Currently, the most sought-after graduates in the labor market are those with not only management competencies but also experience working with software products, operational data, knowledge bases, and ERP systems. The availability of an ERP system offered by the country’s largest IT company, 1C, plays a key role in the educational process at universities. 1C technologies are being actively integrated into the curricula of federal and regional universities. I. N. Ulianov Chuvash State University stands out as the most effective IT training institution in the Chuvash Republic. Faculty of Economics of Chuvash State University has been teaching courses using 1C technologies for over 20 years. 1C:ERP technologies have gained significant interest among the university’s Business Informatics students. The 1C:ERP Enterprise Management 2 program at Chuvash State University is divided into sections: 1) a theoretical section, which includes studying the system’s architecture, modules, and integration with other 1C software products; 2) a practical section, which involves researching the 1C:Enterprise 8 platform and modeling its processes using examples from enterprises in the republic; and 3) project work, whichfocuses on implementing group projects to implement 1C:ERP. During these sections, the most effective application and use of 1C solutions is assessed. The article presents the experience of teaching 1C:ERP Enterprise Management in Chuvash State University and identifies the specifics of improving the implementation of 1C technologies in the university’s educational process. Particular attention is paid to the interaction between the university and the end user — the employer organization. As a result of this interaction, Chuvash State University opened an interfaculty 1C basic laboratory and developed networked forms of delivery for educational programs in the Information Business Analytics specialization.

The purpose of this study is to examine the theoretical and practical aspects of using artificial intelligence systems in the educational process, including current trends and ethical issues, such as the ethics of using ChatGPT for automatically generating texts in academic papers. The study’s materials and methods include analysis of bibliographic sources, collection, systematization, and structuring of information, structural modeling of the subsystems of an e-course based on artificial intelligence technologies. A questionnaire survey of bachelor’s degree students in business informatics was conducted on the use of ChatGPT (or its equivalents) in the educational process. Results . The article highlights the following key areas of artificial intelligence application in higher education: intelligent support for the organization of the educational process; personalized e-learning courses with a neural network mechanism for selecting a flexible, individual educational trajectory; methodological and scientific support for an education system based on artificial intelligence technologies; technical support for the educational process and its information security; strategic management of a university, including the use of intelligent systems for monitoring, analyzing, and planning the educational process. A possible structure for an e-course based on artificial intelligence subsystems is presented.A number of challenges associated with the implementation of artificial intelligence technologies in education are highlighted: technical issues, software problems, personnel issues, organizational and managerial issues, and ethical concerns.A questionnaire survey of bachelors of the business informatics direction was conducted on the use of ChatGPT in the educational process. The survey revealed that 96% of respondents use these chats in some form or another when performing educational tasks, and 88% of them do it systematically. Conclusion. The main technological trends in the application of artificial intelligence in education include the use of machine and computer vision systems, neural network models (including generative pretrained transformer models), and data mining systems. The potential of artificial intelligence systems will make it possible in the future to solve a number of other problems, such as the neural network construction of flexible, personalized student learning paths, and the optimization of structural units of the university.The use of artificial intelligence imposes certain ethical constraints on the educational process. This primarily concerns students’ use of AI-generated results as their own academic achievements. It can be concluded that generative artificial intelligence is a tool that requires careful and measured use to replace creative human intellectual activity.The implementation of innovative technologies such as machine learning, computer vision, big data analytics, robotics, virtual and augmented reality, the internet of things, and others contributes to the optimization of university educational and management processes and the improvement of the quality of education. These trends form the foundation for shaping the image of a modern, competitive higher education institution capable of adapting to new challenges and realizing the full potential of digital transformation.

