ISBN online: 978-80-7509-990-7 | DOI: 10.11118/978-80-7509-990-7
26th Annual International Conference Economic Competitiveness and Sustainability 2024
21.–22. 3. 2024 Mendel University in Brno
- Petr David (Ed.), Hana Vránová (Ed.)
On March 21st and 22nd, 2024, the Faculty of Business and Economics of Mendel University in Brno organized already the 26th international conference “Economic Competitiveness and Sustainability“ with over 70 onsite participants from the Czech Republic, Slovakia, Germany, Poland, Hungary, Ukraine, Norway, Serbia and USA. In the presented Proceedings you find 21 papers which were recommended by conference discussants and selected on the basis of a peer-review process. The presented research outputs contribute to and extend the current state of knowledge and will stimulate further debate not only in academia but also in other institutions of public and private sector. The submitted papers reacts on the current interdisciplinary problems arising in the areas of Economic Policy, Public Finance and Public Administration, Enterprise Information Systems and Technologies, Digital Transformation and Sustainability, Marketing and Management and Finance.
online: 2024, publisher: Mendel University in Brno
 |
Conference papers
OPEN-SOURCE COMPLIANCE: A TACTICAL APPROACH
Ashish Bakshi, Andreas Kotulla, Oldřich Faldík, Oldřich Trenz
DOI: 10.11118/978-80-7509-990-7-0008
As open source becomes increasingly prevalent, understanding the intricacies of various license types, including permissive and copyleft licenses, becomes essential for developers and organizations alike (Tourani, Adams and Serebrenik, 2017). This paper not only explores these license types but also examines the implications of copyright laws and Export Control Compliance (ECC) on open-source software. A significant portion of the paper is dedicated to evaluating key tools used in open-source compliance, such as SW360, FOSSology, OSS Review Toolkit (ORT), and Software Bill of Materials (SBOM). In this paper, a comprehensive analysis of open-source license compliance offers practical insights and recommendations for developers and organizations navigating the complexities of open-source software adoption. The specific contribution of this paper lies in providing a detailed comparative analysis of these tools, alongside a case study on their application in real-time audits.
PERFORMANCE COMPARISON OF HTTP/3 SERVER IMPLEMENTATIONS
Jiří Balej, Tomáš Sochor
DOI: 10.11118/978-80-7509-990-7-0017
The paper opens the question of comparison published open-source webservers with support of HTTP/3. This is brand new protocol standardised in 2022 was developed with aim to speed up web communication and instead of TCP uses UDP with new QUIC protocol. There is summarized current state of HTTP protocols development and studies, where is compared performance of various HTTP versions. The aim of paper is to compare different open-source webserver implementations with HTTP/3 support in laboratory. Five different scenarios were presented to test ordinary real-life situations. The results of all three servers with different content and HTTP/1.1 or HTTP/3 protocols are presented. Main result would be better performance of Caddy and nginx server in bad connection conditions, but without speed limit, large delay or loss the OpenLiteSpeed was fastest.
NATURE OF INTERNAL COMMUNICATION AMONG E-WORKERS, CASE STUDY
Michal Beňo, Jan Kříž, Dagmar Cagáňová, Zuzana Cagáňová
DOI: 10.11118/978-80-7509-990-7-0024
Research background: COVID-19 pandemic caused a rapid shift to full-time remote work environment. Workforce productivity, engagement, and success are affected by how the company interacts with its workforce. Human-to-human connection without clear communication is impossible. Communication is essential for a stable, engaged company. In e-work environment even more. Purpose of the article: The purpose of this study is to provide recommendations for improving the flow of information and stregthen the sense of community among real e-employees in a remote work environment. Methods: a quantitative study (web-based survey) in a Greek multicultural company has been used. Authors tried to find answers to following research questions: How do e-employees perceive internal communication methods in their organization? Which of the internal communication channels were used most effectively? Findings & Value added: Based on the crea ted questionnaire, a total of 7 hypotheses were determined, all of which were statistically confirmed. Obtained data confirms the raising importance of internal communication, especially in times of crisis as employees considered as a homogenous. We can underline the sample based in Greece but located various European countries and in a context of unprecedented crisis. English as predominant spoken language. Finally, this research only explores the role of internal communication in an organizational context (formal, casual, organized, or unplanned). The survey was conducted during pandemics and has some interesting implications for communication professionals and researchers in the field of internal communication. The present study examines internal communication in e-working settings. Previous studies have excluded the situation for e-employees. The results provide new insights into internal communication behaviour in e-work.
