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All papers published in this volume of IOP Conference Series: Earth and Environmental Science has been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.• Type of peer review: Double-blind • Conference submission management system: https://peatlands2021.ru/ • Number of submissions received: 18 • Number of submissions sent for review: 18 • Number of submissions accepted:15 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 83% • Average number of reviews per paper: 2 • Total number of reviewers involved:6 • Any additional info on review process:The abstracts were submitted by the online system which is available on the conference page https://peatlands2021.ru/. Uploading of full paper may only be done by participants who attend and present their research activities during the conference. The submitted full papers are then collected by the committee for review regarding the format, language and suitability of the conference scope. The papers were sent to 2 reviewers according to topic of the papers and reviewer’s competency. Reviewer was given around 2 weeks to conduct review of the paper for publication in IOP Conference Series. Authors have 2-3 weeks to resubmit an updated version of their submissions with the necessary changes for further evaluation, which should follow the comments and suggestions from our reviewers. Only those submissions passed the peer review and accepted by the reviewers and editors will be included in the conference proceeding finally.• Contact person for queries:Name: Kharanzhevskaya Yu. A.Affiliation: Siberian Federal Scientific Centre of Agro-BioTechnologies of the Russian Academy of Sciences, Siberian Research Institute of Agriculture and Peat, Tomsk, 3 Gagarin st., 634050, Russian FederationE-mail: kharan@yandex.ru

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On the following page you will find the declaration form.• Please answer each question.• You should submit the form along with the rest of your submission files.• The deadline is the submission date written in your publishing agreement.All conference organisers/editors are required to declare details about their peer review.We will published the information you provide as part of your proceedings.All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.• Type of peer review: Double-blind• Conference submission management system: To participate in the PIRT-2021 Conference, Participants had to register on the website http://www.pirt.info/?lang=eng#reg_forms and papers had to be sent to the PIRT-2021 Organizing Committee by e-mail: dekan-fn@mail.ruAll information about the format of abstracts and papers was on the web-site: http://www.pirt.info/?lang=eng• Number of submissions received: 61• Number of submissions sent for review: 51• Number of submissions accepted: 38• Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 62,29• Average number of reviews per paper: 2• Total number of reviewers involved:12• Any additional info on review process: Plagiarism check system: antiplagiat.ruAuthors could resubmit the paper with the necessary revisions.• Contact person for queries: Name : Professor Vladimir Olegovich GladyshevAffiliation: Head of the Faculty of Fundamental Sciences,Bauman Moscow State Technical University,5, 2-nd Baumanskaya St., Moscow, 105005, Russian FederationEmail : gladyshev@bmstu.ru

Peer review declaration

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.All conference organisers/editors are required to declare details about their peer review. Therefore, please provide the following information:• Type of peer review: Double-blind• Conference submission management system: Information System “Conferences”• Number of submissions received: 148• Number of submissions sent for review: 148• Number of submissions accepted: 127• Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 85,8%• Average number of reviews per paper: 2• Total number of reviewers involved: 20• Contact person for queries: Andrey V. ShchelkanovOmsk State Technical University, Omsk, Russian FederationEmail: avshchelkanov@omgtu.ru

Peer review declaration

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Double-blind • Conference submission management system: Information System “Conferences” • Number of submissions received: 143 • Number of submissions sent for review: 143 • Number of submissions accepted: 122 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100):85.3% • Average number of reviews per paper: 2 • Total number of reviewers involved:19 • Any additional info on review process: Contact person for queries: Andrey V. ShchelkanovOmsk State Technical University, Omsk, Russian FederationEmail: avshchelkanov@omgtu.ru

