Advanced deep learning approaches to predict supply chain risks under COVID-19 restrictions

Bassiouni, Mahmoud M.; Chakrabortty, Ripon K.; Hussain, Omar Khadeer; Rahman, Humyun Fuad

doi:10.1016/j.eswa.2022.118604

Cited by 42 publications

(22 citation statements)

References 50 publications

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“…It encompasses the entire process, from the suppliers delivering raw materials or semi-finished goods to the manufacturer through the manufacturers transforming and shipping the finished product or service to the end-user or customers. (Bassiouni et al, 2023) Production and price concerns are two types of risks that agriculture supply networks have experienced during the pandemic. Production risk is a situation in which actual output differs from the anticipated output.…”

Section: Literature Reviewmentioning

confidence: 99%

Retail Management of the Food Sector in the Indian Economy during Covid-19: A Systematic Review

Journal¹

2022

IJSREM

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The coronavirus pandemic caused significant changes to businesses worldwide, its rippling effects still being felt today. As businesses adapt to the new restrictions, multiple researchers have analysed the new environment that these organizations operate in. The changes included less footfall in physical stores and an increase in online deliveries leading to stores having to change their entire format of operations. This paper looks to construct a literary review of food retailing and its changes during the COVID-19 pandemic spanning the agriculture and food retail sector supply and demand fluctuations, supply chain disruptions, and the rise of doorstep food deliveries. This paper involves a holistic review of the challenges faced and overcome by food retailing businesses in the past three years, and the prospects of these evolved business models. Our study includes findings from previous research and tries to establish a connection between the problems mentioned above, the increased use of digital services, and the significance of the pandemic as the exacerbator of existing issues in the established infrastructure of the agriculture and food retail sectors. Keywords ; Covid-19 Pandemic; Food supply Chain; Retail; Agriculture

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Section: Literature Reviewmentioning

confidence: 99%

Retail Management of the Food Sector in the Indian Economy during Covid-19: A Systematic Review

Journal¹

2022

IJSREM

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“…Scarcity of labor, shortage of raw materials, and inconsistent supply are three major challenges faced by the global supply chain during the COVID-19 pandemic [ 34 ]. Deep learning can help decision makers actively predict supply chain risks against the background of the pandemic and improve the supply chain’s resilience [ 35 ]. Strategies such as continuous monitoring, information sharing, and real-time data exchange are helpful in dealing with external risks in the supply chain [ 36 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Research on the Anti-Risk Mechanism of Mask Green Supply Chain from the Perspective of Cooperation between Retailers, Suppliers, and Financial Institutions

Chen

Wang

et al. 2022

IJERPH

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Against the background of the pandemic, the mask supply chain faces the risk of pollution caused by discarded masks, the risk of insufficient funds of retailers, and the risk of mask overstock. To better guard against the above risks, this study constructed a two-party game model and a cusp catastrophe model from the perspective of the mask green supply chain, and studied the strategic choices of retailers and suppliers in the supply chain affected by the risk of capital constraints and overstock. The result shows that the risk shocks will lead to the disruption of the mask green supply chain, and the main factors affecting the strategy choice of mask suppliers and retailers are mask recycling rate, deposit ratio, risk occurrence time, etc. In further research, this study involved a mechanism for financial institutions, mask retailers, and the government to jointly deal with the risk of mask overstock, the risk of retailers’ insufficient funds, and the risk of environmental pollution from discarded masks. The research path and conclusion of this study reveal the risks in the circulation area of mask supplies during the pandemic, and provide recommendations for planning for future crises and risk prevention.

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“…While the number of adverse reaction cases to COVID-19 vaccination is extremely small in number relative to the number vaccinated, they cannot be overlooked as they give important information to predict and ameliorate adverse reactions and poor outcomes. Statistical and ML analysis [25] can play a role in characterizing those factors. We have, therefore, analyzed data from patients to clarify the common causes of such reactions.…”

Section: Introductionmentioning

confidence: 99%

Adverse Effects of COVID-19 Vaccination: Machine Learning and Statistical Approach to Identify and Classify Incidences of Morbidity and Postvaccination Reactogenicity

et al. 2022

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Good vaccine safety and reliability are essential for successfully countering infectious disease spread. A small but significant number of adverse reactions to COVID-19 vaccines have been reported. Here, we aim to identify possible common factors in such adverse reactions to enable strategies that reduce the incidence of such reactions by using patient data to classify and characterise those at risk. We examined patient medical histories and data documenting postvaccination effects and outcomes. The data analyses were conducted using a range of statistical approaches followed by a series of machine learning classification algorithms. In most cases, a group of similar features was significantly associated with poor patient reactions. These included patient prior illnesses, admission to hospitals and SARS-CoV-2 reinfection. The analyses indicated that patient age, gender, taking other medications, type-2 diabetes, hypertension, allergic history and heart disease are the most significant pre-existing factors associated with the risk of poor outcome. In addition, long duration of hospital treatments, dyspnoea, various kinds of pain, headache, cough, asthenia, and physical disability were the most significant clinical predictors. The machine learning classifiers that are trained with medical history were also able to predict patients with complication-free vaccination and have an accuracy score above 90%. Our study identifies profiles of individuals that may need extra monitoring and care (e.g., vaccination at a location with access to comprehensive clinical support) to reduce negative outcomes through classification approaches.

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Advanced deep learning approaches to predict supply chain risks under COVID-19 restrictions

Cited by 42 publications

References 50 publications

Retail Management of the Food Sector in the Indian Economy during Covid-19: A Systematic Review

Retail Management of the Food Sector in the Indian Economy during Covid-19: A Systematic Review

Research on the Anti-Risk Mechanism of Mask Green Supply Chain from the Perspective of Cooperation between Retailers, Suppliers, and Financial Institutions

Adverse Effects of COVID-19 Vaccination: Machine Learning and Statistical Approach to Identify and Classify Incidences of Morbidity and Postvaccination Reactogenicity

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