Kemerovo, Kemerovo, Russian Federation
The relevance of the research issue is associated with the need for industrial enterprises to transit to the concept of Industry 4.0, which implies the digitalization of the entire array of knowledge of enterprise employees and the conscious management of this array by managers. The present research features the observance of the interests of the human worker when implementing the enterprise 4.0 knowledge management system according to the requirements of the standard. The purpose of the study is to analyze the international standard ISO 30401:2018 "Knowledge management systems – Requirements" (hereinafter – the Standard) through the prism of the interests of the man of labor. The research methodology is based on the systematic and holistic anthroposocial approach. The novelty lies in the application of the anthroposocial approach to the knowledge economy developed by the author to the formulation of critical comments on the Standard. In terms of knowledge management, the author proposes anthroposociality as a new dimension and a priority of the new economy. Research results: the Standard with its basic terms, categories, and guidelines does not take into account the interests of the creator and holder of knowledge, i.e. the man of labor. In the case of the transition of Russian enterprises to the Standard, there may be obstacles to the formation of the human-oriented knowledge economy with Industry 4.0 in the country. The scope of the results is the development of personnel and social policies at the enterprise 4.0, taking into account critical comments on the Standard. Conclusions: the man of labor is the only creator, distributor, and user of automated production and control systems, as well as applied professional knowledge, which is the source of value at the enterprise 4.0. The standard that regulates the development and implementation of the knowledge management system at the enterprise 4.0 should take into account the interests of an employee as a holistically developing person. The information and technical component of the knowledge management system should be friendly to the human worker of the Industry 4.0 enterprise, saving, and not draining them of their cognitive skills and vitality.
digitalization, ISO standard, applied knowledge, value, anthroposocial approach, anthroposociality, man of labor
1. Schwab K. The fourth industrial revolution. Moscow: Eksmo, 2016, 208. (In Russ.)
2. Miroshnikov V. V., Barabanova I. A., Shkolina T. V. Standardization of knowledge control processes in system of organization quality. Bulletin of Bryansk State Technical Universita, 2019, (1): 52-59. (In Russ.) DOI:https://doi.org/10.30987/article_5c4ed021938851.53086358
3. Moreira F., Ferreira M. J., Seruca I. Enterprise 4.0 - the emerging digital transformed enterprise? Procedia Computer Science, 2018, 138: 525-532.
4. Kudryavtsev D., Sadykova D. Towards architecting a knowledge management system: requirements for an ISO compliant framework. The Practice of Enterprise Modeling. PoEM 2019. Lecture Notes in Business Information Processing, eds. Gordijn J., Guedria W., Proper H. 2019, vol. 369, 36-50. DOI: https://doi.org/10.1007/978-3-030-35151-9_3
5. Corney P. J. As KM evolves, so will the ISO standard. Business Information Review, 2018, 35(4): 165-167. DOI: https://doi.org/10.1177/0266382118810825
6. Wilson J. P., Campbell L. Developing a knowledge management policy for ISO 9001: 2015. Journal of Knowledge Management, 2016, 20(4): 829-844. DOI: https://doi.org/10.1108/JKM-11-2015-0472
7. Kleiner G. B. Intellectual economy of the new age: post-knowledge economy. Ekonomicheskoe vozrozhdenie Rossii, 2020, (1): 35-42. (In Russ.)
8. Zhernov E. E. Firm anthropomorphism: pro et contra. Economist, 2016, (11): 36-46. (In Russ.)
9. Dresvyannikov V. A., Bunimovich I. D. Cloud technologies in knowledge management. Vestnik Kemerovskogo gosudarstvennogo universiteta. Seriia: Politicheskie, sotsiologicheskie i ekonomicheskie nauki, 2018, (4): 67-72. (In Russ.) DOI:https://doi.org/10.21603/2500-3372-2018-4-67-72
10. Schumpeter J. A. Capitalism, socialism and democracy, tr. and ed. Avtonomov V. S. Moscow: Ekonomika, 1995, 539. (In Russ.)
11. Wu I.-L., Chen J.-L. Knowledge management driven firm performance: the roles of business process capabilities and organizational learning. Journal of Knowledge Management, 2014, 18(6): 1141-1164. DOI: https://doi.org/10.1108/JKM-05-2014-0192
12. Yu W.-D., Lin T.-C., Liu S.-J., Chang P.-L. Is the knowledge management system truly cost effective? Case study of KM-enabled engineering problem solving. Journal of Construction Engineering and Management, 2013, 139(2): 216-224. DOI:https://doi.org/10.1061/(ASCE)CO.1943-7862.0000604
13. Alpaydin E. Machine learning: the new AI. Moscow: Izdatelskaia gruppa "Tochka"; Alpina Pablisher, 2017, 208. (In Russ.)
14. Plakitkina L. S. Prospect of development in the Kuznetsk Coal Basin over the period up to 2035. Gornyi zhurnal, 2015, (12): 28-33. (In Russ.) DOI:https://doi.org/10.17580/gzh.2015.12.06
15. Ryazanov V. T. New technological revolution: expectations and variations of the future economic model. Ekonomicheskoe vozrozhdenie Rossii, 2019, (4): 43-51. (In Russ.)
16. Morozova E. A., Kuznecova T. A. The needs of high school student in vocational education. Russian knowledge economy: the contribution of regional researchers: Proc. All-Russian Sci. Conf. from Intern. participation, Kemerovo, October 5-6, 2017, ed. Zhernov E. E. Kemerovo, 2017, 295-299. (In Russ.)
17. Zhernov E. E. Conception of knowledge management in the firm: anthroposociality as the priority dimension. Vestnik Kemerovskogo gosudarstvennogo universiteta. Seriia: Politicheskie, sotsiologicheskie i ekonomicheskie nauki, 2018, (4): 73-79. (In Russ.) DOI:https://doi.org/10.21603/2500-3372-2018-4-73-79
18. Winfield A. F. T., Blum C., Liu W. Towards an ethical robot: internal models, consequences and ethical action selection. Advances in Autonomous Robotics Systems. TAROS 2014. Lecture Notes in Computer Science, 2014, 8717: 85-96. DOI:https://doi.org/10.1007/978-3-319-10401-0_8
19. Winfield A. F., Michael K., Pitt J., Evers V. Machine ethics: the design and governance of ethical AI and autonomous systems. Proceedings of the IEEE, 2019, 107(3): 509-517. DOI:https://doi.org/10.1109/JPROC.2019.2900622