Peer review declaration

All papers published in this volume of Journal of Physics: Conference Series have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.• Type of peer review: Single-blind • Conference submission management system: EasyChair • Number of submissions received: 32 • Number of submissions sent for review: 32 • Number of submissions accepted:14 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100):43 • Average number of reviews per paper: 2.1 • Total number of reviewers involved:14 • Any additional info on review process: Professional translators took part in the preparation of the articles to ensure the good quality of the language. All articles received professional proofreading, in accordance with the requirements of the publisher. Contact person for queries: Sergei Sidorov Saratov State University, Astrakhanskaya, 83, 410012, Saratov, Russian Federatione-mail: sidorovsp@sgu.ru

EDITOR

Prof. Dr. Alexander A. SitnikovPolzunov Altai State technical University, Barnaul, Russian FederationE-mail: msee_astu@mail.ru

Digital organization: Transformation into the new reality

Vladimir I. Ananyin - Senior Lecturer, Department on Business Processes Management, The Russian Presidential Academy of National Economy and Public Administration Address: 82, Prospect Vernadskogo, Moscow, 119571, Russian Federation E-mail:v.ananiin@gmail.comKonstantin V. Zimin - Editor-in-Chief, Information Management Journal, Member of the Board, The Russian Union of CIO Address: 34, Seleznevskaya Street, Moscow, 123056, Russian Federation E-mail: konst.zimin@gmail.comMikhail I. Lugachev - Professor, Head of Department of Economic Informatics, Lomonosov Moscow State University; Academic Supervisor, IBS Corporate UniversityAddress: 1, build. 46, GSP-1, Leninskie Gory, Moscow, 119991, Russian FederationE-mail: mlugachev@gmail.comRinat D. Gimranov - Head of IT Department, OJSC Surgutneftegaz; Head of Surgutneftegaz Department of Vocational Relationships, Surgut State University Address: 1, block 1, Grigoriya Kukuevitskogo Street, Surgut, 628415, Russian FederationE-mail: gimranov_rd@mail.ruKirill G. Skripkin - Associate Professor, Department of Economic Informatics, Lomonosov Moscow State University;Address: 1, build. 46, GSP-1, Leninskie Gory, Moscow, 119991, Russian FederationE-mail:k.skripkin@gmail.com This article discusses the characteristic changes in management practices occurring in the context of the digital transformation of business. It shows the mutual interconnections of these changes, as well as the links to changes in the organizational culture of the organization. Among the new management practices reviewed are those both at the level of the enterprise as a whole (digital products, digital business models, digital management of value creation chains, digital business processes), as well as on the local level in adoption of management decisions - unlimited knowledge and management of the enterprise in real time (Real Time Enterprise). The article demonstrates the need for formation of certain cultural norms in the organization, including total knowledge management and an orientation to rapid changes. Review is made of the succession and qualitative distinctions of traditional automation from digitalization of enterprises. We discuss the possibility of using theories and methods connected with such concepts as complementary assets for research into new forms of organization for the digital enterprise. The article also presents a research program conducted in the framework of a program for digital transformation of activities of the OJSC Surgutneftegaz, Orbita 2.0. In the given research program the accent is placed on analysis of the problem of sustainability of the organization. In order for the organization to be flexible and changeable, it should periodically be in a condition of instability. In the contrary case, strong resistance to change will develop in it. The search for principles and forms of organization ensuring the controllability of sustainable organizations is an important area of this research.

Automatic detection of channels in seismic images via deep learning neural networks

