Skip to main content

Advertisement

SpringerLink
Log in

Healthcare Supply Chain Simulation with Disruption Considerations: A Case Study from Northern Italy

  • Invited paper
  • Published:
Global Journal of Flexible Systems Management Aims and scope Submit manuscript

Abstract

Healthcare supply chains (HSCs) have often been considered different from the usual supply chains (SCs) due to their high level of complexity, the presence of high-valuable medical materials and, finally, the fact that they deal with human lives. Furthermore, HSCs are not excluded from the increasing competitivity that is typical of the modern environment: International Healthcare systems are under increasing pressure to reduce waste and eliminate unnecessary costs while improving the quality and consistency of the care they provide to patient. The aim of this work is to analyse the impact of severe disruptions on SC performance in a Healthcare Supply Chain. More specifically, the objective of this study is to develop an approach to firstly analyse the effects of disruptions in terms of financial and operational performances, and successively to test different proactive and reactive mitigation strategies with the aim to maintain the highest service level, closed to 100%, in order to avoid shortages in hospitals’ wards. Disruptions can have a crucial impact on HSCs, because human lives can possibly be at the stake. Considering that the occurrence of disastrous events has been increasing in the last years, it is becoming inevitable to consider this risk in designing and planning HSCs that are more flexible and resilient. This work demonstrates that for long-lasting disruption, activating a backup supplier represents the most efficient mitigation strategy; on the other hand, for small-scale and short-duration disruptions, lateral transshipment represents a good way to mitigate the negative impacts of disruptions against a little increase in costs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

(Adapted from Azzi et al. 2013)

Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  • Allen, R. W., Taaffe, K. M., & Ritchie, G. (2014). Surgery rescheduling using discrete event simulation: A case study. Proceedings of the Winter Simulation Conference,2014, 1365–1376.

    Google Scholar 

  • AVEN website Unità Logistica Centralizzata. Retrieved 28 February 2014, from http://www.aven-rer.it/areeintervento/MagazzinoCentrLogistica/default.aspx.

  • Azzi, A., Battini, D., Faccio, M., et al. (2014). Inventory holding costs measurement: A multi-case study. International Journal of Logistics Management,25(1), 109–132.

    Article  Google Scholar 

  • Azzi, A., Persona, A., Sgarbossa, F., & Bonin, M. (2013). Drug inventory management and distribution: Outsourcing logistics to third-party providers. Strategic Outsourcing: An International Journal,6(1), 48–64.

    Article  Google Scholar 

  • Bag, S., Gupta, S., & Foropon, C. (2019). Examining the role of dynamic remanufacturing capability on supply chain resilience in circular economy. Management Decision,57(4), 863–885.

    Article  Google Scholar 

  • Bag, S., Gupta, S., & Telukdarie, A. (2018). Importance of innovation and flexibility in configuring supply network sustainability. Benchmarking,25(9), 3951–3985.

    Article  Google Scholar 

  • Battini, D., Faccio, M., Persona, A., & Sgarbossa, F. (2013). Modelling the growing process of integrated healthcare supply networks. International Journal of System Dynamics Applications,2(1), 1–13.

    Article  Google Scholar 

  • Battini, D., Persona, A., & Sgarbossa, F. (2014). A sustainable EOQ model: Theoretical formulation and applications. International Journal of Production Economics,149, 145–153.

    Article  Google Scholar 

  • Berman, O., Krass, D., & Menezes, M. B. C. (2007). Facility reliability issues in network p-median Problems: Strategic centralization and co-location effects. Operations Research,55(2), 332–350.

    Article  Google Scholar 

  • Cappanera, P., Visintin, F., & Banditori, C. (2014). Comparing resource balancing criteria in master surgical scheduling: A combined optimisation-simulation approach. International Journal of Production Economics,158, 179–196.

    Article  Google Scholar 

  • Carbonara, N., & Pellegrino, R. (2017). How do supply chain risk management flexibility-driven strategies perform in mitigating supply disruption risks? International Journal of Integrated Supply Management,11(4), 354–379.

    Article  Google Scholar 

  • Chiu, C.-H., & Choi, T.-M. (2016). Supply chain risk analysis with mean-variance models: A technical review. Annals of Operations Research,240(2), 489–507.

    Article  Google Scholar 

  • Cooper, M. C., Lambert, D. M., & Pagh, J. D. (1997). Supply chain management: More than a new name for logistics. The International Journal of Logistics Management,8(1), 1–14.

    Article  Google Scholar 

  • Croom, S., Romano, P., & Giannakis, M. (2000). Supply chain management: an analytical framework for critical literature review. European Journal of Purchasing & Supply Management,6(1), 67–83.

