Pub Date : 2019-09-30DOI: 10.17323/1998-0663.2019.3.78.96
Y. Turovets, K. Vishnevskiy
The shift to digital technologies in various industries is one of the key goals in the digital agenda. Due to the essential role of interoperability of products and elements in complex systems, standardization stays in the forefront of government policy and business. In manufacturing systems, standards are of a prime importance, since they serve as a channel for modernization and innovation speedup. This paper makes a contributionto the currently rare literature on digital manufacturing standardization as a policy tool to promote digital technologies in business. By comparing five national cases of China, Germany, Japan, the Republic of Korea and the USA, we introduce national models of standardization in smart manufacturing according to the extent of state participation in standardization. In doing so, we examined initiatives in industry, digitalization, the development of a national system of standards, the reference architecture of digital production, as well as the countries’ cooperation in the field. Along with this, an overview of international initiatives in the field is presented, namely the ISO and the IEC. Taking into account the existing landscape, an assessment of the Russian case of digitalization in manufacturing and standardization is presented. Like China, Russia follows the third model of standardization. Given the results, we developed recommendations for Russia with the aim of intensifying efforts at standardization and the country’s presence in the international agenda, as well as to develop a Russian framework for digital transformation in sectors and achieve related economic effects.
{"title":"Standardization in digital manufacturing: implications for Russia and the EAEU","authors":"Y. Turovets, K. Vishnevskiy","doi":"10.17323/1998-0663.2019.3.78.96","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.3.78.96","url":null,"abstract":"The shift to digital technologies in various industries is one of the key goals in the digital agenda. Due to the essential role of interoperability of products and elements in complex systems, standardization stays in the forefront of government policy and business. In manufacturing systems, standards are of a prime importance, since they serve as a channel for modernization and innovation speedup. This paper makes a contributionto the currently rare literature on digital manufacturing standardization as a policy tool to promote digital technologies in business. By comparing five national cases of China, Germany, Japan, the Republic of Korea and the USA, we introduce national models of standardization in smart manufacturing according to the extent of state participation in standardization. In doing so, we examined initiatives in industry, digitalization, the development of a national system of standards, the reference architecture of digital production, as well as the countries’ cooperation in the field. Along with this, an overview of international initiatives in the field is presented, namely the ISO and the IEC. Taking into account the existing landscape, an assessment of the Russian case of digitalization in manufacturing and standardization is presented. Like China, Russia follows the third model of standardization. Given the results, we developed recommendations for Russia with the aim of intensifying efforts at standardization and the country’s presence in the international agenda, as well as to develop a Russian framework for digital transformation in sectors and achieve related economic effects.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43628809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-30DOI: 10.17323/1998-0663.2019.3.52.66
A. Karminsky, Roman Burekhin
This paper is devoted to comparison of the capabilities of various methods to predict the bankruptcy of construction industry companies on a one-year horizon. The authors considered the following algorithms: logit and probit models, classification trees, random forests, artificial neural networks. Special attention was paid to the peculiarities of the training machine learning models, the impact of data imbalance on the predictive ability of models, analysis of ways to deal with these imbalances and analysis of the influence of non-financial factors on the predictive ability of models. In their study, the authors used non-financial and financial indicators calculated on the basis of public financial statements of the construction companies for the period from 2011 to 2017. The authors concluded that the models considered show acceptable quality for use in forecasting bankruptcy problems. The Gini or AUC coefficient (area under the ROC curve) was used as the quality markers of the model. It was revealed that neural networks outperform other methods in predictive power, while logistic regression models in combination with discretization follow them closely. It was found that the effective way to deal with the imbalance data depends on the type of model used. However, no significant impact on the imbalance in the training set predictive ability of the model was identified. The significant impact of non-financial indicators on the likelihood of bankruptcy was not confirmed.
