Scenario analysis and disaster preparedness for port and maritime logistics risk management

A content-aware corpus-based model for analysis of marine accidents

In the past decades, marine accidents brought the serious loss of life and property and environmental contamination. With the accumulation of marine accident data, especially accident investigation reports, compared with subjective reasoning based on expert experience, data-driven methods for analysis and accident prevention are more comprehensive and objective. This paper aims to develop a content-aware corpus-based model for the analysis of marine accidents to mine the accident semantic features. The general research framework is established to combine accident data, expert prior knowledge, and semi-automated natural language processing (NLP) technology. The NLP models are optimized, fused, and applied to the case study of ship collision accidents. The results show that the proposed model can accurately and quickly extract hazards, accident causes, and scenarios from the accident reports, and perform semantic analysis for the latent relationships between them to extend the accident causation theory. This study can provide a powerful and innovative analysis tool for marine accidents for maritime traffic safety management departments and relevant research institutions.

An integrated System Dynamics model for Closed Loop Supply Chains under disaster effects: The case of COVID-19

For a Closed Loop Supply Chain (CLSC), disaster is a risk source of unknown-unknowns, which may result in production disruptions with significant consequences on -but not limited to-profitability. For this reason, we provide a System Dynamics (SD)-based analysis for disaster events on the operation of CLSCs in order to study the system response (production/collection/disassembly/remanufacturing/recycling rates, inventories, cost, profit). This response is examined through the dynamics at a manufacturer, parts producer, collector, and disassembly center level, by providing control mechanisms for resilient CLSCs under disaster effects. In this dynamic analysis, COVID-19 is treated as a disaster event. Five different business scenario settings are presented for the manufacturer, which are considered as alternative mitigation policies in responding to product demand. The extensive simulation results provide insights for policy-makers, which depend on the reduction in manufacturer's production, reduction in product demand and duration of recovery period which are considered as causal effects due to the COVID-19 outbreak. For all combinations, holding base stocks during the pre-disaster period is proposed as the best mitigation policy in terms of manufacturer's inventory. In terms of economic impact, holding base stocks or coordination with third party are revealed as the best choice depending on the combination, while remote inventory policy adoption as the worst choice.

A Dynamic Analysis for Mitigating Disaster Effects in Closed Loop Supply Chains

The increased level of complexity in the case of Closed Loop Supply Chains (CLSCs) turns them into vulnerable systems under a disaster event. The latter calls for a methodological approach that allows a dynamic study under alternative policies in mitigating the disaster effects with a focus on creating sustainable CLSCs. For this reason, we provide a System Dynamics (SD)-based analysis for disaster events on the operation of CLSCs. By “disaster event”, we mean three different categories taking shape on the basis of duration. Furthermore, three different demand patterns emerging due to the disaster event are examined. We assume that the disaster event affects the manufacturer, and we examine the system response under different mitigation policies. For each demand pattern two different mitigation policies at the manufacturer level are examined by considering the total CLSC profit and demand backlog as measures of policy performance. For each combination, extensive simulation experimentation reveals sustainable policy recommendations under alternative settings regarding the reduction in the manufacturer’s production.

From resilience to satisfaction: Defining supply chain solutions for agri-food SMEs through quality approach

Since it is an important human need and many organizations are involved in the value chain, the agricultural food supply chain is exposed to various risks that arise naturally or through human actions. This study aims to develop the application of a quality function deployment approach to increase the resilience of the food supply chain by understanding customer needs and logistical risks in the food supply chain. In-depth studies with empirical analysis were conducted to determine the importance of customer needs, food supply chain risks, and actions to improve supply chain resilience of SMEs in the agri-food industry. The result shows that the top three customer needs are "attractive, bright color", "firm texture" and "fresh smell". The top three risks in the agri-food supply chain are "improper storage," "Harvest Failure" and "Human Resource Risks" and the top three resilience actions are "continuous training," "preventive maintenance," and "supply chain forecasting." The implications of this study are to propose an idea that broadens the perspective of supply chain resilience in the agri-food industry by incorporating the needs of customers in considering how to mitigate the existing risks to the satisfaction of customers, and it also highlights the relatively low skill and coordination of the workforce in agri-food supply chains.

