Business Systems Research

Abstract Background: Constant integration of digital technologies in economic and social life is rapidly and significantly shaping and changing our environment and ourselves. To function in such a world, even in daily routines, it is necessary to possess certain digital competencies. Objectives: This paper aims to examine how university and high-school students of economic orientations from selected European countries self-assess their digital competencies, and to analyse the identified differences. This will enable further understanding of university and high-school students’ digital competencies that can serve as guidance for improving teaching practices and curricula. Methods/Approach: A survey was conducted to collect data that were analysed using non-parametric statistic tests (Mann-Whitney U test and Kruskal-Wallis H test) and Spearman Rank-Order Correlation coefficient. Results: University and high-school students consider to have below intermediate level of digital competencies. High-school students self-assessed digital competencies at a higher level than university students. University students of higher years of study self-assessed digital competencies at a higher level. There is no universal pattern among high-school students of different years of study. University students in the Accounting module and high-school students in the Tourism module assessed their digital competencies at the lowest level in several areas. There is a consistency in self-assessment of digital knowledge and digital skills. Conclusions: The identified below intermediate level of digital competencies and discovered discrepancies indicated the need for educational process improvements to provide university and high-school students with a higher degree of digital competencies. Programming is the most lagging behind in all the observed groups.

Dragana Draganac

Danica Jović

Ana Novak

Business Systems Research Journal

Digital Competencies in Selected European Countries among University and High-School Students: Programming is lagging behind

欧洲部分国家大学生和中学生数字能力：编程能力滞后

Abstract Background The milk processing sector in the Republic of Croatia faces numerous challenges. It is a distinctly bipolar structure, with some entities resembling the largest milk producers in the EU, while many small and medium-sized dairy farms struggle to remain competitive and achieve further progress. To formulate effective policy, it is important to differentiate between these types and address their key challenges. Objectives The aim is to find the most representative solution that will help us define typical dairy farms and upgrade a SiTFarm tool (Slovenian Typical Farm Model), enabling us to assess the situation in Croatia comprehensively. Methods/Approach Cluster analysis was conducted using empirical data obtained from the Croatian Agency for Agriculture and Food. The analysis involved applying both hierarchical and non-hierarchical clustering techniques. Results Two cluster analysis scenarios are presented, differing in the variables used. In each scenario, 16 relatively homogeneous clusters of farms were obtained. Diversity was minimized within these clusters, and they effectively explain the dairy business in Croatia. Conclusions The results of this analysis thus represent an important starting point for further analysis of the dairy sector in Croatia. These findings could help policymakers identify the types of farms that would benefit most from targeted investments to enhance efficiency, economic viability, and environmental sustainability.

Maja Petrač

Krunoslav Zmaić

Jaka Žgajnar

Strategic Categorization of Dairy Cow Farms in Croatia using Cluster Analysis

克罗地亚奶牛场战略分类的聚类分析

Abstract This special issue of Business Systems Research (SI of the BSR) is being co-published by the Slovenian Society INFORMATIKA – Section for Operational Research (SSI -SOR). It focuses on recent advances in Operations Research and Management Science (OR / MS), with a particular emphasis on linking OR / MS with other areas of quantitative and qualitative methods in the context of a multidisciplinary framework. The ten papers that were chosen for this Special Issue of the BSR present advancements and new techniques (methodology) in the field of Operations Research (OR), as well as their application in a variety of fields, including risk management, mathematical programming, game theory, gravity, spatial analysis, logistics, circular economy, continuous improvement, sustainability, e-commerce, forecasting, Gaussian processes, linear regression, multi-layer perceptron, and machine learning.

Samo Drobne

Lidija Zadnik Stirn

Berislav Žmuk

Editorial for the Special Issue: "Novel Solutions and Novel Approaches in Operational Research"

特刊社论：“运筹学中的新解决方案与新方法”

Abstract Background It is a well-known phenomenon that nonlinearities that are inherent in the relationship among economic variables negatively affect the commonly used estimators in the econometric models. The nonlinearities cause an instability of the estimated parameters that, in particular, are unable to capture a local relationship between the response and the covariate. Objectives The main aim of the paper is the simultaneous consideration of spatial effects as well as nonlinearities through an advanced semiparametric spatial autoregressive econometric model. The paper seeks to contribute to empirical studies of regional science focused on the application of semiparametric spatial autoregressive econometric models. Methods/Approach We outline an approach that can be used to correct nonlinearities by incorporating a semiparametric idea within the framework of econometric models. We use an expansion by penalised basis splines that are highly flexible and are able to capture local nonlinearities between variables. Results In the empirical study, we fit different econometric models that attempt to explain the dynamics of the European Union's regional unemployment. Conclusions The results show that regional unemployment exhibits significant spatial dependence, indicating interconnectedness among neighbouring regions and suggesting the adoption of a semiparametric spatial autoregressive model for improved modelling flexibility, surpassing traditional parametric approaches.

