E-trade systems are widely used to automate sales processes. Inefficiencies and bottlenecks in the sales processes lead to business losses. Conventional approaches to identifying problems require much time and result in subjective conclusions. This paper proposes an approach for the analysis of e-trade system processes based on the application of process mining techniques. Process mining aims to discover, analyze, repair and improve real business processes on the basis of behavior of an information system recorded in an event log. Using process mining techniques, we have analyzed process running in an online ticket booking information system. This work has shown that process mining can give insight into the e-trade processes and can produce information for their improvement. The case study carried out allows formulating appropriate recommendations. The article also presents the real outcome of using process mining techniques. We have generalized the applied approach and showed how it could be used to the investigation of a wide spectrum of e-trade information systems. During the case study we mostly used a software framework named ProM, which includes a substantial number of plug-ins implementing process mining methods. Using software for automatic process analysis and discovery, one should be careful with the interpretation of particular methods’ output. Pitfalls and difficulties of applying process mining techniques to the logs of e-trade systems have also been shown.
This article studies the concept of web 3.0, and gives definitions to its major features as we see them. We analyse the interconnections and specific traits of web 3.0 when it is used in e-commerce. The article views the solutions business employs currently, as well as gives prognosis of how business will use web 3.0 in the future.
In 1971 in his Nobel lecture Simon Kuznets noted that the population growth had been ceasing to be the main force
of the economic growth over the last one or two decades. Accordingly, the authors have examined the contemporary
demographic situation in the world based on information given in United Nations (UN) population prospects. This paper
describes the global demographic balance method that includes 5 age cohorts of the population of 20 countries and regions
of the world for the last period of 1950-2010 and UN Population Prospect to 2050. This method has been applied to
analyze quantitative parameters of the demographic situation in developed, least developed and in developing countries.
Developed countries, which had passed the demographic transition, will face a depopulation pattern in XXI. The age
structure of depopulation trends in these countries is given. In least developed countries the population growth has been
persisting but not at so high pace as it was in the second half of the 20
century. BRICS countries stand out from developing
countries. To assess qualitative characteristics of countries of the world the Human Development Index (HDI) has been
used. This paper outlines characteristics of this indicator given by United Nations Development Programme (UNDP).
HDI values for BRICS countries are specified, and a conclusion has been drawn that qualitative growth is needed for
economies of these countries. Outputs of world population simulation and projections by G.P. Gorshkov, B.M. Dolgopolov
and A.A. Akayev, adjusted for the biosphere ultimate capacity, are presented. A conclusion has been formulated that
projections by S.P. Kapitsa and UN experts that disregard the biosphere ultimate capacity are more realistic.
The paper represents methods of expert data collection, consolidation and evaluation for the purpose of development of knowledge bases. The methods assume processing the data with software tools. The data obtained are used for foresight studies, long-term forecasting and development of technology roadmaps (TRM). The technique provides users with the possibility to take various features of an expert into account, as well as to map expert data onto the field of interest of the TRM customer.
The article is based on the results obtained by participants research seminar the faculty of business Informatics of the Higher School of Economics. Objective – to study the possibilities of learning management as a process and application of modern information technologies and tools. The learning process is defined as joint activity of participants for organization of study discipline, receive regular and procedural knowledge. For research the learning process discipline "Modeling and optimization of business processes" was chosen. The features of learning process, requirements of process management, modeling and assessment capabilities of automated process management were defined. The analysis is based on information of real process Faculty of Business Informatics. Requirements for learning process were identified. Different notations for modeling were used: eEPC (ARIS); interaction diagram and behavior diagram (Metasonic). It was shown that satisfaction of requirements for process is provided on subject-oriented approach and it is almost impossible for classical approach. Principles of sharing the learning process into smaller processes, process models (interaction diagrams and behavior diagrams of subjects) are developed. Possibility of changing process management with help of subjects (teachers, students) without programming, including the automated generation of workflow application were presented. Results of research can be useful for any organization thinking about the transition from traditional rigid structure to a more modern reflexive organization with network communications.
The methods of calculating the particular and integral indicators of the applicability for the technological roadmap elements and their attributes. These indicators are applied to the automated tools for the foresight researches, the long-term scientific and technological forecasting, identifying innovative trajectories of the emerging domains evolution
Analytical justification of solutions using a decision support system (DSS) significantly increases the quality of decisions. The existing DSS generally employs 1 or 2 methods of decision-making. It does not always lead to the desired results, as each method is based on certain assumptions and is not universal. The maximum effect can be achieved only insofar a set of decision-making methods is included into the knowledge base of the DSS. The only system that meets these requirements is the Expert Decision Support System (EDSS) developed under supervision of the author. Currently the EDSS includes about 50 decision-making methods. The expansion of the EDSS knowledge base by including new methods will allow for choosing the most suitable method for solving each decision-making task. Enhancing the Decision Table model underlying the system knowledge base allows you to develop the EDSS without complete reworking of the system code. The system knowledge base contains decision rules built on the principle of “if... then...” (if certain conditions of decision making exist, then a definite method of decision-making should be employed). To expand the EDSS knowledge base, ELECTRE collection methods were selected. Their key feature consists in not using the convolution operation of evaluation of the alternatives specified in different scales on individual criteria. This was the reason for selecting the methods of this family. In the article, the algorithms of these methods are adapted for their inclusion in the EDSS. An algorithm for obtaining a criterion-alternative matrix is proposed. It serves as input information for the ELECTRE family methods in cases where there is no objective information for its formation. The results of the study can be used to develop the EDSS, allowing analytical justification of solutions using methods that have not previously been used in the system.
