​Resilient supply chain network design under competition : a case study

This research, motivated by a real-life case study in a highly competitive automobile supply chain, experimentally studies the impact of disruption on the competitiveness of supply chains. The studied supply chain faces two major risks: disruption of suppliers and tough competition from competitors. Any disruption in upstream level of the supply chain leads to an inability to meet demand downstream and causes market share to be lost to the competitors. For such a setting, a resilient topology is redesigned that can recover from and react quickly to any disruptive incidents. To this aim, we speculate there are three policies that can be used to mitigate the disruption risk, namely keeping emergency stock at the retailers, reserving back-up capacity at the suppliers, and multiple-sourcing. The problem is addressed using a mixed integer non-linear model to find the most profitable network and mitigation policies. We design a piecewise linear method to solve the model. Based on the data extracted from an automotive supply chain, practical insights of the research are extracted in a controlled experiment. Our analysis suggests that implementing risk mitigation policies not only work to the advantage of the supply chain by sustaining and improving its market share but also benefit customers by stabilizing retail prices in the market. Using the case study, we analyze the contribution of each risk strategy in stabilizing the supply chain's profit, market share, and retail price. Our analysis reveals that downstream “emergency stock” is the most preferable risk mitigation strategy if suppliers are unreliable

Resilence of complex supply networks

During recent decades supply chains have grown, and became increasingly interconnected due to globalisation and outsourcing. Empirical and theoretical studies now characterise supply chains as complex networks rather than the hierarchical, linear chain structures often theorised in classical literature. Increased topological complexity resulted in an increased exposure to risk, however existing supply chain risk management methodologies are designed based on the linear structure assumption rather than interdependent network structures. There is a growing need to better understand the complexities of supply networks, and how to identify, measure and mitigate risks more efficiently. The aim of this thesis is to identify how supply network topology influences resilience. More specifically, how applying well-established supply chain risk management strategies can decrease disruption impact in different supply network topologies. The influence of supply network topology on resilience is captured using a dynamic agent-based model based on empirical and theoretical supply network structures, without a single entity controlling the whole system where each supplier is an independent decision-maker. These suppliers are then disrupted using various disruption scenarios. Suppliers in the network then apply inventory mitigation and contingent rerouting to decrease impact of disruptions on the rest of the network. To the best of author’s knowledge, this is the first time the impact of random disruptions and its reduction through risk management strategies in different supply network topologies have been assessed in a fully dynamic, interconnected environment. The main lessons from this work are as follows: It has been observed that the supply network topology plays a crucial role in reducing impact of disruptions. Some supply network topologies are more resilient to random disruptions as they better fulfil customer demand under perturbations. Under random disruptions, inventory mitigation is a well-performing shock absorption mechanism. Contingent rerouting, on the other hand, is a strategy that needs specific conditions to work well. Firstly, the strategy must be applied by companies in supply topologies where the majority of supply chain members have alternative suppliers. Secondly, contingent rerouting is only efficient in cases when the reaction time to supplier’s disruption is shorter than the duration of the disruption. It has also been observed that the topological position of the individual company who applies specific risk management strategy heavily impacts costs and fill-rates of the overall system. This property is moderated by other variables such as disruption duration, disruption frequency and the chosen risk management strategy. An additional, important lesson here is that, choosing the supplier that suffered the most from disruptions or have specific topological position in a network to apply a risk management strategy might not always decrease the costs incurred by the whole system. In contrast, it might increase it if not applied appropriately. This thesis underpins the significance of topology in supply network resilience. The results from this work are foundational to the claim that it is possible to design an extended supply network that will be able reduce the impact of certain disruption types. However, the design must consider topological properties as well as moderating variables.PhD in Manufacturin

