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Marketing i Menedžment Innovacij
Article . 2014
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Stochastic methods of machinery enterprise endogenous innovative potential realization management

Authors: Mosin, O.O.;

Stochastic methods of machinery enterprise endogenous innovative potential realization management

Abstract

The aim of the article. The goal of the article is definition of effective stochastic methods of management of realization of the endogenous innovative potential (EIP) of machine-building enterprise through forecasting of enterprise’s level of gross profit on the basis of values of its reserves which constitute EIP. The results of the analysis. Theoretical approaches to management of the machinery enterprise’s innovative development need to be verified by empirical researches. Evaluation of the enterprise’s innovative potential may become crucial for R&D management. Systematization and comparing methods were used to generalize ongoing approaches to enterprise innovative potential determination; deduction method was used for defining the characteristics of the machinery enterprise innovative potential. Various methods of the enterprise innovative potential development management are considered in the article. Special attention is paid to classification of approaches to definition an essence of innovative process. Development of comprehensive approach to choosing the methods of innovative potential management is based on the classification of innovations by their types. Some of the given methods can be applied to management of several types of innovations. So method of the assessment of investment efficiency indicators can be used both for management of product and technological innovations, and method of definition of a stage of innovative development can be applied for both organizational and product innovations. Thus, the scientific novelty of the research is the application of comprehensive approach to enterprise innovative potential development on the basis of allocation of types of introduced innovations and respective methods of management. At the same time further research should consider a problem of definition of an optimum ratio of quantity of introduced technological, product and organizational innovations. It is necessary to investigate the influence of different types of innovations on the enterprise competitiveness and moulding of the organization innovative potential. An estimation algorithm of machinery enterprise innovative potential is designed, which unlike other approaches (resource and managerial) enables to evaluate the shape of innovations potentiality, not their ongoing present shape. An algorithm to estimation of machinery enterprise technological innovative potential is molded. This algorithm enables to evaluate quantitatively the inner reserves of the enterprise which may be used for the implementation of process and product innovations. The implementation of the suggested algorithm enables the enterprises of heavy machinery industry to estimate their own innovative potential, which creates premises for more effective realization of it. Conclusions and directions of further researches. The offered technique of creation of support vectors and neural network models allows predicting the level of gross profit depending on the basis of values of enterprise’s reserves. The offered analytical procedures promote economic development of machine-building enterprises which are an essential part of Ukrainian industry.

Country
Ukraine
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Keywords

ендогенний інноваційний потенціал, резерви підприємства, резервы предприятия, neural network, модель опорных векторов, машинобудівне підприємство, endogenous innovative potential, Marketing. Distribution of products, HF5410-5417.5, машиностроительное предприятие, support vectors model, нейронная сеть, Economics as a science, machinery enterprise, модель опорних векторів, нейронна мережа, эндогенный инновационный потенциал, reserves of enterprise, HB71-74

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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