Purpose . The purpose of research is to reveal the main problems in the field of business process modeling and identify the main directions for the development of appropriate languages and modeling methods, including their reflection in modern educational disciplines and processes. Materials and methods . The methodological basis of the research is the integration of various types of basic models of business processes within the framework of a structural approach to modeling. The research is based on an analysis of the requirements of professional and educational standards in the subject area under consideration. The systematization and classification of the directions was carried out using a systematic approach to the design of educational technologies, as well as taking into account the requirements of state policy in the field of education. Results . This paper analyzes the current state of visual languages, models, methods, and technologies for business process modeling, which are one of the main areas of business process theory developed at the Institute of Control Sciences of the Russian Academy of Sciences. A corresponding classification of visual modeling languages is proposed. The most frequently used notations and dialects of the languages are highlighted and a comparative analysis is conducted, and the main directions of their development are considered. Basic types of modeling technologies are considered, their advantages and disadvantages are identified. Examples of the most commonly used integration and translational modeling technologies are given. An analysis of the state of affairs in the field of formalizing the syntax and semantics of modern visual languages for business process modeling is presented, existing methods for formalizing syntax and semantics are examined, and proposals for their further development are formulated. An analysis of international, domestic, and corporate standards in this area is carried out, their shortcomings are identified, and a list of necessary work in the field of standardization and unification of visual modeling languages is compiled. The following key areas of languages and methods’ development are highlighted: the transition from business process modeling languages to enterprise modeling languages, the development and advancement of formal modeling languages, the development and research of methods for formally describing the syntax and semantics of modeling languages, and the standardization and unification of modeling languages.In terms of training, professional standards were analyzed in a number of areas, identifying the knowledge necessary for performing work on business process modeling and their reflection in the third-generation higher education standards in the fields of “Applied informatics” and “Business informatics”. Based on the analysis of a number of disciplines within bachelor’s and master’s degree programs dedicated to the issues under consideration, their shortcomings and bottlenecks were identified. To prepare relevant specialists, a set of disciplines and a module structure are proposed, tested by the author both in master’s degree programs at leading Russian universities and in commercial courses. Conclusion . In recent years, interdisciplinary research has developed a new direction related to the unification and formalization of various types of human activity. At the same time, the urgent task is to create a general theory of processes, for which it is proposed to adapt the visual languages, methods and models discussed in this article to various categories of activity.

Modern IT and AI solutions open new opportunities for the digitalization of economic mechanisms, which leads to increased efficiency and contributes to business digital transformation processes. This article presents a methodological approach based on design principles from the “Institutional Analysis and Development” framework, which allows for the design of information processes underlying the coordination and governance functions of economic mechanisms. On this basis, an initial version of a concept for systemic digitalization of economic mechanisms has been developed, including a description of a multi-agent platform in the spirit of massively multiplayer online games, which ensures data collection and integration, analytical modeling, and support for coordination and decision-making in complex organizational-economic systems. The proposed approach to systemic digitalization of mechanisms based on IT/AI solutions represents a development of business informatics methods for optimizing business processes, for designing information systems to support managerial decision-making and digital transformation of companies. Overall for the economy, this promises an increase in the marginal productivity of business process participants, reduction of their losses, enhancement of business adaptive capabilities, and, as a result, an increase in the average efficiency of the economy. Based on the proposed concept, a “social order” for the IT/AI industry has been formed, which defines key needed solutions for mechanisms digitalization with expected high positive socio-economic effect.

A data cooperative is a legally organized cooperative whose purpose is the collective collection, management, and use of data collected by its members. In contrast to other data pools, it can act as a democratic self-governing organization in which each member has a say in how data is collected, shared, and analyzed. The members retain control over the data they contribute. They collectively benefit from the resulting data services, for example, through new insights, innovative services, or economic advantages. As a forward-looking model, the data cooperative enables smaller players to access reliable data infrastructure and data resources that would otherwise remain inaccessible. It promotes data sovereignty and strengthens trust in data-driven cooperation. Here, the definition of data derives from the field of business informatics, which gives a scientifically sound typology of data, systematized on several levels. The following elaboration offers conceptual clarification and presentation of central data types. Depending on the context and processing purpose, their classification is essential for business informatics, as they form the raw material for information systems and business processes. Data cooperatives are gaining in importance as a cooperative form of organization enabling democratic co-determination, community benefit, and equal access to data for regional actors.

