In a world economy where globalization reaches almost every corner, the need for a company to attain flexibility has acquired tremendous importance to remain competitive and profitable. This Thesis would present the importance of flexibility in times of uncertain conditions (natural and socio-economic), it would present an analysis of the struggle of Toyota Motors Manufacturing Texas and one of its on-site suppliers Futaba Industrial Texas “FIT” to attain Manufacturing Flexibility through different economic crisis and a natural disaster presenting its strategies to mitigate economic losses and cope with the turbulent environment by developing robust systems. / text

yes / Purpose: The aim of this research therefore is to explore the causes of drug shortages within the pharmaceutical supply chain and assess the adopted mitigation strategies. Research Approach: The study is carried out from an inductive perspective where we seek to understand the phenomenon by a detailed review of extant literature followed by a series of semi-structured interviews with first tier consumers within a case study framework. The respondents were chosen using purposive sampling as those best to comment on the phenomenon under scrutiny. Data was analysed using thematic analysis, where a dual focus was adopted; 1) the preliminary focus was on the identification of system themes (where the system was impacted and the responds e.g. complexity, disruptions and product alternatives) and 2) the secondary focus was the impact on the patient as system recipient and product user (where themes such as stress, anxiety, and adverse drug reactions emerged). Findings and Originality: The analysis show that drug shortages within the pharmaceutical supply chain in the UK occur as a result of stringent regulatory frameworks, faults in the manufacturing processes, lack of Active Pharmaceutical Ingredients, monopolistic wholesaler markets; lack of information dissemination, offshore trading and price manipulations for profit. The impact on the consumers is reported to be extensive and can endure long after the disruptive event occurs. The findings indicate that existing recovery strategies are however cumbersome, add complexity to the supply chain and in extreme cases facilitate the infiltration of counterfeits. The study is innovative as it explores disruptive events and associated recovery strategies which have not been adequately addressed in supply chain management studies to date. Research Impact: This research contributes to existing literature by extending discussions on supply chain disruptions within a dynamic supply chain whilst focusing on product service supply chain recovery strategies and mechanisms. Practical Impact: This study provides Operations/Supply Chain Managers and Pharmaceutical companies and professionals with strategies that can be adopted can adopt in reducing and recovering in a more resilient manner to disruptive events. This thus presents the bedrock for resilient practice and systems design and development, thus reducing system vulnerability and ultimately leading to improved product availability and patient care.

