674
Views
4
CrossRef citations to date
0
Altmetric
Research Article

A simulation-based logistics assessment framework in global pharmaceutical supply chain networks

, &
Pages 1242-1260 | Received 15 Jun 2021, Accepted 04 May 2022, Published online: 01 Jun 2022

References

  • Abdelilah, B., El Korchi, A., & Balambo, M. A. (2018). Flexibility and agility: Evolution and relationship. Journal of Manufacturing Technology Management, 29(7), 1138–1162. https://doi.org/10.1108/JMTM-03-2018-0090
  • Alzoubi, H., & Yanamandra, R. (2020). Investigating the mediating role of information sharing strategy on agile supply chain. Uncertain Supply Chain Management, 8(2), 273–284.
  • Azghandi, R., Griffin, J., & Jalali, M. S. (2018). Minimization of drug shortages in pharmaceutical supply chains: A simulation-based analysis of drug recall patterns and inventory policies. Complexity, 2018, 1–14. https://doi.org/10.1155/2018/6348413
  • Better, M., Glover, F., Kochenberger, G., & Wang, H. (2008). Simulation optimization: Applications in risk management. International Journal of Information Technology & Decision Making, 07(04), 571–587. https://doi.org/10.1142/S0219622008003137
  • Brailsford, S., Carter, M., Harper, P., & Katsikopoulos, K. V. (2020). Special issue on healthcare behavioural OR. Journal of the Operational Research Society, 71(7), 1053–1054. https://doi.org/10.1080/01605682.2020.1766848
  • Chowdhury, M. M. H., & Quaddus, M. (2017). Supply chain resilience: Conceptualization and scale development using dynamic capability theory. International Journal of Production Economics, 188, 185–204. https://doi.org/10.1016/j.ijpe.2017.03.020
  • Christopher, M. (2016). Logistics & supply chain management. Pearson UK.
  • Cockburn, I. M. (2004). The changing structure of the pharmaceutical industry. Health Affairs (Project Hope), 23(1), 10–22. https://doi.org/10.1377/hlthaff.23.1.10
  • Collin, J., & Lorenzin, D. (2006). Plan for supply chain agility at Nokia: Lessons from the mobile infrastructure industry. International Journal of Physical Distribution & Logistics Management, 36(6), 418–430. https://doi.org/10.1108/09600030610677375
  • Davis, R., & John, P. (2018). Application of Taguchi-based design of experiments for industrial chemical processes. In Statistical Approaches With Emphasis on Design of Experiments Applied to Chemical Processes. IntechOpen. https://doi.org/10.5772/intechopen.69501
  • de Carvalho Miranda, R., Montevechi, J. A. B., da Silva, A. F., & Marins, F. A. S. (2017). Increasing the efficiency in integer simulation optimization: Reducing the search space through data envelopment analysis and orthogonal arrays. European Journal of Operational Research, 262(2), 673–681. https://doi.org/10.1016/j.ejor.2017.04.016
  • Dehnad, K. (2012). Quality control, robust design, and the Taguchi method. Springer.
  • Diaz, R., & Ardalan, A. (2010). An analysis of Dual‐Kanban just‐in‐time systems in a non‐repetitive environment. Production and Operations Management, 19(2), 233–245. https://doi.org/10.1111/j.1937-5956.2009.01075.x
  • Diaz, R., & Bailey, M. (2011). Building knowledge to improve enterprise performance from inventory simulation models. International Journal of Production Economics, 134(1), 108–113. https://doi.org/10.1016/j.ijpe.2011.05.024
  • Diaz, R., Bailey, M. P., & Kumar, S. (2016). Analyzing a lost-sale stochastic inventory model with Markov-modulated demands: A simulation-based optimization study. Journal of Manufacturing Systems, 38, 1–12. https://doi.org/10.1016/j.jmsy.2015.09.007
  • Diaz, R., Behr, J., & Tulpule, M. (2010). Discrete-event Simulation. In J. A. Sokolowski & C. M. Banks (Eds.), Modeling and simulation fundamentals: Theoretical underpinnings and practical domains. Wiley.