Digital transformation increasingly positions business informatics at the core of organisational competitiveness, driving companies to digitalise and automate their business processes. In this context, low-code/no-code (LCNC) platforms have emerged as a promising solution within business information systems, enabling rapid development of process-oriented applications with minimal or no programming. By empowering employees without formal IT backgrounds to participate in system development, LCNC platforms address the shortage of IT professionals and help bridge the gap between technical and domain-specific business knowledge. Although vendors emphasise advantages such as ease of use, accelerated development cycles, reduced costs, lower IT dependency and enhanced process innovation, they often overlook the organisational, technological and governance challenges associated with LCNC adoption. This paper systematically identifies key inhibitors and LCNC implementation through a comprehensive literature review, followed by an assessment of their significance across multiple case studies with LCNC users. Seven major inhibitors are identified: vendor lock-in, security and compliance risks, integration challenges, limited scalability, insufficient documentation, limited testing support, and lack of flexibility. Case study findings indicate that lack of flexibility and customisation, vendor lock-in and insufficient testing support represent the most critical barriers. The paper presents preliminary insights from an ongoing investigation into LCNC development.

Introduction: Electronic payment is a rapidly growing field of modern financial transactions, relying on technologies such as tokenization, multi-factor authentication, and encryption to ensure security. At the same time, legal regulations (EU directives and national laws) provide consumer protection against misuse, while this paper presents conclusions on the development of electronic payments in the local market. Aim: The aim of this paper is, on the one hand, to identify key security technologies that enable the safe execution of digital transactions, and on the other hand, to examine the legal framework and the effectiveness of existing regulations. Materials and Methods: In preparing this paper, the authors used a combination of qualitative and comparative research methods. The analysis of specific platforms is illustrated through a case study (PayPal). The materials include professional literature in the fields of business informatics, finance, and law, as well as applicable legal regulations and European directives. Results: The research has shown that electronic payments offer significant advantages in terms of transaction speed and availability, but also carry risks related to data security and potential misuse. The analysis of the legal framework indicates that PSD2 and GDPR provide a wide range of mechanisms for consumer protection, while domestic laws in the region often lag in their implementation. From a technical perspective, modern platforms apply advanced security measures such as encryption and multi-factor authentication, which significantly reduce the risk of fraud. The analysis of the PayPal platform shows that global services have more developed protection mechanisms and more transparent policies, while local banks only partially comply with these standards. Conclusion: Electronic payment is the foundation of the digital economy, but its sustainability depends on the synergy between legal regulation and technological solutions. The analysis has shown that global platforms lead in applying security technologies and transparent rules, while local systems require additional investments and alignment with international standards.

In today's competitive business landscape, a deep understanding of customer behavior and preferences is crucial for strategic success. Customer segmentation emerges as a vital approach to identify distinct customer subgroups, enabling personalized and efficient marketing strategies. However, many companies still struggle to achieve this understanding due to suboptimal data utilization and inaccurate manual grouping methods. To address these challenges, this research proposes and implements a data mining approach using the K-Means Clustering algorithm for automated and measurable customer segmentation. Leveraging the "Customer Personality Analysis" dataset from Kaggle, this study aims to uncover hidden patterns in customer demographics (age, income, marital status, number of children) and purchasing behavior (number and frequency of transactions). A comprehensive data pre-processing pipeline, including handling missing values, feature engineering, irrelevant column removal, categorical transformation, and numerical scaling, ensures data quality and readiness. Using the Elbow Method, four optimal clusters were identified: "Balanced Spenders with Teenagers" (Cluster 0), "Budget-Conscious Families" (Cluster 1), "High-Value Engaged Buyers" (Cluster 2), and "Active Mature Buyers" (Cluster 3). Visualization using Principal Component Analysis (PCA) further confirms significant characteristic differences between these segments. Cluster 2, being the most valuable and responsive segment, requires premium marketing strategies, while Cluster 1, the largest segment, demands a value-oriented approach. The results of this segmentation provide deep strategic insights, enabling companies to allocate marketing resources more efficiently, craft more relevant messages, and ultimately enhance customer satisfaction and business profitability. These findings demonstrate the potential of unsupervised learning in enhancing data-driven customer profiling systems in marketing and business informatics.

This article presents the results of a study on the prevalence and contributing factors of academic misconduct among students at the Omsk branch of the Financial University under the Government of the Russian Federation. The study involved students from various fields of study: business informatics, public and municipal administration, financial management, finance and credit, and accounting, analysis, and auditing. Using descriptive statistics and comparative analysis of survey data, the authors identified a correlation between the year of study and the level of cheating and analyzed students' perceptions of various measures to prevent academic misconduct. The results indicate a high prevalence of plagiarism and cheating, attributed to factors such as high academic workload, stress, and easy access to ready-made solutions. Based on the findings, recommendations are proposed to improve academic integrity, including the development and implementation of educational programs, enhanced monitoring, and the introduction of strict sanctions for violations. A comprehensive approach combining educational initiatives and strict control is deemed necessary for effectively combating academic misconduct. The study highlights the urgent need for a multi-faceted strategy to address this growing problem within the university setting.

