Supply chain risk management: A content analysis-based review of existing and emerging topics

Emrouznejad, Ali; Abbasi, Sina; Sıcakyüz, Çiğdem

doi:10.1016/j.sca.2023.100031

Cited by 40 publications

(5 citation statements)

References 108 publications

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“…A recently promising direction in risk assessment is machine learning (ML) technology that includes deep learning, support vector machines, decision trees, neural networks, Bayesian networks, logistic regression, random forest, ensemble learning, clustering, extreme learning machine, and naive Bayes (Emrouznejad et al, 2023;Yang et al, 2023). The problem in using ML algorithms is the preparation of data sets and the difficulty of interpreting the results.…”

Section: Transport Risk Assessment Techniquesmentioning

confidence: 99%

Transport Risks in the Supply Chains – Post Covid-19 Challenges

Chodakowska,

Bazaras,

Sokolovskij

et al. 2024

Journal of Business Economics and Management

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The COVID-19 pandemic has caused major disruptions in global supply chains with unforeseen and unpredictable consequences. However, the pandemic was not the only reason why supply chain risk management has become more crucial than ever before. In the last decade, the occurrence of previously merely theoretical risks has emphasised the importance of risk management in supply chains. This has increased interest in risk assessment and management, COVID-19 and other disaster impact studies and proposals for more stable and resilient supply chains. This article addresses the problem of transport risk in supply chains in the context of COVID-19. Particular attention is paid to quantitative approaches. Identifying and quantifying risks and modelling their interdependencies contribute to the stability of the supply chains. The analysis presents the current state of knowledge and can serve as a guide for further research. It highlights transport risk management in supply chain management as an important area of investigation. In light of the challenges of the COVID-19 pandemic, the article proposes an approach to transportation risk assessment based on quantitative assessment and interconnection of risk factors.

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Section: Transport Risk Assessment Techniquesmentioning

confidence: 99%

Transport Risks in the Supply Chains – Post Covid-19 Challenges

Chodakowska,

Bazaras,

Sokolovskij

et al. 2024

Journal of Business Economics and Management

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“…The issues at the strategic level of logistics engineering and supply chain management (SCM) relate to the number of distribution warehouses and their locations, the customers assigned to each distribution center, the number of vehicles that deliver customer orders and their routes, etc. If location and route planning are not considered simultaneously, supporting SC costs will increase [31][32][33][34][35][36]. Bektas and Laporte (2011) [37] considered pollution in the vehicle routing problem and presented their proposed model.…”

Section: Literature Review 21 Related Studiesmentioning

confidence: 99%

Designing the Location–Routing Problem for a Cold Supply Chain Considering the COVID-19 Disaster

Abbasi,

Moosivand,

Vlachos

et al. 2023

Sustainability

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In this study, a location routing problem (LRP) model was considered for the distribution network of multiple perishable food items in a cold supply chain (CSC) where vehicles can refuel at gas stations during light of the COVID-19 disaster. Fuel consumption is assumed to vary depending on the cargo transported between nodes when using a non-standard fuel fleet. The problem was formulated as a mixed-integer linear programming (MILP) model to reduce the production of carbon dioxide (CO2). The model was validated using several numerical examples which were solved using the software, LINGO 17.0. The results show that fuel consumption could be reduced in this case. Due to the complexity of the problem, genetically simulated annealing algorithms were developed to solve the actual size problems, and their performance was also evaluated.

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“…While relief distribution aims to provide emergency needs to the population in the shortest possible time and at the lowest possible cost, the flexibility to respond to dynamic demands may be even more vital. The difficulties in crisis distribution are caused by an absence of confidence regarding supply and demand, a lack of predictability about journey times owing to infrastructural obstacles, the channel of communication breaks, logistics issues, security concerns, and a lack of resources [20]. Previous research in this area can be divided into three categories: location-allocation, transportation, and a combination of location-allocation and transportation issues.…”

Section: Related Workmentioning

confidence: 99%

Designing the Distribution Network of Essential Items in the Critical Conditions of Earthquakes and COVID-19 Simultaneously

Abbasi,

Vlachos,

Rekabi

et al. 2023

Sustainability

Self Cite

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Current societies must make the necessary plans for effective responses and to reduce the destructive effects of disasters. For this reason, this research has developed a mathematical programming model under uncertainty for earthquake relief and response during COVID-19. In the presented model, the possibility of facility failure is considered according to the intensity of the earthquake and COVID-19 to increase reliability. The simultaneous occurrence of these disasters presents unique challenges in ensuring the timely delivery of essential supplies to affected regions. Distribution centers (DCs) are considered to be of two types: the first type is local DCs, which use public centers and are close to accident points. These types of centers are prone to failure because they use public facilities. Another type is the reliable DCs built outside the disrupted area, which have a very low probability of loss due to spending more money to build them. In addition, to consider the reliability capabilities, the new model has tried to provide a complete model for transportation planning by considering the multi-trip mode of vehicles. Moreover, this model considers distance restriction at the demand point for the first time because of COVID-19 during the earthquake. The proposed network design aims to offer effective solutions in promptly delivering essential items to affected areas, thereby enhancing disaster management strategies and minimizing the impact of these crises on vulnerable populations. Uncertainty is presented using the probability approach based on the modeling scenario and a case study from the city of Istanbul to illustrate the performance of the suggested model. Finally, the suggested mode is solved with an Lp-metric and goal programming (GP) approach. The results show that in this case, the proposed model shows that effective and efficient aid delivery is possible in terms of time and cost. Therefore, it can help crisis managers respond by providing the required budget and appropriate logistics planning.

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Supply chain risk management: A content analysis-based review of existing and emerging topics

Cited by 40 publications

References 108 publications

Transport Risks in the Supply Chains – Post Covid-19 Challenges

Transport Risks in the Supply Chains – Post Covid-19 Challenges

Designing the Location–Routing Problem for a Cold Supply Chain Considering the COVID-19 Disaster

Designing the Distribution Network of Essential Items in the Critical Conditions of Earthquakes and COVID-19 Simultaneously

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