The model of distribution of human and machine labor at intellectual production in industry 4.0

Author:

Inshakova Agnessa O.,Frolova Evgenia E.,Rusakova Ekaterina P.,Kovalev Sergey I.

Abstract

PurposeThe purpose of the paper is to develop a model of distribution of human and machine labor at intellectual production in Industry 4.0.Design/methodology/approachThe basis of the methodology of the research is regression analysis. The analyzed variables are independent variables that characterize the level of development of human and machine labor in the economy of a country; dependent variables that reflect the effectiveness of the production, marketing and innovative business processes in the economy of country according to “The Global Competitiveness Report” (World Economic Forum); and dependent variables, which show the share of the sphere (agriculture, mining industry, processing industry and service sphere) in the structure of GDP of a country according to the statistics of the World Bank. For determining the change of regression dependencies in dynamics in the interests of reduction of the probability of statistical error, the research is conducted for 2010 and 2018 with application of trend analysis.FindingsBased on the full selection of modern countries that conduct digital modernization, the authors determine statistical dependencies of effectiveness of business processes and development of the spheres of economy on the intensity of application of machine and human labor. This allowed determining significant differences in automatization of business processes: perspectives of application of machine labor are the widest in production and the narrowest in marketing, differentiated logic of organization of intellectual production in different spheres of economy and the specifics of automatization of business processes and spheres of economy in countries of different categories, one of which has to be taken into account during organization of intellectual production in Industry 4.0.Originality/valueThe developed model of optimal distribution of human and machine labor at intellectual production in Industry 4.0 will allow reducing disproportions in effectiveness of different business processes, development of different spheres of economy and growth rate of developed and developing countries. This explains its contribution into provision of well-balanced development of the modern global economic system.

Publisher

Emerald

Subject

General Business, Management and Accounting,Education

Reference36 articles.

1. Human capital flows in failing organizations: an integrated conceptual framework;Journal of Intellectual Capital,2018

2. Transforming to a hyper-connected society and economy – towards an ‘industry 4.0’;Procedia Manufacturing,2015

3. The value of digital ecosystems to the knowledge economy and the growth of intellectual capital,2011

4. Improving operations performance through artificial intelligence, digital, and advanced analytics applications,2019

5. Intertwining the internet of things and consumers' behaviour science: future promises for businesses;Technological Forecasting and Social Change,2018

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