Based on a study of the current state of managerial thought in the Society 4.0 concept and a comparison of the requirements for project management of Society 5.0, the author tries to answer important questions: what is the basis for the forming/changing managerial thought in the context of globalization; what are the roots of the issues of changing the design of thinking and human behavior in the global digital environment of society; where to look for reasons in the errors of business informatics, management features, and unreasonable/unconscious actions of a modern person; how to improve management in business informatics and effectively form the required competencies when training specialists for this sphere of activity in modern conditions of globalized society. These and other relevant issues facing the training system of business informatics and management have been considered, and the issue of the evolution of human culture in the light of project thinking has been reflected. Based on the analysis results, the main aspects of the transformation of managerial thinking of project activities in Society 5.0 have been formulated. The study results show that during the transition from a unipolar world order to a multipolar one, the role of the human-oriented approach in project activities and the importance of forming behavioral competencies of project management specialists increases, and goal setting fundamentally changes.

In the rapidly evolving landscape of information technology, equipping students with practical and industry-relevant skills is essential before they transition into the workforce. This community service program was designed to conduct training initiative to strengthen students’ competencies in information system design. The objective of the program was to enhance participants’ ability to analyze user requirements, model system architectures, and implement structured system design methodologies. Throughout the training, students were introduced to core concepts of system designing such as Data Flow Diagrams, user interface wireframing, and tools related to it. In addition, students gained hands-on experience in using professional tools like draw.io and Figma, which are commonly utilized in system analysis and design processes in real-world IT projects. This training emphasizes the application of structured analysis techniques, logical data modeling, and fundamental software development lifecycle (SDLC) principles. By the end of the program, students demonstrated improved abilities to translate business requirements into technical specifications and were better prepared to engage in entry-level roles or further studies related to software engineering, business informatics, or systems analysis. The initiative highlights the importance of early exposure to system thinking and technical documentation in secondary vocational education, particularly for those pursuing a future in information systems development. The program not only expanded students’ technical knowledge but also encouraged analytical thinking and collaborative problem-solving, which are critical in the field of computer science and information systems

This issue of CSIMQ includes articles that are extended versions of selected papers presented at the workshops of the 23rd International Conference on Perspectives in Business Informatics Research in 2024. The contributions reflect a cross-disciplinary approach, with studies applying conceptual modeling, digital tools, case studies, and surveys to deliver insights into digital transformation and complexity management in modern enterprises. The focus is on small organizations that can adopt solutions traditionally used by larger players to align with global societal goals, such as innovation, performance, ESG requirements. Whether it is about health services, energy management, smart grid optimization, business-IT alignment, all papers emphasize the integration of digital technologies with real-world operations. Global disruptions such as the COVID-19 pandemic, the pursuit of digital transformation, the ongoing demand for innovation, and sustainability imperatives have all intensified the complexity faced by modern organizations. Managing this complexity increasingly requires more sophisticated solutions that integrate digital and physical systems, as well as the alignment of human, technological, and strategic dimensions. Issue 42 of the CSIMQ journal contains articles that illustrate how diverse yet interconnected methodologies can support organizations in navigating digital transformation. These articles exemplify the journal’s commitment to exploring the ways to address complex contemporary challenges.

This article is devoted to the problem of determining the sequence of project implementation in a program of improving business processes of an organization. The relevance of the study is related to current conditions, where the quality of business processes is essential not just for the success, but also for the survival of an organization. Improvement of business processes is a costly program that involves certain projects. The projects of the program cannot be started at the same time due to limited budget and human resources. Thus, we face the task of determining the sequence of stages of program implementations. The solution of this task is one of the most important problems of business informatics. This paper proposes a new criterion for prioritizing projects. It takes into account the fact that funds for projects are generated during the implementation of business processes. The criterion also takes into account the pace of spending the project budget and the need for participation of key employees of the organization. The implementation of the program is divided into a few stages. At each stage, the problem is solved by determining a set of projects whose sum of priorities is maximum and whose resource requirements do not exceed the constraints developed at that stage. The relevance of the article is initiated by looking at the need of enterprises that ensure the airworthiness of civil aviation airplanes. This work is of interest for project program managers of production and service companies, as well as for a wide range of researchers.

