). https:\/\/doi.org\/10.1007\/s40664-014-0041-5","journal-title":"Zentralblatt f\u00fcr Arbeitsmedizin, Arbeitsschutz und Ergonomie"},{"issue":"14","key":"30_CR16","doi-asserted-by":"publisher","first-page":"5858","DOI":"10.3390\/su12145858","volume":"12","author":"G Zhu","year":"2020","unstructured":"Zhu, G., Chou, M.C., Tsai, C.W.: Lessons learned from the COVID-19 pandemic exposing the shortcomings of current supply chain operations: a long-term prescriptive offering. Sustainability 12(14), 5858 (2020)","journal-title":"Sustainability"},{"key":"30_CR17","doi-asserted-by":"crossref","unstructured":"Tosh, P.K., et al.: Medical supply shortages\u2014we are part of the problem\u2026 and solution. In: Mayo Clinic Proceedings. Elsevier (2023)","DOI":"10.1016\/j.mayocp.2023.09.008"},{"key":"30_CR18","doi-asserted-by":"crossref","unstructured":"Mahalle, P.N., et al.: Data analytics: Covid-19 prediction using multimodal data. Intell. Syst. Methods Combat Covid-19 pp. 1\u201310( 2020)","DOI":"10.1007\/978-981-15-6572-4_1"},{"issue":"1","key":"30_CR19","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.ejor.2020.08.001","volume":"290","author":"K Nikolopoulos","year":"2021","unstructured":"Nikolopoulos, K., et al.: Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions. Eur. J. Oper. Res. 290(1), 99\u2013115 (2021)","journal-title":"Eur. J. Oper. Res."},{"key":"30_CR20","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1016\/j.ijid.2021.08.029","volume":"111","author":"C Selinger","year":"2021","unstructured":"Selinger, C., Choisy, M., Alizon, S.: Predicting COVID-19 incidence in French hospitals using human contact network analytics. Int. J. Infect. Dis. 111, 100\u2013107 (2021)","journal-title":"Int. J. Infect. Dis."},{"key":"30_CR21","doi-asserted-by":"crossref","unstructured":"Sriyanto, S., et al.: The role of healthcare supply chain management in the wake of COVID-19 pandemic: hot off the press. Foresight (2021)","DOI":"10.1108\/FS-07-2021-0136"},{"key":"30_CR22","doi-asserted-by":"crossref","unstructured":"Wang, R., et al.: Data analytics for the COVID-19 epidemic. In: 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE (2020)","DOI":"10.1109\/COMPSAC48688.2020.00-83"},{"issue":"11\u201312","key":"30_CR23","doi-asserted-by":"publisher","first-page":"906","DOI":"10.1080\/09537287.2017.1336788","volume":"28","author":"R Chavez","year":"2017","unstructured":"Chavez, R., et al.: Data-driven supply chains, manufacturing capability and customer satisfaction. Prod. Plann. Control 28(11\u201312), 906\u2013918 (2017)","journal-title":"Prod. Plann. Control"},{"issue":"1","key":"30_CR24","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1089\/big.2013.1508","volume":"1","author":"F Provost","year":"2013","unstructured":"Provost, F., Fawcett, T.: Data science and its relationship to big data and data-driven decision making. Big Data 1(1), 51\u201359 (2013)","journal-title":"Big Data"},{"issue":"1","key":"30_CR25","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1080\/00207543.2019.1630770","volume":"58","author":"SS Kamble","year":"2020","unstructured":"Kamble, S.S., Gunasekaran, A.: Big data-driven supply chain performance measurement system: a review and framework for implementation. Int. J. Prod. Res. 58(1), 65\u201386 (2020)","journal-title":"Int. J. Prod. Res."},{"key":"30_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2023.106511","volume":"124","author":"S Nayeri","year":"2023","unstructured":"Nayeri, S., et al.: A data-driven model for sustainable and resilient supplier selection and order allocation problem in a responsive supply chain: a case study of healthcare system. Eng. Appl. Artif. Intell. 