Business Informatics Research Articles

An optimal raw material procurement strategy that minimizes enterprise price risks

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.

A Framework to Identify Non-Achievers in eLearning Business Informatics Lab Courses

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 (LDA) 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.

Building passports in their role as building information systems - background, framework, implications

Abstract Building-related information is essential for performing tasks and making decisions in the design, construction, and management of buildings as well as in transactions. This is increasingly recognized by actors of the real estate industry and by policy makers. As a result, there is a renewed interest in information management solutions and, in particular, building information systems (BISs) with an interface character for multiple tools, such as building passports (BPs) and digital building logbooks (DBLs). Gradually, a better understanding of their main goals and functionalities is evolving due to initiatives in politics, academia, and the real estate industry. However, for wider adoption, a sufficient level of common characteristics regarding the functions, covered data categories, and technical foundations is crucial. Therefore, an information system architecture (ISA) for BPs is proposed that builds upon basics of research on building-related information management and BISs. In addition, selected references are made to insights from business informatics, as this has only marginally been done in traditional approaches of the real estate industry. The ISA provides a holistic view on the relevant elements of a BP and thus serves as a basis for further developments, standardization, and harmonization. The findings are used to discuss practical implications not only for BP design, but also for their use. The authors conclude that the foundation is laid for BPs to become a very useful tool for the transformation of the building stock to support a sustainable development.

Optimising Educational Outcomes: Data and Process Analysis Approaches with Attention to Self-Directed Learning

The swift advancements in technology and the corresponding job market impose increasingly challenging and dynamic requirements on workers. This is a significant obstacle for higher education institutions in adequately preparing their students for contemporary expectations and equipping them to tackle future difficulties. Today's students are "digital natives", and they distinctly absorb knowledge and employ new strategies to learn compared to earlier generations. Hence, it is of utmost significance for higher education institutions to comprehend the student learning process. Learning management systems (LMS) can offer substantial assistance in this endeavor, as they facilitate comprehension of students' learning process, while log files also offer unbiased insights into individual adaptation. This study aims to investigate the learning mechanisms of Business Informatics students at Corvinus University of Budapest by analyzing Moodle's educational data. The objective of the study was to acquire a more comprehensive understanding of the learning patterns exhibited by students in higher education through the utilization of an extensive collection of log files. The central idea revolved around examining the behavioral, motivational, and interest-related dimensions of learning as indicators of self-directed learning. These were examined using two primary methodologies: data analysis and process analysis. The findings indicate that distinct learning patterns exist regarding data and learning processes. Additionally, there are variations in time management and information consumption habits. The results of this study have practical implications for identifying learning patterns and developing tailored interventions to enhance educational achievements.

Neuroenhancement and mental health in students from four faculties - a cross-sectional questionnaire study.

Students face great challenges at the beginning of and during their studies. Competitive experience, exam anxiety, and especially the new performance requirements often cause test anxiety and stressful experiences. The extent of substance use in terms of neuroenhancement (NE) is unclear. Evidence shows associations between NE, increased stress levels, and mental health. We aim to determine the prevalence of NE and alcohol and tobacco use among college students. We also investigate the associations between NE and ADHD, anxiety, depression, and stress experience. In spring 2021, an anonymous online cross-sectional survey was conducted among students of medicine, dentistry, business economics, and business informatics in Würzburg. The survey included the instruments ASRS (ADHD), PSS-10 (stress), PHQ-4 (depression and anxiety), and AUDIT-C (alcohol comsumption), as well as questions about consumption patterns, prior knowledge, and reasons for NE. Of the 5564 students who were invited to participate, 1010 completed the questionnaire (18.2%). Of these, 12.4% indicated NE for the studied period. NE was used in particular during preparations for exams, to enhance performance, and/or to regulate emotions, most commonly through caffeine tablets, cannabis, and methylphenidate. NE was associated with risky use of alcohol or tobacco, and to a lesser extent with ADHD symptoms and stress experience.Conclusions: Students are at risk of substance abuse and NE. Effective stress management and prevention approaches as well as low-threshold services are needed to identify and support students with risk profiles.

