ABSTRACT
The global-local supply chains are affected by the forward and downward propagation of COVID-19. The pandemic disruption is a low-frequency and high-impact (black swan) event. Adapting to the "New Normal" situation requires adequate risk mitigation strategies. This study proposes a methodology to implement a risk mitigation strategy during supply chain disruptions. Random demand accumulation strategies are considered to identify the disruption-driven challenges under different pre and post-disruption scenarios. The best mitigation strategy and the optimal location of distribution centers to maximize the overall profit were determined using simulation-based optimization, greenfield analysis, and network optimization techniques. The proposed model is then evaluated and validated using appropriate sensitivity analysis. The main contribution of the study is to (i) perform cluster-based supply chain disruption analysis, (ii) propose a resilient and flexible model to illustrate the proactive and reactive measures for the ripple effect, (iii) prepare the supply chain for future pandemic-like crises, and (v) reveal the relationship between the pandemic impact and supply chain resilience. A case study of an ice cream manufacturer is used to demonstrate the proposed model.
ABSTRACT
Deployment of secured healthcare information is a major challenge in a web-based environment. eHealth services are subjected to same security threats as other services. The purpose of blockchain is to provide a structure and security to the organization data. Healthcare data deals with confidential information. The medical records can be well organized and empower their propagation in a secured manner through the usage of blockchain technology. The study throws light on providing security of health services through blockchain technology. The authors have analyzed the various aspects of role of blockchain in healthcare through an extensive literature review. The application of blockchain in COVID-19 has also been analyzed and discussed in the study. Further application of blockchain in Indian healthcare has been highlighted in the paper. The study provides suggestions for strengthening the healthcare system by blending machine learning, artificial intelligence, big data, and IoT with blockchain.
Subject(s)
Blockchain , COVID-19 , Humans , Computer Security , Artificial Intelligence , Health Care Sector , COVID-19/epidemiologyABSTRACT
The 2019 coronavirus disease (COVID-19) pandemic has seriously impacted the performance of all types of businesses. It has given a tremendous structural boost to e-commerce enterprises by forcing customers to online shopping over visiting physical stores. Moreover, customer expectations of the digital and operational capabilities of e-commerce firms are also increasing globally. Thus, it has become crucial for an e-commerce enterprise to reassess and realign its business practices to meet evolving customer needs and remain sustainable. This paper presents a comprehensive performance evaluation framework for e-commerce enterprises based on evolving customer expectations due to the COVID-19 pandemic. The framework comprises seven primary criteria, which are further divided into 25 sub-criteria, including two sustainability factors, namely, environmental sustainability and carbon emissions. The evaluation approach is then practically demonstrated by analyzing the case of three Indian e-commerce firms. The results are obtained using a multi-criteria decision-making (MCDM) method, namely, Fuzzy VIKOR, to capture the fuzziness of the inherent decision-making problem. Further, numerical analysis is conducted to evaluate and rank various e-commerce enterprises based on customer expectations and satisfaction benchmarks. The findings explain the most important criteria and sub-criteria for e-commerce businesses to ensure customer expectations along with their economic and environmental sustainability.
