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Impact of cloud-based information sharing on hospital supply chain performance: A system dynamics framework

Author

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  • Gonul Kochan, Cigdem
  • Nowicki, David R.
  • Sauser, Brian
  • Randall, Wesley S.

Abstract

The inadequacies of traditional information sharing are amplified in the healthcare sector. Poor demand and inventory visibility result in demand and supply mismatch of healthcare products in ways that may have dire economic and patient care consequences. For instance, a hospital drug shortage often requires an emergency delivery. These emergency refills increase cost and may disrupt a patient's recovery process. In recent years, innovations in information technology have been leveraged to improve supply chain collaboration and move closer to matching supply with demand. In this article, we build on that body of research by examining cloud computing as an enabler of electronic supply chain management systems (e-SCMs) that enhances collaborative information sharing in a multi-echelon hospital supply chain. We use systems theory and system dynamics to develop two conceptual, causal loop diagrams (CLDs); one representing traditional and the other cloud-based information sharing in a hospital supply chain. CLDs and their equivalent system dynamics models are used to simulate the performance of traditional and cloud-based hospital supply chains. We compare the performance metrics of both models: average inventory levels, lead time, and unfilled orders. The findings of this study show that cloud-based information sharing improves visibility in healthcare supply chains. As supply chain visibility increases, a hospital's responsiveness improves. Hospitals are now in a better position to accommodate fluctuations in patient demand and supply lead times. As a consequence, hospital supply chains will experience reductions in inventory costs, supply costs, and supply shortages.

Suggested Citation

  • Gonul Kochan, Cigdem & Nowicki, David R. & Sauser, Brian & Randall, Wesley S., 2018. "Impact of cloud-based information sharing on hospital supply chain performance: A system dynamics framework," International Journal of Production Economics, Elsevier, vol. 195(C), pages 168-185.
  • Handle: RePEc:eee:proeco:v:195:y:2018:i:c:p:168-185
    DOI: 10.1016/j.ijpe.2017.10.008
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    Cited by:

    1. Ye, Fei & Liu, Ke & Li, Lixu & Lai, Kee-Hung & Zhan, Yuanzhu & Kumar, Ajay, 2022. "Digital supply chain management in the COVID-19 crisis: An asset orchestration perspective," International Journal of Production Economics, Elsevier, vol. 245(C).
    2. Bag, Surajit & Dhamija, Pavitra & Singh, Rajesh Kumar & Rahman, Muhammad Sabbir & Sreedharan, V. Raja, 2023. "Big data analytics and artificial intelligence technologies based collaborative platform empowering absorptive capacity in health care supply chain: An empirical study," Journal of Business Research, Elsevier, vol. 154(C).
    3. A. V. Thomas & Biswajit Mahanty, 2021. "Dynamic assessment of control system designs of information shared supply chain network experiencing supplier disruption," Operational Research, Springer, vol. 21(1), pages 425-451, March.
    4. Zhang, Lu & Cui, Li & Chen, Lujie & Dai, Jing & Jin, Ziyi & Wu, Hao, 2023. "A hybrid approach to explore the critical criteria of online supply chain finance to improve supply chain performance," International Journal of Production Economics, Elsevier, vol. 255(C).
    5. Qing Zhang & Weiguo Fan & Jianchang Lu & Siqian Wu & Xuechao Wang, 2021. "Research on Dynamic Analysis and Mitigation Strategies of Supply Chains under Different Disruption Risks," Sustainability, MDPI, vol. 13(5), pages 1-29, February.
    6. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    7. Javad Gerami & Reza Kiani Mavi & Reza Farzipoor Saen & Neda Kiani Mavi, 2023. "A novel network DEA-R model for evaluating hospital services supply chain performance," Annals of Operations Research, Springer, vol. 324(1), pages 1041-1066, May.
    8. Golrizgashti, Seyedehfatemeh & Hosseini, SeyedHossein & Zhu, Qingyun & Sarkis, Joseph, 2023. "Evaluating supply chain dynamics in the presence of product deletion," International Journal of Production Economics, Elsevier, vol. 255(C).
    9. Orji, Ifeyinwa Juliet & Liu, Shaoxuan, 2020. "A dynamic perspective on the key drivers of innovation-led lean approaches to achieve sustainability in manufacturing supply chain," International Journal of Production Economics, Elsevier, vol. 219(C), pages 480-496.
    10. Ali, Omar & Shrestha, Anup & Soar, Jeffrey & Wamba, Samuel Fosso, 2018. "Cloud computing-enabled healthcare opportunities, issues, and applications: A systematic review," International Journal of Information Management, Elsevier, vol. 43(C), pages 146-158.
    11. Furstenau, Leonardo Bertolin & Zani, Carolina & Terra, Stela Xavier & Sott, Michele Kremer & Choo, Kim-Kwang Raymond & Saurin, Tarcisio Abreu, 2022. "Resilience capabilities of healthcare supply chain and supportive digital technologies," Technology in Society, Elsevier, vol. 71(C).
    12. Pai, Dinesh R. & Rajan, Balaraman & Chakraborty, Subhajit, 2022. "Do EHR and HIE deliver on their promise? Analysis of Pennsylvania acute care hospitals," International Journal of Production Economics, Elsevier, vol. 245(C).
    13. Kim E. Van Oorschot & Luk N. Van Wassenhove & Marianne Jahre, 2023. "Collaboration–competition dilemma in flattening the COVID‐19 curve," Production and Operations Management, Production and Operations Management Society, vol. 32(5), pages 1345-1361, May.
    14. Fei Jiang & Filzah Md Isa & Sin Pei Ng & Mariam Bhatti, 2023. "The Impact of Supply Chain Integration to Supply Chain Responsiveness in Chinese Electronics Manufacturing Companies," SAGE Open, , vol. 13(4), pages 21582440231, December.
    15. Doetzer, Mathias, 2020. "The role of national culture on supply chain visibility: Lessons from Germany, Japan, and the USA," International Journal of Production Economics, Elsevier, vol. 230(C).
    16. Hill, Craig A. & Zhang, G. Peter & Miller, Keith E., 2018. "Collaborative planning, forecasting, and replenishment & firm performance: An empirical evaluation," International Journal of Production Economics, Elsevier, vol. 196(C), pages 12-23.
    17. Imran Ali & Devika Kannan, 2022. "Mapping research on healthcare operations and supply chain management: a topic modelling-based literature review," Annals of Operations Research, Springer, vol. 315(1), pages 29-55, August.
    18. In, Joonhwan & Bradley, Randy V. & Bichescu, Bogdan C. & Smith, Antoinette L., 2019. "Breaking the chain: GPO changes and hospital supply cost efficiency," International Journal of Production Economics, Elsevier, vol. 218(C), pages 297-307.
    19. Ortiz-Barrios, Miguel & Arias-Fonseca, Sebastián & Ishizaka, Alessio & Barbati, Maria & Avendaño-Collante, Betty & Navarro-Jiménez, Eduardo, 2023. "Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: A case study," Journal of Business Research, Elsevier, vol. 160(C).
    20. Iman Ghasemian Sahebi & Seyed Pendar Toufighi & Gencay Karakaya & Shahryar Ghorbani, 2022. "An intuitive fuzzy approach for evaluating financial resiliency of supply chain," OPSEARCH, Springer;Operational Research Society of India, vol. 59(2), pages 460-481, June.
    21. Li, Ying & Dai, Jing & Cui, Li, 2020. "The impact of digital technologies on economic and environmental performance in the context of industry 4.0: A moderated mediation model," International Journal of Production Economics, Elsevier, vol. 229(C).
    22. Liu, Sen & Chan, Felix T.S. & Yang, Junai & Niu, Ben, 2018. "Understanding the effect of cloud computing on organizational agility: An empirical examination," International Journal of Information Management, Elsevier, vol. 43(C), pages 98-111.
    23. K. Katsaliaki & P. Galetsi & S. Kumar, 2022. "Supply chain disruptions and resilience: a major review and future research agenda," Annals of Operations Research, Springer, vol. 319(1), pages 965-1002, December.

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