  • Dubey, R., Altay, N., Gunasekaran, A., Blome, C., Papadopoulos, T., & Childe, S. J. (2018). Supply chain agility, adaptability and alignment: Empirical evidence from the Indian auto components industry. International Journal of Operations & Production Management, 38(1), 129–148. https://doi.org/10.1108/IJOPM-04-2016-0173
  • Dubiel, B., & Tsimhoni, O. (2005). Integrating agent based modeling into a discrete event simulation. Proceedings of the Winter Simulation Conference. https://doi.org/10.1109/WSC.2005.1574355
  • Dural Selcuk, G., & Vasilakis, C. (2021). Evaluating the sustainability of complex health system transformation in the context of population ageing: An empirical system dynamics study. Journal of the Operational Research Society, 1–17. https://doi.org/10.1080/01605682.2021.1992307
  • Ebrahimi, S., Hosseini-Motlagh, S.-M., & Nematollahi, M. (2019). Proposing a delay in payment contract for coordinating a two-echelon periodic review supply chain with stochastic promotional effort dependent demand. International Journal of Machine Learning and Cybernetics, 10(5), 1037–1050. https://doi.org/10.1007/s13042-017-0781-6
  • Eckstein, D., Goellner, M., Blome, C., & Henke, M. (2015). The performance impact of supply chain agility and supply chain adaptability: The moderating effect of product complexity. International Journal of Production Research, 53(10), 3028–3046. https://doi.org/10.1080/00207543.2014.970707
  • Ellis, S. (2020). Solving the COVID-19 Pharma Supply Chain Struggle. T. Inc. https://www.tracelink.com/sites/default/files/_global-asset/pdf/idc-whitepaper-supply-chain-agility-in-the-pharmaceutical-industry.pdf?mkt_tok=Nzc2LUJBVy0yMzAAAAF9qow5_Hp4KUB9hq1eKWwOaPJiPNaRxgQtAw3ielegNw6xWANS-s3HFKEhP6ylLwPvmJs3ElBVTbq5CsHavjyMLuAfxBPh-XvRW0ykRsGQzd__7w
  • Fayezi, S., Zutshi, A., & O'Loughlin, A. (2017). Understanding and development of supply chain agility and flexibility: A structured literature review. International Journal of Management Reviews, 19(4), 379–407. https://doi.org/10.1111/ijmr.12096
  • Fishman, G. S. (2013). Discrete-event simulation: Modeling, programming, and analysis. Springer.
  • Francas, D. (2017). Flexibility strategies for pharma distribution. Retrieved September 28, 2019, from http://www.chemanager-online.com/en/topics/logistics/flexibility-strategies-pharma-distribution
  • Friemann, F., & Schönsleben, P. (2016). Reducing global supply chain risk exposure of pharmaceutical companies by further incorporating warehouse capacity planning into the strategic supply chain planning process. Journal of Pharmaceutical Innovation, 11(2), 162–176. https://doi.org/10.1007/s12247-016-9249-6
  • Gao, S. Y., Simchi-Levi, D., Teo, C.-P., & Yan, Z. (2019). Disruption risk mitigation in supply chains: The risk exposure index revisited. Operations Research, 67(3), 831–852. https://doi.org/10.1287/opre.2018.1776
  • Gartner, D., & Padman, R. (2020). Machine learning for healthcare behavioural OR: Addressing waiting time perceptions in emergency care. Journal of the Operational Research Society, 71(7), 1087–1101. https://doi.org/10.1080/01605682.2019.1571005
  • Gharaei, A., & Pasandideh, S. H. R. (2017). Four-echelon integrated supply chain model with stochastic constraints under shortage condition: Sequential quadratic programming. Industrial Engineering & Management Systems, 16(3), 316–329. https://doi.org/10.7232/iems.2017.16.3.316
  • Gomes, R. F., & Kolachana, S. (2017). Analyzing and prioritizing agility in global pharma supply networks- Pfizer (2016-2017) MIT-ZLC. ZLC-MIT International Logistics Program/Universidad de Zaragoza.
