The Impact of COVID-19 on Supply Chains and E-commerce Logistics

As a result of the COVID-19 pandemic, supply, demand, and logistics have all been affected. Due to its unpredictable severity, the pandemic has highlighted the need to modify the existing supply chain model, the consumer structure model, and the digitization of markets. At the same time, the situation under COVID-19 offers increasing opportunities for e-commerce, including new business models and online commercial activities. This master's thesis aims to analyze how COVID-19 will affect global supply chains and e-commerce. Moreover, it will try to analyze the practices of major e-commerce platforms during the pandemic to determine whether there are opportunities for innovation and development in the future. The study will examine how retailers adapted to supply chain disruptions caused by the pandemic from a practical perspective and highlight the critical role of technology in these processes. The research provides insights into how companies are coping with long-term disruptions. The study we conducted used a qualitative approach, which included a case study and a SWOT analysis. In addition, we analyzed quantitative operational data from public financial reports released by JD.com.Our study examines the effects of a pandemic on supply chains. It also summarises the challenges faced by the retail sector and the strategies used by JD.com during the challenging period. During the pandemic, JD.com was able to handle the various aspects of its supply chain management through an integrated supply chain and intelligence platform. This study presents a supply chain resilience analysis by using actual operational data. Moreover, It suggests that companies should consider operational flexibility and collaboration outside the supply chain to adapt to significant supply chain disruptions like COVID-19

Data Analytics as an Enabler to Strengthen Supply Chain Resilience

This thesis examines the role of data analytics in building supply chain resilience. The aim of the study is to investigate how companies can use data analytics to identify potential supply chain disruptions, mitigate risks, and improve supply chain performance. To achieve this aim, case studies of a companies that has successfully implemented data analytics in its supply chain operations was conducted. The case study analytics included an examination of the specific tools and techniques used, the data sources and types of data analysed, and the insights gained from the analytics. The study also explored the challenges faced during the implementation of data analytics and analysed the effectiveness of these analytics in building supply chain resilience. Case firms were selected based on business and product type. This study includes companies with electronic product and component supply chains. Interviewees were selected based on their data-driving experience and supply chain operations exposure. Seven supply chain specialists from six case firms were interviewed semi-structured. The results show that data analytics provide valuable insights for supply chain management and help companies to proactively identify and mitigate risks. The study also highlights the importance of data quality, data integration, and the need for new skills and capabilities in implementing data analytics in the supply chain. The findings of 4 the study have practical implications for supply chain managers and provide a basis for future research in this area. Overall, the thesis contributes to the growing body of literature on the role of data analytics in building supply chain resilience and provides insights into the challenges and opportunities associated with implementing these analytics in practice

Ten-tier and multi-scale supplychain network analysis of medical equipment: Random failure and intelligent attack analysis

Motivated by the COVID-19 pandemic, this paper explores the supply chain viability of medical equipment, an industry whose supply chain was put under a crucial test during the pandemic. This paper includes an empirical network-level analysis of supplier reachability under Random Failure Experiment (RFE) and Intelligent Attack Experiment (IAE). Specifically, this study investigates the effect of RFA and IAE across multiple tiers and scales. The global supply chain data was mined and analyzed from about 45,000 firms with about 115,000 intertwined relationships spanning across 10 tiers of the backward supply chain of medical equipment. This complex supply chain network was analyzed at four scales, namely: firm, country-industry, industry, and country. A notable contribution of this study is the application of a supply chain tier optimization tool to identify the lowest tier of the supply chain that can provide adequate resolution for the study of the supply chain pattern. We also developed data-driven-tools to identify the thresholds for breakdown and fragmentation of the medical equipment supply chain when faced with random failures or different intelligent attack scenarios. The novel network analysis tools utilized in the study can be applied to the study of supply chain reachability and viability in other industries.Comment: 47 page

The effects of supply chain viability on supply chain performance and marketing performance in case of large manufacturing firm in Ethiopia

Goal: COVID-19 has put the supply chain (SC) through exceptional shocks and disruptions that have never been seen before. It put existing SCs' capabilities to a severe test. Moreover, due to the pandemic, demand and supply have been imbalanced, which has led to questions about societal and SC survivability. This study examines the effects of firms' SC viability on SC and marketing performance. Design/Methodology/Approach: An explanatory research design was employed to examine the relationship between the antecedents of SC viability, SC, and marketing performance using partial least squares (PLS) structural equation modeling (SEM). Moreover, 5-point Likert scale questionnaires are used as a data collection instrument. Results: The finding shows that both SC resilience, SC agility, and sustainable SC have a positive effect on SC performance. Further, SC viability [SC resilience + SC agility + sustainable SC] has a positive effect on SC performance. SC performance also play partial mediation between SC viability and marketing performance. Limitations of the investigation: The study focused only on a limited number of large manufacturing companies in Ethiopia, which excluded other medium- and small-sized firms due to the ongoing war in the northern part of the country. Moreover, the study focused only on one dimension of sustainability (social aspect). Implicações práticas:  O estudo mostra às empresas que os métodos tradicionais de avaliação de risco são insuficientes e não serão mais suficientes para superar uma grave disrupção. Em vez disso, o estudo recomenda que as empresas trabalhem usando determinação antecipada de falhas (AFD) e uma abordagem de equipe vermelha para se preparar para eventos 'desconhecidos'. Além disso, o estudo traz um modelo prático e holístico que mostra a relação entre viabilidade de SC e desempenho de SC e marketing. Originalidade/Valor:  Nenhum dos estudos até agora em SC testou os conceitos de sistemas de viabilidade em SCM adotando disciplinas como modelagem ecológica, biológica e cibernética usando PLS-SEM. Consequentemente, contribui para a literatura existente, mostrando novas evidências empíricas de uma forte relação entre viabilidade SC, desempenho SC e desempenho de marketing

