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Special Issue "Mathematical and Instrumental Methods in the Digital Economy"

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A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Financial Mathematics".

Deadline for manuscript submissions: closed (10 January 2021) | Viewed by 30201

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Special Issue Editor

Dr. Dmitry M. Nazarov

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Guest Editor

Department of Business Informatics, Ural State University of Economics, 620144 Yekaterinburg, Russia
Interests: digital economy; fuzzy model; big data; data mining
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Considering the genesis of world civilization in stages, it can be argued that the beginning of the XXI century is a kind of boundary between the ending life cycle of the industrial era of the development of society and the beginning cycle of the post-industrial era. The key concept of a new stage in the development of civilization is a digital economy based on trends such as scientific and technological progress, globalization of investment and information flows, innovation, big data technology, data mining, development of network structures and communications.

The key characteristic of the economic structure in the digital economy is information and its processing technologies, including mathematical and instrumental methods, as a resource for any economic activity.

The purpose of this Special Issue is a collection of articles devoted to the development and implementation of advanced mathematical and instrumental methods in the digital economy, based on Big Data, Data Mining, and Internet of Things technologies.

Dr. Dmitry M. Nazarov
Guest Editor

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Keywords

Digital economy
Fuzzy model
Big Data
Data Mining
Internet of things
Collaborative economy
Intelligent systems

Published Papers (12 papers)

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Research

25 pages, 5705 KiB

Open AccessArticle

The Measurement of Demographic Temperature Using the Sentiment Analysis of Data from the Social Network VKontakte

Irina Evgenievna Kalabikhina

Evgeniy Petrovich Banin

Imiliya Abduselimovna Abduselimova

German Andreevich Klimenko

and

Anton Vasilyevich Kolotusha

Mathematics 2021, 9(9), 987; https://doi.org/10.3390/math9090987 - 28 Apr 2021

Cited by 6 | Viewed by 2215

Abstract

Social networks have a huge potential for the reflection of public opinion, values, and attitudes. In this study, the presented approach can allow to continuously measure how cold “the demographic temperature” is based on data taken from the Russian social network VKontakte. This is the first attempt to analyze the sentiment of Russian-language comments on social networks to determine the demographic temperature (ratio of positive and negative comments) in certain socio-demographic groups of social network users. The authors use generated data from the comments to posts from 314 pro-natalist groups (with child-born reproductive attitudes) and eight anti-natalist groups (with child-free reproductive attitudes) on the demographic topic, which have 9 million of users from all over Russia. The algorithm of the sentiment analysis for demographic tasks is presented in the article. In particularly, it was found that comments under posts are more suitable for analyzing the sentiment of statements than the texts of posts. Using the available data in two types of groups since 2014, we find an asynchronous structural shift in comments of the corpuses of pro-natalist and anti-natalist thematic groups. Interpretations of the evidences are offered in the discussion part of the article. An additional result of our work is two open Russian-language datasets of comments on social networks. Full article

(This article belongs to the Special Issue Mathematical and Instrumental Methods in the Digital Economy)

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16 pages, 1944 KiB

Open AccessArticle

The Fuzzy Methodology’s Digitalization of the Biological Assets Evaluation in Agricultural Enterprises in Accordance with the IFRS

Kobiljon Khushvakhtzoda (Barfiev)

and

Dmitry Nazarov

Mathematics 2021, 9(8), 901; https://doi.org/10.3390/math9080901 - 19 Apr 2021

Cited by 2 | Viewed by 2679

Abstract

The study of the assessment and reflection of biological assets in the economic processes of agricultural enterprises can be represented as a chain of phenomena in which scientists and practitioners try to study and understand the nature and essence of biological assets in various aspects. This article discusses the principles of accounting for biological assets in the agricultural enterprises’ economic life of the Republic of Tajikistan and identifies the reasons and mechanisms for their reflection based on the principles of the International Financial Reporting System (IFRS) in refraction to the specifics and national features of accounting. The author gives his own interpretation of these approaches and constructs the architecture of the information module for accounting for biological assets and the results of biotransformation, based on the web services architecture (WSA) within the framework of the development trend of these and new accounting models in connection with the transition of the world economy to a digital format. The article provides specific authors’ approaches to implementing this architecture in PHP (Hypertext Preprocessor) and also implements one of the approaches to assessing the value of biological assets, based on the theory of fuzzy sets, taking into account the risk of investment inefficiency. Full article

(This article belongs to the Special Issue Mathematical and Instrumental Methods in the Digital Economy)

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32 pages, 7144 KiB

Open AccessArticle

Image Classification for the Automatic Feature Extraction in Human Worn Fashion Data