FOREIGN TRADE OF WINE AND FRESH GRAPES IN THE VISEGRAD COUNTRIES
Katarína Bírová, Patrik Rovný
DOI: 10.11118/978-80-7509-990-7-0036
The Visegrad countired, as countries of a single grouping that have pledged to help each other and to deepen their trade with each other. These are the countries of the Slovak Republic, the Czech Republic, Hungary and Poland. The main objective of the article is to identify the overall level of trade of the Visegrad countries in the commodity wine and fresh grapes concerning the World, the Visegrad countries as a whole and the individual countries of the Visegrad country. The analysis shall take into account the monetary clarification of trade volumes in millions of euros. The commodity structure is based on the international HS system. The main analysis is carried out through the basic indicators of turnover, trade balance and RCA (Revealed Comparative Advantage). Hungary has a comparative advantage in the wine trade at the World level but also within the Visegrad countries. The Slovak Republic has both comparative advantages and comparative disadvantages within the World and the Visegrad countries, but most of all with the Czech Republic and Poland. The Czech Republic showed comparative advantages only with Poland. Poland has no comparative advantages with any of the Visegrad countries.
PROTECT YOURSELF FROM AI HALLUCINATIONS: EXPLORING ORIGINSAND BEST PRACTICES
Jana Dannhoferová, Petr Jedlička
DOI: 10.11118/978-80-7509-990-7-0049
Although AI-powered chat systems like ChatGPT can be trusted, we shouldn’t rely on them completely. They can sometimes produce irrelevant, misleading or even false responses, known as hallucination effects. The causes can be both systemic and user related. User behavior, particularly in the area of prompt engineering, has an impact on the quality and accuracy of the result provided. Based on the literature review, we have identified the most common types of hallucination effects and provided examples in created categories. Finally, we have highlighted what users should consider when writing prompts and given recommendations for them to minimize hallucination effects in responses obtained from AI systems. Understanding how hallucinations occur can help ensure that these powerful tools are used responsibly and effectively. However, the quality of responses is always a matter of judgment, and the user’s level of expertise and critical thinking is an important factor.
THE USABILITY OF ALGORITHMS FROM GRAPH THEORY IN THE FIELD OF MULTICRITERIA ANALYSIS
Radim Farana
DOI: 10.11118/978-80-7509-990-7-0060
The main ideas, on how to use algorithms from the Graph Theory to improve the process of Multicriteria Analysis were presented in the paper (Farana, 2016). This paper presents practical results obtained by the use of these algorithms in practical decision-making procedures when multicriteria analysis has been used. Graph algorithms were used in two situations when determining the values of the weights of decision criteria. First was the checking, if the Fuller’s triangle, filled in by an expert, is filled in correctly. For this verification, a complete graph is used in which the vertices represent the criteria the orientation of the edges their mutual significance. A method of gluing vertices could be used for criteria with the same significance. The resulting graph must be acyclic. Twenty-five decision tasks with seven or more criteria were analyzed and the obtained results will be presented in the paper. The second application was the elimination of the overdetermination of the assessment in Saaty’s method. A spanning tree describing dependencies between criteria has been used according to the algorithm in (Farana, 2016). Obtained results were compared with the full Saaty’s matrix when the number of compared pairs of criteria is k – 1 for k criteria, compared to the number of k(k – 1)/2 in the classic Saaty’s method. Fifteen decision tasks with seven or more criteria were analyzed and the obtained results will be presented in the paper. The paper presents the differences between the assessment given directly by experts and the assessment obtained using the spanning tree and shows that the described method is applicable in practice. The experience of experts using the proposed procedure, obtained through a guided interview, was mostly positive.
DIFFERENT INSIGHT INTO THE VAT GAP USING MIMIC MODEL
Iva Hasíková
DOI: 10.11118/978-80-7509-990-7-0065
The paper focuses on the estimation of the MIMIC model for quantification of VAT gap. MIMIC model is a specific type of structural equation models, which treats the VAT gap as a latent unmeasurable variable whose emergence and size are influenced by causes and whose presence is reflected in indicators; causes and indicators must be measurable. The contribution of this model is identification of causes of VAT gap, that are potential sources of VAT collection inefficiencies. The MIMIC model was built on data from selected European countries and according to the model VAT gap has these significant causes: openness of economy, corruption perception index, general government expenditure, final consumption and e-government development index. Developed using data from European countries, the model can be applied on each of these countries for quantification of VAT gap. These outputs can support the recommendations leading to improved efficiency of VAT collection.