124, 106511 (2023)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"4","key":"30_CR27","doi-asserted-by":"publisher","first-page":"1164","DOI":"10.1111\/1467-8551.12441","volume":"32","author":"J Sheng","year":"2020","unstructured":"Sheng, J., et al.: COVID-19 pandemic in the new Era of big data analytics: methodological innovations and future research directions. Br. J. Manag. 32(4), 1164\u20131183 (2020)","journal-title":"Br. J. Manag."},{"issue":"8","key":"30_CR28","doi-asserted-by":"publisher","first-page":"2416","DOI":"10.1080\/00207543.2021.1884310","volume":"61","author":"M Sodhi","year":"2021","unstructured":"Sodhi, M., Tang, C., Willenson, E.: Research opportunities in preparing supply chains of essential goods for future pandemics. Int. J. Prod. Res. 61(8), 2416\u20132431 (2021)","journal-title":"Int. J. Prod. Res."},{"issue":"4","key":"30_CR29","doi-asserted-by":"publisher","first-page":"1473","DOI":"10.1007\/s11845-021-02730-z","volume":"191","author":"SVG Subrahmanya","year":"2022","unstructured":"Subrahmanya, S.V.G., et al.: The role of data science in healthcare advancements: applications, benefits, and future prospects. Irish J. Med. Sci. 191(4), 1473\u20131483 (2022)","journal-title":"Irish J. Med. Sci."},{"issue":"1","key":"30_CR30","first-page":"1","volume":"17","author":"G Maramba","year":"2024","unstructured":"Maramba, G., et al.: Healthcare supply chain efficacy as a mechanism to contain pandemic flare-ups: a South Africa case study. Int. J. Inf. Syst. Supply Chain Manage. (IJISSCM) 17(1), 1\u201324 (2024)","journal-title":"Int. J. Inf. Syst. Supply Chain Manage. (IJISSCM)"},{"issue":"11","key":"30_CR31","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2020-040547","volume":"10","author":"A Kirubarajan","year":"2020","unstructured":"Kirubarajan, A., et al.: Mask shortage during epidemics and pandemics: a scoping review of interventions to overcome limited supply. BMJ Open 10(11), e040547 (2020)","journal-title":"BMJ Open"},{"key":"30_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12910-021-00596-5","volume":"22","author":"R Naidoo","year":"2021","unstructured":"Naidoo, R., Naidoo, K.: Prioritising \u2018already-scarce\u2019intensive care unit resources in the midst of COVID-19: a call for regional triage committees in South Africa. BMC Med. Ethics 22, 1\u20139 (2021)","journal-title":"BMC Med. Ethics"},{"key":"30_CR33","doi-asserted-by":"crossref","unstructured":"McEntire, D.A.: The Distributed Functions of Emergency Management and Homeland Security: An Assessment of Professions Involved in Response to Disasters and Terrorist Attacks. CRC Press (2023)","DOI":"10.4324\/9781003350729"},{"key":"30_CR34","unstructured":"McEntire, D.A.: Disaster response and recovery: strategies and tactics for resilience. John Wiley & Sons (2021)"},{"issue":"3","key":"30_CR35","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1016\/j.bpa.2020.11.007","volume":"35","author":"CN Okeagu","year":"2021","unstructured":"Okeagu, C.N., et al.: Principles of supply chain management in the time of crisis. Best Pract. Res. Clin. Anaesthesiol. 35(3), 369\u2013376 (2021)","journal-title":"Best Pract. Res. Clin. Anaesthesiol."},{"key":"30_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijdrr.2024.104303","volume":"102","author":"X Wu","year":"2024","unstructured":"Wu, X., et al.: How to avoid source disruption of emergency supplies in emergency supply chains: a subsidy perspective. Int. J. Disaster Risk Reduction 102, 104303 (2024)","journal-title":"Int. J. Disaster Risk Reduction"},{"issue":"7","key":"30_CR37","doi-asserted-by":"publisher","first-page":"2282","DOI":"10.3390\/s21072282","volume":"21","author":"SJ Alsunaidi","year":"2021","unstructured":"Alsunaidi, S.J., et al.: Applications of big data analytics to control COVID-19 pandemic. Sensors 21(7), 2282 (2021)","journal-title":"Sensors"},{"issue":"2","key":"30_CR38","doi-asserted-by":"publisher","first-page":"1077","DOI":"10.1007\/s10479-022-05157-6","volume":"333","author":"S Benzidia","year":"2024","unstructured":"Benzidia, S., et al.: Big data analytics capability in healthcare operations and supply chain management: the role of green process innovation. Ann. Oper. Res. 333(2), 1077\u20131101 (2024)","journal-title":"Ann. Oper. Res."