ABSTRACT
BACKGROUND: COVID-19 as a pandemic has caused an alarming increase in mortality and morbidity. Viral-induced morphologic changes in the peripheral blood cells are well characterized in certain infections and can direct diagnostic workup to ensure timely therapeutic intervention. This study describes the morphological changes of blood cells in various stages of COVID disease. MATERIALS AND METHODS: A total of thousand COVID-positive patients admitted in the tertiary care center were taken for the study. They were classified as mild, moderate, and severe based on the clinical criteria suggested by World Health Organization. Peripheral smears of the patients were analyzed, and the morphological changes in various blood cells were correlated with the disease stage and coagulation parameters. RESULT(S): The study demonstrated significant morphological changes in the blood cells of COVID patients during the course of disease progression and during the onset of COVID-associated coagulopathy. Leukocytosis, neutrophilia, and toxic changes in neutrophils were seen in the severe stage of the disease and in COVID coagulopathy suggesting these are important indicators of disease severity. Activated lymphocyte was found to be the most common morphological presentation seen in all patients irrespective of the disease stage, whereas plasmacytoid lymphocytes were an important finding in severe-stage disease. Schistocytes an important finding in any other coagulopathy was present only in 1% of cases of COVID coagulopathy. CONCLUSION(S): The study demonstrated significant morphological changes in the blood cells of COVID-positive patients during the course of disease progression. Comprehensive daily complete blood count and peripheral smear examination should be undertaken in patients hospitalized with COVID-19 to predict potential clinical deterioration and signs of disease progression. These morphological changes in peripheral smear can be used as one of the factors indicating disease progression which can formulate for further evaluation. Since follow-up and post-COVID morphological examination were not done, additional research in this aspect can shed light on the clinical categorization of COVID patients based on the morphological findings.Copyright © 2023 Journal of Applied Hematology Published by Wolters Kluwer - Medknow.
ABSTRACT
The COVID-19 pandemic has significantly strained online food delivery services (OFDS) globally. This has challenged OFDS businesses to redesign and deploy technologies to meet customer demand. The purpose of this article is to identify the optimal factors contributing to customer experience with OFDS services during a black swan event such as the COVID-19 pandemic. We followed a four-step research design to identify the optimal factors for OFDS. First, we identified the major episodes in the OFDS process. Second, these episodes were evaluated by customers using the sequential incidence technique. Third, we used an orthogonal design to analyze the episodes at different levels based on customer preferences. Finally, we used the Taguchi approach to calculate the signal-to-noise ratios and identify the optimal factors and their preferred levels. We classify the optimal factors into customer-oriented and service-provider-oriented propositions. The option to select the delivery person and delivery conditions was found to be the most optimal customer-oriented attribute. We discuss the theoretical and managerial implications of the study and suggest major avenues for digital transformations in OFDS for better customer experience. IEEE
ABSTRACT
PurposeAgriculture value chains (AVCs) have experienced unprecedented disruption during the COVID-19 pandemic, with lockdowns and stringent social distancing restrictions making buying and selling behaviours complex and uncertain. This study aims provide a theoretical framework describing the stakeholder behaviours that arise in severely disrupted value chains, which give rise to inter-organisational initiatives that impact industry sustainability.Design/methodology/approachA mixed-methods approach is adopted, in which uncertainty theory and relational governance theory and structured interviews with 15 AVC stakeholders underpin the initial conceptual model. The framework is empirically validated via partial least squares structural equation modelling using data from an online survey of 185 AVC stakeholders based in India.FindingsThe findings reveal that buyer and supplier uncertainty created by the COVID-19 lockdowns gives rise to behaviours that encourage stakeholders to engage in relational governance initiatives. Progressive farmers and other AVC stakeholders welcome this improved information sharing, which encourages self-reliance that positively impacts agricultural productivity and sustainability.Practical implicationsThe new framework offers farmers and other stakeholders in developing nations possibilities to sustain their AVCs even in dire circumstances. In India, this also requires an enabling ecosystem to enhance smallholders' marketing power and help them take advantage of recent agricultural reforms.Originality/valueResearch is scarce into the impact of buyer and seller behaviour during extreme supply chain disruptions. This study applies relational governance and uncertainty theories, leading to a proposed risk aversion theory.