    Article  Google Scholar 

  • de Vries, J., & Huijsman, R. (2011). Supply chain management in health services: An overview. Supply Chain Management: An International Journal,16(3), 159–165.

    Article  Google Scholar 

  • Dolgui, A., Ivanov, D., & Sokolov, B. (2018). Ripple effect in the supply chain: An analysis and recent literature. International Journal of Production Research,56(1–2), 414–430.

    Article  Google Scholar 

  • Dong, L., & Rudi, N. (2004). Who benefits from transshipment? exogenous vs. endogenous wholesale prices. Management Science,50(5), 645–657.

    Article  Google Scholar 

  • Dubey, R., Gunasekaran, A., Childe, S. J., et al. (2019). Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience. International Journal of Production Research. https://doi.org/10.1080/00207543.2019.1582820.

    Article  Google Scholar 

  • Ellram, L. M. (1991). Supply-chain management: The industrial organisation perspective. International Journal of Physical Distribution & Logistics Management,21(1), 13–22.

    Article  Google Scholar 

  • Fahimnia, B., Tang, C. S., Davarzani, H., & Sarkis, J. (2015). Quantitative models for managing supply chain risks: A review. European Journal of Operational Research,247(1), 1–15.

    Article  Google Scholar 

  • Ferrand, Y. B., Magazine, M. J., & Rao, U. S. (2014). Partially flexible operating rooms for elective and emergency surgeries. Decision Sciences Journal of Innovative Education,45(5), 819–847.

    Article  Google Scholar 

  • Gianesello, P., Ivanov, D., & Battini, D. (2017). Closed-loop supply chain simulation with disruption considerations: A case-study on Tesla. International Journal of Inventory Research,4(4), 257–280.

    Article  Google Scholar 

  • Hasani, A., & Khosrojerdi, A. (2016). Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study. Transportation Research Part E: Logistics and Transportation Review,87, 20–52.

    Article  Google Scholar 

  • Hishamuddin H., Sarker R., & Essam D. (2015). A simulation model of a three echelon supply chain system with multiple suppliers subject to supply and transportation disruptions. In: IFAC-PapersOnLine (pp. 2036–2040).

  • Ho, W., Zheng, T., Yildiz, H., & Talluri, S. (2015). Supply chain risk management: A literature review. International Journal of Production Research,53(16), 5031–5069.

    Article  Google Scholar 

  • Hou, J., Zeng, A. Z., & Sun, L. (2017). Backup sourcing with capacity reservation under uncertain disruption risk and minimum order quantity. Computers & Industrial Engineering,103, 216–226.

    Article  Google Scholar 

  • Hou, J., Zeng, A. Z., & Zhao, L. (2010). Coordination with a backup supplier through buy-back contract under supply disruption. Transportation Research Part E: Logistics and Transportation Review,46(6), 881–895.

    Article  Google Scholar 

  • Hussain M, Ajmal MM, Gunasekaran A, Khan M (2018) Exploration of social sustainability in healthcare supply chain. Journal of Cleaner Production, 203, 977–989. https://doi.org/10.1016/j.jclepro.2018.08.157

    Article  Google Scholar 

  • Intercent-ER Agenzia per lo sviluppo dei mercati telematici Bandi e servizi per le imprese. https://intercenter.regione.emilia-romagna.it/.

  • Ivanov, D. (2017a). Simulation-based single vs. dual sourcing analysis in the supply chain with consideration of capacity disruptions, big data and demand patterns. International Journal of Integrated Supply Management,11(1), 24–43.

    Article  Google Scholar 

  • Ivanov, D. (2017b). Simulation-based ripple effect modelling in the supply chain. International Journal of Production Research,55(7), 2083–2101.

    Article  Google Scholar 

  • Ivanov, D. (2018). Revealing interfaces of supply chain resilience and sustainability: A simulation study. International Journal of Production Research,56(10), 3507–3523.

    Article  Google Scholar 

  • Ivanov, D. (2019). Disruption tails and revival policies: A simulation analysis of supply chain design and production-ordering systems in the recovery and post-disruption periods. Computers & Industrial Engineering,127, 558–570.

    Article  Google Scholar 

  • Ivanov, D., & Dolgui, A. (2018). Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience. International Journal of Production Research. https://doi.org/10.1080/00207543.2018.1521025.

    Article  Google Scholar 

  • Ivanov, D., Dolgui, A., & Sokolov, B. (2019a). Handbook of ripple effects in the supply chain. New York: Springer.

