Pub Date : 2020-12-31DOI: 10.17323/2587-814x.2020.4.19.35
R. Rogulin
In this paper a model for the formation of sustainable supply chains of raw materials for a timber processing complex is proposed. The model allows one to optimize the plan of purchases from the Russian Commodity Exchange, as well as the plan of manufacturing finished products. The model presents the task of mathematical programming, whereby the company’s profit is used as the objective function, and the input data include the forecasted values of structure and volumes of offers available on the Russian Commodity Exchange, as well as demand for finished products. The recurrence dependencies of the model describe the flow of raw materials at the enterprise’s warehouse, taking into account revenues from purchased lots, transportation time and consumption of resources that are required for production of simulated volumes of products. Constraints of the model represent formalization of the limited flow of financial resources, taking into account sales and warehouse characteristics. The optimization task deals with variables including volumes of daily output of finished products according to a given nomenclature, as well as variables that specify the inclusion of lots into the portfolio of applications purchased on the exchange. The model solution is found using the branch and bound method with preliminary clipping based on the modified Chvatal–Gomory method. One example considers formation of optimal plans for the purchase and sales in a timber processing complex located in the Primorsky Territory (Russia), which does not have its own forest plots providing production with raw materials. The usefulness of the interaction of the enterprise with the timber department of the commodity and raw materials exchange is assessed.
{"title":"A model for optimizing plans for procurement of raw materials from regions of Russia in a timber-processing enterprise","authors":"R. Rogulin","doi":"10.17323/2587-814x.2020.4.19.35","DOIUrl":"https://doi.org/10.17323/2587-814x.2020.4.19.35","url":null,"abstract":"In this paper a model for the formation of sustainable supply chains of raw materials for a timber processing complex is proposed. The model allows one to optimize the plan of purchases from the Russian Commodity Exchange, as well as the plan of manufacturing finished products. The model presents the task of mathematical programming, whereby the company’s profit is used as the objective function, and the input data include the forecasted values of structure and volumes of offers available on the Russian Commodity Exchange, as well as demand for finished products. The recurrence dependencies of the model describe the flow of raw materials at the enterprise’s warehouse, taking into account revenues from purchased lots, transportation time and consumption of resources that are required for production of simulated volumes of products. Constraints of the model represent formalization of the limited flow of financial resources, taking into account sales and warehouse characteristics. The optimization task deals with variables including volumes of daily output of finished products according to a given nomenclature, as well as variables that specify the inclusion of lots into the portfolio of applications purchased on the exchange. The model solution is found using the branch and bound method with preliminary clipping based on the modified Chvatal–Gomory method. One example considers formation of optimal plans for the purchase and sales in a timber processing complex located in the Primorsky Territory (Russia), which does not have its own forest plots providing production with raw materials. The usefulness of the interaction of the enterprise with the timber department of the commodity and raw materials exchange is assessed.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44403159","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 : 2020-12-31DOI: 10.17323/2587-814x.2020.4.76.95
A. Afanasiev, O. Ponomareva
Transport and communication infrastructure plays an important role in ensuring economic growth, also in the context of the Wuhan coronavirus (SARS-CoV-2) spread worldwide. The role of the communication component increases with the epidemic and the associated restrictive measures, which replace, to a certain extent, the transport component. We offer an econometric study of the macroeconomic production function in the Russian Federation with transport and communication infrastructure (the fixed assets average annual value of the Russian transport and communications sectors) for 1990–2018. The arguments for this function are the average annual value of fixed assets in constant 1990 prices, the average annual rate of the use of production capacities in Russian industry, the average annual number of people employed in the national economy, the average annual value of fixed assets of transport and communications in constant 1990 prices. Our research demonstrates that in 2010–2018 the GDP elasticity to production infrastructure was decreasing. We explain this by the reduction in the volume of capital investments in the infrastructure sector’s fixed assets. In addition, we offer an analytical modification of the macroeconomic production function for 2020 in the context of the spread of the Wuhan coronavirus among the Russian population by introducing into this function the average annual rates of labor and infrastructure capacity use, which, along with the average annual rate of fixed assets capacity use are functions of the predicted values of the daily number of the infected Russian citizens. These predicted values are calculated by the time dependent Gaussian quadratic exponent estimated by the least squares. We present the accuracy of the forecast results for the 2020 spring trends of the daily number of Russian and Moscow population infected with the Wuhan coronavirus. The average APE forecast error for 30 days ahead for Russia is 10.4% and the same for five weeks for Moscow is 10%. Moreover, we make forecasts of the officially published daily number of infected Russian population for fall 2020 – spring 2021.