ABSTRACT
COVID-19 led to several complications like labor shortage, inadequate availability of supply chain facilities, price fluctuation, panic behavior, and uncertainty. Despite the challenges, the farmers and stakeholders adopted different strategies for sustaining the agricultural supply chain performance. Hence, the study proposes to explore the antecedents that led to the ASC performance and their linkages. The study combines literature review and qualitative methods to understand and recognize antecedents that impact ASC performance in developing countries. The conceptual model is built with the underpinning theory (the theory of commitment and organization). A quantitative survey follows the study to validate the theoretical model empirically using covariance-based structure equation modeling (AMOS). The ASC performance in the earlier phase of COVID-19 was disrupted. With time, ASC performance was managed by linking different antecedents. The findings reveal the application and linkage of organization theory and theory of commitment which led to ASC performance. The study finds a unique contribution among academia and practitioners by paving directions to manage the uncertainty during COVID-19 and any such risk triggers in the future. The study offers essential insights for practitioners and policymakers to develop a road map for ASC during the calamities.
ABSTRACT
Novel coronavirus disease (COVID-19) and resulting lockdowns have contributed to major retail operational disturbances around the globe, forcing retail organizations to manage their operations effectively. The impact can be measured as a black swan event (BSE). Therefore, to understand its impact on retail operations and enhance operational performance, the study attempts to evaluate retail operations and develop a decision-making model for disruptive events in Morocco. The study develops a three-phase evaluation approach. The approach involves fuzzy logic (to measure the current performance of retail operations), graph theory (to develop an exit strategy for retail operations based on different scenarios), and ANN and random forest-based prediction model with K-cross validation (to predict customer retention for retail operations). This methodology is preferred to develop a unique decision-making model for BSE. From the analysis, the current retail performance index has been computed as "Average" level and the graph-theoretic approach highlighted the critical attributes of retail operations. Further, the study identified triggering attributes for customer retention using machine learning-based prediction models (MLBPM) and develops a contactless payment system for customers' safety and hygiene. The framework can be used on a periodic basis to help retail managers to improve their operational performance level for disruptive events.
ABSTRACT
Healthcare is one of the most critical sectors due to its importance in handling public health. With the outbreak of various diseases, more recently during Covid-19, this sector has gained further attention. The pandemic has exposed vulnerabilities in the healthcare supply chain (HSC). Recent advancements like the adoption of various advanced technologies viz. AI and Industry 4.0 in the healthcare supply chain are turning out to be game-changers. This study focuses on identifying critical success factors (CSFs) for AI adoption in HSC in the emerging economy context. Rough SWARA is used for ranking CSFs of AI adoption in HSC. Results indicate that technological (TEC) factors are the most influential factor that impacts the adoption of AI in HSC in the context of emerging economies, followed by institutional or environmental (INT), human (HUM), and organizational (ORG) dimensions.
ABSTRACT
Novel coronavirus disease (COVID‐19) and resulting lockdowns have contributed to major retail operational disturbances around the globe, forcing retail organizations to manage their operations effectively. The impact can be measured as a black swan event (BSE). Therefore, to understand its impact on retail operations and enhance operational performance, the study attempts to evaluate retail operations and develop a decision‐making model for disruptive events in Morocco. The study develops a three‐phase evaluation approach. The approach involves fuzzy logic (to measure the current performance of retail operations), graph theory (to develop an exit strategy for retail operations based on different scenarios), and ANN and random forest‐based prediction model with K‐cross validation (to predict customer retention for retail operations). This methodology is preferred to develop a unique decision‐making model for BSE. From the analysis, the current retail performance index has been computed as “Average” level and the graph‐theoretic approach highlighted the critical attributes of retail operations. Further, the study identified triggering attributes for customer retention using machine learning‐based prediction models (MLBPM) and develops a contactless payment system for customers' safety and hygiene. The framework can be used on a periodic basis to help retail managers to improve their operational performance level for disruptive events.
