Business Systems Research : International journal of the Society for Advancing Innovation and Research in Economy

Vol 15 No 2 (2024) Special Issue in Novel Solutions and Novel Approaches in Operational Research

Editor-In-Chief — 2024-10-03

Special Issue in Novel Solutions and Novel Approaches in Operational Research

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

Samo Drobne — 2024-10-03

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.

The Impact of a New Container Port on the Greenhouse Gas Pollution

David Bogataj — 2024-10-03

Background: Large vessels that call at European ports will have to pay for their CO2 emissions from transporting cargo that enters or goes from a European port since January 2024. The costs will increase with increasing global trade. This results in a higher pollution level, including greenhouse gas (GHG) emissions like CO2. Methods/ Approach: Based on the gravity model embedded in a global supply chain, we developed a model to evaluate maritime transport pollution in case a new, sufficiently large container port becomes operational. Additionally, we consider how lousy railway connections to European customers increase transportation costs and pollution. Results: The approach to the well-connected sequences of gravity models in the intercontinental maritime chains evaluates the differences in quantities of cargo between ports when a new port is opened, and the waiting time does not change. We also highlight that poor rail connections can reduce this positive effect. Conclusions: We showed how it is possible to estimate the optimal capacity of a new port with a multi-level gravity model and how this would affect the pollution around the port and on the routes from the port to the final consumers.

Selection Procedure of the Approximation Methods for Deriving Priorities: A Case of Inconsistent Pairwise Comparisons

Vesna Čančer — 2024-10-03

Background: When pairwise comparisons are used to express preferences for alternatives or judgments on criteria's importance, several methods can be used to derive priorities in multi-criteria decision-making. In the case of inconsistency, different methods give different results. Objectives: The main goal of this paper is to present the procedure of measuring the accuracy of the selected approximation methods based on pairwise comparisons compared to the priorities obtained by the eigenvalue method. It also aims to illustrate the procedure on the numerical example characterised by acceptable inconsistency. Methods/Approach: The presented procedure is based on a prescriptive approach, the fixed ratio scale, reciprocal pairwise comparison matrices, and consistency ratio. Mean absolute deviation and mean absolute percentage deviation are used to measure accuracy. Results: The first result is the theoretical statement of the priorities’ accuracy measurement procedure. The results of the numerical example characterised by the preferences of strength slight to strong plus show that, on average, the most accurate approximation method is the geometric mean method. Conclusions: The research contributes to the literature on prescriptive approaches to decision-making. The results can show potential users which approximation method to use and lecturers which of them to include in the curriculum portfolio.

Design of Social Infrastructure and Services Taking into Account Internal Migration by Age Cohort

Samo Drobne — 2024-10-03

Background: European cities and regions are facing depopulation and an ageing population, leading to a shift in the demand and supply of goods and giving rise to the silver economy. This demographic change has an impact on urban and regional planning, which is influenced by both internal and external migration. Objectives: Based on the hypothesis that the attractiveness of locations also depends on the age of the inhabitants, the paper investigates the gravitational effects on the intensity of migration flows by age cohorts. Methods/Approach: This study examines how factors that influence the retention or attraction of people towards specific areas affect migration between age groups at different hierarchical spatial levels, using the gravity model implemented at the Slovenian spatial levels NUTS 2 and NUTS 3. Results: Distance is least important for the 65-74 age group, while wages influence only the youngest cohorts. The capacity of care homes has a significant influence on the attractiveness of older cohorts to move between NUTS 2 regions. There is a high correlation between the factors at the municipal and NUTS 3 levels for the population aged 75+. The factors at NUTS 2 and NUTS 3 levels show a strong correlation for those under 65. Conclusions: These results can form a basis for the development of the silver economy as they show the need for adapted infrastructures and services for older adults. As the age structure is changing, authorities should adapt infrastructures and services to the different levels of central places/regions. The growing number of older people makes research into optimal solutions for long-term care a crucial factor for the silver economy.

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

Andrea Furková — 2024-10-03

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.

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

Aleš Kresta — 2024-10-03

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 & 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.

Age Management Practices and Benefits in Organisation: An Evaluation of the Effect of Economic Sector, Organisation Size, and Family Business Status

Terezie Krestová — 2024-10-03

Background: The ageing of the population impacts all areas and is also a challenge for human resources management. To solve this issue, age management practices are used in organisations. To get the best potential out of everyone, this concept should not only involve older employees but should be focused on all of them. Choosing the right practice to get the desired results is a task for managers. Objectives: The paper aims to determine whether the sector of the economy, the size of the organisation, or the family business status plays a role in determining age management practices and observed benefits. Methods/Approach: Using a questionnaire survey, the most commonly used practices and the observed benefits were identified. Using the chi-square test, differences in chosen categories were confirmed. Results: It can be stated that choosing age management practices is influenced by the economic sector, and the size of the organisation influences observed benefits. Conclusions: The results can guide organisations on which practices to choose and what benefits to expect from implementing age management practices.

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

Tomislav Korotaj — 2024-10-03

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.

Strategic Categorization of Dairy Cow Farms in Croatia using Cluster Analysis

Maja Petrač — 2024-10-03

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.

Estimating Asymmetric Fuel Price Responses in Croatia

Karol Szomolányi — 2024-10-03

Background: According to many studies, the transmission of oil prices to retail fuel prices is asymmetric. Fuel prices react faster if oil prices rise and more slowly if oil prices fall. Different standard econometric procedures lead to different results. The Linex approach, which is based on formulating the non-linear adjustment cost function, reflects the theory. It uses the generalised method of moments to estimate the reaction functions, which demands many observations. Objectives: The paper investigates the price asymmetry in the Croatian retail fuel market using standard approaches and the Linex approach. Methods/Approach: The simple and dynamic asymmetry models, error correction models, threshold autoregressive co-integration, and the Linex approach are used to verify the hypothesis of asymmetric reactions of gasoline and diesel prices in Croatia. Results The results using the standard methods are mixed, while the Linex approach indicates price asymmetry, the size of which is measured with the average price bias. The results correspond to other studies worldwide. Conclusions The authors' preferred Linex approach detects price asymmetries, even with large data samples with frequent changes in trends and volatilities. According to the approach, the question is not whether prices are formed asymmetrically but the size of the asymmetry.

Decision-Making Model to Support Agricultural Policies in Realizing Economic and Social Sustainability

Jaka Žgajnar — 2024-10-03

Background: Achieving economic and social sustainability is the goal of any policy when defining measures. We focus on the beef sector, where many challenges have arisen due to its structural characteristics, such as an unfavourable scale structure, high costs, low efficiency, and a low environmental footprint. This paper presents an example of the support provided by a mathematical programming model in the development of a Common Agricultural Policy Strategic Plan for the period 2023-2027. Methods/approach: It is a model based on linear programming that allows such an ex-ante analysis by calculating production plans at the farm level and aggregating the results at the sector level. Objectives: When defining the interventions, the question arose as to what the reform of the Common Agricultural Policy will bring and to what extent the sector should be supported in meeting these challenges. These were the concerns of agricultural policy that we sought to support by modelling different scenarios. Results: The results show that the situation of the sector will worsen, especially for larger farms, but they also show the great importance of production-related payments to mitigate the negative trend. Conclusions: The applied approach proves to be suitable for supporting the design of agricultural policy and achieving greater economic and social sustainability in the sector.