Businesses globally are challenged to innovate their operations strategies and practices towards tighter delivery times, better quality and cheaper prices to remain profitable in addition to managing unpredictable circumstances well in today’s turbulent business environment. They often have to deal with the apparent paradox of advancing efficiency-fostering approaches such as lean production, and enhancing operational resilience against unanticipated disruptions. The purpose of this study is to investigate whether and how practices in seemingly contradicting paradigms in operations management can be utilised to attain a better competitive position in the face of uncertainties. This thesis is comprised of ‘modules’ of studies designed to systematically address the three research questions. This was necessary due to the different maturity level of the concepts brought together. Predominantly qualitative mixed-method approach was used for the overall research with some quantitative analysis included. The critical incident technique, case study and Bayesian inference were used in the different studies (papers). Operational resilience is characterised in terms of five core functions: sense, build, reconfigure, re-enhance, and sustain (RQ1). Resilience is also operationalised using routine practices that are bundled into internal/external, proactive/reactive dimensions of capabilities that positively influence performance upon recovery from disruption. An analysis showing that lean practice bundles lead to better operational performance under high uncertainty context is also done in this thesis (RQ2). Finally, operational resilience (based on routine practices that form the core functions) was found to have stronger synergies than trade-off with lean (based on practice bundles) in times of turbulence (RQ3). This thesis extends the resource-based view to high uncertainty contexts through empirical evidence and shows that resilience (dynamic) capabilities can be built from practices that firms normally employ; the capabilities are sources of better performance and competitive advantages in turbulent business environments. The thesis contributes to the discussion on the paradox of lean and operational resilience based approaches in the same context; lean practices bundles lend themselves to synergy with resilience capabilities, and leverage competitive gains in turbulent times. Practically, findings of this thesis suggest that companies need not abandon their lean implementation to become more resilient. In fact, it shows that lean implementation should be extended to address value chain processes beyond the shop floor for integrative removal of wastes, while being able to flexibly mitigate disruptions. / La sfida della competitività nei mercati globali dipende in larga parte dalla capacità delle imprese di innovare le loro operations per ottenere termini di consegna sempre più stretti, maggior qualità  a prezzi sempre più competitivi; tutto questo in un contesto industriale e socio-economico sempre più incerto e turbolento. Oggi le imprese sono chiamate a prendere decisioni e ad adottare dei modelli di business dagli effetti contrastanti, come ad esempio l’adozione di pratiche che enfatizzano risultati di efficienza produttiva (i.e. lean production) a fianco di strategie e soluzioni che mirano ad accrescere la capacità del sistema di adattarsi dinamicamente ad eventi perturbanti (resilienza), esterni o interni all’organizzazione. Lo scopo di questa ricerca è quello di investigare se e come l'adozione di pratiche potenzialmente contrastanti nell'ambito della gestione delle operations, possono essere utilizzate per mantenere e migliorare la propria posizione competitiva in contesti di forte incertezza e turbolenza dei mercati. La ricerca si compone di una serie di "moduli", ovvero di singoli studi progettati per affrontare sistematicamente e organicamente le tre domande di ricerca fondamentali, la cui risposta conduce alla proposta di tesi. Questa impostazione si è rivelata necessaria a causa del diverso livello di maturità dei concetti studiati e sviluppati nella tesi. Anche la metodologia di ricerca rispecchia le diverse esigenze e peculiarità dei vari aspetti studiati e per questo è stata definita seguendo un approccio misto, in cui metodi di tipo qualitativo sono affiancati da analisi quantitative che implementano tecniche statistiche. In particolare, nei diversi “moduli” (paper) si utilizzano: la critical incident technique, diverse metodiche di studi di caso, e inferenza Bayesiana. La resilienza operativa è stata caratterizzata secondo cinque funzioni principali (core functions): sense, build, reconfigure, re-enhance, e sustain (RQ1). Ciascuna di queste è tradotta a livello operativo attraverso procedure e pratiche stabili (routine) - interne/esterne, proattive/reattive - che sono in grado di influenzare positivamente le prestazioni a seguito di un evento perturbante. Attraverso la ricerca, viene analizzato l’effetto positivo che differenti pratiche lean (lean practice bundles) inducono sulle prestazioni operative in condizioni di incertezza (RQ2). Infine, un’analisi bayesiana sui parametri tipici di un campione selezionato di eventi incidentali a carico di organizzazioni e supply chain globali ha rivelato che tra resilienza operativa (implementata attraverso specifiche  routine) e