Priorities of training of digital personnel for industry 4.0: social competencies vs technical competencies

Elena G. Popkova (Plekhanov Russian University of Economics, Moscow, Russian Federation)
Kristina V. Zmiyak (Southern Federal University, Rostov na Donu, Russian Federation and Don State Technical University, Rostov-on-Don, Russian Federation)

On the Horizon

ISSN: 1074-8121

Article publication date: 11 October 2019

Issue publication date: 16 October 2019

Abstract

Purpose

The purpose of this paper is to determine the priorities of formation of competencies during training of digital personnel for industry 4.0.

Design/methodology/approach

The author performs two experiments for determining the scenario according to which industry 4.0 develops and will develop: the first experiment is aimed at determining the influence of the number of robots at unemployment level in 2019 and 2022 with the help of regression and correlation analysis (regression curves are built). The second experiment is connected to evaluation of the ratio of the number of robots to the number of population in 2019 and 2022. The research objects are countries with the highest number of robots in the world – i.e. with the highest level of development of industry 4.0; the information and empirical basis is materials of the International Federation of Robotics and the International Monetary Fund for 2019 and their forecasts for 2022.

Findings

The results of the performed experiments showed that in 2019 and 2022 the level of robotization of socio-economic systems of the countries of the world will be very low, and robotization will not cause growth of unemployment. Based on this, it is concluded that industry 4.0 will be developing according to the scenario of moderate automatization and robotization with preservation of domination of human labor in most business processes and spheres of economy. Communications with people will constitute the basis of the activities of digital personnel, and social competencies (with obvious significance of technical competencies) will be of top priority for them.

Originality/value

It is substantiated that technical competencies, with their large importance, will move to the background, while the key task will be society’s adaptation to the new technological mode and making social competencies the highest priority. The social and technical competencies of digital personnel in view of the performed tasks for industry 4.0 are determined.

Keywords

Citation

Popkova, E.G. and Zmiyak, K.V. (2019), "Priorities of training of digital personnel for industry 4.0: social competencies vs technical competencies", On the Horizon, Vol. 27 No. 3/4, pp. 138-144. https://doi.org/10.1108/OTH-08-2019-0058

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited


1. Introduction

Transition to industry 4.0, which started recently in most countries of the world (2012-2018) caused the necessity for formation of a new segment of the labor market – digital personnel; digital personnel use in their professional activities the technical means of the fourth technological mode (the most popular example is robots).

The problem of training of digital personnel consists of the fact that they should conform and be adapted not only to the current but also to the future (which is of higher priority in view of the quickly changing context) needs of the labor market. This determines the topicality of the research that are aimed at reducing the uncertainty as to the set of competencies that will be in demand in the future and have to be mastered by the modern digital personnel.

We offer two alternatives (opposite) hypotheses as to the future needs of economy for digital personnel, which reflect two possible scenarios of development of industry 4.0. According to hypothesis H1, industry 4.0 is developing according to the scenario of total automatization and mass robotization. A vivid sign of implementation of this scenario is quick growth of unemployment. Machine communications dominate in the process of production and the process of distribution. The task of digital personnel within this scenario is brought down to servicing technical means of the fourth technological mode, which envisages foundation on technical competencies.

Hypothesis H2 envisages development of industry 4.0 according to the scenario of moderate automatization and robotization with preservation of domination of human labor in most business processes and spheres of economy. Human communications dominate also in the distribution and most production processes. The task of digital personnel, in this case, is stimulating the implementation of technical devices of the fourth technological mode through stimulation of social adaptation to it with foundation on social competencies.

From the point of view of personnel, simultaneous formation of social and technical competencies is a complex task. Therefore, it is necessary to set the priorities between these contradictory types of competencies. This research is aimed at determining the priorities of formation of competencies during training of digital personnel for industry 4.0.

2. Materials and method

The educational aspects of training of digital personnel, including those regarding the set of the necessary competencies, are discussed in the works of Popkova (2017, 2019), Popkova and Sergi (2019a, 2019b), Popkova et al. (2019), Sergi et al. (2019), Sozinova (2019) and Sukhodolov et al. (2018). The perspectives of future development of industry 4.0 in economies of the modern socio-economic systems are described in the works of Björn et al. (2019), Do et al. (2019), Ma (2019), Adekola and Sergi (2016), Goyal et al. (2017), Popkova and Sergi (2019a, 2019b), Sergi (2003, 2019), Sergi et al. (2012), Sergi et al. (2019), Wamboye et al. (2016) and Wamboye et al. (2015).

