This thesis presents research undertaken to understand and enhance resilience in the UK Food and Drink Manufacturing Sector. It focuses on the development of a conceptual framework which establishes how specific vulnerabilities link to individual mitigation strategies available to the sector and the impact of such strategies on wider sustainability. The research in this thesis is divided into four main parts. The first part consists of three complementary review chapters exploring resilience as a theoretical concept, resilience in the UK Food and Drink Manufacturing sector and existing methods used to study and/or enhance resilience. The second part of the thesis begins by describing how the pragmatic philosophy and abductive stance underpinning the research, in combination with review findings, helped to determine the research techniques used in this work, which included the systematic review process and the mixed methods case study. Next, the research facilitating a novel conceptual framework describing how real-time vulnerabilities can be identified and mitigated in a way that is complimentary to the wider sustainability of the organisation is discussed. The third part of the thesis describes the practical set of tools, presented in the form of a workbook, which enable a Food and Drink Manufacturer to utilise the conceptual framework teachings to enhance their own resilience. The final section details key conclusions regarding the conceptual nature and practical enhancement of resilience for Food and Drink Manufacturers and the wider food system, as well as opportunities for future work. The conceptual integrity and practical usefulness of the conceptual framework and its derivative workbook toolset have been demonstrated through case studies with two UK Food and Drink Manufacturers. Results suggest two major benefits of the framework are the ability to identify an organisation's vulnerabilities based on actual mapping of their supply network and the ability to evaluate mitigating resilience strategies based on their broader impacts elsewhere within the organisation. In summary, the research reported in this thesis has concluded that resilience cannot be seen as a one-off solution for returning to how things were before disruption, but instead is a constant process of learning and adaptation in response to a company's ever-changing operating environments. The framework and workbook presented provide a novel and practical method for UK Food and Drink Manufacturers, of all sizes and production ranges, to identify and respond to their evolving vulnerabilities, as well as providing much needed synthesis and directions for future work at an academic level.

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This dissertation provides empirical and theoretical support for the antecedents and consequences of cyber resilience via three essays on cyber resilience. Essay 1 comprises 2 studies using a multi-method empirical research effort to determine whether emphasizing suppliers' implementation and use of business continuity management (S-BCM) is actually beneficial to buyers. In Study 1, data from 150 managers was collected via a survey-based questionnaire to determine whether buyers' adoption of monitoring supplier operational performance (MS-OP) and monitoring S-BCM (MS-BCM) enhances S-BCM implementation and use. Evidence from Study 1 suggests that MS-BCM is more effective than MS-OP. Moreover, the results suggest that while buyer power positively augments the effectiveness of MS-BCM, it actually has a diminishing effect on the effectiveness of MS-OP. Study 2 uses the data of 114 managers from a vignette-based experiment to determine whether S-BCM leads to improved buyer operational and financial performance. Study 2 offers evidence that confirms the positive link between S-BCM and buyer operational and financial performance. The results also suggest that the use of reward power further enhances the association between S-BCM and buyer performance. Using two studies, Essay 2 examines how supply chain power and learning can be related to cyber resilience capability. Study 1 indicated that powerful buyers and supply chain learning from new knowledge contribute to visibility to build cyber resilience while dominant suppliers are reluctant to share information. The results of Study-2 show that supply chain and operations managers believe that companies and their suppliers would have better operational performance if they invest in the accuracy of visibility. Moreover, supply chains properly can avoid, maintain, and recover from cyber disruption when real-time information is available. Essay 3 focuses on the role of downstream complexity along with enterprise resource planning (ERP) in building cyber resilience in supply chains. The results reveal that ERP systems help supply chains to mitigate the negative effect of downstream complexity on the impact of information sharing in a secure system needed to build cyber resilience in times of data breaches and cyber-attacks. Although the use of information technology increases cyber risk, supply chain managers should take advantage of ERP systems to mitigate the negative effect of complexity in supply chain cyber resilience.

The purpose of this three-essay dissertation is to synthesize and extend the effects of decentralization in decision-making and supply chain complexity in the context of supply chain resilience (SCRES).First essay contributes to theory and practice by expanding resilience thinking into including supply chain orientation and organizational structure and their implications and also responds to prior research arguing for the importance of identifying organizational factors that improve supply chain resilience. Second essay contributes to the supply chain organizational structure and SCRES literature by not just providing empirical support for decentralization of decision making in times of disruptions but more precisely by showing the factors that either impede or facilitate decentralization at the organizational level. Understanding the interplay among these factors is critical to explaining the lack of success for decentralization in the context of SCRES. Third essay contributes to practice by reviewing some of the major complexity drivers present in the supply chains and providing strategies along with a four-step process that practitioners can use to manage complexity.