A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain

[EN] The challenges of global economies foster supply chains to have to increase their processes of collaboration and dependence between their nodes, generating an increase in the level of vulnerability to possible impacts and interruptions in their operations that may affect their sustainability. This has developed an emerging area of interest in supply chain management, considering resilience management as a strategic capability of companies, and causing an increase in this area of research. Additionally, supply chains should deal with the three dimensions of sustainability (economic, environmental, and social dimensions) by incorporating the three types of objectives in their strategy. Thus, there is a need to integrate both resilience and sustainability in supply chain management to increase competitiveness. In this paper, a systematic literature review is undertaken to analyze resilience management and its connection to increase supply chain sustainability. In the review, 232 articles published from 2000 to February 2020 in peer-reviewed journals in the Scopus and ScienceDirect databases are analyzed, classified, and synthesized. With the results, this paper develops a conceptual framework that integrates the fundamental elements for analyzing, measuring, and managing resilience to increase sustainability in the supply chain. Finally, conclusions, limitations, and future research lines are exposed.This study was supported by the Valencian Government in Spain (Project AEST/2019/019).Zavala-Alcívar, A.; Verdecho Sáez, MJ.; Alfaro Saiz, JJ. (2020). A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain. Sustainability. 12(16):1-38. https://doi.org/10.3390/su12166300S1381216Roberta Pereira, C., Christopher, M., & Lago Da Silva, A. (2014). Achieving supply chain resilience: the role of procurement. Supply Chain Management: An International Journal, 19(5/6), 626-642. doi:10.1108/scm-09-2013-0346Pettit, T. J., Fiksel, J., & Croxton, K. L. (2010). ENSURING SUPPLY CHAIN RESILIENCE: DEVELOPMENT OF A CONCEPTUAL FRAMEWORK. Journal of Business Logistics, 31(1), 1-21. doi:10.1002/j.2158-1592.2010.tb00125.xPettit, T. J., Croxton, K. L., & Fiksel, J. (2013). Ensuring Supply Chain Resilience: Development and Implementation of an Assessment Tool. Journal of Business Logistics, 34(1), 46-76. doi:10.1111/jbl.12009Ponis, S. T., & Koronis, E. (2012). Supply Chain Resilience: Definition Of Concept And Its Formative Elements. Journal of Applied Business Research (JABR), 28(5), 921. doi:10.19030/jabr.v28i5.7234Seuring, S., & Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16(15), 1699-1710. doi:10.1016/j.jclepro.2008.04.020Qorri, A., Mujkić, Z., & Kraslawski, A. (2018). A conceptual framework for measuring sustainability performance of supply chains. Journal of Cleaner Production, 189, 570-584. doi:10.1016/j.jclepro.2018.04.073Verdecho, M.-J., Alarcón-Valero, F., Pérez-Perales, D., Alfaro-Saiz, J.-J., & Rodríguez-Rodríguez, R. (2020). A methodology to select suppliers to increase sustainability within supply chains. Central European Journal of Operations Research, 29(4), 1231-1251. doi:10.1007/s10100-019-00668-3Edgeman, R., & Wu, Z. (2016). Supply chain criticality in sustainable and resilient enterprises. Journal of Modelling in Management, 11(4), 869-888. doi:10.1108/jm2-10-2014-0078Marchese, D., Reynolds, E., Bates, M. E., Morgan, H., Clark, S. S., & Linkov, I. (2018). Resilience and sustainability: Similarities and differences in environmental management applications. Science of The Total Environment, 613-614, 1275-1283. doi:10.1016/j.scitotenv.2017.09.086Ahern, J. (2012). Urban landscape sustainability and resilience: the promise and challenges of integrating ecology with urban planning and design. Landscape Ecology, 28(6), 1203-1212. doi:10.1007/s10980-012-9799-zRamezankhani, M. J., Torabi, S. A., & Vahidi, F. (2018). Supply chain performance measurement and evaluation: A mixed sustainability and resilience approach. Computers & Industrial Engineering, 126, 531-548. doi:10.1016/j.cie.2018.09.054Shashi, Centobelli, P., Cerchione, R., & Ertz, M. (2019). Managing