At the same time, the priorities of training of digital personnel for industry 4.0 from the positions of opposition of social and technical competencies are not determined and require further research. For determining the scenario, according to which industry 4.0 is developing and will be developing (i.e. for verification of hypotheses), let us perform two experiments:

  • let us determine the influence of the number of robots on the unemployment level in 2019 and 2022 with the help of regression and correlation analysis (building a regression curve); and

  • let us evaluate the ratio of the number of robots to the number of population in 2019 and 2022.

The research objects are countries that are peculiar for the highest number of robots in the world – i.e. showing the highest level of development of industry 4.0. The information and empirical basis of the research is materials of the International Federation of Robotics and the International Monetary Fund for 2019 and their forecasts for 2022 (Table I).

Based on the data of Table I, two experiments were performed. Their results are presented in Figures 1-3.

According to the presented regression curves, the number of robots does not have statistically significant influence on the unemployment level in the countries of the selection in 2019 (correlation – 8.77 per cent) or 2022 (correlation – 6.52 per cent). In both cases, the connection between these indicators is very low and reverse (negative value of the estimate coefficients in the models of paired linear regression).

Figure 2 shows that the highest population (1,407.27 million people in 2019 and 1,432.26 million people in 2022) and the highest number of robots (165,000 in 2019 and 290,000 in 2022) are observed in China.

Figure 3 shows that the highest number of robots per 10,000 people is observed in Thailand – 28.76 in 2019 and 48.79 in 2022. Thus, the results of the performed experiments showed that in 2019 and 2022 (according to the forecasts of the experts of the International Federation of Robotics and the International Monetary Fund) the level of robotization of socio-economic systems of countries will be very low, and robotization will not cause growth of unemployment.

Based on this, hypothesis H1 is disproved, and hypothesis H2 is proved – industry 4.0 will take place according to the scenario of moderate automatization and robotization with preservation of domination of human labor in most business processes and spheres of economy. Communication with people will be the basis of activities of digital personnel, so social competencies will be a priority for them (with obvious significance of technical competencies).

3. Results

According to the determined scenario of development of industry 4.0, social and technical competencies of digital personnel in view of the performed tasks are determined (Table II).

Table II shows that digital personnel of industry 4.0 are heterogeneous and the sets of their competencies are different for different professions. Independent usage of TD4.0* during production of goods and provision of services (e.g. hi-tech and innovative educational or medical services) are performed by all digital personnel of industry 4.0. For this task, social (communicative) competencies are a priority. Also, the competencies of active usage of TD4.0* are necessary.

Technical and marketing support for usage of TD4.0* by consumers (e.g. in the form of specialized call-center of providers and suppliers of these devices) is performed by the personnel that are involved in the segment of sales of TD4.0* (wholesale and retail, provision of specialized services). For them, social competencies – communicative and psychological – are a priority; also, the competencies of technical support for users during usage of TD4.0* are necessary.

The systems and processes of automatization of production on the basis of TD4.0* are designed by an engineer in industry 4.0 (specialized profession). He has to have the competencies of designer of TD4.0* (knowledge of specific features of these devices), but social competencies – communicative and managerial – are also a priority for him, as he deals with personnel management as well.

Technical maintenances and repairs of TD4.0* are conducted by information and communication technologies (ICT) specialists in industry 4.0. They require communicative competencies (minimum set), but ICT competencies and competencies of technical maintenances and repairs of TD4.0* are a priority for them. Control over automatized productions on the basis of TD4.0* is conducted by auxiliary low-skilled digital personnel of industry 4.0. They do not require social competencies, for technical competencies – competencies of usage of TD4.0* – are a priority for them.

The performed research could influence the modern educational practice of training of digital personnel and the process of its state regulation. The results of the research specify the market’s requirements to digital personnel, due to which they are to be the scientific basis for developing the state educational standards for training of digital personnel and the corresponding educational programs of universities.

4. Conclusion

Thus, because of the research, it was determined that out of two offered hypotheses the hypothesis H2 is correct – industry 4.0 develops according to the scenario of moderate automatization and robotization with preservation of domination of human labor in most business processes and spheres of economy. Thus, in most segments of industry 4.0 and most professions the human communications will dominate, due to which social competencies will have the priority.