{"title":"Comparative analysis of methods for forecasting bankruptcies of Russian construction companies","authors":"A. Karminsky, Roman Burekhin","doi":"10.17323/1998-0663.2019.3.52.66","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.3.52.66","url":null,"abstract":"This paper is devoted to comparison of the capabilities of various methods to predict the bankruptcy of construction industry companies on a one-year horizon. The authors considered the following algorithms: logit and probit models, classification trees, random forests, artificial neural networks. Special attention was paid to the peculiarities of the training machine learning models, the impact of data imbalance on the predictive ability of models, analysis of ways to deal with these imbalances and analysis of the influence of non-financial factors on the predictive ability of models. In their study, the authors used non-financial and financial indicators calculated on the basis of public financial statements of the construction companies for the period from 2011 to 2017. The authors concluded that the models considered show acceptable quality for use in forecasting bankruptcy problems. The Gini or AUC coefficient (area under the ROC curve) was used as the quality markers of the model. It was revealed that neural networks outperform other methods in predictive power, while logistic regression models in combination with discretization follow them closely. It was found that the effective way to deal with the imbalance data depends on the type of model used. However, no significant impact on the imbalance in the training set predictive ability of the model was identified. The significant impact of non-financial indicators on the likelihood of bankruptcy was not confirmed.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41844010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-09-30DOI: 10.17323/1998-0663.2019.3.7.19
S. Podgorskaya, A. Podvesovskii, R. Isaev, N. Antonova
The paper is devoted to fuzzy cognitive modeling, which is an effective tool for studying semistructured socio-economic systems. The emphasis is on the process of developing (identification) fuzzy cognitive models, which are the most complex and critical stage of cognitive modeling. Existing identification methods are classified as either expert or statistical, depending on the source of information used. Typically, when constructing fuzzy cognitive models of semi-structured systems, the system under consideration possesses both quantitative (measurable) factors and factors of a relative, qualitative nature. While statistical data on the quantitative factors may be available, the only available source of information on the qualitative factors is expert knowledge. MODELING OF SOCIAL AND ECONOMIC SYSTEMS
{"title":"Fuzzy cognitive models for socio-economic systems as applied to a management model for integrated development of rural areas","authors":"S. Podgorskaya, A. Podvesovskii, R. Isaev, N. Antonova","doi":"10.17323/1998-0663.2019.3.7.19","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.3.7.19","url":null,"abstract":"The paper is devoted to fuzzy cognitive modeling, which is an effective tool for studying semistructured socio-economic systems. The emphasis is on the process of developing (identification) fuzzy cognitive models, which are the most complex and critical stage of cognitive modeling. Existing identification methods are classified as either expert or statistical, depending on the source of information used. Typically, when constructing fuzzy cognitive models of semi-structured systems, the system under consideration possesses both quantitative (measurable) factors and factors of a relative, qualitative nature. While statistical data on the quantitative factors may be available, the only available source of information on the qualitative factors is expert knowledge. MODELING OF SOCIAL AND ECONOMIC SYSTEMS","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42835080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-30DOI: 10.17323/1998-0663.2019.2.29.42
I. Hodashinsky, M. Nemirovich-Danchenko, S. Samsonov
In this paper, we discuss the construction of fuzzy classifiers by dividing the task into the three following stages: the generation of a fuzzy rule base, the selection of relevant features, and the parameter optimization of membership functions for fuzzy rules. The structure of the fuzzy classifier is generated by forming the fuzzy rule base with use of the minimum and maximum feature values in each class. This allows us to generate the rule base with the minimum number of rules, which corresponds to the number of class labels in the dataset to be classified. Feature selection is carried out by a binary spider monkey optimization (BSMO) algorithm, which is a wrapper method. As a data preprocessing procedure, feature selection not only improves the efficiency of training algorithms but also enhances their generalization capability. In the process of feature selection, we investigate the dynamics of changes in classification accuracy, iteration by iteration, for various parameter values of the binary algorithm and analyze the effect of its parameters on its convergence rate. The parameter optimization of fuzzy rule antecedents uses another spider monkey optimization (SMO) algorithm that processes continuous numerical data. The performance of the fuzzy classifiers based on the rules and features selected by these algorithms is tested on some datasets from the KEEL repository. Comparison with two competitor algorithms on the same datasets is carried out. It is shown that fuzzy classifiers with the minimum number of rules and a significantly reduced number of features can be developed with their accuracy being statistically similar to that of the competitor classifiers.