supply chain resilience to pursue business and environmental strategies. Business Strategy and the Environment, 29(3), 1215-1246. doi:10.1002/bse.2428Ivanov, D. (2017). Revealing interfaces of supply chain resilience and sustainability: a simulation study. International Journal of Production Research, 56(10), 3507-3523. doi:10.1080/00207543.2017.1343507Fahimnia, B., & Jabbarzadeh, A. (2016). Marrying supply chain sustainability and resilience: A match made in heaven. Transportation Research Part E: Logistics and Transportation Review, 91, 306-324. doi:10.1016/j.tre.2016.02.007Ruiz-Benitez, R., López, C., & Real, J. C. (2019). Achieving sustainability through the lean and resilient management of the supply chain. International Journal of Physical Distribution & Logistics Management, 49(2), 122-155. doi:10.1108/ijpdlm-10-2017-0320Pavlov, A., Ivanov, D., Pavlov, D., & Slinko, A. (2019). Optimization of network redundancy and contingency planning in sustainable and resilient supply chain resource management under conditions of structural dynamics. Annals of Operations Research. doi:10.1007/s10479-019-03182-6Khot, S. B., & Thiagarajan, S. (2019). Resilience and sustainability of supply chain management in the Indian automobile industry. International Journal of Data and Network Science, 339-348. doi:10.5267/j.ijdns.2019.4.002Roostaie, S., Nawari, N., & Kibert, C. J. (2019). Sustainability and resilience: A review of definitions, relationships, and their integration into a combined building assessment framework. Building and Environment, 154, 132-144. doi:10.1016/j.buildenv.2019.02.042Davoudabadi, R., Mousavi, S. M., & Sharifi, E. (2020). An integrated weighting and ranking model based on entropy, DEA and PCA considering two aggregation approaches for resilient supplier selection problem. Journal of Computational Science, 40, 101074. doi:10.1016/j.jocs.2019.101074Carvalho, H., Duarte, S., & Cruz Machado, V. (2011). Lean, agile, resilient and green: divergencies and synergies. International Journal of Lean Six Sigma, 2(2), 151-179. doi:10.1108/20401461111135037Wang, Z., & Zhang, J. (2019). Agent-based evaluation of humanitarian relief goods supply capability. International Journal of Disaster Risk Reduction, 36, 101105. doi:10.1016/j.ijdrr.2019.101105Alikhani, R., Torabi, S. A., & Altay, N. (2019). Strategic supplier selection under sustainability and risk criteria. International Journal of Production Economics, 208, 69-82. doi:10.1016/j.ijpe.2018.11.018Zahiri, B., Zhuang, J., & Mohammadi, M. (2017). Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study. Transportation Research Part E: Logistics and Transportation Review, 103, 109-142. doi:10.1016/j.tre.2017.04.009Aboah, J., Wilson, M. M. J., Rich, K. M., & Lyne, M. C. (2019). Operationalising resilience in tropical agricultural value chains. Supply Chain Management: An International Journal, 24(2), 271-300. doi:10.1108/scm-05-2018-0204Statsenko, L., & Corral de Zubielqui, G. (2020). Customer collaboration, service firms’ diversification and innovation performance. Industrial Marketing Management, 85, 180-196. doi:10.1016/j.indmarman.2019.09.013Duong, L. N. K., & Chong, J. (2020). Supply chain collaboration in the presence of disruptions: a literature review. International Journal of Production Research, 58(11), 3488-3507. doi:10.1080/00207543.2020.1712491Bhamra, R., Dani, S., & Burnard, K. (2011). Resilience: the concept, a literature review and future directions. International Journal of Production Research, 49(18), 5375-5393. doi:10.1080/00207543.2011.563826Heckmann, I., Comes, T., & Nickel, S. (2015). A critical review on supply chain risk – Definition, measure and modeling. Omega, 52, 119-132. doi:10.1016/j.omega.2014.10.004Hohenstein, N.