Re-Strategising Government Palliative Support Systems in Tackling the Challenges of COVID-19 Lockdown in Lagos State, Nigeria

This research covered the palliative material distribution project in Lagos State, Nigeria, during the lockdown and restriction on movement because of COVID-19 pandemic. The study engaged reports from extant literature and tertiary data sources such as the newspapers, the Internet, and website source. Relevant data gathered from these sources were conceptually analysed and discussed along with extant literature. The research also adopted the use of rich pictures for further presentation of the research. A key finding from the research is the need to redesign the distribution process and consider proper structuring of the project. And further engagement with the affected stakeholders to address crucial issues such as marginalisation that can defeat the purpose, which is to emancipate the affected indigents of the State from the harrowing effects of COVID-19 lockdown and other emergencies-related critical incidences such as starvation and criminalities. The study proposed a model for a resilience approach to effectively address the current palliative distribution process challenges in Lagos State, the epicentre of COVID-19 in Nigeria.

Decision-Making of Port Enterprise Safety Investment Based on System Dynamics

Safety is the premise of efficiency and effectiveness in the port operation. Safety investment is becoming a vital part of port operation in current era in order to overcome different types of hazards the port operation exposed to. This paper aims to improve the safety level of port operation through analyzing its influencing factors and exploring the interactions between the safety investment and system risk level. By analyzing the key factors affecting the port operation and their mutual relationship within a man–machine–environment–management system, a decision-making model of safety investment in port enterprise was established by system dynamics (SD). An illustration example and a sensitivity analysis were carried out to justify and validate the proposed model. The results show that increasing the total safety investment of port enterprises, improving the safety management investment on personnel, and strengthening the implementation effect of investment can improve the degree of port security to a certain extent. The strength of the proposed work is its practical application in current scenarios using real time data and the ability to provide a baseline approach for port enterprises to formulate safety investment strategy.

A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain

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.

Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic

The increasingly global context in which businesses operate supports innovation, but also increases uncertainty around supply chain disruptions. The COVID-19 pandemic clearly shows the lack of resilience in supply chains and the impact that disruptions may have on a global network scale as individual supply chain connections and nodes fail. This cascading failure underscores the need for the network analysis and advanced resilience analytics we find lacking in the existing supply chain literature. This paper reviews supply chain resilience literature that focuses on resilience modeling and quantification and connects the supply chain to other networks, including transportation and command and control. We observe a fast increase in the number of relevant papers (only 47 relevant papers were published in 2007–2016, while 94 were found in 2017–2019). We observe that specific disruption scenarios are used to develop and test supply chain resilience models, while uncertainty associated with threats including consideration of “unknown unknowns” remains rare. Publications that utilize more advanced models often focus just on supply chain networks and exclude associated system components such as transportation and command and control (C2) networks, which creates a gap in the research that needs to be bridged. The common goal of supply chain modeling is to optimize efficiency and reduce costs, but trade-offs of efficiency and leanness with flexibility and resilience may not be fully addressed. We conclude that a comprehensive approach to network resilience quantification encompassing the supply chain in the context of other social and physical networks is needed to address the emerging challenges in the field. The connection to systemic threats, such as disease pandemics, is specifically discussed.

Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic

The increasingly global context in which businesses operate supports innovation, but also increases uncertainty around supply chain disruptions. The COVID-19 pandemic clearly shows the lack of resilience in supply chains and the impact that disruptions may have on a global network scale as individual supply chain connections and nodes fail. This cascading failure underscores the need for the network analysis and advanced resilience analytics we find lacking in the existing supply chain literature. This paper reviews supply chain resilience literature that focuses on resilience modeling and quantification and connects the supply chain to other networks, including transportation and command and control. We observe a fast increase in the number of relevant papers (only 47 relevant papers were published in 2007-2016, while 94 were found in 2017-2019). We observe that specific disruption scenarios are used to develop and test supply chain resilience models, while uncertainty associated with threats including consideration of "unknown unknowns" remains rare. Publications that utilize more advanced models often focus just on supply chain networks and exclude associated system components such as transportation and command and control (C2) networks, which creates a gap in the research that needs to be bridged. The common goal of supply chain modeling is to optimize efficiency and reduce costs, but trade-offs of efficiency and leanness with flexibility and resilience may not be fully addressed. We conclude that a comprehensive approach to network resilience quantification encompassing the supply chain in the context of other social and physical networks is needed to address the emerging challenges in the field. The connection to systemic threats, such as disease pandemics, is specifically discussed.