Perception intelligence as an element of human intellectual capital and its assessment among university students

Dresvyannikov, V. A.; Dorofeev, V. D.; Taktarova, S. V.

doi:10.1504/ijlic.2019.096931

Cited by 1 publication

(1 citation statement)

References 28 publications

(28 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3rd block: human and artificial intellectual resources in Industry 4.0. High priority of human capital for intellectual production in Industry 4.0 is emphasized in Dresvyannikov et al (2019), Velayutham and Rahman (2018), Amankwah-Amoah (2018), Mehrotra and Malhotra (2019) and Hsiung and Wang (2012). Perspectives of development of intellectual production based on improvement of AI are outlined in Chandrasekaran et al (2019), Brun (2019), IphofenR and Kritikos (2019), Zandi et al (2019), Doyle and Senske (2018) and Wilner (2018).…”

Section: Literature Reviewmentioning

confidence: 99%

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

Inshakova

Frolova

Rusakova

et al. 2020

JIC

View full text Add to dashboard Cite

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.

show abstract