Fedor V. Krasnov - Expert, Science & Technology Centre, Gazprom Neft PJSCAddress: 75-79 liter D, Moika River Embankment, Saint Petersburg, 190000, Russian FederationE-mail: Krasnov.FV@gazprom-neft.ruAlexander V. Butorin - Expert, Science & Technology Centre, Gazprom Neft PJSCAddress: 75-79 liter D, Moika River Embankment, Saint Petersburg, 190000, Russian FederationE-mail: Butorin.AV@gazpromneft-ntc.ruAlexander N. Sitnikov - Deputy Chief Executive Officer for Geology and Field Development, Science & Technology Centre, Gazprom Neft PJSCAddress: 75-79 liter D, Moika River Embankment, Saint Petersburg, 190000, Russian FederationE-mail: Sitnikov.AN@gazpromneft-ntc.ru The business goal of interpreting seismic data has always been addressed by the high-level experts engaged. The authors applied a computer vision approach to interpret seismic data. The expert task of interpreting seismic data has become partially automated via machine learning techniques utilized to classify the images used by the authors. The methods of transformation of seismic traces through spectral decomposition were used to obtain the data set. In the previous works of the authors, methods of spectral decomposition via continuous wavelet transformation were created, and this also laid the foundation of this study. Use of artificial neural networks of deep learning has enabled the authors to meet the goal of image classification. In this regard, it is important to note that the business policy related to information dissemination imposed certain limitations on the computing capacity used and the number of the data labeled. The solution found for the use of trained artificial neural networks and image augmentation helped us to successfully cope with the goal, in spite of the limitations. The results obtained allow us to identify geological units with a test accuracy of 90% rendering to the F1-score measure. This has enabled the Scientific and Technical Center of Gazprom Neft to implement automated procedures in the existing business processes in order to significantly reduce the time needed to process seismic data. The authors consider the possibility of “digitizing” and preserving the knowledge of the highest-level experts in interpreting seismic data, as well as the possibility of using contactless examination to locate geological units in the seismic data within the Gazprom Neft group of companies to be a socially efficient outcome of this study.

Evaluation of the readiness of a company’s IT department for digital business transformation

Evgeniy A. Isaev - Professor, Head of Department of Information Systems and Digital Infrastructure Management, National Research University Higher School of EconomicsAddress: 20, Myasnitskaya Street, Moscow, 101000, Russian FederationE-mail: eisaev@hse.ruNina L. Korovkina - Associate Professor, Department of Information Systems and Digital Infrastructure Management, National Research University Higher School of EconomicsAddress: 20, Myasnitskaya Street, Moscow, 101000, Russian FederationE-mail: nkorovkina@hse.ruMaria S. Tabakova - Graduate of MSc Program, National Research University Higher School of EconomicsAddress: 20, Myasnitskaya Street, Moscow, 101000, Russian FederationE-mail: mstabakova@edu.hse.ru Digital business transformation is a priority for Russian companies in all industries. To develop a company to its full value in the digital environment, it should include an IT department capable of meeting business needs. Evaluation of the current state of the IT department in terms of digital transformation will determine the company’s potential for further development. This article presents a solution to the problem of assessing the IT department’s readiness for digital business transformation by developing a quantitative assessment of the maturity level of the IT department processes for meeting the needs of the enterprise. The approach to solving this problem consists in the joint use of models for assessing the digital maturity of the enterprise as a whole and models for assessing the maturity of the IT department processes and herein is the scientific novelty of the results obtained. At the first stage of the study, based on the analysis of modern information and digital management practices, as well as on the study of approaches to assessing the digital maturity of the enterprise and the processes of the IT department, we developed the requirements for the IT department maturity model of digital business transformation. The study identified the prospects for IT departments that affect its maturity level, developed a model for quantifying each perspective and a model for calculating the minimum level of maturity of the IT department to achieve the expected assessment of the company’s digital maturity. To assess the willingness of IT departments to digitally transform business, a regression equation of IT department maturity level is constructed from the influencing prospects (factors). The results of approbation of the model are presented.

Agility of enterprise information systems: A conceptual model, design principles and quantitative measurement