{"title":"Wuhan coronavirus spread in Russia: macroeconomic production function in regard to transport and communication infrastructure","authors":"A. Afanasiev, O. Ponomareva","doi":"10.17323/2587-814x.2020.4.76.95","DOIUrl":"https://doi.org/10.17323/2587-814x.2020.4.76.95","url":null,"abstract":"Transport and communication infrastructure plays an important role in ensuring economic growth, also in the context of the Wuhan coronavirus (SARS-CoV-2) spread worldwide. The role of the communication component increases with the epidemic and the associated restrictive measures, which replace, to a certain extent, the transport component. We offer an econometric study of the macroeconomic production function in the Russian Federation with transport and communication infrastructure (the fixed assets average annual value of the Russian transport and communications sectors) for 1990–2018. The arguments for this function are the average annual value of fixed assets in constant 1990 prices, the average annual rate of the use of production capacities in Russian industry, the average annual number of people employed in the national economy, the average annual value of fixed assets of transport and communications in constant 1990 prices. Our research demonstrates that in 2010–2018 the GDP elasticity to production infrastructure was decreasing. We explain this by the reduction in the volume of capital investments in the infrastructure sector’s fixed assets. In addition, we offer an analytical modification of the macroeconomic production function for 2020 in the context of the spread of the Wuhan coronavirus among the Russian population by introducing into this function the average annual rates of labor and infrastructure capacity use, which, along with the average annual rate of fixed assets capacity use are functions of the predicted values of the daily number of the infected Russian citizens. These predicted values are calculated by the time dependent Gaussian quadratic exponent estimated by the least squares. We present the accuracy of the forecast results for the 2020 spring trends of the daily number of Russian and Moscow population infected with the Wuhan coronavirus. The average APE forecast error for 30 days ahead for Russia is 10.4% and the same for five weeks for Moscow is 10%. Moreover, we make forecasts of the officially published daily number of infected Russian population for fall 2020 – spring 2021.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45586477","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 : 2020-09-30DOI: 10.17323/2587-814X.2020.3.24.34
Z. Zenkova, W. Musoni
In modern logistics and supply chain management, the task of inventory management is paramount. The total costs of the enterprise and consequently, its profit, directly depend on the accuracy of calculating the volumes and terms of orders. In this work, the problem of increasing the accuracy of calculating the economic order quantity for a product was solved by involving additional information about the known quantile of a given level of the distribution function of the volume of product’s demand. The quantile information was used to recalculate the annual demand for the product, based on a modified estimator of the sales expectation for the period. The modified estimator is asymptotically unbiased, normal, and more accurate than the traditional sample mean in the sense of mean squared error. New formulas for calculating the economic order quantity and its confidence interval were presented and tested on real data on the monthly sales volumes of goods of a large retail store network over two years. It is shown that the classic way of mean calculation led to an underestimation of the volume of the economic order quantity, which in turn increased the risk of a shortage, and hence a drop in the quality of logistics services. The new calculation method also showed that the period between orders should be one day shorter. The work is practically significant; according to its results, recommendations are given to the enterprise.