-O., Feisel, E., Hartmann, E., & Giunipero, L. (2015). Research on the phenomenon of supply chain resilience. International Journal of Physical Distribution & Logistics Management, 45(1/2), 90-117. doi:10.1108/ijpdlm-05-2013-0128Kamalahmadi, M., & Parast, M. M. (2016). A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research. International Journal of Production Economics, 171, 116-133. doi:10.1016/j.ijpe.2015.10.023Ali, A., Mahfouz, A., & Arisha, A. (2017). Analysing supply chain resilience: integrating the constructs in a concept mapping framework via a systematic literature review. Supply Chain Management: An International Journal, 22(1), 16-39. doi:10.1108/scm-06-2016-0197Umar, M., Wilson, M., & Heyl, J. (2017). Food Network Resilience Against Natural Disasters: A Conceptual Framework. SAGE Open, 7(3), 215824401771757. doi:10.1177/2158244017717570Stone, J., & Rahimifard, S. (2018). Resilience in agri-food supply chains: a critical analysis of the literature and synthesis of a novel framework. Supply Chain Management: An International Journal, 23(3), 207-238. doi:10.1108/scm-06-2017-0201Colicchia, C., Creazza, A., Noè, C., & Strozzi, F. (2019). Information sharing in supply chains: a review of risks and opportunities using the systematic literature network analysis (SLNA). Supply Chain Management: An International Journal, 24(1), 5-21. doi:10.1108/scm-01-2018-0003Annarelli, A., & Nonino, F. (2016). Strategic and operational management of organizational resilience: Current state of research and future directions. Omega, 62, 1-18. doi:10.1016/j.omega.2015.08.004Behzadi, G., O’Sullivan, M. J., Olsen, T. L., & Zhang, A. (2018). Agribusiness supply chain risk management: A review of quantitative decision models. Omega, 79, 21-42. doi:10.1016/j.omega.2017.07.005Kochan, C. G., & Nowicki, D. R. (2018). Supply chain resilience: a systematic literature review and typological framework. International Journal of Physical Distribution & Logistics Management, 48(8), 842-865. doi:10.1108/ijpdlm-02-2017-0099Hosseini, S., Ivanov, D., & Dolgui, A. (2019). Review of quantitative methods for supply chain resilience analysis. Transportation Research Part E: Logistics and Transportation Review, 125, 285-307. doi:10.1016/j.tre.2019.03.001Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review. British Journal of Management, 14(3), 207-222. doi:10.1111/1467-8551.00375Rousseau, D. M., Manning, J., & Denyer, D. (2008). 11 Evidence in Management and Organizational Science: Assembling the Field’s Full Weight of Scientific Knowledge Through Syntheses. Academy of Management Annals, 2(1), 475-515. doi:10.5465/19416520802211651Zimmer, K., Fröhling, M., & Schultmann, F. (2015). Sustainable supplier management – a review of models supporting sustainable supplier selection, monitoring and development. International Journal of Production Research, 54(5), 1412-1442. doi:10.1080/00207543.2015.1079340Natarajarathinam, M., Capar, I., & Narayanan, A. (2009). Managing supply chains in times of crisis: a review of literature and insights. International Journal of Physical Distribution & Logistics Management, 39(7), 535-573. doi:10.1108/09600030910996251Tang, C., & Tomlin, B. (2008). The power of flexibility for mitigating supply chain risks. International Journal of Production Economics, 116(1), 12-27. doi:10.1016/j.ijpe.2008.07.008Kleindorfer, P. R., & Saad, G. H. (2009). Managing Disruption Risks in Supply Chains. Production and Operations Management, 14(1), 53-68. doi:10.1111/j.1937-5956.2005.tb00009.xChristopher, M., & Peck, H. (2004). Building the Resilient Supply Chain. The International Journal of Logistics Management, 15(2), 1-14. doi:10.1108/09574090410700275Wu, T., Huang, S., Blackhurst, J., Zhang, X., & Wang, S. (2013). Supply Chain Risk Management: An Agent-Based Simulation to Study the Impact of Retail Stockouts. IEEE Transactions on Engineering Management, 60(4), 676-686. doi:10.1109/tem.2012.2190986Fang, H., & Xiao, R. (2013). Resilient closed-loop supply chain network design based on patent protection. International Journal of Computer Applications in Technology, 48(1), 49. doi:10.1504/ijcat.2013.055566Gong, J., Mitchell, J. E., Krishnamurthy, A., & Wallace, W. A. (2014). An interdependent layered network model for a resilient supply chain. Omega, 46, 104-116. doi:10.1016/j.omega.2013.08.002Mari, S., Lee, Y., & Memon, M. (2014). Sustainable and Resilient Supply Chain Network Design under Disruption Risks. Sustainability, 