Yuri A. Zelenkov - Professor, Department of Information Systems and Digital Infrastructure Management, National Research University Higher School of EconomicsAddress: 20, Myasnitskaya Street, Moscow, 101000, Russian FederationE-mail: yzelenkov @hse.ru A modern enterprise has to react to permanent changes in the business environment by transformation of its own behavior, operational practices and business processes. Such transformations may range from changes of business processes to changes of information systems used to support the business processes, changes in the underlying IT infrastructures and even in the enterprise information system as a whole. The main characteristic of changes in a turbulent business environment and, consequently, in the enterprise information system is unpredictability. Therefore, an enterprise information system should support the operational efficiency of the current business model, as well as provide the necessary level of agility to implement future unpredictable changes of requirements. This article aims to propose a conceptual model of an agile enterprise information system, which is defined as a working system that should eliminate the largest possible number of gaps caused by external events through incremental changes of its own components. A conceptual model developed according to the socio-technical approach includes structural properties of an agile enterprise information system (actors, tasks, technology, and structure). Structural properties define its operational characteristics, i.e. measurable indicators of agility - time, costs, scope and robustness of process of change. Different ways to build such an agile system are discussed on the basis of axiomatic design theory. We propose an approach to measurement of time, cost, scope and robustness of changes which helps to make quantitative estimation of the achieved level of agility.

Competence-based approach to managing staff in public administration on the basis of ontologies

Natalia F. Altukhova - Associate Professor, Head of Department of Business Informatics, Financial University under the Government of the Russian FederationAddress: 38, Scherbakovskaya Street, Moscow, 105187, Russian FederationE-mail: nfaltuhova@fa.ruElena V. Vasileva - Professor, Department of Business Informatics, Financial University under the Government of the Russian FederationAddress: 38, Scherbakovskaya Street, Moscow, 105187, Russian FederationE-mail: evvasileva@fa.ruMariam V. Mirzoyan - Doctoral Student, Department of Business Informatics, Financial University under the Government of the Russian FederationAddress: 38, Scherbakovskaya Street, Moscow, 105187, Russian FederationE-mail: mvmirzoyan@fa.ru The introduction of new management principles in public administration is in many countries linked to the introduction of client-orientation and evaluation by results. In this connection, a good deal of attention should be directed to raising the quality of work of public administration civil servants. This problem is inextricably bound with the task of raising the qualifications and competency level of workers in public administration. In this work, we present an analysis of the current situation in management of public administrations. We distinguish between the problems of managing the competences of public servants. As part of the research, we polled more than 365 public servants from the rank of specialist to chiefs of sections. We highlighted the competences in highest demand among public servants. These are general professional skills, regulatory-legal, competences of results orientation and work efficiency. Least in demand were groups of competences such as change management, self-management and professional growth. The respondents also noted the high demand for renewal of their professional knowledge. However, there remains a problem with exchange of knowledge, when the knowledge received by employees in the best case turns up in conferences but mostly remains only for personal use and is not attached to a single carrier of information. We present proposals for applying an ontological approach to evaluation of the competences of public servants. The set of competences makes it possible with sufficient precision to describe the work behavior which is required for successful performance of the work in the given position or in a group of similar positions. The application of ontologies makes it possible to link the task of evaluating competences through transformation of the enquiry into a set of terms and concepts with the concrete requirements of the project of the planned task or performed function. Computerization is one of the main components in the strategy for developing the public services. Creation of a system of decision support on the basis of mathematical methods to ensure alignment of competences of public servants with the demands made on their functions allows Human Resources to efficiently make its selection of personnel for vacancies in the public organization.

Detection of patterns and trends in patient behavior while using electronic applications and Internet resources for self-diagnosis

