Geographical Indication Rice Supply Chain Risk Management for a Community Enterprise

Geographical indication (GI) rice is unique product from a specific region. Our objective is to study the risk management in the GI rice supply chain of a community enterprise called “Ban Khao Klang”, which produces Sang Yod Muang Phatthalung. From the literature review and in-depth interview of the president of the group, the risk identification, risk measurement, assessment and evaluation for farmers and the enterprise are performed. Then, the priority list of risk management is descending sorted according to the index of severity, probability and cost. The result indicates that the first priority risk for farmer is flood, being in debt, high input cost and inadequate knowledge for organic farming and high production cost for an enterprise. In addition, the group needs support from government in term of subsidy in water pond. Finally, we suggest the improvement of productivity by using proper techniques. Furthermore, the enhancement of community enterprise could be implemented in human skill, teamwork and network. Keywords: Community enterprise; geographical indication rice; risk managemen

Enterprise Resilience Assessment A Quantitative Approach

[EN] Enterprise resilience is a key capacity to guarantee enterprises¿ long-term continuity. This paper proposes a quantitative approach to enhance enterprise resilience by selecting optimal preventive actions to be activated to cushion the impact of disruptive events and to improve preparedness capability, one of the pillars of the enterprise resilience capacity. The proposed algorithms combine the dynamic programming approach with attenuation formulas to model real improvements when a combined set of preventive actions is activated for the same disruptive event. A numerical example is presented that shows remarkable reductions in the expected annual cost due to potential disruptive events.Sanchis, R.; Poler, R. (2019). Enterprise Resilience Assessment A Quantitative Approach. Sustainability. 11(16):1-13. https://doi.org/10.3390/su11164327S1131116Baghersad, M., & Zobel, C. W. (2015). Economic impact of production bottlenecks caused by disasters impacting interdependent industry sectors. International Journal of Production Economics, 168, 71-80. doi:10.1016/j.ijpe.2015.06.011Cagliano, A. C., De Marco, A., Grimaldi, S., & Rafele, C. (2012). An integrated approach to supply chain risk analysis. Journal of Risk Research, 15(7), 817-840. doi:10.1080/13669877.2012.666757Vanpoucke, E., Boyer, K. K., & Vereecke, A. (2009). Supply chain information flow strategies: an empirical taxonomy. International Journal of Operations & Production Management, 29(12), 1213-1241. doi:10.1108/01443570911005974Chaudhuri, A., Boer, H., & Taran, Y. (2018). Supply chain integration, risk management and manufacturing flexibility. International Journal of Operations & Production Management, 38(3), 690-712. doi:10.1108/ijopm-08-2015-0508Oliva, F. L. (2016). A maturity model for enterprise risk management. International Journal of Production Economics, 173, 66-79. doi:10.1016/j.ijpe.2015.12.007Hendry, L. C., Stevenson, M., MacBryde, J., Ball, P., Sayed, M., & Liu, L. (2019). Local food supply chain resilience to constitutional change: the Brexit effect. International Journal of Operations & Production Management, 39(3), 429-453. doi:10.1108/ijopm-03-2018-0184Prior, T., & Hagmann, J. (2013). Measuring resilience: methodological and political challenges of a trend security concept. Journal of Risk Research, 17(3), 281-298. doi:10.1080/13669877.2013.808686Holling, C. S. (1973). Resilience and Stability of Ecological Systems. Annual Review of Ecology and Systematics, 4(1), 1-23. doi:10.1146/annurev.es.04.110173.000245Haimes, Y. Y. (2009). On the Definition of Resilience in Systems. Risk Analysis, 29(4), 498-501. doi:10.1111/j.1539-6924.2009.01216.xDoorn, N. (2015). Resilience indicators: opportunities for including distributive justice concerns in disaster management. Journal of Risk Research, 20(6), 711-731. doi:10.1080/13669877.2015.1100662Scholz, R. W., Blumer, Y. B., & Brand, F. S. (2012). Risk, vulnerability, robustness, and resilience from a decision-theoretic perspective. Journal of Risk Research, 15(3), 313-330. doi:10.1080/13669877.2011.634522Reyes Levalle, R., & Nof, S. Y. (2015). Resilience by teaming in supply network formation and re-configuration. International Journal of Production Economics, 160, 