6(10), 6666-6686. doi:10.3390/su6106666Bueno-Solano, A., & Cedillo-Campos, M. G. (2014). Dynamic impact on global supply chains performance of disruptions propagation produced by terrorist acts. Transportation Research Part E: Logistics and Transportation Review, 61, 1-12. doi:10.1016/j.tre.2013.09.005Costantino, F., Gravio, G. D., Shaban, A., & Tronci, M. (2014). Replenishment policy based on information sharing to mitigate the severity of supply chain disruption. International Journal of Logistics Systems and Management, 18(1), 3. doi:10.1504/ijlsm.2014.062119Kristianto, Y., Gunasekaran, A., Helo, P., & Hao, Y. (2014). A model of resilient supply chain network design: A two-stage programming with fuzzy shortest path. Expert Systems with Applications, 41(1), 39-49. doi:10.1016/j.eswa.2013.07.009Raj, R., Wang, J. W., Nayak, A., Tiwari, M. K., Han, B., Liu, C. L., & Zhang, W. J. (2015). Measuring the Resilience of Supply Chain Systems Using a Survival Model. IEEE Systems Journal, 9(2), 377-381. doi:10.1109/jsyst.2014.2339552LOH, H. S., & THAI, V. V. (2015). Cost Consequences of a Port-Related Supply Chain Disruption. The Asian Journal of Shipping and Logistics, 31(3), 319-340. doi:10.1016/j.ajsl.2015.09.001Torabi, S. A., Baghersad, M., & Mansouri, S. A. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 79, 22-48. doi:10.1016/j.tre.2015.03.005Cardoso, S. R., Paula Barbosa-Póvoa, A., Relvas, S., & Novais, A. Q. (2015). Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty. Omega, 56, 53-73. doi:10.1016/j.omega.2015.03.008Salehi Sadghiani, N., Torabi, S. A., & Sahebjamnia, N. (2015). Retail supply chain network design under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 75, 95-114. doi:10.1016/j.tre.2014.12.015Dixit, V., Seshadrinath, N., & Tiwari, M. K. (2016). Performance measures based optimization of supply chain network resilience: A NSGA-II + Co-Kriging approach. Computers & Industrial Engineering, 93, 205-214. doi:10.1016/j.cie.2015.12.029Liu, F., Song, J.-S., & Tong, J. D. (2016). Building Supply Chain Resilience through Virtual Stockpile Pooling. Production and Operations Management, 25(10), 1745-1762. doi:10.1111/poms.12573Fahimnia, B., Jabbarzadeh, A., & Sarkis, J. (2018). Greening versus resilience: A supply chain design perspective. Transportation Research Part E: Logistics and Transportation Review, 119, 129-148. doi:10.1016/j.tre.2018.09.005Hasani, 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. doi:10.1016/j.tre.2015.12.009Azhmyakov, V., Fernández-Gutiérrez, J. P., Gadi, S. K., & Pickl, S. (2016). A Novel Numerical Approach to the MCLP Based Resilent Supply Chain Optimization. IFAC-PapersOnLine, 49(31), 137-142. doi:10.1016/j.ifacol.2016.12.175Ivanov, D., Sokolov, B., Solovyeva, I., Dolgui, A., & Jie, F. (2016). Dynamic recovery policies for time-critical supply chains under conditions of ripple effect. International Journal of Production Research, 54(23), 7245-7258. doi:10.1080/00207543.2016.1161253Jabbarzadeh, 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. doi:10.1016/j.trb.2016.09.004Babich, V., Burnetas, A. N., & Ritchken, P. H. (2007). Competition and Diversification Effects in Supply Chains with Supplier Default Risk. Manufacturing & Service Operations Management, 9(2), 123-146. doi:10.1287/msom.1060.0122Bogataj, D., Aver, B., & Bogataj, M. (2016). Supply chain risk at simultaneous robust perturbations. International Journal of Production Economics, 181, 68-78. doi:10.1016/j.ijpe.2015.09.009Wang, X., Herty, M., & Zhao, L. (2015). Contingent rerouting for enhancing supply chain resilience from supplier behavior perspective. International Transactions in Operational Research, 23(4), 775-796. doi:10.1111/itor.12151Zeng, B., & Yen, B. P.-C. (2017). Rethinking the role of partnerships in global supply chains: A risk-based perspective. International Journal of Production Economics, 185, 52-62. doi:10.1016/j.ijpe.2016.12.004Lücker, F., & Seifert, R. W. (2017). Building up Resilience in a Pharmaceutical Supply Chain through Inventory, Dual Sourcing and Agility Capacity. Omega, 73, 114-124. doi:10.1016/j.omega.2017.01.001Fattahi, M., Govindan, K., & Keyvanshokooh, E. (2017). Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers. Transportation Research Part E: Logistics and Transportation Review, 101, 176-200. doi:10.1016/j.tre.2017.02.004Kırılmaz, O., & Erol, S. (2017). A proactive approach to supply chain risk management: Shifting orders among suppliers to mitigate the supply side risks. Journal of Purchasing and Supply Management, 23(1), 54-65. doi:10.1016/j.pursup.2016.04.002Li, H., Pedrielli, G., Lee, L. H., & Chew, E. P. (2016). Enhancement of supply chain resilience through inter-echelon information sharing. Flexible Services and Manufacturing Journal, 29(2), 260-285. doi:10.1007/s10696-016-9249-3Otto, C., Willner, S. N., Wenz, L., Frieler, K., & Levermann, A. (2017). Modeling loss-propagation in the global supply network: The dynamic agent-based model acclimate. Journal of Economic Dynamics and Control, 83, 232-269. doi:10.1016/j.jedc.2017.08.001Rezapour, S., Farahani, R. Z., & Pourakbar, M. (2017). Resilient supply chain network design under competition: A case study. European Journal of Operational Research, 259(3), 1017-1035. doi:10.1016/j.ejor.2016.11.041Ledwoch, A., Yasarcan, H., & Brintrup, A. (2018). The moderating impact of supply network topology on the effectiveness of risk management. International Journal of Production Economics, 197, 13-26. doi:10.1016/j.ijpe.2017.12.013Al-Othman, W. B. E., Lababidi, H. M. S., Alatiqi, I. M., & Al-Shayji, K. (2008). Supply chain optimization of petroleum organization under uncertainty in market demands and prices. European Journal of Operational Research, 189(3), 822-840. doi:10.1016/j.ejor.2006.06.081Ivanov, D., Dolgui, A., & Sokolov, B. (2017). Scheduling of recovery actions in the supply chain with resilience analysis considerations. International Journal of Production Research, 56(19), 6473-6490. doi:10.1080/00207543.2017.1401747Das, K. (2019). Integrating Lean, Green, and Resilience Criteria in a Sustainable Food Supply Chain Planning Model. International Journal of Mathematical, Engineering and Management Sciences, 4(2), 259-275. doi:10.33889/ijmems.2019.4.2-022Das, K. (2018). Integrating resilience in a supply chain planning model. International Journal of Quality & Reliability Management, 35(3), 570-595. doi:10.1108/ijqrm-08-2016-0136Arora, V., & Ventresca, M. (2018). Modeling topologically resilient supply chain networks. Applied Network Science, 3(1). doi:10.1007/s41109-018-0070-7Almeida, J. F. de F., Conceição, S. V., Pinto, L. R., de Camargo, R. S., & Júnior, G. de M. (2018). Flexibility evaluation of multiechelon supply chains. PLOS ONE, 13(3), e0194050. doi:10.1371/journal.pone.0194050Mancheri, N. A., Sprecher, B., Deetman, S., Young, S. B., Bleischwitz, R., Dong, L., … Tukker, A. (2018). Resilience in the tantalum supply chain. Resources, Conservation and Recycling, 129, 56-69. doi:10.1016/j.resconrec.2017.10.018Namdar, J., Li, X., Sawhney, R., & Pradhan, N. (2017). Supply chain resilience for single and multiple sourcing in the presence of disruption risks. International Journal of Production Research, 56(6), 2339-2360. doi:10.1080/00207543.2017.1370149Rozhkov, M., & Ivanov, D. (2018). CONTINGENCY PRODUCTION-INVENTORY CONTROL POLICY FOR CAPACITY DISRUPTIONS IN THE RETAIL SUPPLY CHAIN WITH PERISHABLE PRODUCTS. IFAC-PapersOnLine, 51(11), 1448-1452. doi:10.1016/j.ifacol.2018.08.311Sabouhi, 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. doi:10.1016/j.cie.2018.10.001Zavitsas, K., Zis, T., & Bell, M. G. H. (2018). The impact of flexible environmental policy on maritime supply chain resilience. Transport Policy, 72, 116-128. doi:10.1016/j.tranpol.2018.09.020Mitra, K., Gudi, R. D., Patwardhan, S. C., & Sardar, G. (2009). Towards resilient supply chains: Uncertainty analysis using fuzzy mathematical programming. Chemical Engineering Research and Design, 87(7), 967-981. doi:10.1016/j.cherd.2008.12.025Lücker, F., Seifert, R. W., & Biçer, I. (2018). Roles of inventory and reserve capacity in mitigating supply chain disruption risk. International Journal of Production Research, 57(4), 1238-1249. doi:10.1080/00207543.2018.15041