The impact of educational technologies on learning outcomes in higher business education

The paper examines the impact of alternative ways of teaching and the use of various educational technologies on students? performance. Our survey was conducted on a sample of actively enrolled students of Business Informatics at the Faculty of Economics, University of Belgrade, in December 2022. Our results suggest that utilisation of communication and learning platforms (Viber, WhatsApp, Facebook, Moodle and course sites), although widely accepted and favoured by students, has no significant impact on their performance. Students? performance was measured by their average grades and the share of passed examinations in the total number of attended courses (i.e., success rate). We have found evidence that students? performance can be related to the teaching approach. Furthermore, attending classes online worsens students? chances of improving their average grade and their success rate in business informatics courses. On the other hand, the data suggests that students? chances of improving their total average grade improve if they attend classes online.

Smart Sustainable Marketing and Emerging Technologies: Evidence from the Greek Business Market

In the market-shaping literature, markets are viewed as the results of intentional and planned acts. Market shapers do not often create technology themselves despite the fact that technical advancements can hasten changes in smart sustainable marketing. This study assessed the development of emerging technologies in business informatics with a focus on smart sustainable marketing and its relevant emerging technologies. Data were collected using an online questionnaire from 320 marketing professionals in Greece. The study revealed that emerging technologies have a significant relationship with smart sustainable marketing. Drivers of smart sustainable marketing positively enhance the effectiveness of smart sustainable marketing, and innovations in business informatics have a positive effect on smart sustainable marketing. It is clear from our results that the area of emerging technologies and smart sustainable marketing has not received much attention since such developments depend on complementary technologies that make it possible for emerging methods or technologies to integrate resources and co-create value. This study conceptually distinguishes between technology as a market offering and technology as a business platform for market shaping and innovation. Managers in the business industry and elsewhere are urged by this research to more closely examine the development of ancillary technologies, which could serve as platforms for market innovation and market shaping. Discovering and taking advantage of these opportunities is crucial for success in smart sustainable marketing. This study also presents a significant addition to the academic community because of the empirical evidence on the relationships between business informatics, smart sustainable marketing, and new technology. In terms of technology, it expands the theoretical framework of market dynamics and offers a novel perspective on the ways in which technology influences the structure and sustainability of markets.

Professional training in the digital economy development: experience of training students of I. N. Ulianov Chuvash State University to work with "1C:ERP Enterprise Management"

In the context of the modernization of the education system in Russia and the shortage of personnel in the IT industry, there is an urgent need to graduate competent specialists, which is the direct task of universities, as well as to constantly improve their professional IT competencies and retain specialists in the regions, which becomes the task of regular cooperation between universities and employers.Close attention of employers is paid to university graduates who have experience in working with ERP systems designed to automate the company’s business processes. In the situation of import substitution, the greatest demand among enterprises is for domestic ERP systems, among which the leading position is occupied by “1C:ERP Enterprise Management”. Studying this software product at university becomes the key to success in finding a job.The peculiarities of training qualified IT personnel by teaching “1C:ERP Enterprise Management” at the I. N. Ulianov Chuvash State University are considered the example of two bachelor’s degree programs — “Economics” and “Business Informatics”. The sequence of students’ and teachers’ work with “1C” software products, types of disciplines, and modules is presented. The use of cloud technologies gives students free access to 1C educational materials, free connection to 1C information bases, and teachers — a convenient way tocontrol the work of students.

Robotprogramozás oktatásának lehetőségei offline és online környezetben

In the spring of 2020, the Covid-19 pandemic situation put everyone in a particularly difficult situation in all areas of life. Those working in education had to implement their courses online overnight, which until then had been mostly, or even exclusively, offline in the classroom. This challenge also put colleagues teaching robot programming in a difficult situation. At the Károly Róbert Campus and its predecessor institutions, we have been dealing with students studying information technology for almost a decade and a half. We teach subjects related to robotics as optional subjects in the Business Informatics BSc course launched in 2010, and as compulsory subjects in the higher education program for Computer Science running since 2019. In our study, we compare the robotics education implemented in the higher education program for Computer Science in an online and offline environment. We present in detail how the subjects „Methodological Basics of Programming” (first semester) and „Basics of Robotics” (third semester) were implemented before (offline) and during (online) the Covid-19 pandemic. At the end of our investigations, we make conclusions and suggestions about the most important actions after the end of the epidemic situation, how we can prepare with our subjects taught for the situation, if everyday life and the educational environment were to change similarly drastically.