ABSTRACT
COVID-19 led to several complications like labor shortage, inadequate availability of supply chain facilities, price fluctuation, panic behavior, and uncertainty. Despite the challenges, the farmers and stakeholders adopted different strategies for sustaining the agricultural supply chain performance. Hence, the study proposes to explore the antecedents that led to the ASC performance and their linkages. The study combines literature review and qualitative methods to understand and recognize antecedents that impact ASC performance in developing countries. The conceptual model is built with the underpinning theory (the theory of commitment and organization). A quantitative survey follows the study to validate the theoretical model empirically using covariance-based structure equation modeling (AMOS). The ASC performance in the earlier phase of COVID-19 was disrupted. With time, ASC performance was managed by linking different antecedents. The findings reveal the application and linkage of organization theory and theory of commitment which led to ASC performance. The study finds a unique contribution among academia and practitioners by paving directions to manage the uncertainty during COVID-19 and any such risk triggers in the future. The study offers essential insights for practitioners and policymakers to develop a road map for ASC during the calamities.
ABSTRACT
Covid 19 pandemic has severely affected daily lives. It spreads exponentially, taking many lives and shutting down essentially all outside activities. Since no completely effective vaccines are found yet so far until late December 2020, the only effective way to prevent infection from spreading is to maintain social distancing and precautionary methods. The government banned the gatherings to break down the exponential growth chain. To implement this, a lockdown was imposed. This decision had impacted almost every sector, be it industrial, agricultural, tourism or educational. However, as the condition is getting better, life is becoming as it was earlier before the pandemic, slowly resuming all activities. Since the educational institutions are also about to be opened after being closed for nearly 8 months, since march 2020, it is a very challenging task to ensure safety in the college premises without compromising with the health of the faculties, staff and the stakeholders. In this paper, there are various suggestions discussed using which, safety and proper arrangements can be implemented and optimized in the best case wherein the institutions can run uninterruptedly in the case of any pandemic. This paper also discusses the precautions which can be taken if there is a similar situation nearby future
ABSTRACT
Grounded on resource-based view and dynamic capability perspectives, this research aims to explore linkages between the firm's big data management activities (BDMA), green manufacturing (GM) practices, and sustainable business performance (SBP). The research model was empirically evaluated using data collected from 248 pharmaceutical manufacturers in India during the COVID-19 pandemic. The analysis was performed using a covariance-based structural equation modeling using AMOS 20. The results indicate that GM activities impact SBP directly. Further results imply the mediating role of GM practices on the relationship between BDMA and SBP. The analysis reveals that senior management's resource commitment in pharmaceutical firms is a moderating mechanism in strengthening the association between BDMA and GM practices. This study is significant as it provides key theoretical and managerial implications for pharmaceutical sectors during emergent situations.
ABSTRACT
The procurement of food grains from farmers is one of the biggest challenges under the COVID-19 outbreak due to country-wise lockdowns. The present study aims to reconfigure the existing food grain supply chain network. The study advances the extant literature by proposing a novel mathematical model that considers the government guidelines issued to procure food grains from farmers under the COVID-19 situation. The model includes personal distancing, a key parameter relevant in the COVID-19 crisis, and has remained unaddressed in the existing literature. The proposed model is tested in India. The effect of different parameters like personal distancing cost, carbon emission cost, fixed cost, and transportation cost is also investigated under a given set of procurement centers. Finally, the procurement schedule for each procurement center is generated, which is especially useful for managing its activities and is also helpful to farmers to streamline the process. Results indicate that the proposed model is highly effective under pandemic emergencies like the current COVID-19 crisis. Policymakers and the government will find this model helpful in drafting relevant policies regarding food grain procurement under emergencies such as the COVID-19 outbreak. The distribution segment of the supply chain network is not part of the present research work. In future studies, this part could be then added to the whole of the procurement process, and both procurement and distribution can be assessed together again.
