E3S Web Conf.
Volume 217, 2020International Scientific and Practical Conference “Environmental Risks and Safety in Mechanical Engineering” (ERSME-2020)
|Number of page(s)||5|
|Published online||14 December 2020|
Applying implicit knowledge for enterprise architectural transformation
1 Vyatka State University, 36, Moskovskaya str., 610000, Kirov, Russia
2 Vyatka State Agricultural Academy, 133, Oktyabrsky bvld., 610017, Kirov, Russia
3 Moscow State University of Civil Engineering, 26, Yaroslavskoye Shosse, 109377, Moscow, Russia
* Corresponding author: firstname.lastname@example.org
The study describes a simulation model for the formalization of implicit knowledge about the team. The existing algorithms and methods of work to increase the amount of useful knowledge about the human capital of the organization do not allow obtaining knowledge about the development of the team and internal relationships. The effectiveness of architectural transformations directly depends on the quality of human capital management. The proposed model formalizes relations in the organization and proposes to form one of 4 strategies for personnel development, considering the individual characteristics of each of the employees. The article introduces the concepts of types of thinking and their connection to the life cycle of an organization. The study showed that the assessment of the organization’s personnel composition reveals the hidden cause-effect relationships between the effectiveness of the team and the stages of the organization’s life cycle.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.