    Book  Google Scholar 

  • Ivanov, D., Dolgui, A., Sokolov, B., & Ivanova, M. (2017). Literature review on disruption recovery in the supply chain. International Journal of Production Research,55(20), 6158–6174.

    Article  Google Scholar 

  • Ivanov, D., Sokolov, B., & Dolgui, A. (2014). The Ripple effect in supply chains: Trade-off “efficiency-flexibility- resilience” in disruption management. International Journal of Production Research,52(7), 2154–2172.

    Article  Google Scholar 

  • Ivanov, D., Tsipoulanidis, A., & Schönberger, J. (2019b). Global supply chain and operations management: A decision-oriented introduction into the creation of value (2nd ed.). New York: Springer.

    Book  Google Scholar 

  • Jabbarzadeh, A., Fahimnia, B., Sheu, J. B., & Moghadam, H. S. (2016). Designing a supply chain resilient to major disruptions and supply/demand interruptions. Transportation Research Part B: Methodological,94, 121–149.

    Article  Google Scholar 

  • Kitsiou, S., Matopoulos, A., Manthou, V., & Vlachopoulou, M. (2007). Evaluation of integration technology approaches in the healthcare supply chain. International Journal of Value Chain Management,1(4), 325.

    Article  Google Scholar 

  • Kumar, P., Bera, S., Dutta, T., & Chakraborty, S. (2018). Auxiliary flexibility in healthcare delivery system: An integrative framework and implications. Global Journal of Flexible Systems Management,19(2), 173–186.

    Article  Google Scholar 

  • Kwon, I. W. G., Kim, S. H., & Martin, D. G. (2016). Healthcare supply chain management; strategic areas for quality and financial improvement. Technological Forecasting and Social Change,113, 422–428.

    Article  Google Scholar 

  • Lambert, D. M., & Cooper, M. C. (2000). Issues in supply chain management. Industrial Marketing Management,29(1), 65–83.

    Article  Google Scholar 

  • Lin, Y. K., Huang, C. F., Liao, Y. C., & Yeh, C. C. (2017). System reliability for a multistate intermodal logistics network with time windows. International Journal of Production Research,55(7), 1957–1969.

    Article  Google Scholar 

  • Lu, D., Ding, Y., Asian, S., & Paul, S. K. (2018). From supply chain integration to operational performance: The moderating effect of market uncertainty. Global Journal of Flexible Systems Management, 19(Suppl 1), S3–S20.

    Article  Google Scholar 

  • Masi, A., Santarsiero, G., Gallipoli, M. R., et al. (2014). Performance of the health facilities during the 2012 Emilia (Italy) earthquake and analysis of the Mirandola hospital case study. Bulletin of Earthquake Engineering,12(5), 2419–2443.

    Article  Google Scholar 

  • McKone-Sweet, K. E., Hamilton, P., & Willis, S. B. (2005). The ailing healthcare supply chain: A prescription for change. Journal of Supply Chain Management,41(1), 4–17.

    Article  Google Scholar 

  • Ministero delle Infrastrutture e dei Trasporti. (2019). Third parties Freight transportation account: indicatice reference values of the company’s operating costs. http://www.mit.gov.it/documentazione/autotrasporto-merci-conto-di-terzi-valori-indicativi-di-riferimento-dei-costi-di.

  • Mustaffa, N. H., & Potter, A. (2009). Healthcare supply chain management in Malaysia: A case study. Supply Chain Management,14(3), 234–243.

    Article  Google Scholar 

  • Pariazar, M., Root, S., & Sir, M. Y. (2017). Supply chain design considering correlated failures and inspection in pharmaceutical and food supply chains. Computers & Industrial Engineering,111, 123–138.

    Article  Google Scholar 

  • Pavlov, A., Ivanov, D., Dolgui, A., & Sokolov, B. (2018). Hybrid fuzzy-probabilistic approach to supply chain resilience assessment. IEEE Transactions on Engineering Management,65(2), 303–315.

    Article  Google Scholar 

  • Persona, A., Battini, D., & Rafele, C. (2008). Hospital efficiency management: The just-in-time and Kanban technique. International Journal of Healthcare Technology and Management,9(4), 373.

    Article  Google Scholar 

  • Qi, L. (2013). A continuous-review inventory model with random disruptions at the primary supplier. European Journal of Operational Research,225(1), 59–74.

    Article  Google Scholar 

  • Ritchie, L., Burnes, B., Whittle, P., & Hey, R. (2000). The benefits of reverse logistics: The case of the Manchester Royal Infirmary Pharmacy. Supply Chain Management,5(5), 226–233.