At most companies of industry 4.0, technical devices of the fourth technological mode (e.g. robots) will be used as auxiliary means of fragmentary automatization (as PC’s are used now) with preservation of communications with customers during selling the goods and providing the services (marketing is necessary) and communications in the workgroup (personnel management is necessary). Thus, technical competencies, despite their obvious importance, will go to the background, while the key task will be society’s adaptation to the new technological mode, and social competencies will have the priority.

Figures

Regression curves that reflect the influence of the number of robots on the unemployment level in the countries of selection in 2019 and 2022 (forecast)

Figure 1

Regression curves that reflect the influence of the number of robots on the unemployment level in the countries of selection in 2019 and 2022 (forecast)

Number of robots and population in the countries of the selection in 2019 and 2022 (forecast)

Figure 2

Number of robots and population in the countries of the selection in 2019 and 2022 (forecast)

Number of robots per 10,000 people in the countries of the selection in 2019 and 2022 (forecast)

Figure 3

Number of robots per 10,000 people in the countries of the selection in 2019 and 2022 (forecast)

Population, unemployment, and number of robots in the countries of selection in 2019 (at the beginning of the year) and the forecast for 2022

Country Unemployment rate, per cent of total labor force Population, million No. of robots
2019 2022 2019 2022 2019 2022
Brazil 10.855 10 210.679 214.768 900 1,200
Canada 6.7 6.579 37.506 38.757 3,500 6,500
China 4.02 4.02 1,407.27 1,432.26 165,000 290,000
France 8.959 8.318 65.496 66.399 5,200 6,500
Germany 4.208 4.09 83.395 83.454 22,500 26,000
Italy 10.55 9.95 60.74 60.66 9,000 10,500
Japan 3.063 3.063 125.444 123.832 54,000 64,000
Korea 3.3 3.1 51.874 52.509 41,000 46,000
Mexico 4.308 4.249 125.929 129.352 4,500 9,000
Russia 5.5 5.5 143.102 142.351 3,801 4,751
Spain 15.778 14.486 46.126 45.923 4,700 6,500
Taiwan Province of China 3.92 3.92 23.684 23.828 13,000 20,000
Trinidad and Tobago 4.02 3.78 1.386 1.406 4,000 7,000
UK 5.2 5 66.928 68.203 2,400 2,600
USA 4.439 4.993 330.766 338.448 35,000 46,000
Vietnam 2.4 2.4 95.577 97.934 2,500 7,000

Source: Compiled by the author based on International Federation of Robotics (2019) and International Monetary Fund (2019)

Social and technical competencies of digital personnel in view of the performed tasks for industry 4.0

Task Subject of execution of the task Competencies that are necessary for performing the task
Social Technical
Independent usage of TD4.0* during production of goods and provision of services All digital personnel of industry 4.0 Priorities:
communicative competencies
Competencies of active usage of TD4.0*
Technical and marketing support for usage of TD4.0* by consumers Digital personnel that are involved in the segments of sales of TD4.0* (wholesale and retail) Priorities:
communicative competencies;
psychological competencies
Competencies of technical support for users during usage of TD4.0*
Designing systems and processes of automatization of production on the basis of TD4.0* Design engineer in industry 4.0 (specialized profession) Priorities:
communicative competencies;
whole specter of managerial competencies
Competencies of designer of TD4.0*
Technical maintenance and repairs of TD4.0* ICT-specialists in industry 4.0 Communicative competencies (minimum set) Priorities:
ICT competencies;
competencies of technical maintenance and repairs of TD4.0*
Control over automatized productions on the basis of TD4.0* Auxiliary low-qualified digital personnel of industry 4.0 Not required Priorities:
Competencies of usage of TD4.0*
Notes:

TD4.0* – technical devices of the fourth technological mode (e.g. robots); ICT – information and communication technologies

Source: Developed and compiled by the author

References

Adekola, A. and Sergi, B.S. (2016), Global Business Management: A Cross-Cultural Perspective, Routledge, New York, NY.

Björn, M., Ravyse, W., Villafruella, D.S., Luimula, M. and Leivo, S. (2019), “Higher education learner experience with fuzzy feedback in a digital learning environment”, 9th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2018 – Proceedings, Vol. 8639910, pp. 253-260.

Do, H.V., Dorner, D.G. and Calvert, P. (2019), “Discovering the contextual factors for digital library education in Vietnam”, Global Knowledge, Memory and Communication, Vol. 68 Nos 1/2, pp. 125-147.