Pandemic impact on supply chains: strategies to minimize supply chain disruption

Working Paper del Departament d’Organització d’Empreses de la Universitat Politècnica de Catalunya.Covid-19 pandemic has challenged all the areas of living of people in the last year, supply chains were not excluded by it. Restriction measures, global health concerns and drastic-unreasonable demand changes were the main issues supply chains had and still have to face in the most globalized world ever seen. The aim of this work is to understand how the pandemic impacted in the supply chains, the first reactions of companies to minimize the disruption of the production, logistic and supply shock and finally the measures to be taken in order to prevent future problems. The question of this study is, in fact: how did supply chains react to pandemic and what can they do to be more resilient? To answer this question, in the first section we show the chronological development of the pandemic, starting from China’s outbreak and its expansion to the rest of the world, keeping in mind the economical context in which the event takes place. In the second section we first review literature on natural disasters, since it are the most similar events to a pandemic in terms of their effects. Moreover, in the third section we depict the suggestions to move to a more resilient management of the supply chain and the possible measures to be taken by supply chain managers. The focus will be on the improvements and weaknesses of current supply chain management techniques, such as Just-In-Time methodology, in-shoring possibilities and demand management. At this study publishing, supply chains are still struggling with uncertainty associated with the pandemic situation and need to change some of their features and strengthen others to prevent future disruptions. Future researches could take advantage of more specific and updated information on this topic.Preprin

Selecting the right supply chain based on risks

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Purpose – The purpose of this paper is to propose a model that enables a company to select the supply chain strategy based on risk probability p (measure of how likely/often a detrimental event occurs) and risk impact i (expression of the significance of a loss when that event occurs). Design/methodology/approach – This paper discusses four supply chain strategies: agility, robustness, resilience and rigidity. Mathematical models are used for the strategies’ cost functions, which reveal optimal solutions and break-even points in dependence of p and i. Findings – This paper proposes that resilience is appropriate in the case of high supply chain risk probability and impact, and rigidity if both values are low. When only risk impact is low, robustness is optimal, whereas agility is optimal when only risk probability is low. Research limitations/implications – This research extends existing models for selecting the appropriate supply chain strategy. Practical implications – Knowledge of the interplay between the strategies’ cost functions and risk probability and risk impact is vital for companies. This may encourage managers to become more familiar with their strategy costs and supply chain risks. Originality/value – To the author’s knowledge, no corresponding model exists so far that links risk impact and risk probability to the four supply chain strategies

A novel classification of supply chain risks: scale development and validation

Purpose: Supply chain has become an essential element for any organization but risks are the major obstacles in achieving the performance even it can disrupt not only the organization but a whole system. Thus, it is compulsory to manage the risks efficiently and effectively. Risk cannot be managed until properly identified, there are numerous studies on risk identification, after comprehensive literature, it has been revealed that the study that identifies overall supply chain risk is scaring. The manufacturing sector of any country is considered as the backbone of any economy, in Malaysia it is the second largest sector in economic contribution and highest in productivity level. The aim of this study is to provide a reliable tool to assess the overall supply chain risks of Malaysian manufacturing through a systematic process. Design/methodology/approach: A detail literature review has been done for categorization of overall supply chain risk sources. Then an instrument has been developed from a pool of items. The questionnaire was purified through pretesting, pilot testing (by the exploratory view) and reliability and validity tests. The data were collected by email from Federation of Malaysian Malaysia (FMM-2017) through systemic probability sampling. Total 132 final responses have been considered for exploratory factor analysis through SPSS 23. Findings: The finding of this study revealed that overall supply chain risks can be categories into seven constructs that are supply side risks, process side risks, demand side risks, logistic side risks, collaboration side risks and environment side risks and the final questionnaire is consisting of 57 items. Research limitations/implications: This study covered tier 1 members of the supply chain. Secondly, the supply chain of manufacturing organizations only has been considered. Practical implications: This study will help the managers to understand what kind of risk sources they can face and which type of risks under these risk sources they should consider while decision making. This study will update the managers about the identification of risks and their potential negative effects. Originality/value: This article will justify the need for Malaysian manufacturing by providing a validated and reliable instrument for the identification and assessment of their risks under major supply chain risk sources.Peer Reviewe

A Representation of Tactical and Strategic Precursors of Supply Network Resilience Using Simulation Based Experiments

