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1.
Risks ; 11(5), 2023.
Article in English | Web of Science | ID: covidwho-20238588

ABSTRACT

The main focus of this article is the problem of exacerbating agricultural risks in the context of the COVID-19 crisis, which started against the background of the novel coronavirus (COVID-19) pandemic. The motivation for conducting the research presented in this article was the desire to increase the resilience of agricultural companies to economic crises. This paper is aimed at studying the Russian experience of changing the production and financial risks of agricultural companies during the COVID-19 crisis, substantiating the important role of innovations in reducing these risks, and determining the prospects for risk management in agriculture based on innovations to increase its crisis resilience. Using the structural equation modelling (SEM) method, we modelled the contribution of innovations to the risk management of agriculture during the COVID-19 crisis. The advantages of the SEM method, compared to other conventional methods (e.g., independent correlation analysis or independent regression analysis), include the increased depth of analysis, its systemic character, and the consideration of multilateral connections between the indicators. Using the case-study method, a "smart" vertical farm framework is being developed, the risks of which are resistant to crises through the use of datasets and machine learning. The originality of this article lies in rethinking the risks of agriculture from the standpoint of "smart" technologies as a new risk factor and a way to increase resilience to crises. The theoretical significance of the results obtained is that they make it possible to systematically study the changes in the risks of agriculture in the context of the COVID-19 crisis, while outlining the prospects for increasing resilience to crises based on optimising the use of "smart" technologies. The practical significance of the article is related to the fact that the authors' conclusions and applied recommendations on the use of datasets and machine learning by agricultural companies can improve the efficiency of agricultural risk management and ensure successful COVID-19 crisis management by agricultural companies.

2.
International Journal for Quality Research ; 16(1):55-76, 2022.
Article in English | Scopus | ID: covidwho-1675525

ABSTRACT

The purpose of this paper is to substantiate the advantages and to develop applied recommendations for marketing management of quality based on industrial and manufacturing engineering of project activities, in view of the specifics in social and technological entrepreneurship. Originality and novelty of the research are due to its following competitive advantages as compared to the existing published works. Firstly, the essence of quality management based on industrial and manufacturing engineering of project activities in the unity of social and technical criteria of quality is specified. Secondly, the specifics of the COVID-19 are determined, and the recommendations and qualitative landmarks for quality management for the purpose of economic crisis management are offered. Thirdly, the advantages are substantiated, and perspectives of marketing quality management for its systemic increase in view of all modern criteria are determined. Fourthly, the corresponding recommendations for managing products' quality separately for social and technological entrepreneurship are offered. The contribution of this paper to development of the theory and practice of quality management consists in development of marketing tools of quality management, substantiation of differences between quality management in social and technological entrepreneurship, consideration of influence of the COVID-19 crisis on quality, and development of the framework foundations for preventing the reduction of quality. © 2022. All Rights Reserved.

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