ATTITUDES OF PROFESSIONAL NURSE DEGREE STUDENTS ON THE ROLE OF PROFESSIONAL NURSES IN THE HEALTHCARE TEAM

Background: The unique role of a nurse is to assist an individual, sick or healthy, in performing activities that contribute to health or recovery (or a peaceful death), which the individual would perform independently if they had the necessary strength, will, or knowledge. Virginia Henderson (1897–1996) A nurse today, apart from possessing professional knowledge and skills, must be an emotionally mature and stable person in order to be able to understand and deal with human suffering, emergencies, health problems, and ethical dilemmas. She should be ready to accept responsibility and work independently and in a team. Nurses have an important role in solving public health problems. They provide safe, high-quality, effective, and efficient health services, which makes this profession particularly important for the protection and improvement of people's health. Aim: To examine the attitudes and opinions of students about the role of a nurse as a mandatory member of the health team, the satisfaction of the position, and the respectability of the nurse profession in Serbia. Material and Methods: The research was conducted as a cross-sectional study over a period of 2 months. The research was conducted electronically, and the sample consisted of 95 students majoring in professional nursing at the Preschool Teacher Training and Business Informatics College of Applied Studies “Sirmium” and the Preschool Teacher Training and Medical College “Mihailo Palov” in Vršac, students of different genders and ages who actively attended studies at the time of questioning. Results: Most of the surveyed students were female, 85%, while the other 15% were male. Out of the total number of surveyed students, 46.4% do not agree at all or mostly agree with the statement that other members of the team value professional nurses. The majority of students agree with the statement that continuous education is necessary (83.4%). The largest number of students agree with the statement that the job of a professional nurse is as responsible as the job of other members of the healthcare team (92.5%). The opinion of the majority of students is that the job of a professional nurse is more valued abroad than in Serbia (87.5%). Conclusion: Based on the results of the research, we can conclude that there is a prevailing dissatisfaction among students with the position of professional nurse in the health team. Students believe that the job of a professional nurse is just as responsible as the job of other members of the health team, and the continuous education of the nursing staff would contribute to the respectability and adequate position of the nursing profession in Serbia.

Design of a Machine Learning Model to Predict Student Attrition

Higher education institutions are facing a major issue with student dropout rates, which is a global phenomenon that affects a significant portion of enrolled students, particularly those in their first year. The challenge is how to retain students who do not meet requirements during their first year and are at high risk of dropping out, which can have significant economic and social consequences as well as personal ramifications for the students themselves. Universities must prioritize identifying at-risk students and providing targeted assistance to prevent them from leaving the system. Machine learning (ML) models have proven effective in identifying students at risk of dropping out with a high degree of accuracy. In this study, we aim to construct a machine learning model using data extracted from the administration system (Neptun) to predict student dropout rates in the Business Informatics BSc course at the Faculty of Finance and Accounting of Budapest Business School.

Enterprise Evolution: A Discussion from Different Perspectives. Editorial Introduction to Issue 34 of CSIMQ

The current issue provides discussions on different topics that can be summarized as “Enterprise Evolution”. The selected articles continue and elaborate research that was presented in 2022 during workshops at the Perspectives in Business Informatics Research Conference – BIR 2022 in Rostock, Germany. The articles continue the research work presented at the conference, summarize the findings and provide deeper insights and new perspectives. The articles report on research results regarding ethical, social, and environmental accounting; support for post-merger information systems integration; enterprise architecture for inclusion of demand-responsive services in the overall enterprise architecture of transportation companies; and possibilities of SMEs to use robotic solutions for enhancing their processes.

Academic Debt in Higher Education: An Analysis of the Causes and Opportunities to Overcome

Academic debt can cause a significant damage to the Russian economics and the higher education system in the medium term (on the horizon of 5–10 years). The purpose of the study is to identify the key problems based on the results of a comprehensive empirical analysis of the situation of the formation of massive academic debt (using the example of the “Business Informatics” direction at a Russian university) and to substantiate ways to improve the activities of universities in order to overcome them and reduce students’ academic dept. Research methods are general scientific (deduction, induction, generalization, comparative analysis, etc.), as well as special ones (correlation and regression, statistical, sociological surveys, etc.). Analytics and visualization of quantitative data were carried out using MS PowerBI software. Research results. It was revealed that: a) high incoming scores do not guarantee trouble-free education at the university; b) students with low scores (but not less than 160–170) are also able to master quite complicated university programs; c) the presence of academic debts does not depend on the type of disciplines studied (economics / information technology). The number of student dropouts in the studied sample (up to 50% of those who entered with a non-linear dependence on the total USE scores) testifies to the presence of reasons that are not related to the incoming educational potential of students. The results of the study made it possible to structure them into three groups: insufficient motivation, self-organization problems, and “incomplete maturation”. Five groups of students have been identified with an increased risk of accumulating academic debt. The article substantiates the use of indirect educational influence on the students through a special mobile application.