},{"issue":"15","key":"30_CR39","doi-asserted-by":"publisher","first-page":"5330","DOI":"10.3390\/ijerph17155330","volume":"17","author":"IE Agbehadji","year":"2020","unstructured":"Agbehadji, I.E., et al.: Review of big data analytics, artificial intelligence and nature-inspired computing models towards accurate detection of COVID-19 pandemic cases and contact tracing. Int. J. Environ. Res. Public Health 17(15), 5330 (2020)","journal-title":"Int. J. Environ. Res. Public Health"},{"issue":"4","key":"30_CR40","doi-asserted-by":"publisher","first-page":"468","DOI":"10.1080\/14778238.2020.1860665","volume":"19","author":"WT Wang","year":"2021","unstructured":"Wang, W.T., Wu, S.Y.: Knowledge management based on information technology in response to COVID-19 crisis. Knowl. Manag. Res. Pract. 19(4), 468\u2013474 (2021)","journal-title":"Knowl. Manag. Res. Pract."},{"key":"30_CR41","doi-asserted-by":"publisher","first-page":"5541","DOI":"10.3390\/su15065541","volume":"15","author":"B Christos","year":"2023","unstructured":"Christos, B., et al.: A holistic view on the adoption and cost-effectiveness of technology-driven supply chain management practices in healthcare. Sustainability 15, 5541 (2023). https:\/\/doi.org\/10.3390\/su15065541","journal-title":"Sustainability"},{"issue":"1","key":"30_CR42","doi-asserted-by":"publisher","first-page":"1159","DOI":"10.1007\/s10479-020-03685-7","volume":"319","author":"M Queiroz","year":"2022","unstructured":"Queiroz, M., et al.: Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review. Ann. Oper. Res. 319(1), 1159\u20131196 (2022)","journal-title":"Ann. Oper. Res."},{"issue":"4","key":"30_CR43","first-page":"136","volume":"39","author":"AM Nyoni","year":"2022","unstructured":"Nyoni, A.M., Kaushal, S.: Sustainable knowledge management during crisis: focus on Covid-19 pandemic. Bus. Inf. Rev. 39(4), 136\u2013146 (2022)","journal-title":"Bus. Inf. Rev."},{"issue":"2","key":"30_CR44","doi-asserted-by":"publisher","first-page":"71","DOI":"10.3390\/a15020071","volume":"15","author":"H Abdel-Jaber","year":"2022","unstructured":"Abdel-Jaber, H., et al.: A review of deep learning algorithms and their applications in healthcare. Algorithms 15(2), 71 (2022)","journal-title":"Algorithms"},{"issue":"6","key":"30_CR45","doi-asserted-by":"publisher","first-page":"1236","DOI":"10.1093\/bib\/bbx044","volume":"19","author":"R Miotto","year":"2018","unstructured":"Miotto, R., et al.: Deep learning for healthcare: review, opportunities and challenges. Brief. Bioinform. 19(6), 1236\u20131246 (2018)","journal-title":"Brief. Bioinform."},{"key":"30_CR46","doi-asserted-by":"crossref","unstructured":"Bvuchete, M., Grobbelaar, S., Van Eeden, J.: A case of healthcare supply chain visibility in South Africa. In: 2018 3rd Biennial South African Biomedical Engineering Conference (SAIBMEC). IEEE (2018)","DOI":"10.1109\/SAIBMEC.2018.8363179"},{"issue":"12","key":"30_CR47","doi-asserted-by":"publisher","first-page":"9158","DOI":"10.3390\/su15129158","volume":"15","author":"G Maramba","year":"2023","unstructured":"Maramba, G., et al.: KMS as a sustainability strategy during a pandemic. Sustainability 15(12), 9158 (2023)","journal-title":"Sustainability"},{"key":"30_CR48","doi-asserted-by":"crossref","unstructured":"Kiger, M.E., Varpio, L.: Thematic analysis of qualitative data: AMEE guide no. 131. Med. Teach. 