SMART OCCUPANCY DETECTOR FOR MODEL RAILROAD
Jan Horáček, Jiří Rybička
DOI: 10.11118/978-80-7509-990-7-0075
For control of a model railway, simple track occupancy detectors are in use to detect the presence and absence of a vehicle on the track. However, these detectors do not use the full potential of a digital command control (DCC) system. A RailCom technology allows information to be obtained from the ve- hicle’s DCC decoder, thus the detector can receive operationally important data from the rolling stock vehicle. The subject of the paper is the description of requirements and design of an own RailCom detec- tor MTB-RC, which presents an alternative to commercially available model railway RailCom detectors. MTB-RC is an open-source and open-hardware project, which is also compatible with the rest of the trackside hardware used in the Track Vehicle Control Laboratory FBE MENDELU. MTB-RC can read the addresses of the DCC decoders present on the track and transmit them to the railway control software via MTBbus.
USE OF ANNOTATED IMAGE DATA FOR FRUIT DIVERSITY ANALYSIS
Miroslav Jaroš, Jiří Podivín, Petr Pernes, Oldřich Trenz
DOI: 10.11118/978-80-7509-990-7-0084
This paper deals with a method of development of an annotated image dataset for the detection and classification of plant tissues, aimed at supporting automation in agriculture. The work includes a collection of high-definition image data, their annotation and utility scripts, with the aim of creating a universally accessible dataset for the scientific community. The method is designed to be compatible with off-the-shelf hardware, in order to better support research and development in the field of automated plant identification and plant disease diagnostics. This approach has the potential to significantly improve the efficiency of cultivation processes and support the implementation of advanced technologies in the agricultural sector, along with the automation of this sector.
ADAPTIVE DATACENTER MONITORING BASED ON THE LORAWAN NETWORK INFRASTRUCTURE
Andrej Juríčka, Jiří Balej
DOI: 10.11118/978-80-7509-990-7-0093
High availability and quick response to abnormal situations are the key aspects for a reliable datacenter. Cooperation between physical environment monitoring and high-level cluster / container orchestration could increase the overall durability of the entire system. This paper describes the proposal of an entry-level monitoring system based on the LoRaWAN network infrastructure from a physical point of view to the application point of view. All components are open-source use, without any additional license cost. Compared to typical monitoring applications, the cost-effective and main advantage lies in the interconnection solution for a large datacenter environment. The entire system consists of well-known technologies and applications interconnected via reliable protocols, with the addition of environment-specific rulesets. Based on these preferences, the management of systems such as virtualization or container orchestration systems can be more flawless and energy efficient.
EVOLVING LANDSCAPE OF ARTIFICIAL INTELLIGENCE IN GEORGIA
Nadia Mtchedlidze, Zuzana Papulová
DOI: 10.11118/978-80-7509-990-7-0099
The current paper provides a detailed evaluation of Artificial Intelligence (AI) adoption in Georgia, identifying the opportunities and challenges within political, economic, social, technological, legal, and environmental contexts. We developed a novel theoretical framework to characterize AI stakeholders and used an Autoregressive Distributed Lag (ARDL) model to investigate how AI influences macroeconomic indicators like high-technology exports. The findings indicate significant positive short-term and long-term impacts of R&D expenditure on high-technology exports, with ICT goods exports also contributing positively over time. In contrast, real GDP negatively affects these exports, suggesting the need for policy adjustments to support AI implementation. The study highlights the importance of strengthening policy frameworks and promoting digital education to enhance AI integration in Georgia’s digital strategy.
BEHAVIORAL EXPERIMENTS IN PUBLIC SECTOR
Mária Murray Svidroňová, Nikoleta Jakuš Muthová
DOI: 10.11118/978-80-7509-990-7-0111
In this paper we present preliminary results of a research project aimed at mapping the preferences of young people in the areas of public sector such as housing, employment and commuting. To do so we will employ methods of behavioral economics and experiments. First of all, we did a bibliometric analysis of studies dealing with behavioral experiments in the selected areas to reveal a gap for future research. We focused on a time period of 2010–2023. For mapping we used VosViewer and data from the Web of Science database. Results indicate that even there are some experiments done in the areas of housing, employment or commuting, there is no methodology based on behavioral economics to reveal the preferences of young people in these areas.