80-93. doi:10.1016/j.ijpe.2014.09.036Kamalahmadi, 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.2015.10.023Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The International Journal of Logistics Management, 20(1), 124-143. doi:10.1108/09574090910954873Comfort, L. K., Sungu, Y., Johnson, D., & Dunn, M. (2001). Complex Systems in Crisis: Anticipation and Resilience in Dynamic Environments. Journal of Contingencies and Crisis Management, 9(3), 144-158. doi:10.1111/1468-5973.00164Ayyub, B. M. (2013). Systems Resilience for Multihazard Environments: Definition, Metrics, and Valuation for Decision Making. Risk Analysis, 34(2), 340-355. doi:10.1111/risa.12093Cox Jr., L. A. T. (2012). Community Resilience and Decision Theory Challenges for Catastrophic Events. Risk Analysis, 32(11), 1919-1934. doi:10.1111/j.1539-6924.2012.01881.xSchmitt, 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. doi:10.1016/j.ijpe.2012.01.004Dabhilkar, M., Birkie, S. E., & Kaulio, M. (2016). Supply-side resilience as practice bundles: a critical incident study. 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M., & Jackson, S. (2009). Towards a Conceptual Framework for Resilience Engineering. IEEE Systems Journal, 3(2), 181-191. doi:10.1109/jsyst.2009.2017397Pettit, 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.xBellman, R. (1954). The theory of dynamic programming. Bulletin of the American Mathematical Society, 60(6), 503-516. doi:10.1090/s0002-9904-1954-09848-8Cord, J. (1964). A Method for Allocating Funds to Investment Projects when Returns are Subject to Uncertainty. Management Science, 10(2), 335-341. doi:10.1287/mnsc.10.2.335Weingartner, H. M. (1966). Capital Budgeting of Interrelated Projects: Survey and Synthesis. Management Science, 12(7), 485-516. doi:10.1287/mnsc.12.7.485Weingartner, H. M., & Ness, D. N. (1967). Methods for the Solution of the Multidimensional 0/1 Knapsack Problem. 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From supply chain risk to system-wide disruptions: research opportunities in forecasting, risk management and product design

Purpose Supply chains must rebuild for resilience to respond to challenges posed by systemwide disruptions. Unlike past disruptions that were narrow in impact and short-term in duration, the Covid pandemic presented a systemic disruption and revealed shortcomings in responses. This study outlines an approach to rebuilding supply chains for resilience, integrating innovation in areas critical to supply chain management. Design/methodology/approach The study is based on extensive debates among the authors and their peers. The authors focus on three areas deemed fundamental to supply chain resilience: (1) forecasting, the starting point of supply chain planning, (2) the practices of supply chain risk management and (3) product design, the starting point of supply chain design. The authors’ debated and pooled their viewpoints to outline key changes to these areas in response to systemwide disruptions, supported by a narrative literature review of the evolving research, to identify research opportunities. Findings All three areas have evolved in response to the changed perspective on supply chain risk instigated by the pandemic and resulting in systemwide disruptions. Forecasting, or prediction generally, is evolving from statistical and time-series methods to human-augmented forecasting supplemented with visual analytics. Risk management has transitioned from enterprise to supply chain risk management to tackling systemic risk. Finally, product design principles have evolved from design-for-manufacturability to design-for-adaptability. All three approaches must work together. Originality/value The authors outline the evolution in research directions for forecasting, risk management and product design and present innovative research opportunities for building supply chain resilience against systemwide disruptions

A Conceptual Reference Framework for Enterprise Resilience Enhancement