{"title":"The economic order quantity taking into account additional information about the known quantile of the cumulative distribution function of the product’s sales volume","authors":"Z. Zenkova, W. Musoni","doi":"10.17323/2587-814X.2020.3.24.34","DOIUrl":"https://doi.org/10.17323/2587-814X.2020.3.24.34","url":null,"abstract":"In modern logistics and supply chain management, the task of inventory management is paramount. The total costs of the enterprise and consequently, its profit, directly depend on the accuracy of calculating the volumes and terms of orders. In this work, the problem of increasing the accuracy of calculating the economic order quantity for a product was solved by involving additional information about the known quantile of a given level of the distribution function of the volume of product’s demand. The quantile information was used to recalculate the annual demand for the product, based on a modified estimator of the sales expectation for the period. The modified estimator is asymptotically unbiased, normal, and more accurate than the traditional sample mean in the sense of mean squared error. New formulas for calculating the economic order quantity and its confidence interval were presented and tested on real data on the monthly sales volumes of goods of a large retail store network over two years. It is shown that the classic way of mean calculation led to an underestimation of the volume of the economic order quantity, which in turn increased the risk of a shortage, and hence a drop in the quality of logistics services. The new calculation method also showed that the period between orders should be one day shorter. The work is practically significant; according to its results, recommendations are given to the enterprise.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48608106","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 : 2020-09-30DOI: 10.17323/2587-814X.2020.3.7.23
Tatiana Bogdanova, A. Kamalova, T. Kravchenko, A. Poltorak
The solution of the housing problem for many decades has been and remains one of the most important tasks facing the nation. The problem of modeling the value of residential properties is becoming more and more urgent, since a high-quality forecast makes it possible to reduce risks, both for government bodies and for realtors specializing in the purchase and sale of residential properties, as well as for ordinary citizens who buy or sell apartments. Predictive models allow us to get an adequate assessment of both the current and future situation on the residential property market, to identify trends in the cost of housing and the factors influencing these changes. This involves both the qualitative characteristics of the particular property, and the general condition and the dynamics of the real estate market. Russia is characterized by significant differences in the level of development of regions, therefore, by differences in trends of supply and demand prices for real estate. Valuation of residential properties at the regional level is particularly important, since all of the above determines the social and economic importance of this problem. This article presents a comprehensive model for estimating the value of residential properties in the secondary housing market of Moscow using decision tree methods and ordinal logistic regression. A predictive model of the level of housing comfort was built using the CRT decision tree method. The results of this forecast are used as input information for an ordinal logistic regression model for estimating the value of residential properties in the secondary market of Moscow. Testing the model on real data showed the high predictive ability of the model we generated. MODELING OF SOCIAL AND ECONOMIC SYSTEMS
{"title":"Problems of modeling the valuation of residential properties","authors":"Tatiana Bogdanova, A. Kamalova, T. Kravchenko, A. Poltorak","doi":"10.17323/2587-814X.2020.3.7.23","DOIUrl":"https://doi.org/10.17323/2587-814X.2020.3.7.23","url":null,"abstract":"The solution of the housing problem for many decades has been and remains one of the most important tasks facing the nation. The problem of modeling the value of residential properties is becoming more and more urgent, since a high-quality forecast makes it possible to reduce risks, both for government bodies and for realtors specializing in the purchase and sale of residential properties, as well as for ordinary citizens who buy or sell apartments. Predictive models allow us to get an adequate assessment of both the current and future situation on the residential property market, to identify trends in the cost of housing and the factors influencing these changes. This involves both the qualitative characteristics of the particular property, and the general condition and the dynamics of the real estate market. Russia is characterized by significant differences in the level of development of regions, therefore, by differences in trends of supply and demand prices for real estate. Valuation of residential properties at the regional level is particularly important, since all of the above determines the social and economic importance of this problem. This article presents a comprehensive model for estimating the value of residential properties in the secondary housing market of Moscow using decision tree methods and ordinal logistic regression. A predictive model of the level of housing comfort was built using the CRT decision tree method. The results of this forecast are used as input information for an ordinal logistic regression model for estimating the value of residential properties in the secondary market of Moscow. Testing the model on real data showed the high predictive ability of the model we generated. MODELING OF SOCIAL AND ECONOMIC SYSTEMS","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41753191","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 : 2020-09-30DOI: 10.17323/2587-814X.2020.3.35.53