  • Grimaud, F., Dolgui, A., & Korytkowski, P. (2014). Exponential smoothing for multi-product lot-sizing with heijunka and varying demand. Management and Production Engineering Review, 5(2), 20–26. https://doi.org/10.2478/mper-2014-0013
  • Hansen, K. R. N., & Grunow, M. (2015). Planning operations before market launch for balancing time-to-market and risks in pharmaceutical supply chains. International Journal of Production Economics, 161, 129–139. https://doi.org/10.1016/j.ijpe.2014.10.010
  • Harraf, A., Wanasika, I., Tate, K., & Talbott, K. (2015). Organizational agility. Journal of Applied Business Research (JABR), 31(2), 675. https://doi.org/10.19030/jabr.v31i2.9160
  • Hong, Y.-Y., Lin, F.-J., & Yu, T.-H. (2016). Taguchi method-based probabilistic load flow studies considering uncertain renewables and loads. IET Renewable Power Generation, 10(2), 221–227. https://doi.org/10.1049/iet-rpg.2015.0196
  • Huang, Y. (2020). The Coronavirus Outbreak Could Disrupt the U.S. Drug Supply. Retrieved April 20, 2020, from https://www.cfr.org/in-brief/coronavirus-disrupt-us-drug-supply-shortages-fda
  • Huq, F., Pawar, K. S., & Rogers, H. (2016). Supply chain configuration conundrum: How does the pharmaceutical industry mitigate disturbance factors? Production Planning & Control, 27(14), 1206–1220.
  • Ivanov, D., & Sokolov, B. (2013). Control and system-theoretic identification of the supply chain dynamics domain for planning, analysis and adaptation of performance under uncertainty. European Journal of Operational Research, 224(2), 313–323. https://doi.org/10.1016/j.ejor.2012.08.021
  • Ivanov, D., Sokolov, B., & Dolgui, A. (2014). The Ripple effect in supply chains: Tradeoff ‘efficiency-flexibility-resilience’ in disruption management. International Journal of Production Research, 52(7), 2154–2172. https://doi.org/10.1080/00207543.2013.858836
  • Ivanov, D., Sokolov, B., & Kaeschel, J. (2010). A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations. European Journal of Operational Research, 200(2), 409–420. https://doi.org/10.1016/j.ejor.2009.01.002
  • Jafari, H. (2015). Logistics flexibility: A systematic review. International Journal of Productivity and Performance Management, 64(7), 947–970. https://doi.org/10.1108/IJPPM-05-2014-0069
  • Jetly, G., Rossetti, C. L., & Handfield, R. (2014). A multi-agent simulation of the pharmaceutical supply chain. In Agent-based modeling and simulation (pp. 133–154). Springer.
  • Kelton, W. D., Sadowski, R., & Zupick, N. (2014). Simulation with Arena (5th ed.). McGraw Hill.
  • Khan, B. S. H., Govindan, K., & Jeyapaul, R. (2010). Optimisation of genetic algorithm parameters in flow shop scheduling using grey relational analysis. International Journal of Advanced Operations Management, 2(1/2), 25–45. https://doi.org/10.1504/IJAOM.2010.034584
  • Kheybari, S., Ishizaka, A., & Salamirad, A. (2021). A new hybrid risk-averse best-worst method and portfolio optimization to select temporary hospital locations for Covid-19 patients. Journal of the Operational Research Society, 1–18. https://doi.org/10.1080/01605682.2021.1993758
  • King, D. W., Hodson, D. D., & Peterson, G. L. (2017). The role of simulation frameworks in relation to experiments. 2017 Winter Simulation Conference (WSC). https://doi.org/10.1109/WSC.2017.8248123
  • Krotov, V., Junglas, I., & Steel, D. (2015). The mobile agility framework: An exploratory study of mobile technology enhancing organizational agility. Journal of Theoretical and Applied Electronic Commerce Research, 10(3), 1–7. https://doi.org/10.4067/S0718-18762015000300002
  • Kumar, A., Luthra, S., Mangla, S. K., & Kazançoğlu, Y. (2020). COVID-19 impact on sustainable production and operations management. Sustainable Operations and Computers, 1, 1–7. https://doi.org/10.1016/j.susoc.2020.06.001
  • Law, A. M., Kelton, W. D., & Kelton, W. D. (2000). Simulation modeling and analysis (Vol. 3). McGraw-Hill.