Goyal, S., Kapoor, A., Esposito, M. and Sergi, B.S. (2017), “Understanding business model-literature review of concept and trends”, International Journal of Competitiveness, Vol. 1 No. 2, pp. 99-118.

International Federation of Robotics (2019). “WR 2018 industrial robots executive summary”, available at: https://ifr.org/free-downloads/ (accessed 5 June 2019).

International Monetary Fund (2019), “World economic outlook database”, available at: www.imf.org/external/pubs/ft/weo/2017/01/weodata/weoselgr.aspx (accessed 5 June 2019).

Ma, L. (2019), “Research on distance education image correction based on digital image processing technology”, Eurasia Journal on Image and Video Processing, Vol. 2019 No. 1, p. 18.

Popkova, E.G. (2017), “Economic and legal foundations of modern Russian society: a new institutional theory”, Advances in Research on Russian Business and Management, Information Age Publishing, Charlotte (NC).

Popkova, E.G. (2019), “Preconditions of formation and development of industry 4.0 in the conditions of knowledge economy”, Studies in Systems, Decision and Control, Vol. 169 No. 1, pp. 65-72.

Popkova, E.G. and Sergi, B.S. (2019a), “Will industry 4.0 and other innovations impact Russia’s development?”, Exploring the Future of Russia's Economy and Markets, Emerald Publishing, pp. 34-42.

Popkova, E.G. and Sergi, B.S. (2019b), “Will industry 4.0 and other innovations impact Russia’s development?”, in Sergi, B.S. (Ed.) Exploring the Future of Russia’s Economy and Markets: Towards Sustainable Economic Development, Emerald Publishing, Bingley, pp. 51-68.

Popkova, E.G., Morozova, I.A. and Litvinova, T.N. (2019), “Transformational processes in the media system under industry conditions 4.0: future outlines and perspectives (reflections on the article by Alexander, P., Sukhodolov, DSc: in economics, professor and Irina, A., Kuznetsova, PhD in engineering, associate professor “designing the mass media as a homeostatic system by means of automation engineering: basic concepts, structure, components)”, Theoretical and Practical Issues of Journalism, Vol. 7 No. 1, pp. 145-154.

Sergi, B.S. (Ed.) (2019), Tech, Smart Cities, and Regional Development in Contemporary Russia, Emerald Publishing Limited, Bingley.

Sergi, B.S., Bagatelas, W.A. and Kubicova, J. (Eds) (2012), Industries and Markets in Central and Eastern Europe, Ashgate Publishing.

Sergi, B.S. (2003), Economic Dynamics in Transitional Economies: The Four-P Governments, the EU Enlargement, and the Bruxelles Consensus, Routledge, New York, NY.

Sergi, B.S., Popkova, E.G., Bogoviz, A.V. and Litvinova, T.N. (2019), Understanding Industry 4.0: AI, the Internet of Things, and the Future of Work, Emerald Publishing Limited, Bingley.

Sergi, B.S., Popkova, E.G., Bogoviz, A.V. and Ragulina, J.V. (2019), “Entrepreneurship and economic growth: the experience of developed and developing countries”, Entrepreneurship and Development in the 21st Century, Emerald publishing limited, pp. 3-32.

Sozinova, A.A. (2019), “Causal connections of formation of industry 4.0 from the positions of the global economy”, Studies in Systems, Decision and Control, Vol. 169, pp. 131-143.

Sukhodolov, A.P., Popkova, E.G. and Litvinova, T.N. (2018), Models of Modern Information Economy: Conceptual Contradictions and Practical Examples, Emerald Publishing Limited, Bingley, pp. 1-38.

Wamboye, E., Adekola, A. and Sergi, B.S. (2016), “ICTs and labour productivity growth in Sub-Saharan Africa”, International Labour Review, Vol. 155 No. 2, pp. 231-252.

Wamboye, E., Tochkov, K. and Sergi, B.S. (2015), “Technology adoption and growth in Sub-Saharan African countries”, Comparative Economic Studies, Vol. 57 No. 1, pp. 136-167.

Corresponding author

Elena G. Popkova can be contacted at: elenapopkova@yahoo.com

About the authors

Elena G. Popkova is based at the Plekhanov Russian University of Economics, Moscow, Russian Federation.

Kristina V. Zmiyak is based at Southern Federal University, Rostov na Donu, Russian Federation and Don State Technical University, Rostov-on-Don, Russian Federation.