lean production (implementata attraverso specifiche lean practice bundles) esistono fenomeni sinergici più forti dei meccanismi di trade-off, quando valutati in contesti turbolenti (RQ3). I risultati della tesi contribuiscono ad ampliare e rafforzare un approccio teorico contingent resource-based view all’analisi delle organizzazioni che operano in regimi di forte incertezza (complessità e dinamicità); il contributo originale si concentra in particolar modo nel fornire evidenza empirica che le capacità di resilienza di una organizzazione (dynamic capabilities) possono essere costruite su processi e routine normalmente eseguite dalle imprese. Ove disponibili, queste capacità sono usate come fonte di miglioramento prestazionale e per l’ottenimento di un vantaggio competitivo in contesti turbolenti. Ulteriori evidenze supportano la tesi che un’ampia gamma di lean practices possono essere usate in maniera sinergica per un ulteriore rafforzamento della resilienza operativa. Dal punto di vista pratico e in contrasto con parte della letteratura esistente, la tesi offre ai manager industriali solidi argomenti per non abbandonare la propria strategia lean o limitare i propri obiettivi di efficienza allo scopo di conseguire una maggiore resilienza operativa. Si dimostra infatti che quando l’adozione di partiche lean viene estesa ad una porzione sempre più ampia della value chain, alla conseguente riduzione degli sprechi si associa anche una maggior flessibilità nella gestione di eventi perturbanti o distruttivi. / I dagens turbulenta affärsklimat står företag världen över inför utmaningen att på ett effektivt sätt hantera oförutsägbara händelser och samtidigt förnya sina verksamheter med syfte att uppnå kortare leveranstider, bättre kvalitet och ökad lönsamhet. I dessa ansträngningar möter företagen ofta det skenbara dilemmat av att vissa arbetssätt såsom lean produktion ställs i kontrast mot aktiviteter syftande till att skapa återhämtningsförmåga, dvs angreppssätt och rutiner för att hantera oväntade störningar (operational resilience). Syftet med denna avhandling är att undersöka om och hur dessa två olika arbetssätt, med till synes motstridiga paradigm, kan användas för att uppnå ökad konkurrenskraft för företag verksamma under osäkra marknadsförhållanden. Avhandlingen består av fem artiklar och syftar till att, på ett systematiskt sätt, avhandla tre övergripande forskningsfrågor. Uppdelningen i artiklar motiveras av olikheter i mognadsgrad hos de båda grundbegreppen. En kombination av forskningsmetoder har använts. Den övergripande forskningsstrategin har varit kvalitativ och fallstudiebaserad. Även kritiska händelse metoden, (Critical Incident Technique, CIT) och kvantitativa metoder såsom statistisk analys och Bayesiansk inferens har använts som komplement i några av artiklarna. Resultaten visar att operativ återhämtningsförmåga kan beskrivas i termer av fem kärnfunktioner: uppfatta, formera, konfigurera, återförbättra och bibehålla (RQ1). Resultaten visar även att återhämtningsförmågan kan operationaliseras såsom kombinationer av sammansatta organisatoriska rutiner (practice bundles) vilka kan karaktäriseras i termer av interna/externa och proaktiva/reaktiva dimensioner. Kombinationer av dessa sammansatta organisatoriska rutiner har identifierats vilka både samverkar och förstärker varandra i situationer av störning och efterföljande återhämtning. Vidare visas att implementering av lean rutiner leder till ökad effektivitet i situationer karakteriserade av hög osäkerhet (RQ2). Avslutningsvis visar resultaten att återhämtningsförmåga och lean, operationaliserade som kärnfunktioner respektive sammansatta organisatoriska rutiner, har stark samverkan då det gäller att hantera störningar. Några sammansatta organisatoriska rutiner har dock en trade-off relation till vissa kärnfunktioner (RQ3) Ur ett teoretiskt perspektiv utökar avhandlingen det resursbaserade synsättet till att även inkludera företag som verkar under osäkra marknadsförhållanden. Resultaten visar att (dynamisk) återhämtningsförmåga kan byggas med hjälp av metoder som företagen normalt använder idag (sammansatta organisatoriska rutiner). Genom att omkonfigurera existerande förmågor och rutiner skapas en källa till ökad produktivitet och ökad konkurrenskraft. Således bidrar avhandlingen till diskussionen om det skenbara dilemmat av att en samtidig användning av strategier baserade på lean production och strategier fokuserande på återhämtningsförmåga (operational resilience) samverkar och förstärker varandra snarare än motverkar varandra. Avhandlingens praktiska implikation är att företag inte behöver överge sitt lean arbetssätt för att öka sin återhämtningsförmåga (operational resilience). I själva verket, bör företag utgå ifrån existerande lean arbetssätt och utvidga dessa till att även omfatta processer utanför den direkta tillverkningen. / <p>This thesis is produced as part of the EMJD Programme <em>European Doctorate in Industrial Management (EDIM) </em>funded by the European Commission, Erasmus Mundus Action 1.</p><p>EDIM is run by a consortium consisting of the industrial management departments of three institutions.</p><p>•KTH Royal Institute of Technology, Stockholm, Sweden</p><p>•Politecnico de Milano, POLIMI, Milan, Italy</p><p>•Universidad Politécnica de Madrid, UPM, Madrid, Spain</p><p>QC 20151105</p><p></p>