  • Lee, H. L. (2002). Aligning supply chain strategies with product uncertainties. California Management Review, 44(3), 105–119. https://doi.org/10.2307/41166135
  • Li, Y., Zobel, C. W., Seref, O., & Chatfield, D. (2020). Network characteristics and supply chain resilience under conditions of risk propagation. International Journal of Production Economics, 223, 107529. https://doi.org/10.1016/j.ijpe.2019.107529
  • Liu, M., & Zhang, D. (2016). A dynamic logistics model for medical resources allocation in an epidemic control with demand forecast updating. Journal of the Operational Research Society, 67(6), 841–852. https://doi.org/10.1057/jors.2015.105
  • Lupkin, S. (2020). What would it take to bring more pharmaceutical manufacturing back to the U.S.? National Public Radio (NPR). https://www.npr.org/sections/health-shots/2020/04/24/843379899/pandemic-underscores-u-s-dependence-on-overseas-factories-for-medicines
  • Manzo, G., & Matthews, T. (2014). Potentialities and limitations of agent-based simulations. Revue Française de Sociologie, 55(4), 653–688.
  • Mehralian, G., Zarenezhad, F., & Rajabzadeh Ghatari, A. (2015). Developing a model for an agile supply chain in pharmaceutical industry. International Journal of Pharmaceutical and Healthcare Marketing, 9(1), 74–91. https://doi.org/10.1108/IJPHM-09-2013-0050
  • Nagurney, A., Li, D., & Nagurney, L. S. (2013). Pharmaceutical supply chain networks with outsourcing under price and quality competition. International Transactions in Operational Research, 20(6), 859–888.
  • Nair, A., & Reed‐Tsochas, F. (2019). Revisiting the complex adaptive systems paradigm: Leading perspectives for researching operations and supply chain management issues. Journal of Operations Management, 65(2), 80–92. https://doi.org/10.1002/joom.1022
  • Nelson, B. (2013). Foundations and methods of stochastic simulation: A first course. Springer.
  • Nematollahi, M., Hosseini-Motlagh, S.-M., & Heydari, J. (2017). Economic and social collaborative decision-making on visit interval and service level in a two-echelon pharmaceutical supply chain. Journal of Cleaner Production, 142, 3956–3969. https://doi.org/10.1016/j.jclepro.2016.10.062
  • Niziolek, L., Chiam, T. C., & Yih, Y. (2012). A simulation-based study of distribution strategies for pharmaceutical supply chains. IIE Transactions on Healthcare Systems Engineering, 2(3), 181–189. https://doi.org/10.1080/19488300.2012.709583
  • Nouri, M., Hosseini-Motlagh, S.-M., Nematollahi, M., & Sarker, B. R. (2018). Coordinating manufacturer's innovation and retailer's promotion and replenishment using a compensation-based wholesale price contract. International Journal of Production Economics, 198, 11–24. https://doi.org/10.1016/j.ijpe.2018.01.023
  • Oey, E., & Nitihardjo, E. C. (2016). Selecting regional postponement centre using PESTLE-AHP-TOPSIS Methodology: A Case Study in a Pharmaceutical Company. Global Business Review, 17(5), 1250–1265. https://doi.org/10.1177/0972150916656696
  • Otten, M., Dijkstra, S., Leeftink, G., Kamphorst, B., Meierink, A. O., Heinen, A., Bijlsma, R., & Boucherie, R. J. (2021). Outpatient clinic scheduling with limited waiting area capacity. Journal of the Operational Research Society, 1–22. https://doi.org/10.1080/01605682.2021.1978347