[EN] Enterprise resilience is a key capacity to guarantee enterprises' long-term continuity. This paper proposes the enterprise resilience Conceptual Reference Framework to characterize enterprise resilience capacity. The framework is composed of 71 disruptive events that enterprises consider as endangerments to their continuity. The framework also comprises constituent capabilities of enterprise resilience in terms of preparedness and recovery capabilities and elements that support the transition from the AS IS situation to the TO BE one, which are preventive actions (for preparedness capability) and knowledge registration actions (for recovery capability). From the preparedness perspective, 403 preventive actions are currently defined. Each preventive action is specific for every disruptive event. However, it is worth noting that a preventive action can also be applied to different disruptive events. From the recovery perspective, the proposed framework indicates knowledge registration related to (i) the occurrence of disruptive events; (ii) the recovery actions performed to re-establish the normal enterprise operation level. Further research lines are addressed to develop quantitative methods and tools to assess the extent of enterprises' resilience following the foundations of the proposed conceptual framework.This work was supported in part by the European Commission under the Grant Agreement No. 691249 and the Spanish State Research Agency (Agencia Estatal de Investigacion) under the Reference No. RTI2018-101344-B-I00-AR.Sanchis, R.; Canetta, L.; Poler, R. (2020). A Conceptual Reference Framework for Enterprise Resilience Enhancement. Sustainability. 12(4):1-27. https://doi.org/10.3390/su12041464S127124Christopher, M., & Peck, H. (2004). Building the Resilient Supply Chain. 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Guide for Climate-Resilient Cities: An Urban Critical Infrastructures Approach. Sustainability, 11(17), 4727. doi:10.3390/su11174727The Importance of Resilience. Why Do Some Children Bounce Back from Adversity Better Than Others—and Can That Quality Be Taught?http://content.time.com/time/magazine/article/0,9171,1015897,00.htmlSmith, P., Hutchison, D., Sterbenz, J. P. G., Schöller, M., Fessi, A., Karaliopoulos, M., … Plattner, B. (2011). Network resilience: a systematic approach. IEEE Communications Magazine, 49(7), 88-97. doi:10.1109/mcom.2011.5936160Stoltz, P. G. (2003). Building resilience for uncertain times. Leader to Leader, 2004(31), 16-20. doi:10.1002/ltl.58Labaka, L., Hernantes, J., & Sarriegi, J. M. (2015). Resilience framework for critical infrastructures: An empirical study in a nuclear plant. Reliability Engineering & System Safety, 141, 92-105. doi:10.1016/j.ress.2015.03.009Home, J. F., & Orr, J. E. (1997). Assessing behaviors that create resilient organizations. Employment Relations Today, 24(4), 29-39. doi:10.1002/ert.3910240405Riolli, L., & Savicki, V. (2003). Information system organizational resilience. Omega, 31(3), 227-233. doi:10.1016/s0305-0483(03)00023-9Madni, A. M., & Jackson, S. (2009). Towards a Conceptual Framework for Resilience Engineering. IEEE Systems Journal, 3(2), 181-191. doi:10.1109/jsyst.2009.2017397Resiliencia Organizacional. Transformando la Adversidad en Fuente de Innovaciónhttp://www.gerenciadinamicahoy.com/2011/02/resiliencia-organizacional.htmlThe Agility Advantage: A Survival Guide for Complex Enterprises and Endeavorshttps://apps.dtic.mil/dtic/tr/fulltext/u2/a631225.pdfGilly, J.-P., Kechidi, M., & Talbot, D. (2014). Resilience of organisations and territories: The role of pivot firms. European Management Journal, 32(4), 596-602. doi:10.1016/j.emj.2013.09.004Kamalahmadi, 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.2015.10.023Mamouni Limnios, E. A., Mazzarol, T., Ghadouani, A., & Schilizzi, S. G. M. (2014). The Resilience Architecture Framework: Four organizational archetypes. European Management Journal, 32(1), 104-116. doi:10.1016/j.emj.2012.11.007Cabral, I., Grilo, A., & Cruz-Machado, V. (2012). A decision-making model for Lean, Agile, Resilient and Green supply chain management. International Journal of Production Research, 50(17), 4830-4845. doi:10.1080/00207543.2012.657970Pettit, 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.12009Soni, U., Jain, V., & Kumar, S. (2014). Measuring supply chain resilience using a deterministic modeling approach. Computers & Industrial Engineering, 74, 11-25. doi:10.1016/j.cie.2014.04.019Munoz, A., & Dunbar, M. (2015). On the quantification of operational supply chain resilience. International Journal of Production Research, 53(22), 6736-6751. doi:10.1080/00207543.2015.1057296Kim, Y., Chen, Y.