Transport networks have to provide carriers with time-efficient alternative routes in case of disruptions. It is, therefore, essential for transport network planners and operators to identify sections within the network which, if broken, have a considerable negative impact on the networks performance. Research on transport network analysis provides lots of different approaches and models in order to identify such critical sections. Most of them, however, are only applicable to mono-modal transport networks and calculate indices which represent the criticality of sections by using aggregated data. The model presented, in contrast, focuses on the analysis of intermodal transport networks by using a traffic micro simulation. Based on available, real-life data, our approach models a transport network as well as its actual traffic participants and their individual decisions in case of a disruption. The resulting transport delay time due to a specific disruption helps to identify critical sections and critical networks, as a whole. Therefore, the results are a valuable decision support for transport network planners and operators in order to make the infrastructure less vulnerable, more attractive for carriers and thus more economically sustainable. In order to show the applicability of the model we analyse the Austrian intermodal transport network and show how critical sections can be evaluated by this approach. (authors' abstract)

abstract: The complexity of supply chains (SC) has grown rapidly in recent years, resulting in an increased difficulty to evaluate and visualize performance. Consequently, analytical approaches to evaluate SC performance in near real time relative to targets and plans are important to detect and react to deviations in order to prevent major disruptions. Manufacturing anomalies, inaccurate forecasts, and other problems can lead to SC disruptions. Traditional monitoring methods are not sufficient in this respect, because com- plex SCs feature changes in manufacturing tasks (dynamic complexity) and carry a large number of stock keeping units (detail complexity). Problems are easily confounded with normal system variations. Motivated by these real challenges faced by modern SC, new surveillance solutions are proposed to detect system deviations that could lead to disruptions in a complex SC. To address supply-side deviations, the fitness of different statistics that can be extracted from the enterprise resource planning system is evaluated. A monitoring strategy is first proposed for SCs featuring high levels of dynamic complexity. This presents an opportunity for monitoring methods to be applied in a new, rich domain of SC management. Then a monitoring strategy, called Heat Map Contrasts (HMC), which converts monitoring into a series of classification problems, is used to monitor SCs with both high levels of dynamic and detail complexities. Data from a semiconductor SC simulator are used to compare the methods with other alternatives under various failure cases, and the results illustrate the viability of our methods. To address demand-side deviations, a new method of quantifying forecast uncer- tainties using the progression of forecast updates is presented. It is illustrated that a rich amount of information is available in rolling horizon forecasts. Two proactive indicators of future forecast errors are extracted from the forecast stream. This quantitative method re- quires no knowledge of the forecasting model itself and has shown promising results when applied to two datasets consisting of real forecast updates. / Dissertation/Thesis / Doctoral Dissertation Industrial Engineering 2015

Supply chain management (SCM) is the oversight of materials, information, and finances as they move in a process from supplier to manufacturer to wholesaler to retailer to consumer. Supply chain management involves coordinating and integrating these flows both within and among companies as efficiently as possible. The supply chain consists of interconnected components that can be complex and dynamic in nature. Therefore, an interruption in one subnetwork of the system may have an adverse effect on another subnetworks, which will result in a supply chain disruption. Disruptions from an event or series of events can have costly and widespread ramifications. When a disruption occurs, the speed at which the problem is discovered becomes critical. There is an urgent need for efficient monitoring of the supply chain. By examining the vulnerability of the supply chain network, supply chain managers will be able to mitigate risk and develop quick response strategies in order to reduce supply chain disruption. However, modeling these complex supply chain systems is a challenging research task. This research is concerned with developing an extended Bayesian Network approach to analyze supply chain disruptions. The aim is to develop strategies that can reduce the adverse effects of the disruptions and hence improve overall system reliability. The supply chain disruptions is modeled using Bayesian Networks-a method of modeling the cause of current and future events, which has the ability to model the large number of variables in a supply chain and has proven to be a powerful tool under conditions of uncertainty. Two impact factors are defined. These are the Bayesian Impact Factor (BIF) and the Node Failure Impact Factor (NFIF). An industrial example is used to illustrate the application proposed to make the supply chain more reliable.