Galina A. Polynskaya - Associate Professor, Department of Marketing, Lomonosov Moscow State UniversityAddress: 1, Leninskie Gory, Moscow, 119991, Russian FederationE-mail: g.polinskaya@outlook.comMargarita G. Mesropyan - Doctoral Student, Economic Sociology and Demography Specialty, Financial University under the Government of the Russian FederationAddress: 49, Leningradsky Prospekt, Moscow, 125993, Russian FederationE-mail: m.mesropyan.93@gmail.com Information and communication technologies have changed the world, affecting all sectors of the national economy including the medical industry. There is rapid growth in the dependence of the quality of medical services on the use of information systems. Gradually, information systems are beginning to take over part of doctors’ work. Digitalization also has affected ordinary citizens. There is a growing popularity of electronic applications and Internet resources in the health care industry among users of the network. As a result, self-diagnosis and self-treatment are improving with their use. Therefore, it is important to assess the possibilities for the coexistence of traditional medicine with modern digital technology opportunities that the citizens are facing these days. The authors of this research have carried out a series of studies to identify the patterns of patient behavior using electronic applications and Internet resources for self-diagnosis, as well as factors that contribute to or impede the development of such use. The following actions were performed: high-quality content analysis of medical web applications, 40 in-depth interviews with doctors and pharmacists, a mini focus group with representatives of the health service, as well as an online survey of two hundred respondents in the social network Facebook. As a result of the study, patients were segmented according to typical behavioral patterns with regard to the use of electronic applications and Internet resources in the field of medicine. We identified the attitude towards Internet self-diagnosis of doctors and pharmacists on the one hand and patients, on the other, as well as factors contributing to or impeding the growth of Internet diagnostics.

Estimating the net premium using additional information about a quantile of the cumulative distribution function

Zhanna N. Zenkova - Associate Professor, Institute of Applied Mathematics and Computer Science, National Research Tomsk State University; SRO “Association of professional actuaries”Address: 36, Lenin Street, Tomsk, 63403047, Russian Federation E-mail: zhanna.zenkova@mail.tsu.ruElizaveta A. Krainova - Doctoral Student, Institute of Applied Mathematics and Computer Science, National Research Tomsk State University;Address: 36, Lenin Street, Tomsk, 63403047, Russian Federation E-mail: lanshakoval@gmail.com In this paper, the task of increasing the accuracy of net premium estimations in non-life insurance is considered. Improvements are achieved by involving additional information about a known q-quantile of loss cumulative distribution function. The additional information is used by projection the empirical cumulative distribution function onto the class of cumulative distribution functions with a certain q-quantile, and then the modified empirical cumulative distribution function is substituted into the integral that yields the mean value. This allows us to obtain a modified estimation of mean value using additional information about the q-quantile which is unbiased and its variance is asymptotically less than the variance of the classical sample mean, so that the mean-square error of the modification is also smaller. Therefore, the modified estimation is more accurate than the classical one for a large sample size. The influence of a quantile value on the variance of the new estimation is studied for uniform, triangular and normal distributions. It is suggested that the minimum of the variance is reached when a known quantile is equal to the median (symmetry center) for symmetrical distribution. Based on Simpson triangular distribution, it was shown that for cases of skewed distributions involving the quantile allows one to decrease the variance more significantly than for symmetrical ones. The modified estimation of mean value is applied to a real data set for calculation of a net premium. The data contain information about payments for voluntary health insurance of some insurance company. It is demonstrated that the classical method underestimates the net premium, and so it could lead to the company’s bankruptcy. After applying the new modified technique, the net premium becomes higher and the bankruptcy risk is reduced as well. This paper contains practically significant results which make it possible to give important recommendations to an insurance company.

Using a web analytics system as the basis for integration with CPA services

Vyacheslav I. Zhukov - Assistant Professor, Department of Innovation and Business in Information Technologies, National Research University Higher School of EconomicsAddress: 20, Myasnitskaya Street, Moscow, 101000, Russian FederationE-mail: vzhukov@hse.ruMikhail M. Komarov - Associate Professor, Department of Innovation and Business in Information Technologies, National Research University Higher School of EconomicsAddress: 20, Myasnitskaya Street, Moscow, 101000, Russian FederationE-mail: mkomarov@hse.ru In modern e-business, there are many ways to attract potential customers to the site both with the help of offline and online methods. Companies usually use several channels to attract customers, differing in the placement of advertising, payment models and other parameters. One of the most popular online methods is using CPA networks, which allow webmasters to place on their websites links to the advertised website and earn rewards for customers who purchased a service by clicking on the link. CPA networks work on the basis of payment for achieving targeted goals. A targeted goal can occur both online and offline. The most important task is to link the source of attraction (usually certain UTM tags) to the target goal of the client, since remuneration for the CPA network should only occur for orders from customers who are drawn to the CPA network. There are problems fixing operations, linking to source of attraction, storing and providing access to these data. In this paper, we give a brief overview of various approaches to solving the problem: log analysis, use of marketing pixels and web analytics tools. We have analyzed the benefits and challenges of these methods, which were given to solve the task of fixing the target actions of clients and provided access to the data for the CPA network. Also in this article, we have described a practical case of integration with the CPA network based on the use of end-to-end web analytics. The advantages, disadvantages and limitations of the proposed method are set out in this paper.