ABSTRACT
Purpose Advances in information technology coupled with the need to build resilience against disruptions by pandemics like COVID-19 continue to emphasize offshoring services in the software industry. Service-level agreements (SLAs) have served as a key mechanism for safeguarding against risk in offshore service arrangements. Yet, variations in service cost and quality persist. This study aims to open up the blackbox linking SLAs to offshore project outcomes by examining (1) how the provisions in these contracts affect the ability of project teams - the work unit primarily in charge of producing the offshored service - to achieve their objectives and fulfill client requirements and (2) how differences in contextual factors shape the effects of these provisions. Design/methodology/approach The authors incorporate the role of organizational work practice differences to understand the challenges that 270 offshore project teams faced in coordinating and integrating technical and business domain knowledge across organizational boundaries in offshore arrangements. The examined offshore IT projects were managed by a leading software vendor in India and several of its US-based clients over a three-year period. Findings The authors demonstrate that organizational work practice differences represent a barrier to offshore project success, and that project team transition processes are an important mechanism for overcoming these barriers. Moreover, the authors find that transition processes represent key mediating mechanisms through which SLA provisions affect offshore project outcomes. Originality/value The study findings shed light on how SLAs shape software project teams' balance between activities aimed at meeting client needs and those aimed at containing costs.
ABSTRACT
Purpose: Agriculture value chains (AVCs) have experienced unprecedented disruption during the COVID-19 pandemic, with lockdowns and stringent social distancing restrictions making buying and selling behaviours complex and uncertain. This study aims provide a theoretical framework describing the stakeholder behaviours that arise in severely disrupted value chains, which give rise to inter-organisational initiatives that impact industry sustainability. Design/methodology/approach: A mixed-methods approach is adopted, in which uncertainty theory and relational governance theory and structured interviews with 15 AVC stakeholders underpin the initial conceptual model. The framework is empirically validated via partial least squares structural equation modelling using data from an online survey of 185 AVC stakeholders based in India. Findings: The findings reveal that buyer and supplier uncertainty created by the COVID-19 lockdowns gives rise to behaviours that encourage stakeholders to engage in relational governance initiatives. Progressive farmers and other AVC stakeholders welcome this improved information sharing, which encourages self-reliance that positively impacts agricultural productivity and sustainability. Practical implications: The new framework offers farmers and other stakeholders in developing nations possibilities to sustain their AVCs even in dire circumstances. In India, this also requires an enabling ecosystem to enhance smallholders' marketing power and help them take advantage of recent agricultural reforms. Originality/value: Research is scarce into the impact of buyer and seller behaviour during extreme supply chain disruptions. This study applies relational governance and uncertainty theories, leading to a proposed risk aversion theory. © 2021, Emerald Publishing Limited.
ABSTRACT
Purpose: During the COVID-19 pandemic, the three-dimensional (3D) printing community is actively participating to address the supply chain gap of essential medical supplies such as face masks, face shields, door adapters, test swabs and ventilator valves. This paper aims to present a comprehensive study on the role of 3D printing during the coronavirus (COVID-19) pandemic, its safety and its challenges. Design/methodology/approach: This review paper focuses on the applications of 3D printing in the fight against COVID-19 along with the safety and challenges associated with 3D printing to fight COVID-19. The literature presented in this paper is collected from the journal indexing engines including Scopus, Google Scholar, ResearchGate, PubMed, Web of Science, etc. The main keywords used for searches were 3D printing COVID-19, Safety of 3D printed parts, Sustainability of 3D printing, etc. Further possible iterations of the keywords were used to collect the literature. Findings: The applications of 3D printing in the fight against COVID-19 are 3D printed face masks, shields, ventilator valves, test swabs, drug deliveries and hands-free door adapters. As most of these measures are implemented hastily, the safety and reliability of these parts often lacked approval. The safety concerns include the safety of the printed parts, operators and secondary personnel such as the workers in material preparation and transportation. The future challenges include sustainability of the process, long term supply chain, intellectual property and royalty-free models, etc. Originality/value: This paper presents a comprehensive study on the applications of 3D printing in the fight against COVID-19 with emphasis on the safety and challenges in it. © 2020, Emerald Publishing Limited.