Competition between human and artificial intellectual capital in production and distribution in Industry 4.0
| Pages | 531-547 |
| DOI | https://doi.org/10.1108/JIC-11-2019-0275 |
| Date | 22 April 2020 |
| Published date | 22 April 2020 |
| Author | Irina V. Gashenko,Natalia N. Khakhonova,Irina V. Orobinskaya,Yulia S. Zima |
| Subject Matter | Knowledge management,HR & organizational behaviour,Behavioural accounting,Organizational structure/dynamics |
Competition between human and
artificial intellectual capital in
production and distribution in
Industry 4.0
Irina V. Gashenko and Natalia N. Khakhonova
Rostov State University of Economics, Rostov na Donu, Russian Federation
Irina V. Orobinskaya
Voronezh State Agricultural University Named After the Emperor Peter the Great,
Voronezh, Russian Federation, and
Yulia S. Zima
Rostov State University of Economics, Rostov na Donu, Russian Federation
Abstract
Purpose–The purpose of the research is to study the consequences of total (comprehensive) automatization of
entrepreneurship for interested parties through the prism of competition human and artificial intellectual
capital in production and distribution in Industry 4.0.
Design/methodology/approach –The research is conducted with application of scenario analysis,
regression analysis, imitation modeling, forecasting and non-linear multi-parametric optimization with the
simplex method.
Findings –The authors perform scenario modeling of competition between human and artificial intellectual
capital in production and distribution in Industry 4.0 and offer recommendationsfor pro-active management of
competition between human and artificial intellectual capital in production and distribution in Industry 4.0.
Originality/value –Contrary to the existing approach to studying competition between human and artificial
intellectual capital in Industry 4.0, automatization of distribution, not production, is most preferable. This
shows increase of the value of human intellectual capital in distributionduring its automatization based on AI.
This is an unprecedented and breakthrough conclusion for the modern economic science. It allows creating a
completely new direction of research of competition between human and artificial intellectual capital in
production and distribution in Industry 4.0, in which optimization of social consequences is achieved not by
means of restraint of automatization but by means of its stimulation. The key condition is stimulation of
automatization of distribution with limited automatization of production. Based on this conclusion, it is
recommended to continue research in continuation of the presented work.
Keywords Competition, Human intellectual capital, AI, Automatization, Production, Distribution, “Smart”
technologies, Industry 4.0
Paper type Research paper
1. Introduction
Industry 4.0 is a general name for the fourth technological mode, whose specific feature is a
high level of automatization of entrepreneurial processes. Two directions are distinguished
within transition to Industry 4.0. The 1st direction is automatization of production. Within
this direction, human labor in industrial production is replaced by machine labor. For this,
separate intellectual departments of companies (e.g. “smart”plants) are created, in which all
technical devices are compatible and are under artificial intelligence (AI) control.
It should be noted that autonomy of production departments is relative. They perform a
detailed algorithm of actions on production of industrial goods and their quality control. The
Total
automatization
of
entrepreneurship
531
JEL Classification —D41, E24, F66, G34, J16, J21, J31, L13, M14, O16, O31, O32, O33, O38
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/1469-1930.htm
Received 27 November 2019
Revised 6 January 2020
Accepted 26 January 2020
Journal of Intellectual Capital
Vol. 21 No. 4, 2020
pp. 531-547
© Emerald Publishing Limited
1469-1930
DOI 10.1108/JIC-11-2019-0275
most obvious drawback of “smart”production departments is large capital expenditures and
their high energy-intensity. The multiple advantages include economy of resources,
guarantee of quality of industrial goods, long term of usage of machine devices, full
transparency and control of the production process, its predictability, strict observation of the
terms and conditions of production, and safety dye to absence of the involvement of humans
in potentially dangerous activities.
2nd direction: automatization of distribution. This direction envisages automatization of
marketing, sales, logistics and management of supply chains. As a rule, automatization is
partial and is brought down to intellectual decision support, formation of information
systems for business, knowledge data base management based on neural networks,
processing of big data and their storing with application of cloud and blockchain
technologies. The key role in distribution remains with human intellectual capital, which
accepts orders, forms the content and logic of marketing communications, and makes final
decisions in view of machine recommendations and the factors that are ignored by AI (e.g.
corporate social and ecological responsibility).
During the first –preparatory –stage of transition to Industry 4.0, which is connected to
formation of the digital economy and implementation of R&D on development of the leading
production technologies that are necessary for increasing the level of automatization of
entrepreneurial processes—these directions were studied separately in 2012–2019. This
could be explained by the fact that during automatization of production and distribution
different digital technologies should be used, and there are different natural (objective) limits
of automatization.
In the near future (2020–2024) there will be a new stage of technological progress, which
will feature development of the leading production technologies and which will start the
next –second –stage of transition to Industry 4.0, which will consist of direct implementation
of mass initiatives on increasing the levelof automatization of entrepreneurial processes. This
requires a complex scientific view on the perspectives of automatization of production. Thus,
studies of total (comprehensive) automatization of entrepreneurship became very important.
The current studies of total automatization are unified by the common approach to its
elaboration through the prism of limits. It is supposed that automatization of production and
distribution is equally profitable and ensures advantages, but –in view of the current
technologies –it is allowable to a different extent. According to the logic of the existing
scientific studies within the existing approach, the highest level of automatization will be
achieved in production, as there are examples of fully automatized “smart”plants and other
companies’production departments.
Automatization of distribution is significantly limited by imperfection of AI, in particular,
in the sphere of communication with humans (e.g. with customers). A serious drawback of the
applied approach to studying the total automatization is its focus on the interests of
entrepreneurship. Interests of other concerned parties are not taken into account, though an
obvious result of increase of the level of automatization is increase of competition between
human and artificial intellectual capital.
A unilateral view on Industry 4.0 could lead to the fact that instead of expected
advantages in the form of quick increase of revenues and profitability the companies will face
a socio-economic crisis (mass unemployment, crisis of over-production due to reduction of the
volume of effective demand) and will bear losses. Against this background, quick economic
growth and increase of global competitiveness of the economy –which are the basis for
state’s support for automatization –will not be achieved.
That’s why there’s a need for a new approach to studying the total automatization of
entrepreneurship in view of all interested parties—entrepreneurs, their employees and the
state, which represents the society’s interests. This predetermined the purpose of the
research, which consists in systemic study of the consequences of total (comprehensive)
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