Research on Enterprise in Modern Economy

ARTIFICIAL INTELLIGENCE ADOPTION CHALLENGES IN THE SMALL AND MEDIUM-SIZED ENTERPRISE SECTOR: A COMPARATIVE ANALYSIS OF POLAND, GERMANY AND DENMARK

2025-12-23T06:37:39+01:00

Background and Objective: Recognising the vital role of SMEs in driving economic growth and the uneven AI adoption levels across EU countries, this article explores AI adoption within SMEs in Poland, Germany and Denmark, highlighting the barriers they face. The study aims to enhance understanding of the factors that hinder SMEs from adopting AI technology. Recognising and addressing these challenges is essential for SMEs to succeed.

Materials and Methods: The study compares AI adoption in the SME sectors of Poland, Germany and Denmark within the EU context, focusing on the barriers and challenges. The article synthesises cross-country evidence from prior empirical studies and statistics drawn from Eurostat databases and the Digital Economy and Society Index.

Results: Internal capabilities are the strongest predictors of AI adoption, and environmental support is helpful only when institutions are mature. Barriers typically cluster, with varying intensity, around data availability and quality, skills gaps, costs, integration with legacy systems, privacy, and cultural resistance. The article consolidates scattered EU evidence into an accessible benchmark and offers country-specific recommendations to boost SME AI adoption.

Practical implications: The article provides insights that can support entrepreneurs in successfully integrating AI technologies. It is also helpful for policymakers to promote AI adoption, thereby boosting the competitiveness of small and medium-sized enterprises.

Conclusion and summary: The gap in AI adoption is closely linked to the overall level of digitalisation, and limited digital infrastructure in the economy hampers the deployment of AI solutions in the SME sector. AI programmes for small and medium-sized enterprises need to be tailored to each country’s level of adoption.

CREATIVE ACCOUNTING PRACTICES AND THEIR ROLE IN COMPANY FAILURES

2025-12-23T06:44:11+01:00

Background and Objective: Creative accounting refers to the manipulation of accounting standards and practices in ways that remain technically legal but distort the true financial position of a firm. While such practices may temporarily enhance a company’s financial image, they often erode transparency, mislead investors, and increase systemic risks.

Study Design/Materials and Methods: This paper examines the nature of creative accounting, its advantages and disadvantages, and its role in major corporate scandals, including Enron, Parmalat, Satyam, Toshiba, Lehman Brothers, and others. Through a qualitative case study approach, the research explores the mechanisms by which creative accounting evolves into fraud and corporate collapse.

Results: The case study analysis revealed that despite short-term benefits of creative accounting, it contributes to large bankruptcies and destabilises financial markets.

Practical implications: The findings suggest that while creative accounting provides short-term benefits such as increased valuations and capital inflows, it ultimately undermines corporate credibility, contributes to large-scale bankruptcies, and destabilises financial markets.

Conclusion and summary: The paper concludes by highlighting preventive measures, including stricter auditing practices, enhanced corporate governance, whistleblower protection, and forensic accounting techniques.

INFORMATION SOURCES AND RECOMMENDATION CHANNELS INFLUENCING PATIENTS’ CHOICES OF WOMEN’S PHYSIOTHERAPY CLINICS: A CASE STUDY OF THE OSTEO KOBIETA CLINIC

2025-12-23T06:52:18+01:00

Background and Objectives: When choosing a healthcare provider, female patients rely on a variety of information sources and recommendation channels. With ongoing digitalisation, online reviews and educational content on social media are becoming increasingly important. This study aimed to analyse sources of information about the private Osteo Kobieta clinic in Gdynia, and identify factors influencing patients’ choices of women’s physiotherapy services.

Study Design and Methods: A cross-sectional study was conducted from January to June 2025 during the registration of the patients’ first visit. A paper-based survey was completed by 550 women aged 23–70 years. The questionnaire addressed information sources (friend recommendations, physician referrals, online reviews, social media) and assessed the perceived credibility of each channel using a five-point Likert scale.

Results: The most common information source was recommendations from friends (49%), followed by gynaecologist referrals (23%). Google Maps reviews were important (12%), especially among younger patients. Social media content played a supporting role, with over half of respondents declaring that it builds trust in the clinic. The credibility ratings were noted for physician referrals (mean rating 4.7/5) and friend recommendations (4.5/5).

Practical Implications: The findings highlight the need to combine relationship marketing based on personal and physician referrals with a professional digital presence. Educational content on social media enhances transparency, the credibility of services, and the authority of specialists.

Conclusions and Summary: The study confirms that personal and physician recommendations are key drivers of patients’ decisions, while digital sources play a complementary role in strengthening confidence and supporting the choice of healthcare providers. The results provide a basis for further analysis of the role of social media content in healthcare marketing and its impact on patients’ decision-making across age groups.

MODELLING THE PRICE FORMATION PROCESS FOR GREEN ENERGY TO ACHIEVE CLIMATE NEUTRALITY

2025-12-23T06:57:46+01:00

Background and Objective: This paper investigates the process of setting tariffs in green energy under conditions of instability, aiming to ensure financial sustainability, attract investments, and achieve climate neutrality. The objective is to develop a comprehensive model that accounts for economic, social, political, technological and environmental factors influencing the formation of tariffs in the renewable energy sector.

Study Design/Materials and Methods: A multi-stage methodological approach is proposed, incorporating quantitative and qualitative indicators into composite indices. The study includes a literature review on tariff formation, dynamic pricing, and sustainability factors. The Harrington scale is applied to assess the management level of tariff formation under varying degrees of instability.

Results: The findings reveal that a higher level of management in tariff formation correlates with increased renewable energy production. The model underscores the significance of adaptive strategies to address economic, political, social, technological and ecological uncertainties, leading to the stable growth of green energy generation.

Practical Implications: The proposed composite index can be integrated into administrative and monitoring systems, enabling policymakers and energy market stakeholders to adjust tariffs promptly and adopt appropriate strategies such as stable, flexible, investment-oriented, crisis and participatory management to maintain market stability and foster sustainable energy development.

Conclusion and Summary: Regular monitoring and timely adjustments of tariff formation models are essential for mitigating risks posed by external uncertainties. The recommended framework facilitates comprehensive assessment and strategic decision-making, ultimately supporting climate neutrality goals and sustainable development in the green energy sector.

STATISTICAL MEASURES OF THE OUTPUT GAP DISTRIBUTION AMONG EUROPEAN COUNTRIES IN THE YEARS 2000–2019

2025-12-23T10:30:18+01:00

Background and Objective: The concept of full capacity utilisation is central in macroeconomic theory and economic policy. One of the most employed variables is the output gap, which shows the gap between real and potential production. The aim of the paper is a statistical analysis of the output gap for 27 European countries in the years 2000–2019, and to investigate the distribution of the output gap.

Study Design/Materials and Methods: Annual output gap data (AMECO database) are analysed for 27 European countries during the period 2000–2019 (540 observations). Statistical measures such as mean, median, standard deviation, kurtosis and skewness are used.

Results: A statistical analysis of the whole sample reveals an almost symmetrical distribution of the output gap for the analysed countries and period. Investigation of particular country cases indicates a more complex picture.

Practical implications: Results suggest that the output gap, which is partially the outcome of economic policies conducted by fiscal and monetary authorities, occurs with almost equal frequency below and above full capacity utilisation.

Conclusion and summary: Output gaps in European countries occur with almost equal frequency, but the situation among countries and periods is more complex. Some waves of business cycles when output gaps in most of the analysed countries change simultaneously are also indicated.