  • Pal, S., & Mahapatra, G. (2017). A manufacturing-oriented supply chain model for imperfect quality with inspection errors, stochastic demand under rework and shortages. Computers & Industrial Engineering, 106, 299–314. https://doi.org/10.1016/j.cie.2017.02.003
  • Qin, R., Liao, H., & Jiang, L. (2021). An enhanced even swaps method based on prospect theory with hesitant fuzzy linguistic information and its application to the selection of emergency logistics plans under the COVID-19 pandemic outbreak. Journal of the Operational Research Society, 1–13. https://doi.org/10.1080/01605682.2021.1897485
  • Rahiminezhad Galankashi, M., Helmi, S. A., Abdul Rahim, A. R., and Rafiei, F. M. (2019). Agility assessment in manufacturing companies. Benchmarking: An International Journal, 26(7), 2081–2104. https://doi.org/10.1108/BIJ-10-2018-0328
  • Razavi, N., Gholizadeh, H., Nayeri, S., & Ashrafi, T. A. (2020). A robust optimization model of the field hospitals in the sustainable blood supply chain in crisis logistics. Journal of the Operational Research Society, 72(12), 2804–2826. https://doi.org/10.1080/01605682.2020.1821586
  • Roy, S., Prasanna Venkatesan, S., & Goh, M. (2021). Healthcare services: A systematic review of patient-centric logistics issues using simulation. Journal of the Operational Research Society, 72(10), 2342–2364.
  • Sabouhi, F., Pishvaee, M. S., & Jabalameli, M. S. (2018). Resilient supply chain design under operational and disruption risks considering quantity discount: A case study of pharmaceutical supply chain. Computers & Industrial Engineering, 126, 657–672. https://doi.org/10.1016/j.cie.2018.10.001
  • Sangari, M. S., Razmi, J., & Zolfaghari, S. (2015). Developing a practical evaluation framework for identifying critical factors to achieve supply chain agility. Measurement, 62, 205–214. https://doi.org/10.1016/j.measurement.2014.11.002
  • Seebacher, G., & Winkler, H. (2015). A capability approach to evaluate supply chain flexibility. International Journal of Production Economics, 167, 177–186. U6 – http://www.scopus.com/inward/record.url?eid=2-s2.0-84937414817&partnerID=40&md5=b0d844effc471a10e6cd26d92c529c22 M4 – Citavi https://doi.org/10.1016/j.ijpe.2015.05.035
  • Settanni, E., Harrington, T. S., & Srai, J. S. (2017). Pharmaceutical supply chain models: A synthesis from a systems view of operations research. Operations Research Perspectives, 4, 74–95. https://doi.org/10.1016/j.orp.2017.05.002
  • Shah, T. R., & Sharma, M. (2014). Comprehensive view of logistics flexibility and its impact on customer satisfaction. International Journal of Logistics Systems and Management, 19(1), 43–61. https://doi.org/10.1504/IJLSM.2014.064030
  • Shams, R., Vrontis, D., Belyaeva, Z., Ferraris, A., & Czinkota, M. R. (2021). Strategic agility in international business: A conceptual framework for “agile” multinationals. Journal of International Management, 27(1), 100737.
  • Simchi-Levi, D., Schmidt, W., Wei, Y., Zhang, P. Y., Combs, K., Ge, Y., Gusikhin, O., Sanders, M., & Zhang, D. (2015). Identifying risks and mitigating disruptions in the automotive supply chain. Interfaces, 45(5), 375–390. https://doi.org/10.1287/inte.2015.0804
  • Simchi-Levi, D., & Simchi-Levi, E. (2020). We need a stress test for critical supply chains. Harvard Business Review, 28.