    Article  Google Scholar 

  • Rivard-Royer, H., Landry, S., & Beaulieu, M. (2002). Hybrid stockless: A case study. International Journal of Operations & Production Management,22(4), 412–424.

    Article  Google Scholar 

  • Schmitt, A. J., & Singh, M. (2012). A quantitative analysis of disruption risk in a multi-echelon supply chain. International Journal of Production Economics,139(1), 22–32.

    Article  Google Scholar 

  • Seidscher, A., & Minner, S. (2013). A Semi-Markov decision problem for proactive and reactive transshipments between multiple warehouses. European Journal of Operational Research,230(1), 42–52.

    Article  Google Scholar 

  • Shishebori, D., & Babadi, A. Y. (2015). Robust and reliable medical services network design under uncertain environment and system disruptions. Transportation Research Part E: Logistics and Transportation Review,77, 268–288.

    Article  Google Scholar 

  • Shojaie, A. A., Babaie, S., Sayah, E., Mohammaditabar, D. (2018). Analysis and prioritization of green health suppliers using Fuzzy ELECTRE method with a case study. Global Journal of Flexible Systems Management, 19(1), 39–52.

    Article  Google Scholar 

  • Situm, M., & Mateos, R. M. M. (2017). The strategic view of supply chain management and its association with risk. International Journal of Integrated Supply Management,11(1), 87–134.

    Article  Google Scholar 

  • Snyder, L. V., Atan, Z., Peng, P., et al. (2016). OR/MS models for supply chain disruptions: A review. IIE Transactions (Institute of Industrial Engineers),48(2), 89–109.

    Google Scholar 

  • Sushil. (2015). Strategic flexibility: The evolving paradigm of strategic management. Global Journal of Flexible Systems Management, 16(2), 113–114

    Article  Google Scholar 

  • Sushil. (2016) Strategic flexibility in ecosystem. Global Journal of Flexible Systems Management, 17(3), 247–248

    Article  Google Scholar 

  • Sushil. (2017). Does flexibility mitigate or enhance risk? Global Journal of Flexible Systems Management, 18(3), 169–171

    Article  Google Scholar 

  • Tagaras, G., & Vlachos, D. (2010). Effectiveness of stock transshipment under various demand distributions and nonnegligible transshipment times. Production and Operations Management,11(2), 183–198.

    Article  Google Scholar 

  • Tan, K. C., Kannan, V. R., & Handfield, R. B. (1998). Supply chain management: Supplier performance and firm performance. Journal of Supply Chain Management,34(3), 2.

    Article  Google Scholar 

  • Tang, C. S. (2006). Perspectives in supply chain risk management. International Journal of Production Economics,103(2), 451–488.

    Article  Google Scholar 

  • Tang, O., & Musa, S. N. (2011). Identifying risk issues and research advancements in supply chain risk management. International Journal of Production Economics,133(1), 25–34.

    Article  Google Scholar 

  • Technical Council on Lifeline Earthquake Engineering. (2017). Hospitals and healthcare systems. In Tohoku, Japan, Earthquake and Tsunami of 2011 (pp. 741–757).

  • Timajchi, A., Mirzapour Al-e-Hashem, S. M. J., & Rekik, Y. (2018). Inventory routing problem for hazardous and deteriorating items in the presence of accident risk with transshipment option. International Journal of Production Economics,209, 302–315.

    Article  Google Scholar 

  • Vanany, I., Zailani, S., & Pujawan, N. (2009). Supply chain risk management: Literature review and future research. International Journal of Information Systems and Supply Chain Management (IJISSCM),2(1), 16–33.

    Article  Google Scholar 

  • Wadhwa, S., Madaan, J., & Saxena, A. (2007). Need for flexibility and innovation in healthcare management systems. Global Journal of Flexible Systems Management,8(1–2), 45–54.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Management and Engineering, University of Padova, Stradella San Nicola 3, 36100, Vicenza, Italy

    Riccardo Aldrighetti, Ilenia Zennaro, Serena Finco & Daria Battini

Authors
  1. Riccardo Aldrighetti
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ilenia Zennaro
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Serena Finco
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Daria Battini
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Riccardo Aldrighetti.

Ethics declarations

Conflict of interest

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aldrighetti, R., Zennaro, I., Finco, S. et al. Healthcare Supply Chain Simulation with Disruption Considerations: A Case Study from Northern Italy. Glob J Flex Syst Manag 20 (Suppl 1), 81–102 (2019). https://doi.org/10.1007/s40171-019-00223-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40171-019-00223-8

Keywords

Search

Navigation