Yes / The purpose of this research is to establish the necessary and sufficient conditions for food safety and security during pandemic outbreaks, focusing on the case of COVID-19 to ensure resilience of the food supply chain. The study emphasises on the complexity theory of fuzzy set Qualitative Comparative Analysis (fsQCA), to establish a result-driven definition of Industry 5.0 (I5.0) during and post pandemics. The results of this study revealed that a combination of conditions derived from pandemic policy related reforms and I5.0 enablers will assist manufacturers and suppliers in establishing food safety and security during and post the COVID-19 era in a developing economy. Food safety and security being the goal, based on a survey of 140 food companies, this study provides insights to manufacturers and policymakers to enable selective implementation of I5.0 enabling technologies and pandemic policies.

Yes / Purpose: The aim of this research is to evaluate if the Complex Adaptive Systems theory can be used to explain resilience strategies within the pharmaceutical supply chain Research Approach: An in depth review of literature surrounding resilience in the pharmaceutical supply chain. In order to pursue this study agenda, data was collected from Scopus, the largest peer review journal as well as EBSCOhost. The PRISMA guideline was adopted in the systematic review process where 34 peer reviewed papers in the field of CAS, supply chain and supply chain resilience were identified with respect to methodologies employed, location of the study and approaches. Findings and Originality: The systematic review of literature shows that there are inherent similarities between the concept of resilience and the CAS theory. The CAS theory explains that PSC’s are dynamic, have emergent behaviours complex, adaptive, interconnected as well as possess schemas that regulate their operations. Hence if resilience strategies are to be employed to mitigate disruptive events they need to be harnessed in a manner to fit this particular supply chain. This work is innovative as it provides a new insight into the contemporary discourse on resilience strategy creation and deployment, examining the use of this theory in the PSC, and thus provides original contribution. Research Impact: This study contributes to the existing literature base, by providing theoretical underpinnings in the area of resilience and the pharmaceutical supply chain. This furthers the CAS agenda, SCR agenda and also presents an innovative output which warrants more detailed analysis and feasibility testing. Practical Impact: Complexity principles are multi-scaled and multi-domain and as such the suggestions put forward in this theoretical framework can be adopted in various supply chain networks as well as disruptive events. It provides new insights with regards to structures for managers seeking to design and improve resilience supply chains, a key element of which is the adoption of a holistic analysis by SC managers when developing resilience strategies. This is critical if disruptions are to be identified and mitigated before their impact is felt.

In recent years, rare catastrophic disasters have triggered pharmaceutical supply chain disruptions, resulting in product shortages and other problems that have negatively impacted healthcare delivery. Since the health sector is part of many nations’ critical infrastructure, ensuring minimal disruption in the supporting supply chains is an essential aspect of national security. While traditional risk management approaches have proven adequate for handling independent routine operational risks, these methods are inadequate for infrequent disruptive risks that propagate further risks, producing a domino effect in complex systems. Since today’s pharmaceutical supply chains have many characteristics of complex systems, elucidating the disruptive risks and required resilience capabilities, through knowledge gained from actual disasters, can be valuable in developing mitigation strategies. This research aims to investigate two catastrophic disasters that disrupted pharmaceutical supply chains in recent years. The first case explores the impact of a localized Category IV hurricane that hit Puerto Rico and disrupted the supply chain for saline, an essential product used in the treatment of many illnesses. The risk events that propagated from the disaster are identified and modeled using a Bayesian network to determine where resilience should be strengthened. In accordance with ISO 31000 risk management guidelines, Bayesian networks have been identified as appropriate tools for modeling complex system risks. The second case employs a qualitative research study on the vaccine supply chain supporting mass immunization during the COVID-19 pandemic. A content analysis is conducted to extract the insights of over 100 professionals on disruptors and resilience capability requirements of the COVID-19 vaccine supply chain. The results indicate that a large and diverse set of risk factors and resilience capabilities are pertinent to pharmaceutical supply chains during localized severe weather and global pandemic disasters. Furthermore, to mitigate the impacts of severe weather risk in the case of Puerto Rico, the predominant type of resilience required is absorptive capacity, while in the case of the mass immunization vaccine supply chain, adaptive capacity is key. These findings should be useful to national leaders, pharmaceutical supply chain and healthcare sourcing managers, disaster preparedness officers, and others charged with pharmaceutical supply chain resilience.