Stefan Rohrmanstorfer

Mikhail Komarov

and

Felix Mödritscher

Mathematics 2021, 9(6), 624; https://doi.org/10.3390/math9060624 - 16 Mar 2021

Cited by 5 | Viewed by 3371

Abstract

With the always increasing amount of image data, it has become a necessity to automatically look for and process information in these images. As fashion is captured in images, the fashion sector provides the perfect foundation to be supported by the integration of a service or application that is built on an image classification model. In this article, the state of the art for image classification is analyzed and discussed. Based on the elaborated knowledge, four different approaches will be implemented to successfully extract features out of fashion data. For this purpose, a human-worn fashion dataset with 2567 images was created, but it was significantly enlarged by the performed image operations. The results show that convolutional neural networks are the undisputed standard for classifying images, and that TensorFlow is the best library to build them. Moreover, through the introduction of dropout layers, data augmentation and transfer learning, model overfitting was successfully prevented, and it was possible to incrementally improve the validation accuracy of the created dataset from an initial 69% to a final validation accuracy of 84%. More distinct apparel like trousers, shoes and hats were better classified than other upper body clothes. Full article

(This article belongs to the Special Issue Mathematical and Instrumental Methods in the Digital Economy)

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20 pages, 1477 KiB

Open AccessArticle

Optimization of Energy Consumption in Chemical Production Based on Descriptive Analytics and Neural Network Modeling

Alexey I. Shinkevich

Tatiana V. Malysheva

Yulia V. Vertakova

and

Vladimir A. Plotnikov

Mathematics 2021, 9(4), 322; https://doi.org/10.3390/math9040322 - 06 Feb 2021

Cited by 6 | Viewed by 2129

Abstract

Improving the energy efficiency of chemical industries and increasing their environmental friendliness requires an assessment of the parameters of consumption and losses of energy resources. The aim of the study is to develop and test a method for solving the problem of optimizing the use of energy resources in chemical production based on the methodology of descriptive statistics and training of neural networks. Research methods: graphic and tabular tools for descriptive data analysis to study the dynamics of the structure of energy carriers and determine possible reserves for reducing their consumption; correlation analysis with the construction of scatter diagrams to identify the dependences of the range of limit values of electricity consumption on the average rate of energy consumption; a method for training neural networks to predict the optimal values of energy consumption; methods of mathematical optimization and standardization. The authors analyzed the trends in the energy intensity of chemical industries with an assessment of the degree of transformation of the structure of the energy portfolio and possible reserves for reducing the specific weight of electrical and thermal energy; determined the dynamics of energy losses at Russian industrial enterprises; established the correlation dependence of the range of limiting values of power consumption on the average rate of power consumption; determined the optimal limiting limits of the norms for the loss of electrical energy by the example of rubbers of solution polymerization. The results of the study can be used in the development of software complexes for intelligent energy systems that allow tracking the dynamics of consumption and losses of energy resources. Using the results allows you to determine the optimal parameters of energy consumption and identify reserves for improving energy efficiency. Full article

(This article belongs to the Special Issue Mathematical and Instrumental Methods in the Digital Economy)

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24 pages, 820 KiB

Open AccessArticle

On the Effectiveness of the Digital Legal Proceedings Model in Russia

Karasev Anatoly Tikhanovich

Savoskin Alexander Vladimirovich

and

Meshcheryagina Veronika Aleksandrovna

Mathematics 2021, 9(2), 125; https://doi.org/10.3390/math9020125 - 07 Jan 2021

Cited by 2 | Viewed by 1890

Abstract

Within the framework of this research, on the basis of the dialectical unity of its legal and mathematical components, on the basis of general scientific (analysis, synthesis, deduction and induction, abstraction, structural and functional method) and special research methods (formal-legal, method of legal construction, formal-logical, system, technical-legal analysis, statistical method, methods of mathematical statistics and probability theory, etc.), a model of digital legal proceedings in Russia is proposed. The article explains the optimal variant between the components of the digital legal proceedings model in Russia, as well as providing an analysis and evaluation of the effectiveness of the digital legal proceedings model and the prospects for the development of digital legal proceedings. It is concluded that there is a need to develop legal regulation in terms of introducing the definition of “electronic evidence”, types of electronic evidence; it is recognized as a positive practice of implementing a video-conferencing system that ensures the implementation of citizens’ rights to participate in a court session, which significantly reduces the time for case consideration; the need to create a single Internet portal for receiving, processing, and providing electronic documents by all authorities in Russia is explained. In this research, it is explained that the use of mathematical algorithms in evaluating evidence and modeling the behavior of participants in trials is now at an early stage of development, which allows them to be used only in the consideration of similar cases. Full article

(This article belongs to the Special Issue Mathematical and Instrumental Methods in the Digital Economy)