Background: Trade regulations, the pandemic, and other disruptions have revealed the vulnerability of long and complex supplier networks. At the same time, there is an increasing need for firms to operate sustainably. An emerging topic in supply chain management literature is the phenomenon of near- and reshoring, addressing the process of moving previously offshored activities closer to or back into the country of origin. However, a missing link in research has been to base findings on in-depth primary data from managers, especially in times of crisis. Therefore, this study explores how relocation decisions are affected by disruption events and the increasing need for sustainable businesses. Purpose: This study aims to discover how the relocation of value-adding activities is influenced by today’s unpredictable business environment and the increasing awareness of economies’ social and environmental impact. Method: The study employs a qualitative research method using an inductive approach by semi-structured interviews with five Swedish manufacturing enterprises with global supply chains. The interviews were conducted with two CEOs, two supply chain managers, one sales and production manager, and one project manager. Conclusion: Recent disruption events have made near- and reshoring decisions a serious consideration amongst business leaders. The findings and analysis showed that relocation decisions are implemented more partially in order to diversify the manufacturing facilities geographically, in order to make supply chains more resilient. Additionally, there exists a great tension between the rapidly changing, unpredictable business environment and the long-term nature of relocation decisions. Sustainability, on the other hand, was identified as a positive side effect rather than the main driver for the relocation of production sites within the traditional manufacturing industry.

We are trying to explore and analyze the possible relationship between digitalization and the valuation of global logistics companies. We focus on the top 70 global logistics companies listed on reputable stock exchanges around the world by market value and go through their annual reports and audited financial accounts with a view to create an insight on their level of digitalization. We observe that there is an obvious increase in attention to digitalization by the logistics service providers throughout the world over the last decade. While we are not in the position to prove a causal relationship between digitalization and valuation, we find that an increase in digitalization awareness is strongly related to growth in both financial performance and market valuation in the logistics industry, especially during the recent disrupting period caused by the COVID-19 pandemic. It seems that investors across different major capital markets, from New York to London, Frankfurt to Tokyo, Hong Kong to Shanghai, are willing to reward digitalization efforts made by a logistics company in the form of both higher absolute value and rate of increase of market capitalization. / Business Administration/Finance

No description available.

This dissertation consists of three essays studying three closely related aspects of supply chain resilience. The first essay is "Value of Supply Disruption Information and Information Accuracy", in which we examine the factors that influence the value of supply disruption information, investigate how information accuracy influences this value, and provide managerial suggestions to practitioners. The study is motivated by the fact that fully accurate disruption information may be difficult and costly to obtain and inaccurate disruption information can decrease the financial benefit of prior knowledge and even lead to negative performance. We perform the analysis by adopting a newsvendor model. The results show that information accuracy, specifically information bias and information variance, plays an important role in determining the value of disruption information. However, this influence varies at different levels of disruption severity and resilience capacity. The second essay is "Quantifying Supply Chain Resilience: A Dynamic Approach", in which we provide a new type of quantitative framework for assessing network resilience. This framework includes three basic elements: robustness, recoverability and resilience, which can be assessed with respect to different performance measures. Then we present a comprehensive analysis on how network structure and other parameters influence these different elements. The results of this analysis clearly show that both researchers and practitioners should be aware of the possible tradeoffs among different aspects of supply chain resilience. The ability of the framework to support better decision making is then illustrated through a systemic analysis based on a real supply chain network. The third essay is "Network Characteristics and Supply Chain Disruption Resilience", in which we investigate the relationships between network characteristics and supply chain resilience. In this work, we first prove that investigating network characteristics can lead to a better understanding of supply chain resilience behaviors. Later we select key characteristics that play a critical role in determining network resilience. We then construct the regression and decision tree models of different supply chain resilience measures, which can be used to estimate supply chain network resilience given the key influential characteristics. Finally, we conduct a case study to examine the estimation accuracy. / Ph. D.