MICROCONTROLLERS SUITABLE FOR ARTIFICIAL INTELLIGENCE
Petr Pernes, Miroslav Jaroš, Jiří Podivín, Oldřich Trenz
DOI: 10.11118/978-80-7509-990-7-0120
Artificial intelligence (AI) has become increasingly prevalent in various applications, from self-driving cars to facial recognition. However, the implementation of AI on resource-constrained devices such as microcontrollers has been a challenge due to the limited computational power and memory. In recent years, advances in AI technology and the development of specialized hardware have enabled the realization of AI on microcontrollers. This opens new opportunities for AI applications in domains such as embedded systems, the Internet of Things (IoT), and wearable devices. This article provides an overview of microcontrollers suitable for AI, discusses their benefits and challenges, presents a methodology for selecting suitable microcontrollers for AI applications, and highlights the criteria essential for effective implementation. Additionally, initial results from applying this methodology, including a comparative analysis of various microcontrollers, are discussed. Key findings emphasize the potential of specific microcontrollers like ARM Cortex-M7, Arm Ethos-U55, STMicroelectronics STM32F429, and Espressif ESP32-S3/C3 in AI applications. Future directions for the evolution of AI-enabled microcontrollers are also explored.
ANALYTICAL PLATFORM
Jan Přichystal, Roman Valovič
DOI: 10.11118/978-80-7509-990-7-0127
The Analytical Platform is an online platform that simplifies work of analytical department, front-office, back-office and compliance for investment firms. It is using an artificial intelligence, data analytics and machine learning in finance and investments. Analytical Platform helps investment funds, securities traders and professional investors gain higher alpha, and lower beta and get flawless records of investment decisions. It offers various specialized tools and services in a flexible and personalized way to fit investor’s needs. This article presents the components of the platform, the technologies used for the development and approaches for sentiment analysis and summarization of financial articles as a source of key information for decision support.
A LITERATURE REVIEW OF BUSINESS PERFORMANCE MEASUREMENT
Nikola Sobotková
DOI: 10.11118/978-80-7509-990-7-0137
The paper is aimed at a critical review of the literature dealing with the measurement of business performance. Because, nowadays the importance of implementing modern and effective management methods to maintain competitive advantage in almost all business sectors is emphasised, given the increasing competitive pressure. The measurement of business performance is also an important aspect of management and decision-making in organisations. Various indicators are currently being investigated to show the importance of modern approaches and effective measurement systems. This paper aims to identify a list of these modern methods, their bottlenecks and point out the possibility of introducing new and better indicators for performance measurement. The aim of this work is thus to create a critical review of the literature, especially about the latest findings of research articles on the selected topic. The purpose of this article is then to point out the limits of the current state of literature in the field of modern methods to measure business performance and highlight possible research gaps arising from the review in this area.
HOW DOES A COUNTRY’S LEVEL OF ECONOMIC DEVELOPMENT INFLUENCE DIGITAL ADVANCEMENT? EVIDENCE FROM EUROPEAN COUNTRIES
Anđelka Stojanović, Isidora Milošević, Sanela Arsić
DOI: 10.11118/978-80-7509-990-7-0148
Recent years have brought numerous challenges to Europe and the world in the form of a complex geopolitical situation, threats to the safety and health of the population, deepening economic differences, and a lack of natural resources. Dealing with some of the challenges mentioned above is carried out through digitization and the development of the single market. The European Commission enacted numerous documents and implemented a series of activities aimed at strengthening the European digital market. Actions and policies aim to support digitization to increase economic activity and achieve other social benefits such as empowerment of people, solidarity and sustainability. Due to unequal initial levels of development and the readiness of states, companies and individuals for the changes brought by information technologies, a digital divide emerged. The main research question in this paper is whether the achieved level of economic development conditions the level of digitization. It also examines which elements in the digital transformation can be most influenced to reduce the digital divide. Structural equation modeling (SEM) is applied to answer the research question. The importance of the results is reflected in the fact that by confirming the connections between the digital level and economic parameters, the direction of influence on the reduction of digital divides and the fulfillment of globally set goals related to social equality can be defined.
MOBILE AUGMENTED REALITY OBJECT DETECTION APPLICATION
Jan Strnad, Jaromír Landa
DOI: 10.11118/978-80-7509-990-7-0159
This article proposes a Mobile Augmented Reality (MAR) application for object detection. The application can detect predefined objects in the camera stream and display infor- mation about them. Object detection poses many challenges, and a common approach is to perform it remotely on a server. However, this requires an active internet connection. Alternatively,detection can be performed locally using a model stored on the device.How- ever, not all devices have the capability to perform real-time detection. We have created a Mobile Augmented Reality app that can detect objects in the camera stream. The app can perform detection locally or remotely, depending on the device’s configuration. Sec- ondly, the app’s ability to perform detection locally or remotely makes it versatile. The paper has two main contributions. Firstly, the proposed application architecture can be applied to any similar MAR app. The application was tested on multiple Android devices to determine the minimum configuration required for local object detection.
