ABSTRACT
Background: The Food Commerce industry has flourished massively during the past decade in South Kolkata in West Bengal, with new outlets opening every now and then, so much so that this region is known as 'Food Street'. Regardless of their scale of operations, each of these outlets had well established themselves, catering to their respective target markets and earning decent amount of revenue over the years. However, this growth suffered a setback owing to the origin of novel Coronavirus SARS-n-CoV-2. The growth rate declined to a great extent over the span of two years, with recent studies showing an overall stunted growth rate. Even though online marketing of these outlets and selling the food through delivery apps have aided the entrepreneurs, the cost to revenue ratio is not at par with that of the times before the pandemic hit. Overall, the pandemic has impacted the eateries in more way than initially imagined. Objectives: (a) To reveal the various problems and scenarios of managing food business during the Covid-19 pandemic in South Kolkata region;(b) To compare the present scenario of the food industry with how things were before prior to the pandemic to understand the nature of change during this time frame;and, (c) To describe the challenges and methods implemented by the food retail business entrepreneurs and managers of the randomly selected establishments to hold a steady business flow during the Covid-19 pandemic. Methodology: The study follows a descriptive research design. Therefore, the research will describe the characteristics of the sample under study. The food outlets of South Kolkata have been chosen as the study location. 100 respondents were selected. The respondents are those who consume food from these outlets such that they represent the wider target market of the 'Food Street'. Both Primary Data and Secondary Data were used. Primary Data was collected through sample survey. Random Sampling technique was used to choose the respondents. The study used quantitative data, therefore, only Quantitative analysis was performed. Results: The Research was able to depict the comparison between the present scenario and the situation prior to the pandemic. The study was able to reveal the challenges and problems that the food outlets had to suffer from. Also, the methods or strategies taken up by the entrepreneurs of these outlets to overcome the pandemic were discovered. 46% of the respondents opted for "Mobile Food Delivery" as their strategy to revive from losses. Conclusion: With COVID-19 having altered - and still in the process of altering - the definition of "normal" across the world, most industries are still scrambling to adjust. The effect on the restaurant industry has been particularly dramatic. With restaurants and pubs closed for sit-down service, many establishments are struggling to keep their heads above water. The food outlets located in South Kolkata shares the same fate and the research is able to highlight this effectively.
ABSTRACT
The entire world faced locked down scenario due to the outbreak of nCOVID-19 corona virus outbreak. The fast and relentless spread nCOVID-19 has basically segmented the populace only into three subclasses, namely susceptible, infected, and recovered compartments. Adapting the classical SIR-type epidemic modeling framework, the direct person-to-person contact transmission is taken as the direct route of transmission of nCOVID-19 pandemic. In this research, the authors have developed two models of the nation-wide trends of the outburst of the nCOVID-19 infection using an SIR model and also an ARIMA model. They have studied the quantile plots, regression residual plots and R pair plots of the dataset by simple supervised machine learning algorithms. This study compares both models and higher correlation of the developed models with reality which suggests the extent of accuracy of these models. The study also suggested some possible way-out to get rid of this situation by providing a trade-off between ‘flattening of the curve’ as well as less economic turbulence. The projections are intended to provide an action plan for the socioeconomic counter measures to alleviate COVID-19 in India. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The study focuses on the information flow on twitter during the corona virus outbreak. Tweets related to #coronavirus are studied using sentiment analysis and topic modelling using Latent Dirichlet Allocation post preprocessing. The study concluded that the information flow was accurate and reliable related to corona virus outbreak with minimum misinformation. LDA analysis had identified the most relevant and accurate topics related to corona virus outbreak and sentiment analysis confirmed the prevalence of negative sentiments like fear along with positive sentiments like trust. Governments and Healthcare authorities & institutions effectively utilized to spread accurate and reliable information on twitter. © 2020 IAEME.