Yury F. Telnov, V. Kazakov, V. Trembach
The relevance of developing knowledge-based systems used to support innovative processes for creating products and services is related to the objective need to reduce the life cycle of products under the influence of modern digital technologies in developing network enterprises. Well-known research results in the field of model-oriented design of products, processes, systems and enterprises do not fully provide semantic interoperability in the interaction of stakeholders in the innovation process. The aim of this work is to build a knowledge-based system architecture that implements semantic interoperability of network enterprise participants at various stages of the product lifecycle. The work is based on the use of a model-oriented approach to building a digital thread at all stages of the product lifecycle, an ontological approach to semantic modeling of a distributed knowledge base and a multiagent approach to organizing interaction between interested participants in the innovation process. The paper proposes a functional architecture of a knowledge-based system that includes modules for planning the innovation process, forming product value characteristics and functional requirements, construction and value chain design. A multi-level system of ontologies of the innovation process is also developed and its application in the work of functional modules that provide access to MODELING OF SOCIAL AND ECONOMIC SYSTEMS
{"title":"Developing a knowledge-based system for the design of innovative product creation processes for network enterprises","authors":"Yury F. Telnov, V. Kazakov, V. Trembach","doi":"10.17323/2587-814X.2020.3.35.53","DOIUrl":"https://doi.org/10.17323/2587-814X.2020.3.35.53","url":null,"abstract":"The relevance of developing knowledge-based systems used to support innovative processes for creating products and services is related to the objective need to reduce the life cycle of products under the influence of modern digital technologies in developing network enterprises. Well-known research results in the field of model-oriented design of products, processes, systems and enterprises do not fully provide semantic interoperability in the interaction of stakeholders in the innovation process. The aim of this work is to build a knowledge-based system architecture that implements semantic interoperability of network enterprise participants at various stages of the product lifecycle. The work is based on the use of a model-oriented approach to building a digital thread at all stages of the product lifecycle, an ontological approach to semantic modeling of a distributed knowledge base and a multiagent approach to organizing interaction between interested participants in the innovation process. The paper proposes a functional architecture of a knowledge-based system that includes modules for planning the innovation process, forming product value characteristics and functional requirements, construction and value chain design. A multi-level system of ontologies of the innovation process is also developed and its application in the work of functional modules that provide access to MODELING OF SOCIAL AND ECONOMIC SYSTEMS","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48949965","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 : 2020-09-30DOI: 10.17323/2587-814X.2020.3.67.81
Yury Zelenkov, Elizaveta Lashkevich
This paper proposes a model of the impact of technology on the standard of living based on fuzzy linear regression. The Human Development Index (HDI) was chosen as a dependent variable as an indicator of the health and well-being of the population. The explanatory variables are the Network Readiness Index (NRI), which measures the impact of information and communication technologies (ICT) on society and the development of the nation, and the Global Innovation Index (GII), which measures the driving forces of economic growth. The analysis is based on data for 2019 for four groups of countries with different levels of GDP per capita. For developed countries, the positive and balanced impact of innovation and ICT on living standards has been confirmed. For two groups of developing countries (upper and lower middle income), the GII coefficient was found to be negative. A more indepth analysis showed that this is due to the state of political and social institutions. This fact means that without a simultaneous increase in the maturity of institutions, stimulation of other areas of innovative development (education, knowledge and technology, infrastructure) leads to a decrease in the quality of life.