Introduction. Successful mastery of the object-oriented modeling methodology of business processes requires students of Business Informatics to invest significant time and effort in practical activities. How do students of this specialty perceive UML activity diagrams? Why do the models they create contain defects that reduce the quality of the diagrams? Does the defects number in the model depend on the education level of its author? The purpose of the study is to find answers to these pressing questions that will help adjust the training of business informaticians in creating activity diagrams and developing their sustainable professional modeling competencies.Materials and methods. A survey of students in the disciplines of object-oriented analysis and design was conducted on the degree of complexity of perception of activity diagrams and the prospects for their further use. The responses of 363 respondents were studied. The pedagogical experiment was carried on a corpus of 124 activity diagrams created by bachelor's and master's degree program students majoring in Business Informatics and related fields. The classification of defects, the search for a relationship between the defects number of different classes, as well as between the complexity measure of the model and the defects number in it were performed out. Statistical and correlation analysis was performed using open source software.Results. Business process models are generally not perceived by students as easy to create and necessary in practical activities. However, future business analysts plan to use them in practice first and foremost. The hypotheses in normality testing of the defects number samples in the models of bachelor's and master's degree program students, including by classes of defects, as well as samples of the complexity measure of these diagrams, were not confirmed. Rank correlation was used, which showed the existence of a statistically significant positive relationship between the defects number of different classes, taking into account the education level of the authors of the models, as well as between the defects number in model and its complexity.Discussion and conclusions. Survey data processing showed that students perceive activity diagrams as a complex type of models, and business informaticians understand their importance in analytical work. Bachelor's and master's degree program students experience similar difficulties when creating business process models. An element of activity diagrams has been identified, which is the main source of defects. Master's degree students with a Bachelor of Business Informatics degree were unable to create defect-free models. This indicates the use of incorrect modeling patterns by substituting the concepts of the analysis stage with the concepts of the information system design stage. Elimination of the identified causes of defects in activity diagrams during the learning process will contribute to improving the quality of the latter and developing the corresponding competencies in students.

This study shares the possibilities of designing ESP practical tasks for teach-ing IT students. The aim of the study is to discover the students’ needs for learning ESP and design new practical tasks closely connected with professional English practical tasks for IT students. Our study consists of phases are accommodating to students’ needs, analyzing the syllabus and manuals for teaching professional English for developing the practical tasks based on the students’ needs in their future job, approving the new practi-cal tasks by the experts. Data is collected using questionnaires and interviews of students and teachers. Participants of the pedagogical experiment are the 2nd and the 3d year stu-dents of «Computing Engineering» and «Business Informatics» educational programs and teachers of ESP from S. Seifullin Kazakh Agro technical Research University. The results contribute that ESP practical tasks have effect on the way IT students learn profes-sional English and the way IT students think. The study information has practical invest-ment for designing materials for ESP. Keywords: analyzing, professional English, , tasks, IT, developing model.

Abstract This study explores recent trends in the adoption of research methods and publication practices within the Business Informatics (Wirtschaftsinformatik, WI) community in German-speaking countries, taking into account the various research paradigms in the Information Systems (IS) discipline. A scientometric analysis of more than 1,800 peer-reviewed journal articles by WI professors from 2010 to 2020 reveals two key findings. First, research methods from positivist, interpretive, and constructivist paradigms have been adopted in a balanced manner, reflecting progress and maturity within the WI community. Second, a trend toward increased publication in international IS journals was observed, with constructivist research notably well represented. These findings indicate a growing presence of the WI community in international IS journals while maintaining methodological diversity.