Combined method to detect communities in graphs of interacting objects

Sofiya Y. Lobanova - BSc Program Student, Tikhonov Moscow Institute of Electronics and Mathematics, National Research University Higher School of EconomicsAddress: 20, Myasnitskaya Street, Moscow, 101000, Russian FederationE-mail: s.lobanova@usabilitylab.netAlexander A. Chepovskiy - Associate Professor, School of Applied Mathematics, Tikhonov Moscow Institute of Electronics and Mathematics, National Research University Higher School of EconomicsAddress: 20, Myasnitskaya Street, Moscow, 101000, Russian FederationE-mail: aachepovsky@hse.ru In this paper, we propose and implement a method for detecting intersecting and nested communities in graphs of interacting objects of different natures. For this, two classical algorithms are taken: a hierarchical agglomerate and one based on the search for k-cliques. The combined algorithm presented is based on their consistent application. In addition, parametric options are developed that are responsible for actions with communities whose sizes are smaller than the given k, and also with single vertices. Varying these parameters allows us to take into account differences in the topology of the original graph and thus to correct the algorithm. The testing was carried out on real data, including on a group of graphs of a social network, and the qualitative content of the resulting partition was investigated. To assess the differences between the integrated method and the classical algorithms of community detections, a common measure of similarity was used. As a result, it is clearly shown that the resulting partitions are significantly different. We found that for the approach proposed in the article the index of the numerical characteristic of the partitioning accuracy, modularity, can be lower than the corresponding value for other approaches. At the same time, the result of an integrated method is often more informative due to intersections and nested community structure. A visualization of the partition obtained for one of the examples by an integrated method at the first and last steps is presented. Along with the successfully found set of parameters of the integrated method for small communities and cut off vertices in the case of social networks, some shortcomings of the proposed model are noted. Proposals are made to develop this approach by using a set of parametric algorithms.This work was supported by the Russian Foundation for Basic Research (projects No. №16-29-09546 and №16-07-00641)

Modeling and optimization of business processes and process systems under conditions of uncertainty

Alexander G. Madera - Professor, Department of Mathematics of the Faculty of Economics, National Research University Higher School of EconomicsAddress: 20, Myasnitskaya Street, Moscow, 101000, Russian FederationE-mail: amadera@hse.ru This paper is devoted to mathematical modeling and optimization of business processes and process systems under conditions of uncertainty. At present, modeling of business processes is mainly descriptive, which does not allow quantitative modeling and optimization in the design of processes and process systems. In addition, the existing methods of decision-making in business processes are based on the assumption that the decisive factors are deterministic. Despite uncertainty of the real processes caused by the uncertainty of future costs of resources, the market environment, economy, finances, etc,, the factors of an uncertain future are either not taken into account, or are believed to be the same as those observed currently. In this paper, a stochastic interval mathematical optimization model is developed. This model allows us to simulate in a quantitative way the business processes and process systems in which they take place, taking into account the uncertainties of the future state of the economy, finances, market environment, costs of resources, as well as future realization of chances and risks related to the productive, supporting, and service processes. The criterion for optimality of the model is the maximization of the smallest deviation of the projected chances and risks, which makes it possible to make the best decision in the case that the most unfavorable conditions for the business process occur in the future. The criterion of optimality adopted in the mathematical model takes into account not only the uncertainty of the future state of the economy, finance, and market environment, but also the psychology of decision-making and the subjective nature of judgments and estimates. We present a concept and method for estimating the inductive (logical, subjective) probabilities of the occurrence of uncertain predicted business process factors. The models and methods developed in the paper make it possible to carry out mathematical modeling and optimization of business processes in a variety of activities without restrictions on the complexity of the structural model of the business process, the qualitative and quantitative composition of the connections in the process systems. On their basis, a software package for the quantitative design of business processes and process systems under conditions of uncertainty can be developed.