Defining the Metaverse: A Systematic Literature Review

The term Metaverse is emerging as a result of the late push by multinational technology conglomerates and a recent surge of interest in Web 3.0, Blockchain, NFT, and Cryptocurrencies. From a scientific point of view, there is no definite consensus on what the Metaverse will be like. This paper collects, analyzes, and synthesizes scientific definitions and the accompanying major characteristics of the Metaverse using the methodology of a Systematic Literature Review (SLR). Two revised definitions for the Metaverse are presented, both condensing the key attributes, where the first one is rather simplistic holistic describing “a three-dimensional online environment in which users represented by avatars interact with each other in virtual spaces decoupled from the real physical world”. In contrast, the second definition is specified in a more detailed manner in the paper and further discussed. These comprehensive definitions offer specialized and general scholars an application within and beyond the scientific context of the system science, information system science, computer science, and business informatics, by also introducing open research challenges. Furthermore, an outlook on the social, economic, and technical implications is given, and the preconditions that are necessary for a successful implementation are discussed.

Mathematical Management – Operations Research in the United States and Western Europe, 1945 – 1990

The rise of Operations Research, which provides mathematical models for the management of commercial enterprises, in the political knowledge culture of Cold War Science is shown and then transferred to the institutionalization of Operations Research in Europe and in the Federal Republic of Germany. The predecessor organizations of the German Society for Operations Research are presented and the interaction of the annual conference of this society with the conferences on a European and worldwide level. It tells how numerous chairs for corporate research and operations research were founded at universities between 1960 and 1980. The connection between Operations Research and the macroeconomic field of econometrics in chairs, conferences and publications is explained and problematized. The great flood of publications on the subject of Operations Research between 1960 and 1980 is referred to, but the rise of the competing field of business informatics in the 1980s halted the success of Operations Research. Based on the historical study by Alexander Nützenadel, the difference between the field of econometrics, which is based on empirical data, and the field of operations research, which is more academically oriented, is worked out. The methodological approach of Operations Research is referred to as abstractification. An example for abstractification is the transport model of linear optimization, which simplifies (abstractifies) economic reality to such an extent that it can be transformed into manageable formulas. However, the transport model is unsuitable for applications in the real economy and thus serves only as a self-referential project for the academic sector. This contribution shows that Operations Research lacks the level of empirical implementation of mathematical models known from econometrics and the social sciences. How transport optimization was taken up in the political knowledge cultures of the Eastern bloc (1945 – 1990) and in the German Democratic Republic is dealt with in a section.

Review of the Monograph “The Monetary System of Russia: Formation through Reforms”

The review considers a collective monograph edited by M. N. Konyagina, dedicated to the history of the formation of the modern domestic monetary system, the beginning of which comes from the reign of the young Ivan the Terrible. The theme of the book today is relevant not only in the context of improving the financial literacy of citizens, the formation of knowledge among students acquiring an economic specialty, but also to demonstrate the fact that the Russian ruble has repeatedly been stable, and the domestic monetary system has outpaced the European ones at certain historical stages. The publication discusses the structure of the publication, highlights particularly interesting developments, emphasizes the contribution of the co-authors not only to the monograph itself, but also to the development of thematic areas, which is confirmed by numerous published works by them. The reviewer gives an overall high positive assessment of the reviewed work, as well as recommendations for further deepening the subject under study.The author of the review is convinced that the book will be useful for students of the educational fields “Economics”, “Management”, “Business Informatics”, “State and Municipal Administration”, teachers, business representatives in the field of financial intermediation, as well as a wide range of readers for understanding economic processes in the difficult history of Russia.