Purpose Digital transformation is a key factor in the competitiveness of modern businesses. However, the shortage of IT specialists poses a significant challenge. The significant underrepresentation of women in IT-related programmes in higher education further increases the skills shortage and reduces diversity and creativity. Against this background, this study aims to investigate the gender-specific factors influencing the decision to pursue IT-related degrees in the context of business informatics (B-Inf) in Germany to understand why few young women choose this field of study. Design/methodology/approach A quantitative survey was conducted with 186 undergraduate students in Germany. The survey examined the perceptions and priorities of both male and female students when choosing their field of study. Findings The results reveal that women place greater emphasis on job security and societal impact when selecting their field of study, whereas men tend to prioritise interest in technology, personal development and enjoyment of IT-related work. Originality/value Although previous research has focused on computer science programmes, little attention has been paid specifically to B-Inf programmes, which are a distinct discipline combining computer science and business administration. This study contributes new insights into the gender-specific preferences influencing the choice of B-Inf degrees, offering practical implications for increasing female participation and addressing the IT skills gap.

The widespread use of artificial intelligence technologies, data analysis, and their positioning as the foundation for the development of the future economy significantly increases the demand for certain specialists. In this context, it is essential to focus on the methodology for teaching data analysis in universities. The aim of this article is to develop the basis of a taxonomy for creating practical data analysis tasks and to test its applicability. The author examines the main taxonomies of educational tasks, arguing that their limited applicability to the field of data analysis is due to its multidisciplinary and multifaceted nature. A horizontal-vertical taxonomy of educational tasks is proposed, based on three core processes: thinking, communication, and activity. The complexity of tasks is suggested as the key criterion for the vertical part of the taxonomy. Using the topic of “linear regression” as an example, typical tasks corresponding to primary and secondary processes, as well as their intersections, are presented. Specific assignments for Master’s students in the “Business Informatics” program within the course “Computer Data Analysis” using the R language are developed and demonstrated. The need for further research in this area is justified, and a number of questions for future work are posed.

This article is devoted to the problem of theoretical and information support for decision-making in strategic management of raw material procurement processes. The study is timely, because there is currently significant volatility in prices for raw materials. This poses very difficult challenges for managers. Finding solutions is one of the most important areas of business informatics. This article discusses a procurement strategy in two stages: at the beginning and middle of the month. The price of raw materials is known only at the beginning of the month. Price is a continuous random variable. You can predict only the interval of its change. Here the interval is directly used to determine the purchase volume at a known price. The authors derived a functional dependence of the maximum risk according to Savage on the amount of purchased raw materials at the beginning of the month. As a result, it was possible to establish the amount of raw materials to be purchased at the beginning of the month to reduce maximum risk to a minimum. Using the example of corn purchases, we carried out a comparative analysis of possible methods for determining these intervals based on an analysis of price time series. The findings are useful for managers of processing enterprises. This work is the first to solve the problem of minimizing the maximum risk when purchasing raw materials.

Learning management systems store valuable data in their repositories. Analyzing such data could contribute to identifying non-achievers in eLearning courses. This study presents an integrated framework (encompassing stages from a risk management process) to predict non-achievers in eLearning Business Informatics Lab Courses through a discriminant function analysis of student engagement data. In detail, data regarding with student interaction with the learning activities were elicited from the Moodle LMS log files. The paper also presents a specific eLearning Business Informatics Lab Course, designed upon Business Informatics competencies, tailored to a Business Informatics Curriculum for undergraduate Accounting Students. A discriminant function analysis was used to develop a competent prediction model. Linear discriminant functions were generated for achievers and non-achievers respectively. Students were classified into non-achievers or achievers according to the maximum score of the discriminant functions. The high classification percentage of our model indicates that our framework could be used to identify non-achievers in any eLearning Business Informatics Lab course sharing the same structure. A linear discriminant analysis was also employed to indicate the training potential of our model. The evaluation metrics of our trained model indicate that our model could potentially be used to develop an alert system. Received: 12 March 2024 | Revised: 30 May 2024 | Accepted: 10 June 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The data that support the findings of this study will be available to researchers upon demand. Author Contribution Statement Vassilis Zakopoulos: Conceptualization, Formal analysis, Writing - original draft, Writing - review & editing, Supervision. Ioannis Georgakopoulos: Conceptualization, Methodology, Software, Formal analysis, Writing - original draft, Writing - review & editing. Constantinos Dalakouras: Investigation. Panagiotis Dimitrakopoulos: Investigation. Ioannis Liomas: Software, Investigation.