Fuzzy simulation of organizational adjustment processes management based on heat supply balanced scorecard

Bazil, Gulmira; Adilova, Shinar K.; Abzhanova, L. K.; Sugurova, Laura A.; Yerzhanova, Mira

doi:10.1007/s41062-020-00435-3

Cited by 3 publications

(2 citation statements)

References 20 publications

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“…Unfortunately, in the scientific literature, we were unable to find fuzzy models for identifying implicit factors of the IC. At the same time, there are works that offer fuzzy tools in relation to a wide variety of implicit factors of socioeconomic systems [38][39][40][41].…”

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confidence: 99%

Formation of the causal field of indicators for an organization’s intellectual capital development: A concept and a fuzzy economic and mathematical model

Zavalin,

Nedoluzhko,

Solodukhin

2023

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The development of intellectual capital theory through the introduction of the concept of implicitness involves considering intellectual capital as an implicit factor, so that the process of its formation is largely determined by the impact of specific hidden factors whose impact is expressed implicitly and is difficult to formalize. Currently, the process of selecting explicit and implicit factors affecting intellectual capital is not formalized in domestic and foreign studies, and therein is the relevance of this work. The purpose of this study was to develop a scheme for selecting explicit and implicit factors in the development of the organization’s intellectual capital in conjunction with its strategy based on a modified Balanced Scorecard, taking into account the distribution of indicators by types of cognitive activity. The implementation of this scheme was carried out by developing a fuzzy economic and mathematical model suitable for practical use. The main feature of the model is the possibility of fuzzy setting of “cut-off boundaries” for explicit and implicit factors. We present the results of testing the model on the example of a large regional university. Sets of explicit and implicit factors of the university’s intellectual capital are given for various “cut-off boundaries” using various defuzzification methods.

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confidence: 99%

Formation of the causal field of indicators for an organization’s intellectual capital development: A concept and a fuzzy economic and mathematical model

Zavalin,

Nedoluzhko,

Solodukhin

2023

Bus. Inform.

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confidence: 99%

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2023

Bus. Inform.

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The mission of the journal is to develop business informatics as a new field within both information technologies and management. It provides dissemination of latest technical and methodological developments, promotes new competences and provides a framework for discussion in the field of application of modern IT solutions in business, management and economics.The journal publishes papers in the following areas: modeling of social and economic systems, digital transformation of business, innovation management, information systems and technologies in business, data analysis and business intelligence systems, mathematical methods and algorithms of business informatics, business processes modeling and analysis, decision support in management.The journal is included into the list of peer reviewed scientific editions established by the Supreme Certification Commission of the Russian Federation.

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Comparative Analysis of Production Functions of Complex Variables of the Predictive Model of Resource Support for the Process of Heat Generation

Bazil,

Mukhanov,

Iskakova

et al. 2023

2023 IEEE International Conference on Smart Information Systems and Technologies (SIST)

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Fuzzy simulation of organizational adjustment processes management based on heat supply balanced scorecard

Cited by 3 publications

References 20 publications

Formation of the causal field of indicators for an organization’s intellectual capital development: A concept and a fuzzy economic and mathematical model

Formation of the causal field of indicators for an organization’s intellectual capital development: A concept and a fuzzy economic and mathematical model

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Comparative Analysis of Production Functions of Complex Variables of the Predictive Model of Resource Support for the Process of Heat Generation

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