Specifics of the integration of Business Intelligence and Big Data technologies in the processes of economic analysis

Stanislav Mitrovic - University of Novi Sad, Republic of Serbia; Doctoral Student of the Faculty of Economics, Lomonosov Moscow State UniversityAddress: 1, Leninskie Gory, Moscow, 119991, Russian FederationE-mail: Mitrovic.Stanislav@hotmail.com The volume of data used for economic analysis of the activities of organizations is growing every year. Despite the fact that all information required for economic analysis is available from various sources, such data are very often useless for analysis from the point of view of their economic potential. The purpose of this study is to outline a foundation for integrating Business Intelligence and Big Data into economic analysis processes. The theoretical and methodological basis of this study is provided by scientific research, methodological and practical developments of domestic and foreign authors on the application of IT solutions in economic analysis. According to the results of the research, modern information technologies, in particular, the Business Intelligence and Big Data systems have considerably changed the possibilities for improving economic analysis and reducing decision-making time. From the methodological point of view, many aspects of integration of BI and Big Data solutions and their implementation in the economic analysis processes in Russia’s companies remain insufficiently developed. The foreign market of modern information technologies for business analytics has a longer history and is being developed more rapidly. The main conclusions of the study indicate that modern organizations operating on a highly competitive market should understand that the accumulation of Big Data does not always lead to the expected business benefits. In this context, the conclusion is that a modern company should not set as its goal to process all the available data in order to improve the quality of its economic analysis. It is more significant to use the entire volume of data for segmentation, which allows effective construction of a large number of models for small clusters, solving specific problems of economic analysis based on the application of modern IT systems.

An architectural approach to IT–business alignment

Pavel V. Malyzhenkov - Associate Professor, Department of Information Systems and Technologies, National Research University Higher School of Economics Address: 25/12, Bolshaya Pecherskaya Street, Nizhniy Novgorod, 603155, Russian Federation E-mail: pmalyzhenkov@hse.ruMarina I. Ivanova - Student, Business Informatics MSc Program, National Research University Higher School of Economics Address: 25/12, Bolshaya Pecherskaya Street, Nizhniy Novgorod, 603155, Russian Federation E-mail: miivanova_1@edu.hse.ru Information technologies have evolved from their traditional back-office role to a strategic resource role that can not only support but also shape business strategies. Still, different analytical sources indicate that only a small number of projects complete on-time and on-budget, leading to initially specified goals and results. The main problem is the creation and formalization of an IT-business alignment mechanism which for over a decade has been ranked as a top-priority management concern and is widely covered in theoretical literature. However, the field is dominated by conceptual studies, while there is little research on practical ways to achieve the alignment. Moreover, most of the existing research focuses on the alignment assessment using questionnaire methods based on the subjective judgement of IT and business executives. From this point of view, Enterprise Architecture development as a methodological approach to the mutually aligned business and IT architectures’ design, represents a suitable tool for solving this problem. However, most of the existing EA approaches do not distinguish between different IT-business alignment perspectives. This paper attempts to provide practical guidance for IT-business alignment as well as strategic guidance for EA development by integrating the traditional Strategic Alignment Model and the TOGAF framework.