{"title":"Feature selection for fuzzy classifier using the spider monkey algorithm","authors":"I. Hodashinsky, M. Nemirovich-Danchenko, S. Samsonov","doi":"10.17323/1998-0663.2019.2.29.42","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.2.29.42","url":null,"abstract":"In this paper, we discuss the construction of fuzzy classifiers by dividing the task into the three following stages: the generation of a fuzzy rule base, the selection of relevant features, and the parameter optimization of membership functions for fuzzy rules. The structure of the fuzzy classifier is generated by forming the fuzzy rule base with use of the minimum and maximum feature values in each class. This allows us to generate the rule base with the minimum number of rules, which corresponds to the number of class labels in the dataset to be classified. Feature selection is carried out by a binary spider monkey optimization (BSMO) algorithm, which is a wrapper method. As a data preprocessing procedure, feature selection not only improves the efficiency of training algorithms but also enhances their generalization capability. In the process of feature selection, we investigate the dynamics of changes in classification accuracy, iteration by iteration, for various parameter values of the binary algorithm and analyze the effect of its parameters on its convergence rate. The parameter optimization of fuzzy rule antecedents uses another spider monkey optimization (SMO) algorithm that processes continuous numerical data. The performance of the fuzzy classifiers based on the rules and features selected by these algorithms is tested on some datasets from the KEEL repository. Comparison with two competitor algorithms on the same datasets is carried out. It is shown that fuzzy classifiers with the minimum number of rules and a significantly reduced number of features can be developed with their accuracy being statistically similar to that of the competitor classifiers.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47271273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-30DOI: 10.17323/1998-0663.2019.2.7.17
T. Voznesenskaya, F. Krasnov, R. Yavorsky, Polina Chesnokova
{"title":"Modeling self-organizing teams in a research environment","authors":"T. Voznesenskaya, F. Krasnov, R. Yavorsky, Polina Chesnokova","doi":"10.17323/1998-0663.2019.2.7.17","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.2.7.17","url":null,"abstract":"","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46430371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-30DOI: 10.17323/1998-0663.2019.2.59.72
O. Dolganova, E. Deeva
Digital transformation is one of the current trends of business development in modern economies. This article discusses the main problems faced by Russian companies in the course of digital transformations of their activities, and the tools for preliminary diagnosis of the company’s readiness for such transformations. Based on the analysis and synthesis of information from reports of Russian and international research and consulting companies, and relying on the results of scientifi c research by Russian and foreign experts, the authors identifi ed seven key typical problems that most Russian companies may encounter in the initial stages of implementing digital transformation. The problems identifi ed are ranked in order of their importance for the successful implementation of digital transformations. For the eff ective implementation of digital transformation, the authors propose to use the architectural approach in accordance with the recommendations of the TOGAF standard, which allows managing changes in a comprehensive manner, taking into account the needs, opportunities and constraints of both the business system and the IT infrastructure. The work substantiates the need for conducting the diagnosis of the company’s readiness at the initial stage of digital transformations. Such diagnosis can reveal the existing internal constraints that may become an obstacle to achieving the desired result of digital transformation. To identify the main adverse events, causes and problems of organizations with low levels of digital maturity, a method for constructing a tree of current reality has been implemented an analytical toolkit for studying cause-eff ect relationships with undesirable features. Practical recommendations on the classifi cation of causes and problems are provided to assess current readiness and plan for transition to the desired state of business system and IT infrastructure. The proposed approach will allow organizations to identify their problem areas, drawing on the consolidated experience of other companies, as well as to determine the possibility of their adjustment in order to create favorable conditions for digital transformations. INFORMATION SYSTEMS AND TECHNOLOGIES IN BUSINESS
{"title":"Company readiness for digital transformations: problems and diagnosis","authors":"O. Dolganova, E. Deeva","doi":"10.17323/1998-0663.2019.2.59.72","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.2.59.72","url":null,"abstract":"Digital transformation is one of the current trends of business development in modern economies. This article discusses the main problems faced by Russian companies in the course of digital transformations of their activities, and the tools for preliminary diagnosis of the company’s readiness for such transformations. Based on the analysis and synthesis of information from reports of Russian and international research and consulting companies, and relying on the results of scientifi c research by Russian and foreign experts, the authors identifi ed seven key typical problems that most Russian companies may encounter in the initial stages of implementing digital transformation. The problems identifi ed are ranked in order of their importance for the successful implementation of digital transformations. For the eff ective implementation of digital transformation, the authors propose to use the architectural approach in accordance with the recommendations of the TOGAF standard, which allows managing changes in a comprehensive manner, taking into account the needs, opportunities and constraints of both the business system and the IT infrastructure. The work substantiates the need for conducting the diagnosis of the company’s readiness at the initial stage of digital transformations. Such diagnosis can reveal the existing internal constraints that may become an obstacle to achieving the desired result of digital transformation. To identify the main adverse events, causes and problems of organizations with low levels of digital maturity, a method for constructing a tree of current reality has been implemented an analytical toolkit for studying cause-eff ect relationships with undesirable features. Practical recommendations on the classifi cation of causes and problems are provided to assess current readiness and plan for transition to the desired state of business system and IT infrastructure. The proposed approach will allow organizations to identify their problem areas, drawing on the consolidated experience of other companies, as well as to determine the possibility of their adjustment in order to create favorable conditions for digital transformations. INFORMATION SYSTEMS AND TECHNOLOGIES IN BUSINESS","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41874449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-30DOI: 10.17323/1998-0663.2019.2.73.83