{"title":"Fuzzy regression model of the impact of technology on living standards","authors":"Yury Zelenkov, Elizaveta Lashkevich","doi":"10.17323/2587-814X.2020.3.67.81","DOIUrl":"https://doi.org/10.17323/2587-814X.2020.3.67.81","url":null,"abstract":"This paper proposes a model of the impact of technology on the standard of living based on fuzzy linear regression. The Human Development Index (HDI) was chosen as a dependent variable as an indicator of the health and well-being of the population. The explanatory variables are the Network Readiness Index (NRI), which measures the impact of information and communication technologies (ICT) on society and the development of the nation, and the Global Innovation Index (GII), which measures the driving forces of economic growth. The analysis is based on data for 2019 for four groups of countries with different levels of GDP per capita. For developed countries, the positive and balanced impact of innovation and ICT on living standards has been confirmed. For two groups of developing countries (upper and lower middle income), the GII coefficient was found to be negative. A more indepth analysis showed that this is due to the state of political and social institutions. This fact means that without a simultaneous increase in the maturity of institutions, stimulation of other areas of innovative development (education, knowledge and technology, infrastructure) leads to a decrease in the quality of life.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49199506","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 : 2020-09-30DOI: 10.17323/2587-814X.2020.3.54.66
V. Kuzmin, A. Menisov, I. Shastun
{"title":"An approach to identifying bots in social networks based on the special association of classifiers","authors":"V. Kuzmin, A. Menisov, I. Shastun","doi":"10.17323/2587-814X.2020.3.54.66","DOIUrl":"https://doi.org/10.17323/2587-814X.2020.3.54.66","url":null,"abstract":"","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44627107","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 : 2020-09-30DOI: 10.17323/2587-814X.2020.3.82.95
R. Zhukov
Modern models and methods for evaluating complex systems are associated with hierarchical socioeconomic systems (HSES) implemented on the basis of software systems (expert systems and decision support systems) and used at the regional and municipal levels of government. As usual, such systems have the functionality of analytics and building scenario variants for the development of research objects. However, they do not give quantified values of the state and impact factors at which the complex system under consideration can come to a given state. At the same time, the question of determining such a set state associated with the construction of standards (expected values) for elements, classes or levels of the HSES is still open. In some cases, to make an informed decision it is sufficient to obtain aggregated quantitative estimates and recommendations concerning the further functioning of the research object. This article presents the author’s approach, which allows us to evaluate the functioning of hierarchical socio-economic systems and provides expert opinions for making management decisions implemented on the basis of the EFRA software package. The algorithm includes stages of analysis and synthesis-stages of the basic method of system analysis. The novelty of the proposed approach is the possibility of taking into account the specific conditions of the status and impact of complex systems that provides an opportunity to build their own standard. Additionally, the procedures of standardization and normalization (reduction to a scale from 0 to 1) make it possible to avoid the influence of different units of measurement of results of operation and economies of scale. On the example of regions of the Central Federal district according to data for 2014–2017, estimates of the use of information and telecommunications technologies by the population were obtained, and the optimization problem was solved for the Tula Region, on the basis of which directions related to increasing the region’s readiness for digitalization were proposed. INFORMATION SYSTEMS AND TECHNOLOGIES IN BUSINESS
{"title":"An approach to assessing the functioning of hierarchical socio-economic systems and decision-making based on the EFRA software package","authors":"R. Zhukov","doi":"10.17323/2587-814X.2020.3.82.95","DOIUrl":"https://doi.org/10.17323/2587-814X.2020.3.82.95","url":null,"abstract":"Modern models and methods for evaluating complex systems are associated with hierarchical socioeconomic systems (HSES) implemented on the basis of software systems (expert systems and decision support systems) and used at the regional and municipal levels of government. As usual, such systems have the functionality of analytics and building scenario variants for the development of research objects. However, they do not give quantified values of the state and impact factors at which the complex system under consideration can come to a given state. At the same time, the question of determining such a set state associated with the construction of standards (expected values) for elements, classes or levels of the HSES is still open. In some cases, to make an informed decision it is sufficient to obtain aggregated quantitative estimates and recommendations concerning the further functioning of the research object. This article presents the author’s approach, which allows us to evaluate the functioning of hierarchical socio-economic systems and provides expert