-S., & Linderman, K. (2014). Supply network disruption and resilience: A network structural perspective. Journal of Operations Management, 33-34(1), 43-59. doi:10.1016/j.jom.2014.10.006Erol, O., Sauser, B. J., & Mansouri, M. (2010). A framework for investigation into extended enterprise resilience. Enterprise Information Systems, 4(2), 111-136. doi:10.1080/17517570903474304Pettit, 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.xLee, A. V., Vargo, J., & Seville, E. (2013). Developing a Tool to Measure and Compare Organizations’ Resilience. Natural Hazards Review, 14(1), 29-41. doi:10.1061/(asce)nh.1527-6996.0000075Sanchis, R., & Poler, R. (2019). Enterprise Resilience Assessment—A Quantitative Approach. Sustainability, 11(16), 4327. doi:10.3390/su11164327How Poisoned Tylenol Became a Crisis-Management Teaching Modelhttps://time.com/3423136/tylenol-deaths-1982/Benzene Incident Haunts Perrierhttps://news.google.com/newspapers?nid=1345&dat=19910219&id=L8gSAAAAIBAJ&sjid=CfoDAAAAIBAJ&pg=3676,2504946&hl=esBDO Technology Risk Factor Reporthttps://www.bdo.com/getattachment/d10c417f-beb7-4bb9-8835-2b2ec727ce2b/attachment.aspx?2017-Technology-Riskfactor-Report-Brochure_WEB.pdfSupply Chain Resilience Report 2015http://www.bcifiles.com/bci-supply-chain-resilience-2015.pdfCabero Almenara, J., & Barroso Osuna, J. (2013). La utilización del juicio de experto para la evaluación de TIC: el Coeficiente de competencia experta. Bordón. 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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. 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Optimising the Preparedness Capacity of Enterprise Resilience Using Mathematical Programming

[EN] In today's volatile business arena, companies need to be resilient to deal with the unexpected. One of the main pillars of enterprise resilience is the capacity to anticipate, prevent and prepare in advance for disruptions. From this perspective, the paper proposes a mixed-integer linear programming (MILP) model for optimising preparedness capacity. Based on the proposed reference framework for enterprise resilience enhancement, the MILP optimises the activation of preventive actions to reduce proneness to disruption. To do so, the objective function minimizes the sum of the annual expected cost of disruptive events after implementing preventive actions and the annual cost of such actions. Moreover, the algorithm includes a constraint capping the investment in preventive actions and an attenuation formula to deal with the joint savings produced by the activation of two or more preventive actions on the same disruptive event. The management and business rationale for proposing the MILP approach is to keep it as simple and comprehensible as possible so that it does not require highly mathematically skilled personnel, thus allowing top managers at enterprises of any size to apply it effortlessly. Finally, a real pilot case study was performed to validate the mathematical formulation.This work was supported by the Spanish State Research Agency (Agencia Estatal de Investigacion) under the Reference No. RTI2018-101344-B-I00-AR.Sanchis, R.; Duran-Heras, A.; Poler, R. (2020). Optimising the Preparedness Capacity of Enterprise Resilience Using Mathematical Programming. Mathematics. 8(9):1-29. https://doi.org/10.3390/math8091596S12989Day, J. M. (2013). Fostering emergent resilience: the complex adaptive supply network of disaster relief. International Journal of Production Research, 52(7), 1970-1988. doi:10.1080/00207543.2013.787496Kumar, S., & Anbanandam, R. (2019). 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Homeland security preparedness: Balancing protection with resilience in emergent systems. Systems Engineering, 11(4), 287-308. doi:10.1002/sys.20101Sanchis, R., Canetta, L., & Poler, R. (2020). A Conceptual Reference Framework for Enterprise Resilience Enhancement. Sustainability, 12(4), 1464. doi:10.3390/su12041464Lee, A. V., Vargo, J., & Seville, E. (2013). Developing a Tool to Measure and Compare Organizations’ Resilience. Natural Hazards Review, 14(1), 29-41. doi:10.1061/(asce)nh.1527-6996.0000075Kim, Y., Chen, Y.