Risk Management In Supply Chain Integration Using A Business Intelligence Optimization Approach

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThe goal of this proposal is to develop a theoretical model that will assist organizations in building and adapting their supply chains to a new, better, and more robust model, using technology and tools that were not available just a few years ago. The coronavirus pandemic has uncovered resilient weaknesses in countries and organizations, and we hope to use Data Analytics and Business Intelligence approaches to turn those weak spots into strengths and competitive advantage through this study. Having this in mind, this study aims to identify the association between supply chain risk management (SCRM) and business intelligence architectures. Thus, this study aims to fill the gap of information and studies in this area by providing relevant inputs that may be used on other studies in this field

Supply chain risk management : systematic literature review and a conceptual framework for capturing interdependencies between risks

The purpose of this research is to conduct a comprehensive and systematic review of the literature in the field of 'Supply Chain Risk Management' and identify important research gaps for potential research. Furthermore, a conceptual risk management framework is also proposed that encompasses holistic view of the field. 'Systematic Literature Review' method is used to examine quality articles published over a time period of almost 15 years (2000 - June, 2014). The findings of the study are validated through text mining software. Systematic literature review has identified the progress of research based on various descriptive and thematic typologies. The review and text mining analysis have also provided an insight into major research gaps. Based on the identified gaps, a framework is developed that can help researchers model interdependencies between risk factors

Optimisation of energy supply chains considering sustainability aspects

The supply chain of energy sources and, in particular, natural gas is prone to endogenous and exogenous disruptions that affect the system’s operational performance and flow capacity, thereby contributing to greenhouse gases (GHG) through methane (CH4) emissions. Although there are operational strategies to improve the gas supply chain, the need for resilience-driven optimisation that provides a system-based workflow to mitigate continuous and prolonged disruptions in the midstream remains crucial. This study focuses on developing a novel optimisation model that investigates the potential of a complementary design in the natural gas supply chain as a mitigation approach, enhancing throughput delivery without disconnections, and exploring the potential retrofit benefits of an existing natural gas supply chain infrastructure. To achieve this, optimisation in the supply chain’s transmission echelon is deployed to increase flexibility capacity, reduce gas losses, and minimise emissions. In this study, a lateral relief pipeline in the transmission node is proposed as an alternative pathway for gas flow to increase the resilience of the supply chain. This proposed strategy transmits excess trapped gas between inlet and outlet nodes during plant shutdowns within operational and contractual constraints. This redundancy compensates for downtime and pressure drop caused by shutdowns of system nodes during disruptions. The objective of the optimisation problem is to maximise throughput through flow flexibility and minimise carbon dioxide (CO2) emissions through a reduction in gas losses. Different scenarios are introduced to achieve the objective function optimum. Firstly, the baseline scenario (BS) of the system’s status is analysed under normal conditions to identify the flow rate gap. Then the disruption scenario (DS) is introduced where the impact of the lateral relief pipeline to mitigate unplanned shutdowns is analysed by using defined parameters in a steady state (SS). With a fixed shutdown period, the variation in plant node performance is examined at different flow rates. Lastly, in a transient state (TS), the pressure variation between the inlet and the outlet nodes in the mainline and when the relief pipeline node is opened is investigated. All scenarios affect the supply chain’s overall performance; therefore, the resulting flow rates are compared for optimum decision making. A multi-stream, multi-period, single-product transmission model to satisfy consumer demand within a given time frame is developed for the simulation, formulated as a mixed-integer linear programming (MILP) model, and applied within an optimisation framework where interruptions to the supply chain are studied to optimise the strategic planning problem. The optimisation procedure is formulated in a deterministic environment, and the model is run using General Algebraic Modelling System (GAMS) 26.14 with the CPLEX solver 12 in an intel ® core ™ i7 and a zerooptimality gap. Data collected from gas companies in the case study country are analysed and used to forecast and calculate the gas flow rate and the required capacity to meet growing demand. The data accessed enhance the applicability of the proposed model. Also, the interactions between the nodes in the supply chain are adjusted to mitigate interruptions and increase overall efficiency. Furthermore, an economic analysis of the proposed complementary design is carried out to ascertain possible tradeoffs between costs and resilience. Finally, a sensitivity analysis is conducted to assess the impact of key parameters on the overall model’s prediction

Building Resilient Supply Chains in Industry 4.0 : The case of the medical equipment industry

The medical equipment industry is facing a new set of challenges in the era of Industry 4.0, where supply chains are becoming more complex and vulnerable to disruptions. The research question is "How to build resilient medical equipment supply chains in industry 4.0?" The study employs a qualitative approach, including a single case study, using interviews. The study identifies the critical success factors and the main challenges faced by the medical equipment industry in building resilient supply chains. The study also presents a framework for building resilient medical equipment supply chains in Industry 4.0, which includes an interdependency of strategies to enhance the resilience of medical equipment supply chains by addressing the different phases of supply chain resilience. This thesis contributes to the existing literature by providing insights into the influence of Industry 4.0 on supply chain resilience in the medical equipment industry, and by providing practical recommendations for building resilient medical equipment supply chains