42(8), 846\u2013854 (2020)","DOI":"10.1080\/0142159X.2020.1755030"},{"issue":"6","key":"30_CR49","doi-asserted-by":"publisher","first-page":"807","DOI":"10.1016\/j.cptl.2018.03.019","volume":"10","author":"A Castleberry","year":"2018","unstructured":"Castleberry, A., Nolen, A.: Thematic analysis of qualitative research data: is it as easy as it sounds? Curr. Pharm. Teach. Learn. 10(6), 807\u2013815 (2018)","journal-title":"Curr. Pharm. Teach. Learn."},{"key":"30_CR50","doi-asserted-by":"publisher","DOI":"10.1016\/j.techfore.2020.120557","volume":"165","author":"S Benzidia","year":"2021","unstructured":"Benzidia, S., Makaoui, N., Bentahar, O.: The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance. Technol. Forecast. Soc. Chang. 165, 120557 (2021)","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"30_CR51","unstructured":"Arafatur, R., et al.: Data-driven dynamic clustering framework for mitigating the adverse economic impact of Covid-19 lockdown practices. Sustain. Cities Soc. (2020)"},{"key":"30_CR52","unstructured":"Sanders, N.R.: Big data driven supply chain management: a framework for implementing analytics and turning information into intelligence. Pearson Education (2014)"},{"key":"30_CR53","doi-asserted-by":"publisher","DOI":"10.3389\/fpubh.2020.562882","volume":"8","author":"S Bhaskar","year":"2020","unstructured":"Bhaskar, S., et al.: At the epicenter of COVID-19-The tragic failure of the global supply chain for medical supplies. Front. Public Health 8, 562882 (2020)","journal-title":"Front. Public Health"},{"key":"30_CR54","unstructured":"Guiyang, Z., Mabel, C., Christina, T.: Lessons learned from the COVID-19 Pandemic exposing the shortcomings of current supply chain operations: a long-term prescriptive offering. Sustainability (2020)"},{"key":"30_CR55","doi-asserted-by":"crossref","unstructured":"Xu, S., Tan, K.H.: Data-driven inventory management in the healthcare supply chain. In: Supply Chain and Logistics Management: Concepts, Methodologies, Tools, and Applications. IGI Global. pp. 1390\u20131403 (2020)","DOI":"10.4018\/978-1-7998-0945-6.ch067"},{"key":"30_CR56","doi-asserted-by":"publisher","DOI":"10.1016\/j.tre.2020.102067","volume":"142","author":"P Dutta","year":"2020","unstructured":"Dutta, P., et al.: Blockchain technology in supply chain operations: applications, challenges and research opportunities. Transp. Res. Part E Logistics Transp. Rev. 142, 102067 (2020)","journal-title":"Transp. Res. Part E Logistics Transp. Rev."},{"issue":"2","key":"30_CR57","first-page":"49","volume":"14","author":"R Jayaraman","year":"2019","unstructured":"Jayaraman, R., Salah, K., King, N.: Improving opportunities in healthcare supply chain processes via the internet of things and blockchain technology. Int. J. Healthc. Inf. Syst. Informatics (IJHISI) 14(2), 49\u201365 (2019)","journal-title":"Int. J. Healthc. Inf. Syst. Informatics (IJHISI)"},{"key":"30_CR58","unstructured":"Amico, A.: Modeling the dynamics of distribution networks: a data-driven approach to supply chains. ETH Zurich (2023)"},{"issue":"13","key":"30_CR59","doi-asserted-by":"publisher","first-page":"3748","DOI":"10.3390\/su11133748","volume":"11","author":"R Moro Visconti","year":"2019","unstructured":"Moro Visconti, R., Morea, D.: Big data for the sustainability of healthcare project financing. Sustainability 11(13), 3748 (2019)","journal-title":"Sustainability"},{"key":"30_CR60","doi-asserted-by":"publisher","DOI":"10.1016\/j.bdr.2021.100190","volume":"25","author":"I Ahmed","year":"2021","unstructured":"Ahmed, I., et al.: A framework for pandemic prediction using big data analytics. Big Data Research 25, 100190 (2021)","journal-title":"Big Data Research"},{"issue":"3","key":"30_CR61","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1097\/01.NURSE.0000806160.64587.92","volume":"52","author":"H Annolino","year":"2022","unstructured":"Annolino, H.: Leveraging predictive analytics to reduce influenza and COVID-19-related adverse events. Nursing 52(3), 35 (2022)","journal-title":"Nursing"},{"issue":"2","key":"30_CR62","first-page":"937","volume":"15","author":"I Hasan","year":"2023","unstructured":"Hasan, I., et al.: Data analytics and knowledge management approach for COVID-19 prediction and control. Int. J. Inf. Technol. 