  • Singh, R. K., Kumar, R., & Kumar, P. (2016). Strategic issues in pharmaceutical supply chains: A review. International Journal of Pharmaceutical and Healthcare Marketing, 10(3), 234–257. https://doi.org/10.1108/IJPHM-10-2015-0050
  • Sokol, E. (2020). What the New Coronavirus means for the pharmaceutical industry. Pharma News Intelligence. https://pharmanewsintel.com/news/what-the-new-coronavirus-means-for-the-pharmaceutical-industry
  • Sousa, R. T., Liu, S., Papageorgiou, L. G., & Shah, N. (2011). Global supply chain planning for pharmaceuticals. Chemical Engineering Research and Design, 89(11), 2396–2409. https://doi.org/10.1016/j.cherd.2011.04.005
  • Swafford, P. M., Ghosh, S., & Murthy, N. (2008). Achieving supply chain agility through IT integration and flexibility. International Journal of Production Economics, 116(2), 288–297. https://doi.org/10.1016/j.ijpe.2008.09.002
  • Swafford, P. M., Ghosh, S., & Murthy, N. N. (2006). A framework for assessing value chain agility. International Journal of Operations & Production Management, 26(2), 118–140. U6-http://www.scopus.com/inward/record.url?eid=2-s2.0-33644601468&partnerID=40&md5=c4e2c0bdfa3467e5c39814a2b1864d5cM4-Citavi. 10.1108/01443570610641639.
  • Tarafdar, M., & Qrunfleh, S. (2017). Agile supply chain strategy and supply chain performance: Complementary roles of supply chain practices and information systems capability for agility. International Journal of Production Research, 55(4), 925–938. https://doi.org/10.1080/00207543.2016.1203079
  • Thomas, C., & Dasgupta, N. (2020). Global supplier India curbs drug exports as coronavirus fears grow. Reuters. https://www.reuters.com/article/us-health-coronavirus-india/global-supplier-india-curbs-drug-exports-as-coronavirus-fears-grow-idUSKBN20Q0ZZ
  • Thomas, K. (2020). First Drug Shortage Caused by Coronavirus, F.D.A. Says. But It Won’t Disclose What Drug or Where It’s Made. The New York Times. https://www.nytimes.com/2020/02/28/health/drug-coronavirus-shortage.html
  • Utiger, L., & Mencer, M. (2016). A Cure for Pharmaceutical Supply Chain Complexity http://www.unitrans-us.com/newsroom/Attachments_Uploads/Four_StepsBetterSupplyChain.pdf
  • Vinodh, S., & Aravindraj, S. (2015). Benchmarking agility assessment approaches: A case study. Benchmarking: An International Journal, 22(1), 2–17. https://doi.org/10.1108/BIJ-04-2013-0037
  • Xu, Z., Elomri, A., Kerbache, L., & El Omri, A. (2020). Impacts of COVID-19 on global supply chains: Facts and perspectives. IEEE Engineering Management Review, 48(3), 153–166. https://doi.org/10.1109/EMR.2020.3018420
  • Yadav, P., Désir, A. (2021). Boosting vaccine production needs the right degree of flexibility. https://knowledge.insead.edu/operations/boosting-vaccine-production-needs-the-right-degree-of-flexibility-17621
  • Yakutcan, U., Demir, E., Hurst, J. R., & Taylor, P. C. (2022). Patient pathway modelling using discrete event simulation to improve the management of COPD. Journal of the Operational Research Society, 73(4), 754–725. https://doi.org/10.1080/01605682.2020.1854626
  • Yoon, J., Talluri, S., & Rosales, C. (2020). Procurement decisions and information sharing under multi-tier disruption risk in a supply chain. International Journal of Production Research, 58(5), 1362–1383.
  • Yu, K., Cadeaux, J., & Song, H. (2017). Flexibility and quality in logistics and relationships. Industrial Marketing Management, 62, 211–225. https://doi.org/10.1016/j.indmarman.2016.09.004
  • Yu, K., Luo, B. N., Feng, X., & Liu, J. (2018). Supply chain information integration, flexibility, and operational performance. The International Journal of Logistics Management, 29(1), 340–364. https://doi.org/10.1108/IJLM-08-2016-0185

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.