Andrea Furková

Peter Knížat

Beyond Parametric Bounds: Exploring Regional Unemployment Patterns Using Semiparametric Spatial Autoregression

超越参数边界：利用半参数空间自回归模型探索区域失业模式

Abstract Background This study analyzes education, training, and the youth labor market in central and eastern Europe. Objectives This study aims to evaluate similarities and differences in youth labor markets among eleven central and eastern European countries from 2008 to 2021. It specifically examines three aspects: wage ratios, early departure from education or training, and the share of the population not in employment, education, or training. Methods/Approach This study applies hierarchical clustering and multidimensional scaling to panel data. The complete-link method organizes countries into clusters. This study combines three-dimensional Cartesian projections and two-dimensional projections based on multidimensional scaling with dendrograms and heatmaps, to graphically illustrate the "school-to-work" transition across this region. Results Clustering highlights the Visegrád countries, the Baltics, and the Balkans as zones with internally homogeneous yet externally heterogeneous challenges for the youth generation. As the outliers in each of these regions, Poland, Estonia, and Bulgaria support clustering solutions that deviate from conventional understandings of central and eastern Europe. Conclusions Historical and geographical ties continue to define this region’s youth labor markets across political and economic dimensions. Clustering analysis identifies triumphs and struggles in policymaking in some of the poorest and most politically challenging member-states of the European Union.

Tomislav Korotaj

James Ming Chen

Nataša Kurnoga

School-to-Work Transition in the Youth Labor Market in Central and Eastern Europe: A Cluster Analysis Approach

中欧和东欧青年劳动力市场中从学校到工作的过渡：一种聚类分析方法

Abstract Background Traditional asset pricing models face challenges from financial anomalies, prompting exploration through behavioural finance theory. This study analyses the nuanced relationship between individual investor sentiment and key stock market variables. Objectives To assess the impact of individual investor sentiment on stock returns, volatilities, and trading volumes using the American Association of Individual Investors (AAII) sentiment index. Methods/Approach Using regression models, we examine the relationship between individual investor sentiment and various stock characteristics across 480 components of the Standard &amp; Poor's 500 index. Results We find a positive relationship between the AAII sentiment index and stock returns and a negative relationship with volatility and trading volume. Conclusions Our study contributes to understanding the intricate role of individual investor sentiment in financial markets.

Aleš Kresta

Jialei Xiong

Bahate Maidiya

Sentiment and Stock Characteristics: Comprehensive Study of Individual Investor Influence on Returns, Volatility, and Trading Volumes

情感与股票特征：个体投资者对收益、波动性和交易量影响的全面研究

Abbreviation	Bus. Syst. Res. J.
Journal Impact	1.19
Quartiles(Global)	BUSINESS(Q4)

ISSN	1847-8344, 1847-9375
h-index	15

Publication Information	Publisher: Walter de Gruyter GmbH，Publishing cycle: ，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 2017，Proportion of original research papers: 96.55%，Self Citation Rate:0.00%， Gold OA Rate: 100.00%
Average review cycle	网友分享经验：22 Weeks

Business Systems Research

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Digital Competencies in Selected European Countries among University and High-School Students: Programming is lagging behind

Strategic Categorization of Dairy Cow Farms in Croatia using Cluster Analysis

Editorial for the Special Issue: "Novel Solutions and Novel Approaches in Operational Research"

Beyond Parametric Bounds: Exploring Regional Unemployment Patterns Using Semiparametric Spatial Autoregression

School-to-Work Transition in the Youth Labor Market in Central and Eastern Europe: A Cluster Analysis Approach

Strategic Categorization of Dairy Cow Farms in Croatia using Cluster Analysis

Editorial for the Special Issue: "Novel Solutions and Novel Approaches in Operational Research"

Beyond Parametric Bounds: Exploring Regional Unemployment Patterns Using Semiparametric Spatial Autoregression

School-to-Work Transition in the Youth Labor Market in Central and Eastern Europe: A Cluster Analysis Approach

Sentiment and Stock Characteristics: Comprehensive Study of Individual Investor Influence on Returns, Volatility, and Trading Volumes