Modeling the processes in a healthcare system plays a large role in understanding its activities and serves as the basis for increasing the efficiency of medical institutions. The tasks of analyzing and modeling large amounts of urban healthcare data using machine learning methods are of particular importance and relevance for the development of industry solutions in the framework of digitalization of the economy, where data is the key factor in production. The problem of automatic analysis and determination of clinical pathways groups of patients based on clustering methods is considered in this research. Existing projects in this area reflect a great interest on the part of the scientific community in such studies; however, there is a need to develop a number of methodological approaches for their further practical application in urban outpatient institutions, taking into account the specifics of the organization being analyzed. The aim of the study is to improve the quality of management and segmentation of patient input flow in urban medical institutions based on cluster analysis methods for the further development of recommendation services. One approach to achieving this goal is the development and implementation of clinical pathways, or patient trajectories. In general, the clinical pathway of a patient might be interpreted as the trajectory when receiving medical services in respective institutions. The approach of developing groups of patient routes by the hierarchical agglomerative algorithm with the Ward method and Additive Regularization of Topic Models (ARTM) is presented in this article. A computational experiment based on public data on the routes of patients with a diagnosis of sepsis is described. One feature of the proposed approach is not just the automation of the determination of similar groups of patient trajectories, but also the consideration of clinical pathways patterns to form recommendations for organizing the resource allocation of a medical institution. The proposed approach to segmenting the input heterogeneous flow of patients in urban medical institutions on the basis of clustering consists of the following steps: 1) preparing the data of the medical institution in the format of an event log; 2) encoding patient routes; 3) determination of the upper limit of the clinical pathway length; 4) hierarchical agglomerative clustering; 5) additive regularization of topic models (ARTM); 6) identifying popular patient route patterns. The resulting clusters of routes serve as the foundation for the further development of a simulation model of a medical institution and provide recommendations to patients. In addition, these groups may underlie the development of the robotic process automation system (RPA), which simulates human actions and allows you to automate the interpretation of data to manage the resources of the institution.
Enterprise architecture design is a complex process which makes it possible to synchronize the capabilities and needs of business and information technologies (IT). It can be achieved by clarifying the understanding and formalization of the business processes and the interaction of the elements of the system through their formal description. The large number of interacting business processes and enterprise architecture entities raises the question of verifying their correctness. Therefore, it is necessary to formalize the requirements for architecture and be able to automatically verify them. In this paper, we propose a method for detecting logical contradictions in enterprise architecture models based on a model checking approach adopted in the context of business modeling. As an enterprise architecture description language, we use the modern open and independent ArchiMate standard. Developed by The Open Group, the standard provides a general specification for business processes, organizational structures, information flows, IT-systems and the technical infrastructure description of the enterprise. As a verifier, the language and tools of the MIT Alloy Analyzer system were chosen; they facilitate analysis of model constraints in terms of relational logic by automatically generating structures that satisfy the requirements of a logical model. In this paper, we propose to simplify and automate the process of specification and verification of enterprise architecture domain models using Archi - the visual editor for ArchiMate models. We have developed the editor plug-in which translates the enterprise architecture models into the language of the MIT Alloy Analyzer system and uses the meta-model of the ArchiMate specification as the basis for constructing specific domain models. The proposed method and software solutions have been tested using the ArciSurance case and their enterprise architecture model. The research was carried out with financial support of Russian Fund of Basic Research No. 16-06-00184 A “Development and investigation models of online-discussion based on materials of political news”
Pattern analysis is a new area in data analysis related with the search for relationships between the objects, the construction of the objects classification and study of object’s changes over time. In the first part of the article the notion of ‘pattern’ is introduced, and a survey of methods of cluster analysis and pattern analysis is presented.