-S., & Linderman, K. (2014). Supply network disruption and resilience: A network structural perspective. Journal of Operations Management, 33-34(1), 43-59. doi:10.1016/j.jom.2014.10.006Soni, U., Jain, V., & Kumar, S. (2014). Measuring supply chain resilience using a deterministic modeling approach. Computers & Industrial Engineering, 74, 11-25. doi:10.1016/j.cie.2014.04.019Munoz, A., & Dunbar, M. (2015). On the quantification of operational supply chain resilience. International Journal of Production Research, 53(22), 6736-6751. doi:10.1080/00207543.2015.1057296Pettit, 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.12009Manopiniwes, W., & Irohara, T. (2016). Stochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster response. International Journal of Production Research, 55(4), 979-996. doi:10.1080/00207543.2016.1211340Sanchis, R., & Poler, R. (2019). Enterprise Resilience Assessment—A Quantitative Approach. Sustainability, 11(16), 4327. doi:10.3390/su11164327Namdar, 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:10.1080/00207543.2017.1370149Wang, 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.12151Aleksić, A., Stefanović, M., Arsovski, S., & Tadić, D. (2013). An assessment of organizational resilience potential in SMEs of the process industry, a fuzzy approach. Journal of Loss Prevention in the Process Industries, 26(6), 1238-1245. doi:10.1016/j.jlp.2013.06.004Tan, R. R., Aviso, K. B., Cayamanda, C. D., Chiu, A. S. F., Promentilla, M. A. B., Ubando, A. T., & Yu, K. D. S. (2016). A fuzzy linear programming enterprise input–output model for optimal crisis operations in industrial complexes. International Journal of Production Economics, 181, 410-418. doi:10.1016/j.ijpe.2015.10.012Tadić, D., Aleksić, A., Stefanović, M., & Arsovski, S. (2014). Evaluation and Ranking of Organizational Resilience Factors by Using a Two-Step Fuzzy AHP and Fuzzy TOPSIS. 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A Strategies Alignment Approach to Manage Disruptive Events in Collaborative Networks

[EN] Enterprises of the supply chain are currently embedded in dynamic and turbulent environments, having to deal with the appearance of disruptive events. When an enterprise is affected by a disruptive event, the consequences of the disruption not only impact in the enterprise itself, but also influences on the other partners of the network to which it belongs. Thus, disruptive events exceed the capability of individual actors, impacting on the network performance. Consequently, network partners have to collaboratively make decisions to soften the negative impacts on the performance. In this regard, after a disruption takes place, network enterprises should be aware of activating a set of sustainable and resilience strategies that attenuate the performance loss and reduce the disruption recovery time. Nevertheless, the diverse nature of disruptions means that a wide range of varied and sometimes contradictory strategies can be formulated, resulting in conflict situations among the collaborative network (CN) partners. The current paper proposes an approach that makes it possible to collaboratively manage the strategies to activate when a disruptive event occurs, so that the selected strategies are aligned. The strategies alignment approach, proposed in the paper, makes it possible to select those strategies that have a positive impact, or a minimum negative impact, on the objectives defined, not only in the enterprise itself, but also in the objectives defined by the rest of CN partners. The alignment of strategies makes it possible to reduce the performance level loss when a disruption takes place. Thus, the strategies alignment approach aims at activating those strategies that maximize the performance of the CN, achieving levels of performance equal or higher than the levels previous to the disruption, limiting the adverse effects produced by the disruptive events, and contributing to a more sustainable-resilient CN. Finally, in order to validate the proposal, a case study is presented. The proposed model is validated to deal with a drop in demand due to a political embargo, in a textile CN.This research was funded by Ayuda Vali+D Formacion-Andres Navarro (ACIF/2012/006). (16/04/12-16/04/15) GENERALITAT VALENCIANA.Andres, B.; Marcucci, G. (2020). A Strategies Alignment Approach to Manage Disruptive Events in Collaborative Networks. Sustainability. 12(7):1-23. https://doi.org/10.3390/su12072641S123127Camarinha-Matos, L. M., & Afsarmanesh, H. (2005). Collaborative networks: a new scientific discipline. 