opinions for making management decisions implemented on the basis of the EFRA software package. The algorithm includes stages of analysis and synthesis-stages of the basic method of system analysis. The novelty of the proposed approach is the possibility of taking into account the specific conditions of the status and impact of complex systems that provides an opportunity to build their own standard. Additionally, the procedures of standardization and normalization (reduction to a scale from 0 to 1) make it possible to avoid the influence of different units of measurement of results of operation and economies of scale. On the example of regions of the Central Federal district according to data for 2014–2017, estimates of the use of information and telecommunications technologies by the population were obtained, and the optimization problem was solved for the Tula Region, on the basis of which directions related to increasing the region’s readiness for digitalization were proposed. INFORMATION SYSTEMS AND TECHNOLOGIES IN BUSINESS","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44879301","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 : 2020-06-30DOI: 10.17323/2587-814x.2020.2.36.47
R. Karayev, N. Sadikhova
The paper provides a brief description of cognitive management, which opens up unique opportunities for the effective management of enterprises in modern complex and unstable conditions. The problems of commercializing this promising paradigm are discussed. It is pointed out that the main, critical one of these problems is due to the lack of developed engineering of cognitive management. A conceptual framework for solving this problem is proposed, based on the convergence of the ideas and methods of the “cognitive school” and the empirical experience gained in knowledge engineering. The results of using the conceptual framework in four research projects of different industry orientations, with different internal conditions and different dynamics of the external environment are presented. The engineering prospects of the proposed framework are discussed in terms of the commercialization of the cognitive school identified by H. Mintzberg, B. Ahlstrand and D. Lampel 30 years ago.
{"title":"The advantages of cognitive approach for enterprise management in modern conditions","authors":"R. Karayev, N. Sadikhova","doi":"10.17323/2587-814x.2020.2.36.47","DOIUrl":"https://doi.org/10.17323/2587-814x.2020.2.36.47","url":null,"abstract":"The paper provides a brief description of cognitive management, which opens up unique opportunities for the effective management of enterprises in modern complex and unstable conditions. The problems of commercializing this promising paradigm are discussed. It is pointed out that the main, critical one of these problems is due to the lack of developed engineering of cognitive management. A conceptual framework for solving this problem is proposed, based on the convergence of the ideas and methods of the “cognitive school” and the empirical experience gained in knowledge engineering. The results of using the conceptual framework in four research projects of different industry orientations, with different internal conditions and different dynamics of the external environment are presented. The engineering prospects of the proposed framework are discussed in terms of the commercialization of the cognitive school identified by H. Mintzberg, B. Ahlstrand and D. Lampel 30 years ago.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41871208","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 : 2020-06-30DOI: 10.17323/2587-814x.2020.2.21.35
F. Belousov, I. Nevolin, N. Khachatryan
This paper offers an approach for solving a problem that arises for railway transport operators. The task is to manage the fleet of freight railcars optimally in terms of profit maximization. The source data for the transport operator is a list of requests received from customers, as well as the location of railcars at the beginning of the planning period. The request formed by each customer consists of departure station, destination station, name and volume of cargo that the customer would like to transport. The request also contains the rate that the customer has to pay to the transport operator for each loaded wagon transported. Planning is carried out for a month in advance and consists, on the one hand, in selecting the most profitable requests for execution, on the other hand – in building a sequence of cargo and empty runs that will fulfill the selected requests with the greatest efficiency. Direct transportation of loaded and empty railway cars is carried out by Russian Railways with preknown tariffs and time standards for each of the routes. At the same time, tariffs for driving loaded wagons are additional costs for the customer of the route specified in the request (customers pay both the transport operator for the use of wagons and Russian Railways); transportation of empty wagons is paid by transport operators. To solve this problem, one of the possible ways to reduce it to a largedimensional linear programming problem is proposed. An algorithm is proposed, the result of which is a problem written in the format of a linear programming problem. To demonstrate the approach clearly, a simplified problem statement is considered that takes into account only the main factors of the modeled process. The paper also shows an example of a numerical solution of the problem based on simple model data. MODELING OF SOCIAL AND ECONOMIC SYSTEMS
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