15(2), 937\u2013954 (2023)","journal-title":"Int. J. Inf. Technol."},{"key":"30_CR63","doi-asserted-by":"crossref","unstructured":"Hassan, S., et al.: Big data and predictive analytics in healthcare in Bangladesh: regulatory challenges. Heliyon (2021)","DOI":"10.1016\/j.heliyon.2021.e07179"},{"key":"30_CR64","doi-asserted-by":"publisher","DOI":"10.1016\/j.tre.2020.101967","volume":"138","author":"K Govindan","year":"2020","unstructured":"Govindan, K., Mina, H., Alavi, B.: A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: a case study of Coronavirus Disease 2019 (COVID-19). Trans. Res. Part E Logistics Trans. Rev. 138, 101967 (2020)","journal-title":"Trans. Res. Part E Logistics Trans. Rev."},{"key":"30_CR65","unstructured":"Konstantinos, N., et al.: Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions. Eur. J. Oper. Res. (2021)"},{"key":"30_CR66","doi-asserted-by":"crossref","unstructured":"Alotaibi, S., Mehmood, R.: Big data enabled healthcare supply chain management: opportunities and challenges. In: Smart Societies, Infrastructure, Technologies and Applications: First International Conference, SCITA 2017, Jeddah, Saudi Arabia, November 27\u201329, 2017, Proceedings 1. Springer (2018)","DOI":"10.1007\/978-3-319-94180-6_21"},{"key":"30_CR67","doi-asserted-by":"publisher","first-page":"1089","DOI":"10.1016\/j.procir.2019.03.258","volume":"81","author":"Q Li","year":"2019","unstructured":"Li, Q., Liu, A.: Big data driven supply chain management. Procedia CIRP 81, 1089\u20131094 (2019)","journal-title":"Procedia CIRP"},{"key":"30_CR68","doi-asserted-by":"publisher","DOI":"10.1016\/j.techfore.2020.120417","volume":"163","author":"W Yu","year":"2021","unstructured":"Yu, W., et al.: Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: an organizational information processing theory perspective. Technol. Forecast. Soc. Chang. 163, 120417 (2021)","journal-title":"Technol. Forecast. Soc. Chang."},{"issue":"6","key":"30_CR69","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.3390\/app9061207","volume":"9","author":"B Shen","year":"2019","unstructured":"Shen, B., Guo, J., Yang, Y.: MedChain: efficient healthcare data sharing via blockchain. Appl. Sci. 9(6), 1207 (2019)","journal-title":"Appl. Sci."},{"key":"30_CR70","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2019.104040","volume":"134","author":"A Hasselgren","year":"2020","unstructured":"Hasselgren, A., et al.: Blockchain in healthcare and health sciences\u2014A scoping review. Int. J. Med. Informatics 134, 104040 (2020)","journal-title":"Int. J. Med. Informatics"},{"issue":"5","key":"30_CR71","doi-asserted-by":"publisher","first-page":"505","DOI":"10.3390\/electronics8050505","volume":"8","author":"F Jamil","year":"2019","unstructured":"Jamil, F., et al.: A novel medical blockchain model for drug supply chain integrity management in a smart hospital. Electronics 8(5), 505 (2019)","journal-title":"Electronics"},{"key":"30_CR72","doi-asserted-by":"publisher","DOI":"10.1016\/j.meegid.2021.104834","volume":"92","author":"D Chaturvedi","year":"2021","unstructured":"Chaturvedi, D., Chakravarty, U.: Predictive analysis of COVID-19 eradication with vaccination in India, Brazil, and USA. Infect. Genet. Evol. 92, 104834 (2021)","journal-title":"Infect. Genet. Evol."