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OR/MS Models for Supply Chain Disruptions: A Review. SSRN Electronic Journal. doi:10.2139/ssrn.1689882Egbelakin, T., Poshdar, M., Walsh, K. Q., Ingham, J., Johnston, D., Becker, J., … Rasheed, E. (2018). Preparation of small to medium-sized enterprises to earthquake disaster. Bulletin of the New Zealand Society for Earthquake Engineering, 51(4), 171-182. doi:10.5459/bnzsee.51.4.171-182Kimura, N., Hoshino, S., & Onitsuka, K. (2019). Analyzing the Association Between Disaster Risk Preparedness and Environmental Consciousness of Small and Medium-Sized Enterprises: The Case of Sukagawa City, Fukushima Prefecture, Japan. Journal of Disaster Research, 14(8), 1047-1058. doi:10.20965/jdr.2019.p1047Ivanov, D. (2017). Simulation-based ripple effect modelling in the supply chain. International Journal of Production Research, 55(7), 2083-2101. doi:10.1080/00207543.2016.1275873Morrish, S. C., & Jones, R. (2020). Post-disaster business recovery: An entrepreneurial marketing perspective. Journal of Business Research, 113, 83-92. doi:10.1016/j.jbusres.2019.03.041Nair, A., & Vidal, J. M. (2011). Supply network topology and robustness against disruptions – an investigation using multi-agent model. International Journal of Production Research, 49(5), 1391-1404. doi:10.1080/00207543.2010.518744Kim, Y., Chen, Y.-S., & Linderman, K. (2014). Supply network disruption and resilience: A network structural perspective. Journal of Operations Management, 33-34(1), 43-59. doi:10.1016/j.jom.2014.10.006Kamalahmadi, 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.2015.10.023Sanchis, R., & Poler, R. (2019). Enterprise Resilience Assessment—A Quantitative Approach. Sustainability, 11(16), 4327. doi:10.3390/su11164327Pei, J., & Liu, W. (2019). Evaluation of Chinese Enterprise Safety Production Resilience Based on a Combined Gray Relevancy and BP Neural Network Model. Sustainability, 11(16), 4321. doi:10.3390/su11164321Blackhurst *, J., Craighead, C. W., Elkins, D., & Handfield, R. B. (2005). An empirically derived agenda of critical research issues for managing supply-chain disruptions. International Journal of Production Research, 43(19), 4067-4081. doi:10.1080/00207540500151549Reyes Levalle, R., & Nof, S. Y. (2017). Resilience in supply networks: Definition, dimensions, and levels. Annual Reviews in Control, 43, 224-236. doi:10.1016/j.arcontrol.2017.02.003Rajesh, R. (2018). On sustainability, resilience, and the sustainable–resilient supply networks. Sustainable Production and Consumption, 15, 74-88. doi:10.1016/j.spc.2018.05.005Jabbarzadeh, A., Fahimnia, B., & Sabouhi, F. (2018). Resilient and sustainable supply chain design: sustainability analysis under disruption risks. International Journal of Production Research, 56(17), 5945-5968. doi:10.1080/00207543.2018.1461950Mari, S., Lee, Y., & Memon, M. (2014). Sustainable and Resilient Supply Chain Network Design under Disruption Risks. Sustainability, 6(10), 6666-6686. doi:10.3390/su6106666Kaur, H., & Singh, S. P. (2016). Sustainable procurement and logistics for disaster resilient supply chain. Annals of Operations Research, 283(1-2), 309-354. doi:10.1007/s10479-016-2374-2Mari, S., Lee, Y., & Memon, M. (2016). Sustainable and Resilient Garment Supply Chain Network Design with Fuzzy Multi-Objectives under Uncertainty. Sustainability, 8(10), 1038. doi:10.3390/su8101038Ivanov, D. (2017). Revealing interfaces of supply chain resilience and sustainability: a simulation study. International Journal of Production Research, 56(10), 3507-3523. doi:10.1080/00207543.2017.1343507Barthe-Delanoë, A.-M., Montarnal, A., Truptil, S., Bénaben, F., & Pingaud, H. (2018). Towards the agility of collaborative workflows through an event driven approach – Application to crisis management. International Journal of Disaster Risk Reduction, 28, 214-224. doi:10.1016/j.ijdrr.2018.02.029Zhu, W., & Wang, Z. (2018). The Collaborative Networks and Thematic Trends of Research on Purchasing and Supply Management for Environmental Sustainability: A Bibliometric Review. Sustainability, 10(5), 1510. doi:10.3390/su10051510Ivanov, 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:10.1080/00207543.2016.1161253Sanchis, R., & Poler, R. (2013). Definition of a framework to support strategic decisions to improve Enterprise Resilience. IFAC Proceedings Volumes, 46(9), 700-705. doi:10.3182/20130619-3-ru-3018.00600AnyLogichttps://www.anylogic.com/Abylaev, M., Pal, R., & Torstensson, H. (2014). Resilience challenges for textile enterprises in a transitional economy and regional trade perspective - a study of Kyrgyz conditions. International Journal of Supply Chain and Operations Resilience, 1(1), 54. doi:10.1504/ijscor.2014.065459Li, W.-Y., Chow, P.-S., Choi, T.-M., & Chan, H.-L. (2016). Supplier integration, green sustainability programs, and financial performance of fashion enterprises under global financial crisis. Journal of Cleaner Production, 135, 57-70. doi:10.1016/j.jclepro.2016.06.048Venkatesh, V. G., Rathi, S., & Patwa, S. (2015). Analysis on supply chain risks in Indian apparel retail chains and proposal of risk prioritization model using Interpretive structural modeling. Journal of Retailing and Consumer Services, 26, 153-167. doi:10.1016/j.jretconser.2015.06.001Yang, S., Song, Y., & Tong, S. (2017). Sustainable Retailing in the Fashion Industry: A Systematic Literature Review. Sustainability, 9(7), 1266. doi:10.3390/su9071266Sanctions against Russia and the Russian Embargo: Billions of Euros Damage to ‘Made in Italy’ Productshttp://www.europarl.europa.eu/doceo/document/E-8-2018-002225_EN.htm