The agile project management approach has been considered to be one of the most popular approaches for developing IT solutions. Use of this approach allows us to change the requirements at any stage of the IT project, and one of the twelve principles of Agile Manifesto, – “Simplicity”, – promotes the use of a minimum amount of project documentation. One of the disadvantages limiting the implementation in such resource-intensive projects as Information Systems Projects (ISP) is the risk of exceeding budgets and time limits. Therefore it is highly important to develop such a tool that will contribute in discussion and approval process with the customer before changes are started so as to minimize the possibilities of changes at further stages of the project. This article investigates the possibility of applying holistic methods of the Enterprise Architecture (EA) in order to support solutions design during an Information System Project, in particular, in the form of documentation at the stage before implementation planning. The main aim of our research is to develop a tool that will help the customer to understand the planned changes and will contribute in that their infl uence on the already existing EA is taken into account. This article fi rst reviews standards of IT project management in the context of recommendations for “conceptual project” outcomes. Next, the results of interviews conducted with IT consultants are presented. The proposed Architectural Solution (AS) is a document that completes the stage of design and coordinating IT changes. It is based on the application of methods and models from the fi eld of EA. We believe this solution may be a suffi cient document for coordinating projects that are conducted under agile philosophy.
Developing variants of scenarios for a production enterprise’s achieving a desirable fi nancial position using simulation modeling tools requires a specifi cation and verifi cation of requirements for the simulation model. Availability of such variants of scenarios allows stakeholders to select the most effi cient solution. The verifi cation is performed by business analysts and key stakeholders; the aim is to assess readiness of the requirements for fi nal approval and to check that the requirements provide all material information for future work. Verifi cation includes evaluating the requirements regarding their compliance with the company’s business analysis standards, as well as assessment of the model’s completeness and common terminology used for description of the requirements. Understanding the desired solution, which meets all the stakeholders’ requirements, is the most important element in requirements verifi cation. For developing a simulation model, which is essential for determining variants of development scenarios and covers fi nancial fl ows of a typical production company, a list of verifi ed requirements is determined. Criteria of requirements verifi cation include not only acceptance criteria, but also the Graphical Requirements Analysis framework (GRA framework), that is used for verifi cation of functional requirements. The verifi ed requirements should be used at diff erent stages of constructing the simulation model, which is focused on development of scenarios for achieving the production enterprise’s desired future fi nancial position. Modeling scenarios of future development of the types “what will happen, if…?” and “what to do to achieve the goal?”, using simulation modeling systems allows one to dramatically increase the quality of decision making.
The purpose of this article is the analysis of leading European research in the field of knowledge visualization from the point of view of the accumulated theoretical base, practice of application, problems, and trends. The need for digital business transformation for survival in the era of high-speed, mobile intelligent applications and big data has become apparent. However, understanding and interpretation of information can be performed only by humans. Modern managers cope with information «explosion» through visualization. Visualization helps them to understand, to compress and to demonstrate the ocean of numbers, words, and ideas. The number of works devoted to the theme of visualization is growing every year. There are numerous studies on the visualization of networks and relationships, and visualization of communication with a consumer. Fewer articles have been devoted to the visualization of knowledge in the implementation of business practices. At the same time, scientists are examining one specific area of application of visualization and only a few contribute to the theory of the subject and study it in a versatile manner. The latter include the works of researchers from the University of St. Gallen (Switzerland), which we call in this article the St. Gallen School. We propose systematization of the following basic stages of research formation of the aforementioned School: 1) the preliminary stage, 2) the stage of empirical data accumulation, and 3) the stage of theory development. The School's contribution to the theory and practice of management was analyzed. Its contribution to theory includes the classification of visualization techniques, a description of visualization use in business, the development of the boundary objects theory, as well as a detailed description of experimental studies. Contribution to business practices means implementation of educational projects and the development of new visual models. The fragmented nature of research is identified: theoretical work is focused on how several visual models influence the implementation of certain business practices; empirical work often describes consulting projects, but do not provide an understanding of how to apply visualization techniques when there is no researcher-consultant. Based on our analysis of the literature, we demonstrate that the major trend in information processing is focus on knowledge representation based on data, not data as such. The challenging areas related to applied research methods are highlighted as follows: lack of consistency, and lack of distinction between the concepts of «data visualization» and - «knowledge visualization». Thus, there is a need to distinguish visualization of knowledge in a separate area of study.
The article contains the analysis of the impact of information and communication technologies as well as mobile technologies for the conduction of small and medium business in the emerging countries. Special approach is suggested for the development of the concept of business-processes management on small and medium enterprises.
This study presents the analysis of one of the major contemporary transformational forces – the Internet of Things (IoT), which significantly influences the future development of all spheres of life. The purpose of the research is to identify the potential economic effects of IoT implementation in different markets. To achieve this goal, the following tasks are consistently solved in the study: identification and classification of the main IoT applications markets; detection, assessment and analysis of the economic effects of the IoT in the selected segments within the proposed classification; formation of future directions of IoT development. Based on the combination of such methodological approaches as technology life cycle and technology adoption life cycle, perspectives of the IoT development are set out. The technology life cycle is viewed through the prism of the methodology of the research company Gartner (the Gartner Hype Cycle for Emerging Technologies), based on establishing a consensus among a wide range of assessments of leading experts in the field of information and communication technologies. Comparison of the two methods and expert assessments allows us to conclude that, according to the methodology of technology adoption life cycle, the Internet of Things is of interest only for a group of “early adopters.”