COMPARATIVE ANALYSIS OF SELECTED TIME SERIES FORECASTING APPROACHES FOR INDIAN MARKETS
Ankit Tripathi, Arpit Tripathi, Oldřich Trenz, Pawan Kumar Mishra
DOI: 10.11118/978-80-7509-990-7-0167
Financial market analysis and prediction have been topics of interest to traders and investors for decades. This study assesses the performance of selected time series prediction methods like deep learning algorithms (Long short-term memory model (LSTM)), traditional statistical models (Seasonal Auto Regressive Integrated Moving Approach with eXogenous regressors (SARIMAX)), and advanced ensemble learning algorithms (XGBoost and FB-Prophet) using real-world data from the Indian financial market. The stock prices of Reliance Company serve as a case study, enabling a thorough evaluation of predictive accuracy and errors of the models. A pre-processing approach has been proposed and implemented, integrating significant economic factors (Gold Price, USD to INR conversion, Consumer Price Index (CPI), Wholesale Price Index (WPI) and Indian 10-year yield bond) and evaluated with technical metrics (Mean squared error, Mean Absolute Error and R2 Score). The study investigates how the inclusion of these factors impacts prediction accuracy across the selected time series prediction methods. The comparative evaluation of models before and after the pre-processing method sheds light on the evolving predictive accuracy of LSTM, SARIMAX, FB-Prophet, and XGBoost. The study showed that the SARIMAX (extension of ARIMA with seasonality and exogenous factors) and XGBOOST performed relatively well with the proposed approach while LSTM and FB prophet (though advanced) did not perform as expected in Indian financial markets. This research contributes to advancing the understanding of time series forecasting in the financial market of India, offering practical insights for decision-makers and researchers.
DIGITIZATION OF THE METHODOLOGY FOR ASSESSING THE SUSTAINABILITY OF PLANT PRODUCTION SYSTEMS
Pavel Turčínek, Vojtěch Krejsa
DOI: 10.11118/978-80-7509-990-7-0187
This contribution describes how a web application was created based on the given methodology for assessing the sustain-ability of plant production systems. The key indicators of this methodology are introduced. The way of transformation into digital form is shown. The outputs of the created application are presented.
SURVEY OF LARGE LANGUAGE MODELS ON THE TEXT GENERATION TASK
Michaela Veselá, Oldřich Trenz
DOI: 10.11118/978-80-7509-990-7-0195
This paper focuses on the comparison of GPT, GPT-2, XLNet, T5 models on text generation tasks. None of the autoencoder models are included in the comparison ranking due to their unsuitability for text generation tasks. The comparison of the models was performed using the BERT-score metric, which calculates precision, recall and F1 values for each sentence. The median was used to obtain the final results from this metric. A preprocessed dataset of empathetic dialogues was used to test the models, which is presented in this paper and compared with other datasets containing dialogues in English. The tested models were only pre-trained and there was no fine-tune on the dataset used for testing. The transformers library from Hugging face and the Python language were used to test the models. The research showed on the pre-trained dataset empathic dialogues has the highest precision model T5, recall and F1 has the highest precision model GPT-2.
ENHANCING MICRO-CREDENTIALS WITH BLOCKCHAIN
Martin Záklasník, Veronika Konečná, Oldřich Faldík, Oldřich Trenz, Andrej Gono
DOI: 10.11118/978-80-7509-990-7-0201
The article addresses the problem of using micro-credentials in the educational process and explores the possibilities of their deployment through blockchain technology. The topic of micro-credentials as the first step in the process of digitalization of the educational process is presented along with the setting of its trustworthiness. A variety of advantages can be associated with micro-credentials, including the confirmation of individual transactions at the level of the educational process. One of the main problems in the centralized storage of micro-credentials is the risk of unauthorized access and the possibility of leakage of sensitive information. This paper proposes the implementation of blockchain technology as a way to decentralize data storage. This would eliminate the threat of unauthorized access and provide a higher level of data security and integrity. Challenges associated with a centralized certificate authority such as scalability issues and outages are also discussed. It can be evaluated that blockchain can provide a robust and reliable framework for digitizing certificates in the education sector. The conclusions of the paper highlight the benefits of decentralization through blockchain and the need to open up the certification network for corporate certificates. Overall, the paper discusses the importance and benefits of using blockchain technology to enhance the security and efficiency of digital certificates in the education sector.