Literature review on specific types of risk faced by firms

UIDB/00667/2020This contribution presents a literature review focused on four types of risk that firms may face during their operation, namely, operational risk, supply chain risk, strategic risk, and enterprise risk. The applied methodology consisted of an online search of databases regarding scientific documents in English, published in different journals; the search was based on several keywords/strings (themes) that had to be included just as in the article title. The number of surveyed papers by theme showed a variation from 40 to 600 and the number of citations of those papers showed a wider variation from 2 to 918. Selected articles from the four themes were analyzed and the first five with more citations were read in full to make a synopsis of each article. However, to reduce the length of the current paper, only two synopses of each theme were explicitly included here. Overall, the findings show that firm’s risks are an important subject for academic researchers, managers and stakeholders, for risky situations can occur and sometimes lead to very heavy losses. A few research gaps were identified, either the lack of quantitative models for the assessment and management of enterprises’ risks, or insufficient practical support/expertise, namely through case studies and/or well-designed surveys. The review ends with the limitations and contributions of the study.publishersversionpublishe

The effects of blockchain on supply chain trust : a thesis presented in partial of the requirements for the Master of Supply Chain Management at Massey University, Palmerston North, New Zealand

Enterprises place strategic importance on supply chains to effectively manage their flow of materials, products, and information. Supply chains primary aim is to have the right product, at the right place, at the right cost, at the right time. Therefore, any gain in efficiency leads to a competitive advantage for the enterprise. A key element to achieving differentiation from competitors is through collaborative partnerships with supply chain suppliers and ultimately, this is achieved by the presence of high-level trust amongst stakeholders. The academic pursuit of this research paper is to explore the type of trust found in supply chain relationships and what effect the adoption of an innovative technology like blockchain would have on trust. Through a thorough literature review, this research thesis addresses comparisons of types of trust, the importance of trust and how trust is achieved in supply chains. Blockchain is, by all definitions, a nascent technology and this amplifies concerns of risk from enterprise and further increases its barriers to adoption. This research thesis argues that blockchain is particularly exposed to a slow rate of adoption due to a lack of knowledge of what distinguishes it from other exponential technologies. In arguing this the research seeks to answer the question: how does blockchain affect trust in supply chain relationships? Through the development of a survey and semi-structured interviews, responses capture the attitude of supply chain professionals surrounding perceived trust in their supply chain, their piloting of exponential technologies and the biggest inhibitors they have experienced to implementing blockchain in their organisations. One of the conclusions of this research is that through the successful implementation of blockchain, enterprises are likely to see increased trust, sustainability, visibility, and efficiency. This cannot be achieved however without an increased understanding from management about the technology, its use cases, and the efficiencies it will bring to a modern, resilient, and adaptive supply chain. This research establishes that the future for blockchain is optimistic if greater awareness of the technological benefits is exposed to the supply chain industry and its various stakeholders