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16 pages, 722 KiB

Open AccessFeature PaperArticle

Causality: Intelligent Valuation Models in the Digital Economy

Dmitry Nazarov

Mathematics 2020, 8(12), 2174; https://doi.org/10.3390/math8122174 - 05 Dec 2020

Cited by 6 | Viewed by 1903

Abstract

The study of the economic process can be presented as a chain of reflections on the causes and consequences of the particular phenomenon’s occurrence, within the framework of which scientists try to study and understand the nature of cause-and-effect relationships and find out the mechanisms of their occurrence. This article discusses three well-known conceptual approaches to the assessment of causation in socioeconomic sciences: successionist causation, configurational causation, and generative causation. The author gives his own interpretation of these approaches, constructs graphic interpretations, and also offers such concepts as a linear sequence of factors, the causal field, and the causal space of factors in the economy and socioeconomic processes. Within the framework of these approaches, the development trends of these and new models are formulated, taking into account the transition of the world economy to a digital format. The article contains specific examples from the author of the causality models’ implementation in scientific research related to assessing the impact of corporate culture on the main indicators of an organization’s performance in various contexts. Full article

(This article belongs to the Special Issue Mathematical and Instrumental Methods in the Digital Economy)

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25 pages, 1092 KiB

Open AccessArticle

Mathematical Support for Financing Social Innovations

Evgeny Popov

Anna Veretennikova

and

Alisa Safronova

Mathematics 2020, 8(12), 2144; https://doi.org/10.3390/math8122144 - 01 Dec 2020

Cited by 2 | Viewed by 1738

Abstract

The use of socially innovative projects for solving social problems by actively involving civil society is a promising and much sought-after area of social development. However, the priority of social goals over economic outcomes in the implementation of such projects significantly limits the speed and effectiveness of their implementation. In this connection, the use of a mathematical tool for the financing and resource provision of social innovations creates new opportunities in terms of the assessment and development of such projects. In order to develop and substantiate tools for the mathematical support of financing social innovations, the role of the collaborative economy in the development of social innovations initiated from below is substantiated. The proposed mathematical toolkit includes a linear algorithm describing the logic of the developed approach, a methodology for assessing socially-innovative projects based on an adapted McKinsey matrix, a methodology for assessing the institutional environment, as well as a mapping of project correspondences in an adapted McKinsey matrix along with collaborative economic tools recommended for resource provision. The described set of collaborative economy tools is recommended for use in the development and implementation of social innovations. The mathematically-described algorithm proposed by the authors is aimed at developing resource provision strategies for social projects by evaluating their competitiveness and attractiveness in terms of the social function they perform while taking the characteristics of the particular institutional environment into consideration. The result of applying this algorithm comprises a set of collaborative economy tools for use in the development and implementation of socially-innovative projects. The application of this algorithm is shown on the example of an evaluation of ten projects implemented in the Ural region and applying for assistance from support funds. The theoretical significance of the proposed results lies in the development of methodological tools for assessing socially-innovative projects. The practical significance lies in the possibility of applying the obtained results in the development of an online calculator used to assist in forming a social project resource provision strategy. Full article

(This article belongs to the Special Issue Mathematical and Instrumental Methods in the Digital Economy)

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23 pages, 1551 KiB

Open AccessArticle

Regional Digital Economy: Assessment of Development Levels

Anatoly Sidorov

and

Pavel Senchenko

Mathematics 2020, 8(12), 2143; https://doi.org/10.3390/math8122143 - 01 Dec 2020

Cited by 18 | Viewed by 4528

Abstract

A model of a composite index of the development level digital economy of regions in various sizes is proposed. It is based on a functional network as a kind of directed graph, structured by levels based on the principles of hierarchy, modularity and balance, as well as the availability of data on the development of the digital economy. The scalar value of the required quantity was determined by means of additive convolution. The influence of the subjective factor was excluded by moving away from the expert determination of weighing measures of particular indicators (which are included in the composite index) and using a calculation based on the standard deviation. The proposed approach was tested in the framework of identifying the differentiation of the development level digital economy of regions in Russia, as well as comparing European and Russian practices. Full article

(This article belongs to the Special Issue Mathematical and Instrumental Methods in the Digital Economy)