Modeling the influence of foreign investments on food security based on panel cointegration models

Elena D. Kopnova - Associate Professor, Department of Statistics and Data Analysis, National Research University Higher School of EconomicsAddress: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation E-mail:ekopnova@hse.ruLilia A. Rodionova - Associate Professor, Department of Statistics and Data Analysis, National Research University Higher School of EconomicsAddress: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation E-mail: lrodionova@hse.ru The paper studies the problems of food security as the basis for the stability of the country’s economic development. Despite the economic growth of most countries in the world, the problems of hunger continue to be acute in developing countries. This undermines the food security of these countries and can pose a threat to world peace as a whole. Numerous studies show that foreign investment plays an important role in the creation of food security, but this effect is ambiguous. The most common methods of analysis in recent researchеs are descriptive analysis and panel data models. In this article, our approach to analyzing the impact of foreign investment is based on panel cointegration models; the interpretation of the results uses the impulse response function based on an error correction model. Countries of North Africa are considered as an example of the implementation of this approach. Data from the World Bank and the Food and Agriculture Organization for 1991-2014 for seven countries (Algeria, Egypt, Libya, Morocco, Sudan, Tunisia, Western Sahara) were selected for analysis. In this paper, we have also tested the methodology for selecting the food security indicator based on analysis of the matrix of cointegration relations. The results show that foreign investment has a significant long-term impact on food security, but in the short term no effect was detected. The proposed modeling methodology can be extended to any region of the world to monitor and evaluate the effectiveness of the current economic policy to combat hunger and poverty.

Analysis of the consistency of enterprise architecture models using formal verification methods

Э.А. Бабкин - кандидат технических наук, PhD in Computer Science, профессор кафедры информационных систем и технологий, Национальный исследовательский университет «Высшая школа экономики»Адрес: 603155, г. Нижний Новгород, ул. Большая Печерская, д. 25/20E-mail: eababkin@hse.ruН.О. Пономарев - студент магистерской программы «Бизнес-информатика», Национальный исследовательский университет «Высшая школа экономики»; инженер группы разработки программного обеспечения АО «Интел»Адрес: 603155, г. Нижний Новгород, ул. Большая Печерская, д. 25/20E-mail:nik4nikita@gmail.com Разработка архитектуры предприятия является сложным процессом, но в то же время позволяет решить проблему синхронизации возможностей и потребностей бизнеса и информационных технологий (ИТ). Решение данной проблемы достигается за счет уточнения понимания и формализации описания бизнес-процессов и взаимодействия элементов системы путем их формального описания. Наличие большого числа взаимодействующих бизнес-процессов и сущностей архитектуры предприятия объясняет необходимость проверки их корректности. Поэтому необходимо их автоматически верифицировать, на основе формализации требований к архитектуре. В данной работе предлагается метод обнаружения логических противоречий в моделях архитектуры предприятия, на основе частного случая подхода к проверке моделей, примененного в бизнес-моделировании. В качестве языка описания архитектуры предприятия в работе используется современный открытый и независимый язык ArchiMate. Разрабатываемый The Open Group стандарт предоставляет общую спецификацию для описания построения и функционирования бизнес-процессов, организационных структур, информационных потоков, ИТ-систем и технической инфраструктуры предприятия. В качестве верификатора выбран формальный язык реляционной логики и инструментарий системы MITAlloy Analyzer, позволяющий выполнять анализ ограничений модели в терминах реляционной логики путем автоматической генерации структур, которые удовлетворяют требованиям логической модели. В данной работе предлагается упростить и автоматизировать процесс спецификации и верификации моделей предметной области архитектуры предприятия с помощью визуального редактора конструирования моделей на языке ArchiMate - Archi. Разработанный авторами плагин к редактору осуществляет трансляцию моделей архитектуры предприятия на язык системы Alloy Analyzer и в качестве основы для построения конкретных моделей предметной области использует метамодель ключевых элементов спецификации ArchiMate. Предложенный метод и программные решения апробированы на примере пользовательского кейса архитектуры предприятия компании ArciSurance.Исследование выполнено при финансовой поддержке РФФИ в рамках научного проекта № 16-06-00184 А «Разработка и исследование моделей online-дискуссии на материале обсуждения политических новостей»