Predicting Master’s students’ academic performance: an empirical study in Germany

The tremendous growth in electronic educational data creates the need to have meaningful information extracted from it. Educational Data Mining (EDM) is an exciting research area that can reveal valuable knowledge from educational databases. This knowledge can be used for many purposes, including identifying dropouts or weak students who need special attention and discovering extraordinary students who can be offered lifetime opportunities. Although former studies in EDM used an extensive range of features for predicting students’ academic achievement (in terms of (i) achieved grades or (ii) passing and failing), those features are sometimes not obtainable for practical usage, and therefore, the prediction models are not feasible for employment. This study uses data mining (DM) algorithms to predict the academic performance of master’ s students by using a non-extensive data set and including only the features that are easy to collect at the beginning of a studying program. To perform this study, we have collected over 700 students' records from 2010 to 2018 from the Faculty of Business Informatics and Mathematics at the University of Mannheim in Germany. Those records include demographics and post-enrollment features such as semester grades. The empirical results show the following: (i) the most significant features for predicting students' academic achievements are the students’ grades in each semester (importance rate between 14 and 36%), followed by the distance from students’ accommodation to university (importance rate between 6 and 18%) and culture (importance rate between 7 and 17%). On the other hand, gender, age, the numbers of failed courses, and the number of registered and unregistered exams per semester are less significant for the predictions. (ii) As expected, predictions performed after the second semester is more accurate than those performed after the first semester. (iii) Unsurprisingly, models that predict two classes yield better results than those that predict three. (iv) Random Forest classifier performs the best in all prediction models (0.77–0.94 accuracy), and using oversampling methods to deal with imbalanced data can significantly improve the performance of DM methods. For future work, we recommend testing the predictive models on other master programs and a larger datasets. Furthermore, we recommend investigating other oversampling approaches.

Development and Validation of a Critical Thinking Assessment-Scale Short Form

This study presents and validates the psychometric characteristics of a short form of the Critical Thinking Self-assessment Scale (CTSAS). The original CTSAS was composed of six subscales representing the six components of Facione’s conceptualisation of critical thinking. The CTSAS short form kept the same structures and reduced the number of items from 115 in the original version, to 60. The CTSAS short form was tested with a sample of 531 higher education students from five countries (Germany, Greece, Lithuania, Romania, and Portugal) enrolled in different disciplinary fields (Business Informatics, Teacher Education, English as a Foreign Language, Business and Economics, and Veterinary Medicine). The confirmatory analysis was used to test the new instrument reliability, internal consistency, and construct validity. Both the models that hypothesized the six factors to be correlated and to tap into a second-order factor representing the complex concept of critical thinking, had acceptable fit to the data. The instrument showed strong internal consistency (α = 0.969) and strong positive correlations between skills and between the skills and the overall scale (p < 0.05). Despite the unbalanced sex distribution in the population (close to 75% females), the instrument retained its factorial structure invariance across sexes. Therefore, the new instrument shows adequate goodness of fit and retained stability and reliability, and is proposed as a valid and reliable means to evaluate and monitor critical thinking in university students.

ASPIRING EARLY CHILDHOOD TEACHERS’ SELF-PERCEPTION OF THEIR COMPETENCE IN THE INTEGRATION OF DIGITAL TECHNOLOGIES INTO EARLY CHILDHOOD EDUCATIONAL PRACTICE

The aim of this research is to consider the differences in aspiring early childhood teachers’ self-perception of their competence in the integration of digital technologies into early childhood educational practice, before and after the realization of the teaching process, and before and after passing the exam for the elective course titled “An early childhood teacher in a digital environment”. The research sample consisted of thirty-five third-year students of the Preschool Teacher Training and Business Informatics College of Applied Studies - Sirmium, who took and passed the exam in the elective subject “An early childhood teacher in a digital environment”. The results of the study show that aspiring early childhood teachers assess their competence for the integration of digital technologies into early childhood educational practice more positively after attending classes and taking the exam in the course “An early childhood teacher in a digital environment”. Future early childhood teachers feel more competent in applying digital technologies to all four areas of early childhood teachers’ work: direct work with children, real program development, professional development and professional public action.

Post hoc identification of student groups: Combining user modeling with cluster analysis.

This study aims to discover groups of students enrolled in the emergency remote teaching online course based on the various course-related data collected throughout the first year of COVID-19 pandemic. Research was conducted among 222 students enrolled in the course "Business Informatics" at the Faculty of Organization and Informatics of the University of Zagreb in the academic year 2020/2021. Overlays were used to model students' success on the various quizzes and exams within the course. The k-means clustering was employed to classify students into groups, based on combination of students' overlay values, frequency of accessing course lessons and the final grades. Three distinct clusters (i.e., students' groups) were discovered and explained in the given context. The identified groups of students can be used for future adaptations of the online course design in order to improve the retention and their final grades.