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

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.

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.

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.

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.

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

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.

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

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.

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.

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.

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.

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.

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.

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

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.

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

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.

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

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.

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.

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.

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.

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.

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.

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.

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

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.

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

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

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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

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.

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

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.

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.

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.

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.

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.

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.

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

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

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

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.

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.

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

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.

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.

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.

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.