Modern supply chains are becoming increasingly complex and are exposed to higher levels of risk. Globalization, market uncertainty, mass customization, technological and innovation forces, among other factors, make supply networks more susceptible to disruptions (both those that are man-made and/or ones associated with natural events) that leave suppliers unavailable, shut-down facilities and entail lost capacity. Whereas several models for disruption management exist, there is a need for operational representations of concepts such as resilience that expand the practitioners’ understanding of the behavior of their supply chains. These representations must include not only specific characteristics of the firm’s supply network but also its tactical and strategic decisions (such as sourcing and product design). Furthermore, the representations should capture the impact those characteristics have on the performance of the network facing disruptions, thus providing operations managers with insights on what tactical and strategic decisions are most suitable for their specific supply networks (and product types) in the event of a disruption. This research uses Agent-Based Modeling and Simulation (ABMS) and an experimental set-up to develop a representation of the relationships between tactical and strategic decisions and their impact on the performance of multi-echelon networks under supply uncertainty. Two main questions are answered: 1) How do different tactical and strategic decisions give rise to resilience in a multi-echelon system?, and 2) What is the nature of the interactions between those factors, the network’s structure and its performance in the event of a disruption? Product design was found to have the most significant impact on the reliability (Perfect Order Fulfillment) for products with high degrees of componentization when dual sourcing is the chosen strategy. However, when it comes to network responsiveness (Order Fulfillment Cycle Time), this effect was attenuated. Generally, it was found that the expected individual impact these factors have on the network performance is affected by the interactions between them

The moderating impact of supply network topology on the effectiveness of risk management

While supply chain risk management offers a rich toolset for dealing with risk at the dyadic level, less attention has been given to the effectiveness of risk management in complex supply networks. We bridge this gap by building an agent based model to explore the relationship between topological characteristics of complex supply networks and their ability to recover through inventory mitigation and contingent rerouting. We simulate upstream supply networks, where each agent represents a supplier. Suppliers’ connectivity patterns are generated through random and preferential attachment models. Each supplier manages its inventory using an anchor-and-adjust ordering policy. We then randomly disrupt suppliers and observe how different topologies recover when risk management strategies are applied. Our results show that topology has a moderating effect on the effectiveness of risk management strategies. Scale-free supply networks generate lower costs, have higher fill-rates, and need less inventory to recover when exposed to random disruptions than random networks. Random networks need significantly more inventory distributed across the network to achieve the same fill rates as scale-free networks. Inventory mitigation improves fill-rate more than contingent rerouting regardless of network topology. Contingent rerouting is not effective for scale-free networks due to the low number of alternative suppliers, particularly for short-lasting disruptions. We also find that applying inventory mitigation to the most disrupted suppliers is only effective when the network is exposed to frequent disruptions; and not cost effective otherwise. Our work contributes to the emerging field of research on the relationship between complex supply network topology and resilience

Coping with uncertainties via resilient supply chain framework

Supply chain resilience (SCR) is a promising area budding from the emergent admiration to minimise supply chain disruptions by practitioners and by researchers across the globe. To inflate monetary earnings, many organisations execute initiatives such as comprehensive reach of supply chains, amplified outsourcing, shorter product life cycles, reduced buffers and centralisation. These initiatives are effective in stable surroundings, but they could make supply chain vulnerable to various types of disruptions. The main thrust of this research is, to propose a conceptual model for endowing deeper knowledge of how uncertainty from suppliers, customers and existing supply chain structure amplifies vulnerability and consequently increases supply chain risk exposure. In accordance with fitness landscape theory, this paper accepts a complex systems perspective to view supply chain organisations and understand their capabilities. It focuses on diminishing the vulnerability of supply chain systems and the ability to design systems to be more resilient to chang

Safety Engineering with COTS components

Safety-critical systems are becoming more widespread, complex and reliant on software. Increasingly they are engineered through Commercial Off The Shelf (COTS) (Commercial Off The Shelf) components to alleviate the spiralling costs and development time, often in the context of complex supply chains. A parallel increased concern for safety has resulted in a variety of safety standards, with a growing consensus that a safety life cycle is needed which is fully integrated with the design and development life cycle, to ensure that safety has appropriate influence on the design decisions as system development progresses. In this article we explore the application of an integrated approach to safety engineering in which assurance drives the engineering process. The paper re- ports on the outcome of a case study on a live industrial project with a view to evaluate: its suitability for application in a real-world safety engineering setting; its benefits and limitations in counteracting some of the difficulties of safety en- gineering with COTS components across supply chains; and, its effectiveness in generating evidence which can contribute directly to the construction of safety cases