},{"key":"30_CR73","first-page":"1","volume-title":"Handbook of data science approaches for biomedical engineering","author":"S Mishra","year":"2020","unstructured":"Mishra, S., et al.: Analysis of the role and scope of big data analytics with IoT in health care domain. In: Handbook of data science approaches for biomedical engineering, pp. 1\u201323. Elsevier (2020)"},{"key":"30_CR74","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1007\/978-3-031-82810-2_5","volume-title":"Artificial Intelligence-Enabled Security for Healthcare Systems: Safeguarding Patient Data and Improving Services","author":"S Gupta","year":"2025","unstructured":"Gupta, S., Kapoor, M., Debnath, S.K.: AI and healthcare analytics. In: Artificial Intelligence-Enabled Security for Healthcare Systems: Safeguarding Patient Data and Improving Services, pp. 87\u2013100. Springer (2025)"},{"key":"30_CR75","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2021.108405","volume":"245","author":"M Queiroz","year":"2022","unstructured":"Queiroz, M., et al.: Supply chain resilience in the UK during the coronavirus pandemic: a resource orchestration perspective. Int. J. Prod. Econ. 245, 108405 (2022)","journal-title":"Int. J. Prod. Econ."},{"issue":"8","key":"30_CR76","doi-asserted-by":"publisher","first-page":"2124","DOI":"10.1108\/MD-06-2018-0669","volume":"57","author":"M Khan","year":"2019","unstructured":"Khan, M.: Challenges with big data analytics in service supply chains in the UAE. Manag. Decis. 57(8), 2124\u20132147 (2019)","journal-title":"Manag. Decis."},{"issue":"1","key":"30_CR77","first-page":"4","volume":"12","author":"G Maramba","year":"2020","unstructured":"Maramba, G., Coleman, A., Ntawanga, F.: Causes of challenges in implementing computer-based knowledge management systems in healthcare institutions: a case study of private hospitals in Johannesburg, South Africa. Afr. J. Inf. Syst. 12(1), 4 (2020)","journal-title":"Afr. J. Inf. Syst."},{"issue":"4","key":"30_CR78","doi-asserted-by":"publisher","first-page":"81","DOI":"10.4018\/IJKM.2020100105","volume":"16","author":"G Maramba","year":"2020","unstructured":"Maramba, G., Smuts, H.: Guidelines for selecting appropriate knowledge management system implementation frameworks. Int. J. Knowl. Manage. (IJKM) 16(4), 81\u2013108 (2020)","journal-title":"Int. J. Knowl. Manage. (IJKM)"},{"key":"30_CR79","doi-asserted-by":"publisher","DOI":"10.1017\/dsj.2020.25","volume":"6","author":"M Cantamessa","year":"2020","unstructured":"Cantamessa, M., et al.: Data-driven design: the new challenges of digitalization on product design and development. Des. Sci. 6, e27 (2020)","journal-title":"Des. Sci."}],"container-title":["Lecture Notes in Computer Science","Pervasive Digital Services for People\u2019s Well-Being, Inclusion and Sustainable Development"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-06164-5_30","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,27]],"date-time":"2025-09-27T06:02:52Z","timestamp":1758952972000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-06164-5_30"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,28]]},"ISBN":["9783032061638","9783032061645"],"references-count":79,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-06164-5_30","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,28]]},"assertion":[{"value":"28 September 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"I3E","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Conference on e-Business, e-Services and e-Society","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Limassol","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cyprus","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"i3e2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cyprusconferences.org\/i3e2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}