Most firms are still failing to think strategically and systematically about managing supply disruption risk and most of the supply chain management efforts are focused on reducing supply chain operation costs rather than managing disruption. Some innovative firms have taken steps to implement supply chain risk management (SCRM). Inventory management is part of SCRM because supply disruptions negatively affect the reliability of deliveries from suppliers and the costs associated with the ordering process. The complexity of existing inventory models makes it challenging to combine the management of the supply process and inventory in a single model due, for example, to the difficulty of including the characteristics of the disruption process in the supply chain network structure. Therefore, there is a need for a simple flexible model that can incorporate the key elements of supply disruption in an inventory model. This thesis presents a series of models that investigate the importance of information on disruption discovery and recovery for a firm’s supply and inventory management. A simple two-echelon supply chain with one firm and two suppliers (i.e., referred to as the onshore and offshore suppliers) in a single product/component setting has been considered in this thesis for the purpose of experimental analyses. The sourcing decisions that the firm faces during periods of supply disruption are examined leading to an assessment of how information about the risk and length of disruption and recovery can be used to facilitate the firm’s sourcing decisions and monitor the performance of stock control during the disruption. The first part of this thesis analyses basic ordering models (Model 1 and Model 2 respectively) without the risk of supply disruption and with the risk of supply disruption. The second part analyses the value of supply disruption information, using a model with advance information on the length of disruption (Model 3) and a model with learning about the length of disruption (Model 4). The third part explores a quantitative recovery model and the analyses in this part consider of three models. Model 5 assumes a basic phased recovery model, Model 6 assumes advance information about the phased recovery process and Model 7 assumes learning about the phased recovery process. The last part of this thesis investigates the order pressure scenario that exists in the firm’s supply chain. Under this scenario, disruption to one part of the supply chain network increases demand on the remainder resulting in a lower service levels than normal. This scenario is applied to all the previous models apart from Model 1. The models in this thesis are examined under finite and infinite planning horizons and with constant and stochastic demand. The objective of the models is to minimise the expected inventory cost and optimise the order quantity from the suppliers given the different assumptions with respect to the length of supply disruption and information about the recovery process. The models have been developed using the discrete time Markov decision process (DTMDP) technique and implemented using the Java programming language. The findings of this thesis could be used to help a firm that is facing the risk supply disruption to develop its SCRM program. The findings highlight the importance of considering quantitative measures of the disruption and recovery processes, something which is still not popular within SCRM in some organisations.

In this study, value of demand information and the importance of option contracts are investigated for a supply chain consisting of a buyer and two suppliers in a single period setting. One supplier is cheap but prone to disruptions whereas the other one is perfectly reliable but expensive. At the beginning of the period, buyer orders from the unreliable supplier and reserves from the reliable supplier through a contract that gives buyer an option to use reserved units after getting disruption information of first supplier. We introduce three models which differ in terms of the level of information available when the ordering decisions are made. In the full information model, the options are exercised after getting disruption and demand information / in the partial information model, the options are exercised after getting disruption information before demand information. In the no information model, there is no options contract and units are ordered from the reliable supplier when buyer has no information about demand and disruption. Through the analysis of these models, we explore the value of advance demand and disruption information in the presence of an options contract.

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京都大学 / 新制・課程博士 / 博士(医学) / 甲第25156号 / 医博第5042号 / 新制||医||1070(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 川上 浩司, 教授 森田 智視, 教授 寺田 智祐 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

The introduction of the theoretical part is devoted to the analysis of threats, another part to the rescue of animals. In the next part, I focused on zoological gardens and evacuation of animals. The last chapter of the theoretical part deals with the evacuation of selected species of animals. When selecting individual species, I focused on those that are most represented in Dvorec Zoo. The aim of my thesis was to create an analysis of the preparedness of the selected zoo to selected crisis situations and to identify the risks of evacuation of the zoo. In order to achieve these goals, I have set research questions - how is the zoo prepared for selected crisis situations? And what are the possible risks associated with evacuating selected species? In the second part of my thesis I focused on the research itself, which included an interview with the director of Dvorec Zoo. Based on the interview and my own observation I processed the KARS method. The KARS method has identified 6 risks that could compromise the operation of Dvorec Zoo. These risks include extreme wind, large-scale gas supply disruption, large-scale electricity supply disruption, snow calamity, and extremely low temperatures. Based on the identified risks, I created a plan for MU solution for Dvorec Zoo. In the MU solution plan, I focused primarily on the impacts on operation, planned measures, procedures and responsible people. Dvorec Zoo will, of course, be provided with this plan.

