Study of the Negative & the Positive Impact of Coronavirus Pandemic on Different Types of Industry, Businesses & the Society
Notice bibliographique
Résumé
Wesleyan Journal of Research, UGC Care-listed | ISSN: 0975-1386 | Peer-reviewed Journal Vol. 13 No. 69 (March 2021) Research Article: Management Study of the Negative & the Positive Impact of Coronavirus Pandemic on Different Types of Industry, Businesses & the Society Shubham Parsoya and Dr. Asif Perwej School of Management Studies (SOMS), Sangam University (SU), Bhilwara, Rajasthan, India Abstract: In the background of unforeseen occurrence scenario of COVID-19 nationwide pandemic, this paper has created an endeavour to study the impact of coronavirus pandemic (COVID-19) on differing kinds of companies and industries in numerous ways. Once the emergence of Corona pandemic in India introduced, the matter of public health condition has become core issue of the people in India and it's been on the forefront in conjunction with alternative and related serious issues of migrant labour, loss of employment, economic and industrial instability etc., and on the other side with the massive population size and its ever growing rate over the last 3 decades, the general public health scenario has been deteriorated significantly, and the occurrence of COVID-19 since 2019 has changed the entire world’s functioning accordingly. Internationally the Pandemic of COVID-19 has affected all sections of the economy and nobody will specifically predict when the pandemic is going to be over and everything are going to be like our past days. With the beginning of the unfold of COVID-19, business and various other industries, such as; region trade, transport industry, food industry, agriculture industry, housing industry, education industry, cinema industry, energy industry, producing industry, music industry, mining trade, were straightaway clean up, and the outside travelling and domestic travel activities were also withheld for the unknown length on such moment. The impact of Covid-19 on all such industries was very big. Globally all business and industry are witnessing serious threat with the spreading of COVID-19. All the countries have the first preference of the protection of the people, interference of unfold and health care of the infected folks. However, there are some types of industries that are becoming some extreme number of advantages from such COVID-19 pandemic conditions in some direct or indirect ways. Such industries are; Education (EdTech) industries, E-retail industries, Banking, financial services and insurance industries (BFSI). Medical sector, Information technology and knowledge Technology Enabled Services, Etc. Keywords: Pandemic, COVID-19, Industries, Businesses, Impact, Problems, World, Economy Conference Details:- International Conference on Analytical & Interdisciplinary Research – 2021 (ICAIR-2021) 05th - 06th February, 2021 https://www.sangamuniversity.ac.in/inner-pages/ICAIR-2021.php Description about the author: - Mr. Shubham Parsoya, Ex-Assistant Professor, School of Management Studies Ph.D. Doctoral Researcher (Business & Management) Master of Business Administration (MBA) in (Human Resources Management and Marketing Management) from Guru Gobind Singh Indraprastha University, New Delhi, India Bachelor of Commerce (B.Com.) Lean Six Sigma Champion Certified Professional (LSSCCP), School of Business Leadership Colorado, United States Six Sigma Yellow Belt Certified Professional (SSYBCP), Project Management Institute Accounting Fundamentals Certified Professional (AFCP), Corporate Finance Institute, Vancouver, Canada, United States
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».