A. Druzhaev, D. Isaev, Eugene Ogurechnikov
{"title":"Principles of managing development of EPM systems","authors":"A. Druzhaev, D. Isaev, Eugene Ogurechnikov","doi":"10.17323/1998-0663.2019.2.73.83","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.2.73.83","url":null,"abstract":"","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42748953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-30DOI: 10.17323/1998-0663.2019.2.18.28
A. Maron, T. Kravchenko, T. Shevgunov
{"title":"Estimation of resources required for restoring systems of computer complexes with elements of different significance","authors":"A. Maron, T. Kravchenko, T. Shevgunov","doi":"10.17323/1998-0663.2019.2.18.28","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.2.18.28","url":null,"abstract":"","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42416370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-30DOI: 10.17323/1998-0663.2019.2.43.58
V. Grekul, E. Isaev, N. Korovkina, T. Lisienkova
{"title":"Developing an approach to ranking innovative IT projects","authors":"V. Grekul, E. Isaev, N. Korovkina, T. Lisienkova","doi":"10.17323/1998-0663.2019.2.43.58","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.2.43.58","url":null,"abstract":"","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67910655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-03-31DOI: 10.17323/1998-0663.2019.1.45.58
Mariya Myznikova, L. Brazhnikova
Raising the eff ectiveness of strategic management in conditions of high complexity and dynamic change of modern management systems requires the development of an appropriate mathematical toolkit. The task of raising eff ectiveness of strategic management is especially topical for heat supply enterprises of the Donetsk region, where operations have been complicated by a number of general system problems, and by the presence of substantial external challenges. At the same time, the question of using mathematical apparatus to raise the eff ectiveness of strategic management of enterprises in the sphere of residential-communal services appears not to have been widely studied. In this regard, the objective of this study is raising the eff ectiveness of strategic management of heat supply enterprises of the Donetsk region by developing a respective toolkit of mathematical modeling. To achieve the goal we have set, in this work we carried out an analysis of the viability of the system using the methodology proposed by S. Beer; we made an analysis of the elements of the market of heat supply, and also developed system dynamic models based on the approach of J.W. Forrester. As a result of our research, we discovered the basic problems infl uencing the viability of the system at the strategic level. It was established that the problems revealed are the consequence of the imperfections of the methodological base, including absence of timely information on the dynamics of the external environment, forecasting of the key parameters, a toolkit for making decisions, etc. For the purpose of fi nding a toolkit to improve the methodological base, we performed an analysis and forecast of the heat supply market in the Donetsk region as part of the external environment which exerts a very signifi cant infl uence on the activity of the heat supply enterprises of the Donetsk region. In the course in the residential communal sphere the problem presence of a training sample and two test samples. In addition, in the course of analyzing the market we discovered new forms of demand for heat supply services – lost demand and unpaid demand. On the basis of the dependencies established, we built a model for forecasting the behavior of consumers of a heat supply company oriented to the level of marketing. With the help of this model, by means of supplements to it and modifi cations, we built a complex model of strategic management of heat supply enterprises of the Donetsk region allowing us to analyze the eff ectiveness of using one or another lever of strategic management on the basis of scenario analysis.
{"title":"Development of strategic management tools for heat supply enterprises in the Donetsk region","authors":"Mariya Myznikova, L. Brazhnikova","doi":"10.17323/1998-0663.2019.1.45.58","DOIUrl":"https://doi.org/10.17323/1998-0663.2019.1.45.58","url":null,"abstract":"Raising the eff ectiveness of strategic management in conditions of high complexity and dynamic change of modern management systems requires the development of an appropriate mathematical toolkit. The task of raising eff ectiveness of strategic management is especially topical for heat supply enterprises of the Donetsk region, where operations have been complicated by a number of general system problems, and by the presence of substantial external challenges. At the same time, the question of using mathematical apparatus to raise the eff ectiveness of strategic management of enterprises in the sphere of residential-communal services appears not to have been widely studied. In this regard, the objective of this study is raising the eff ectiveness of strategic management of heat supply enterprises of the Donetsk region by developing a respective toolkit of mathematical modeling. To achieve the goal we have set, in this work we carried out an analysis of the viability of the system using the methodology proposed by S. Beer; we made an analysis of the elements of the market of heat supply, and also developed system dynamic models based on the approach of J.W. Forrester. As a result of our research, we discovered the basic problems infl uencing the viability of the system at the strategic level. It was established that the problems revealed are the consequence of the imperfections of the methodological base, including absence of timely information on the dynamics of the external environment, forecasting of the key parameters, a toolkit for making decisions, etc. For the purpose of fi nding a toolkit to improve the methodological base, we performed an analysis and forecast of the heat supply market in the Donetsk region as part of the external environment which exerts a very signifi cant infl uence on the activity of the heat supply enterprises of the Donetsk region. In the course in the residential communal sphere the problem presence of a training sample and two test samples. In addition, in the course of analyzing the market we discovered new forms of demand for heat supply services – lost demand and unpaid demand. On the basis of the dependencies established, we built a model for forecasting the behavior of consumers of a heat supply company oriented to the level of marketing. With the help of this model, by means of supplements to it and modifi cations, we built a complex model of strategic management of heat supply enterprises of the Donetsk region allowing us to analyze the eff ectiveness of using one or another lever of strategic management on the basis of scenario analysis.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2019-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42018635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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