Background: COVID-19 has brought so many changes in the business environment and in the ways of doing business. Food retail companies in Sweden have been trying to cope with the changes and challenges and have made necessary decisions to become resilient. It is in their urge to become resilient; however, the implementation is arduous at times. Purpose: The purpose of the thesis is two-folded. One is to know the supply chain inefficiencies, and the other is to understand how the inefficiencies can be mitigated through the actions of the supply chain professionals. Method: Semi-structured questions have been asked in the interviews to gather in-depth insights from the industry expert. The interviews were taken from the branch managers of food retail stores in Sweden. The analysis has been done based on the content analysis. Findings: Content analysis assisted the emergence of the factors. It was done by analyzing the quotes from the branch managers. Therefore, the relationship between the characteristics and the RBV theory has been scrutinized. Conclusion: The purpose of the thesis was to find the inefficiencies of the food retail supply chain in pandemic times. Also, it was to find the solution about how the supply chain inefficiencies can be tackled to ensure supply chain resilience in the food retail stores in Sweden. For that purpose, data have been collected right from the field where the action takes place, and therefore, the data have been analyzed. Hence, the problems have been found, and the solutions have been recommended.

Resilience has been measured using qualitative and quantitative metrics in engineering,economics, psychology, business, ecology, among others. This dissertation proposes a resilience metric that explicitly incorporates the intensity of the disruptive event to provide a more accurate estimation of system resilience. A comparative analysis between the proposed metric and average performance resilience metrics for linear and nonlinear loss and recovery functions suggests that the new metric enables a more objective assessment of resilience for disruptions with different intensities. Moreover, the proposed metric is independent of a control time parameter. This provides a more consistent resilience estimation for a given system and when comparing different systems. The metric is evaluated in the study of community resilience during a pandemic influenza outbreak and the analysis of supply chain resilience. As a result, the model quantifies constant, increasing and decreasing resilience, enables a better understanding of system response capabilities in contrast with traditional average performance resilience metrics that always capture decreasing resilience levels when the disruptive events magnitude increases. In addition, resilience drivers are identified to enhance resilience against disruptive events. Once resilience drivers have been found, then a multi-objective resource allocation model is proposed to improve resilience levels. Previous resilience optimization models have been developed mainly based on a single resilience metric. The existing bi-objective models typically maximize resilience while the recovery cost is minimized. Although the single metric approach improves system resilience some of their limitations are that the solution is highly dependent on the selected resilience index and generally few optimal points are found. To overcome the rigidity of a unique metric a bi-objective model is proposed to maximize two key resilience dimensions, the absorptive and restorative capacities. This approach has the potential to offer multiple non-dominated solutions increasing decision makers alternatives where the single metric solutions are included.

The first primary objective of this dissertation is to develop a framework that can quantitatively measure complexity of manufacturing systems in various configurations, including conjoined and disjoined systems. In this dissertation, an analytical model for manufacturing systems complexity that employs information entropy theory is proposed and verified. The model uses probability distribution of information regarding resource allocations that are described in terms of interactions among resources for part processing and part processing requirements. In the proposed framework, both direct and indirect interactions among resources are modeled using a matrix, called interaction matrix, which accounts for part processing and waiting times. The proposed complexity model identifies a manufacturing system that has evenly distributed interactions among resources as being more complex, because under disruption situation more information is required to identify source of the disruption. In addition, implicit relationships between the system complexity and performance in terms of resource utilizations, waiting time, cycle time and throughput of the system are studied in this dissertation by developing a computer program for simulating general job shop environment. The second primary objective of this dissertation is to develop a mathematical model for measuring the vulnerability of the supply chain systems. Global supply chains are exposed to different kinds of disruptions. This has promoted the issue of supply chain resilience higher than ever before in business as well as supporting agendas. In this dissertation, an extension of the proposed measure for manufacturing system complexity is used to measure the vulnerability of the supply chain systems using information entropy theory and influence matrix. We define the vulnerability of supply chain systems based on required information that describes the system in terms of topology and interrelationship among components. The proposed framework for vulnerability modeling in this dissertation focus on disruptive events such as natural disasters, terrorist attacks, or industrial disputes, rather than deviations such as variations in demand, procurement and transportation.