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19 pages, 1553 KiB

Open AccessArticle

The Use of the Foresight Methods in Developing an Algorithm for Conducting Qualitative Examination of the Research Activities Results on the Example of the Republic of Kazakhstan

and

Mathematics 2020, 8(11), 2024; https://doi.org/10.3390/math8112024 - 13 Nov 2020

Cited by 7 | Viewed by 1979

Abstract

In modern conditions, it is interesting to study foresight as an effective tool for identifying new strategic scientific directions. Its purpose is to develop an algorithm for conducting qualitative expertise in the application of the foresight methods with the ability to integrate forecast estimates. Currently, the vast majority of research activities results do not contribute to the innovative development of the state. To solve this problem, it is necessary to ensure a stable systemic relationship between specific sectors of the economy and higher education. The algorithm is developed on the basis of a systematic approach to the foresight methods and the use of the methods of bibliometrics, scientometrics, patent analysis and forecasting. The results and conclusions of this study are: an algorithm has been developed for conducting qualitative examination of the results of scientific activities in order to increase its practical significance, in which the authors propose the foresight methods as the most optimal tool for choosing priority areas of science and technology. Putting this approach into practice will make it possible to increase the efficiency of the foresight methods by both reducing time costs, and rationally using monetary and human resources. Full article

(This article belongs to the Special Issue Mathematical and Instrumental Methods in the Digital Economy)

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30 pages, 413 KiB

Open AccessFeature PaperArticle

Some Economic Dynamics Problems for Hybrid Models with Aftereffect

Eugene Bravyi

Vladimir Maksimov

and

Pyotr Simonov

Mathematics 2020, 8(10), 1832; https://doi.org/10.3390/math8101832 - 19 Oct 2020

Cited by 4 | Viewed by 1868

Abstract

In this paper, we consider a class of economic dynamics models in the form of linear functional differential systems with continuous and discrete times (hybrid models) that covers many kinds of dynamic models with aftereffect. The focus of attention is periodic boundary value problems with deviating argument, control problems with respect to general on-target vector-functional and questions of stability to solutions. For boundary value problems, some sharp sufficient conditions of the unique solvability are obtained. The attainability of on-target values is under study as applied to control problems with polyhedral constraints with respect to control, some estimates of the attainability set as well as estimates to a number of switch-points of programming control are presented. For a class of hybrid systems, a description of asymptotic properties of solutions is given. Full article

(This article belongs to the Special Issue Mathematical and Instrumental Methods in the Digital Economy)

16 pages, 1444 KiB

Open AccessArticle

Fuzzy Set Models for Economic Resilience Estimation

and

Mathematics 2020, 8(9), 1516; https://doi.org/10.3390/math8091516 - 04 Sep 2020

Cited by 10 | Viewed by 1689

Abstract

(1) Presented models are proposed for analyzing the resilience of an economic system in a framework of a 4 × 6 matrix, the core of which is a balanced scorecard (BSC). Matrix rows present strategic perspectives, matrix columns present strategic maps. (2) Resilience assessment models are based on fuzzy logic and soft computing, combined with systemic-cybernetic approaches to building presented models. The simplest models are Zadeh linguistic variables that describe key performance indicators (KPIs). The BSC model is an acyclic graph with fuzzy links that are calibrated based on special rules. The information obtained during the simulation is aggregated through a matrix aggregate calculator (MAC). (3) The BSC model was used to assess the economic resilience of a small electrical enterprise in Russia, numbering 2000 people with revenue of approximately 100 million euros per year. The BSC model included about 70 KPIs and 200 fuzzy links. Also, the presented MAC model was applied to obtain linguistic classifiers in five basic industries, using the example of a comparative analysis of 82 international industrial companies. (4) The proposed models allow not only to describe the economic system and its external environment, but also solutions aimed at increasing resilience, within the unified framework. Full article

(This article belongs to the Special Issue Mathematical and Instrumental Methods in the Digital Economy)

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15 pages, 994 KiB

Open AccessArticle

Intelligent Automation System on a Single-Board Computer Platform for the Agro-Industrial Sector

Elena Butsenko

Aleksandr Kurdyumov

and

Aleksandr Semin

Mathematics 2020, 8(9), 1480; https://doi.org/10.3390/math8091480 - 02 Sep 2020

Cited by 3 | Viewed by 2610

Abstract

The latest technologies in agribusiness include a range of IT solutions that reduce manual intervention with the top priority tasks to improve, develop, and implement projects based on smart agriculture, which operates on the principles of automation and robotization of production. The aim of the study is to develop a system of automated control of business processes for an agricultural enterprise. The system allows for remote collection and processing of data on technical and economic performance of the farming enterprise. It proves to be a low-cost solution due to the use of affordable and available equipment. When designing the system, the authors described its back end, as well as the connectivity architecture between sensors and modules on one side, and the microcontroller on the other. The paper features modules for monitoring and controlling electrical energy consumption, lighting, temperature, and humidity written in C ++ programming language. Test modules that were controlled by the Arduino microcontroller were analyzed. Further development of the system may involve devising and introducing IoT technologies based on the use of various architectural platforms for practical application. Full article

(This article belongs to the Special Issue Mathematical and Instrumental Methods in the Digital Economy)

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