The ongoing semiconductor shortage impacts organizations throughout the supply chain operationally and financially. Limited material for a sudden increase in demand during the Covid-19 pandemic led to a heightened supplier power and result in the prioritization of customers. Companies like the test-bench producer for the automobile industry Loccioni face thereby the challenges of being a relatively small and thereby almost invisible company in the automotive supply chain. The purpose of this master thesis is to research what pre- and post-disruptive strategies mitigate the negative impact of supply disruptions for organizations with small- and medium-sized enterprises (SME) character in the context of the semiconductor shortage. Additionally, it aims to understand the supplier-buyer power shift during such events and how supply chain trends like lean management contribute to the vulnerability of organizations to such risks. To answer the research question, a qualitative case study was conducted with the high-tech manufacturer Loccioni. Data was collected through a period of ethnography and un-/semi-structured interviews and assessed through thematic analysis. The developed conceptual framework provides a wholesome guidelinefor SMEs or SME alike companies on how to incorporate reactive risk management by considering the whole disruption cycle (pre- and postdisruptive) to mitigate impacts caused by the semiconductor shortage or similar crisis. The findings of this case study show that it is important to lower dependencies on single suppliers and strive for a flexible working culture to encourage turning challenges into opportunities and being decisive during disruptive events. Following a lean approach with a just-in-time strategy is considered a high risk when not having an evolved supply risk monitoring and analyzing system implemented. Therefore, proactive risk-mitigating approaches, such as safety buffers, building few but close relationships and engaging in cooperative activities, are encouraged. Also, even though the resources of SMEs are limited, is alertness towards supply chain risks considered crucial requiring activities like supplier audits and a well supporting IT infrastructure. During disruption, crucial quick and flexible reactions are enabled by agile project management and entrepreneurial efforts fostered by the company culture. Keeping a balance between being too flexible and structured is mandatory to act efficiently. It is important to create a database and safety stock of the critical material and adjust procurement strategies by multi-sourcing and increased escalation efforts. Internally and externally combined efforts can be key to optimizing operations, sourcing the shortage materials and finding alternative technologies to substitute. Strategic collaborations with supply chain partners, exploitationof customer relationships and continuous communication are crucial for smaller enterprises to maintain customer satisfaction. However, there is no single solution for every organization, but rather suggestions which need to be adjusted and evaluated against a company’s business strategy and competitive advantage.

The spread of COVID-19 pandemic in the world and the importance of controlling it in all regions have made managing this crisis a great challenge for all countries. The devastating effect on global automotive supply chains due to the disruptions has resulted in losses and shut down of production facilities owing to government restrictions due to the spread of infections leading to supply breakdown across all tiers of supply chain. It has resulted in shortage of crucial components to the automobile industry. A stochastic goal programming model is developed to incorporate disruptions in the supply chain. The model is used to simulate the current crisis of COVID-19 as numerical cases. Supply chain resilient strategy such as China Plus One strategy that involves diversification of supplier base to other locations along with China is analysed. The key finding is that a China-Plus-One strategy appears to be beneficial to both parties involved, organizations that seek to pursue it for reasons of risk diversification, cost reduction or avoidance of overreliance on China and for Plus-One host economies which gain the benefits of FDI. The contribution of the study is in integrating the supply chain resilience literature and operational research tools to model a global supply chain under uncertainty and making a case for change in supply chain strategy from efficient supply chain to resilient supply chains. The study attempts to support the implementation of the China Plus One Strategy as the most suitable resilient strategy post COVID-19. / Spridningen av covid-19-pandemin i världen och vikten av att kontrollera den i alla regioner har gjort att hantera denna kris till en stor utmaning för alla länder. Den förödande effekten på globala fordonsförsörjningskedjor på grund av störningarna har resulterat i förluster och nedläggningar av produktionsanläggningar på grund av statliga restriktioner på grund av spridningen av infektioner som leder till leveransuppdelning över alla nivåer av försörjningskedjan. Det har resulterat i brist på avgörande komponenter till bilindustrin. En stokastisk målprogrammeringsmodell utvecklas för att införliva störningar i försörjningskedjan. Modellen används för att simulera den nuvarande krisen med COVID-19 som numeriska fall. En strategi för motståndskraftig leveranskedja som China Plus En strategi som innebär diversifiering av leverantörsbasen till andra platser tillsammans med Kina analyseras. Nyckelresultatet är att en China-Plus-One-strategi verkar vara till nytta för båda inblandade parter, organisationer som försöker eftersträva den på grund av riskdiversifiering, kostnadsreduktion eller undvikande av övertilltro till Kina och för Plus-One-värdekonomier som vinner fördelarna med utländska direktinvesteringar. Studiens bidrag är att integrera litteraturen om försörjningskedjans motståndskraft och operativa forskningsverktyg för att modellera en global försörjningskedja under osäkerhet och göra ett argument för förändring av strategin för försörjningskedjan från effektiv försörjningskedja till spänstiga försörjningskedjor. Studien försöker stödja implementeringen av China Plus One-strategin som den mest lämpliga motståndskraftiga strategin efter COVID-19.

The modern supply chain is long, complex, interconnected and global, and plays a fundamental role in business competitiveness. These conditions, along with various supply chain management trends in recent years have increased risks in supply chains which threaten supply chain performance. Greater impact, especially on cost, from an increased threat of supply disruptions is one area of particular concern. Companies today are struggling to find effective means to manage this increased risk and avoid adverse financial impacts. An approach to managing supply disruption risk in supply chains based on the minimization of the total cost of ownership (TCO) of the supply chain is explored in this thesis. Insights are provided into an appropriate view of supply chain risk and a general four step risk management process to guide the design and evaluation of a new risk management tool based on such an approach. A prototype of the new total cost-based, modeling and simulation tool was created in partnership with ProModel Corporation and a government contractor that requested to remain anonymous. A preliminary assessment of the effectiveness of this tool in minimizing TCO and providing an interface useable by non-modelers is provided. This study also reviews and compares a sample set of current supply chain risk management methods and tools and compares them with the new tool for relevance in aiding users in managing supply disruption risk. Based on literature findings and preliminary feedback from pilot contextual demonstrations of the tool, the total cost approach to risk modeling appears promising, although the execution needs to be improved with further enhancements made to the prototype tool. In this preliminary study and evaluation, sufficient evidence is not available to determine that the new prototype tool is any more effective than other currently available risk management tools to provide necessary information to make supply chain risk management decisions that minimize TCO of a supply chain. Suggestions for further development of the tool, especially for improvement of the total cost approach, are provided as well as a preliminary evaluation procedure and survey instruments for a more robust evaluation of the new tool.