Erstida Ulvidienė

To improve the marketing activity and brand management and justify the most effective marketing decisions, organizations should implement different information technologies, mathematical methods and models into the marketing decision support system (MDSS). The goal of this paper is to form an architecture of an MDSS, the model base of which is developed on Data Science tools, in particular regression analysis and machine learning methods. The proposed MDSS is a multi-agent information system comprising nine intellectual agents (market environment monitoring, data processing, marketing mix modeling, price policy support, portfolio management, strategic analysis, forecasting, customer segmentation, and customer classification). The functionality of these agents is realized through Data Science, which allows for the optimization of marketing activities (e.g., an effective brand management strategy and its elements (portfolio strategy, price policy, and media strategy) or solving the problems of attracting new and retaining current customers with the maximal return on marketing investments). The MDSS analyzes the marketing environment, media activity, and business indicators by constructing different models and forecasting various combinations of marketing factors to select the best one. The joint work of MDSS agents provides decision-makers with interactive reports. The research findings offer a scientific basis for making effective marketing decisions based on data, and the proposed MDSS can become part of an intelligent system for planning marketing activities.

The paper examines the transparency of public finances, with a specific focus on the transparency of Ukraine’s defense budget. The relevance of this study arises from the ongoing war and the increasing public demand for accountability. The study aims to identify concrete measures to address existing gaps in defense budget transparency. The paper applies a comparative methodology, analyzing the feasibility of implementing Scandinavian transparency practices, particularly from Sweden and Norway, which are known for their advanced budgetary oversight mechanisms.
The study identifies key challenges, including bureaucratic inertia, limited technical capacity, political constraints, and national security concerns. To address these issues, the paper evaluates strategies such as developing digital budget platforms for real-time access to defense expenditures, participatory budgeting, and enhanced institutional accountability. The results indicate that Ukraine could benefit from secure digital platforms for real-time access to defense budget data, targeted legislative amendments to improve oversight, strengthened institutional capacity for in-depth budget reviews, and public consultations on non-sensitive areas of defense spending to foster public trust.
The findings suggest that gradual and context-sensitive improvements in defense budget transparency are both feasible and essential for optimizing resource allocation and strengthening public confidence. By providing a structured approach, this study contributes to the broader discourse on public finance transparency, offering practical recommendations tailored to Ukraine’s specific challenges.

Type of the article: Research Article

Abstract
This study examines the relationship between the Kaitz index (a measure of the minimum wage relative to median earnings) and the size of the shadow economy across selected European countries. The analysis uses Eurostat official statistics for 2018–2022 (panel data). Research investigates whether higher minimum wages, as reflected in the Kaitz index, contribute to labor market distortions, informal employment, and tax evasion. To quantify the shadow economy, we employ the Multiple Indicators Multiple Causes (MIMIC) approach, a method widely used in empirical studies of the shadow economy. The shadow economy level is calculated as the proportion of hidden value added relative to GDP. The results reveal that increases in both the Kaitz index and GDP growth are significantly linked with reductions in the shadow economy, while previous levels of informality contribute to its persistence. These insights highlight the potential of minimum wage regulation and sustained economic growth as tools for reducing informal employment, particularly when supported by strong institutional enforcement. The results indicate a statistically significant relationship between the Kaitz index and the shadow economy share, highlighting implications for wage and labor market policy.