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SELF-ADAPTING ALGORITHMS: ENHANCING ORGANIZATION CAPABILITY

I. Kazina, R. Kopitov

First published: 2019https://doi.org/10.5593/SWS.ISCSS.2019.2/S05.089View metrics

Abstract

A new approach, which ensures the obtainment of an objective conclusion about the state of the enterprise at the current time, is proposed. The peculiarity of the approach is the presence of an algorithm, which ensures not only the transformation of numerous performance standards into the specific measures of efficiency, but also the implementation of the transition from a variety of traditional models to a unique method. Thus, the conditions for the adoption of the management system that is capable of organizing a stable operation of an enterprise in the context of arbitrary occurring disturbances both at the level of external influence and at the level of response impact are created. This refers to self-adapting tools that determine the operational capability of the organization based on a single criterion. Such criterion is the dimensionless coordinate of a strategic position, which is located relative to a finitely set destination point. The calculated value of the coordinate is fixed within the framework of the strategic field by sequential determination of the significance of the specially selected attributes. The selection of such attributes is carried out within the framework of the formed hierarchy of values, which consists of fifteen nodes. The connection between the nodes is ensured by application of methodological principles of construction of metasystems and the use of Haitun analysis, which allows identifying the semantic units of operational definitions.

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Publication details

Title
SELF-ADAPTING ALGORITHMS: ENHANCING ORGANIZATION CAPABILITY
Authors
I. Kazina, R. Kopitov
Proceedings
6th SWS International Scientific Conference on Social Sciences ISCSS 2019
Publisher
STEF92 Technology
Year
2019
Pages
733-740
SWS Citekey
Kazina20195733740
ISSN
2682-9959
ISBN
978-619-7408-92-8
Language
en
Publication type
Proceedings Paper
Keywords
methodologyqualityperformancemaintenancerecovery
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