Svitlana Bilan
57211968274
Publications - 7
Emotion-based insights into pro-environmental video campaigns: A study on waste sorting behavior in Ukraine
Publication Name: Environmental Economics
Publication Date: 2025-01-01
Volume: 16
Issue: 2
Page Range: 50-72
Description:
This study aims to examine how different types of pro-environmental video content (featuring humans versus AI-generated characters) influence household waste sorting attitudes and behaviors among Ukrainian residents. The research was conducted in two stages using a mixed-method approach. In the first stage, 102 individuals aged 18-45 watched two videos on waste sorting and completed an online questionnaire. Cluster and variance analyses were performed using Statistica software. In the second stage, 35 participants underwent a laboratory-based emotion analysis using iMotions software, heart rate monitors, and galvanic skin response sensors at the Behavioral Lab of Sumy State University (Ukraine) from May to July 2024. The results revealed that videos featuring real people were more effective in generating interest (average rating: 3.5 vs. 3.2) and emotional engagement, particularly joy and contempt, which were the most frequently expressed emotions. Cluster analysis identified four distinct respondent groups. Cluster 1 (39.2%) - primarily young women - responded positively to human-led videos but showed limited behavioral change. Cluster 2 (19.6%) - women aged 26-35 - reacted positively to both videos and were most willing to adopt waste sorting behavior. Cluster 3 (23.5%) - primarily men - showed moderate engagement and sorted waste occasionally. Cluster 4 (17.6%) - highly educated women - exhibited the least positive responses and were least likely to change their behavior. The emotion analysis confirmed that videos featuring real people elicited stronger emotional responses across all categories, whereas AI-generated videos prompted higher levels of anger but generally weaker engagement.
Open Access: Yes
Policy priorities for improving Global Innovation Index score and innovative performance in upper-middle-income countries: Implications for Armenia
Publication Name: Problems and Perspectives in Management
Publication Date: 2025-01-01
Volume: 23
Issue: 1
Page Range: 569-583
Description:
As an upper-middle-income country, Armenia should develop and implement targeted policies, such as increased R&D investments, education reforms, and industry-academia collaboration, to enhance its innovation performance. Strengthening these areas is expected to contribute to higher Global Innovation Index (GII) rankings, reflecting improved national innovation capacity. This study aims to estimate the impact of various GII components (including pillars, sub-indices, and sub-pillars) on the overall GII and pillar scores for upper-middle-income countries. Based on these findings, the study seeks to identify Armenia’s key policy priorities and provide targeted recommendations for enhancing its innovation performance. This study employs a cross-sectional regression to analyze the factors influencing GII scores in upper-middle-income countries, assessing the impact of sub-indices, pillars, and sub-pillars. The analysis reveals that market sophistication and creative outputs strongly influence GII scores among upper-middle-income countries, contributing significantly to national innovation performance. Additionally, knowledge and technology outputs, human capital and research, and infrastructure pillars show a statistically significant impact at the 5% level. Notably, even minor improvements in innovation output sub-index scores account for substantial variations in GII rankings. These findings suggest that Armenia should prioritize targeted education reforms, increase R&D investment, and strengthen university-industry linkages to enhance its innovation ecosystem and improve its global competitiveness.
Open Access: Yes
REGIONAL DISPARITIES AND DUAL DYNAMICS: ECONOMIC GROWTH AND INCOME INEQUALITY IN KAZAKHSTAN
Publication Name: Economics and Sociology
Publication Date: 2024-01-01
Volume: 17
Issue: 2
Page Range: 241-255
Description:
This study examines the complex relationships between economic growth and income inequality in different regions of Kazakhstan, revealing the nuances of their interaction. The article aims to assess the long-term and short-term effects of economic growth on income inequality in both forward and reverse directions across the regions of Kazakhstan. Employing region-specific time series data allowed us to examine the bidirectional impact of economic growth on inequality, using an error correction model (ECM) to describe short-run and long-run relationships. The results highlight that the relationship between economic growth and income inequality is heterogeneous across regions, reflecting each area's unique economic and social landscapes. The estimation results support the hypothesis of an inverted U-shaped Kuznets curve linking GRP per capita to inequality with varying starting points for different regions. Regarding the inverse relationship, we identified a positive causal relationship for the West Kazakhstan, Zhambyl and Pavlodar regions, indicating that increased income inequality stimulated economic growth. The study also highlights the significant role of trade, labour force, investment and government consumption in shaping these relationships.
Open Access: Yes
Relationship between work-family conflict and emotional exhaustion in health care workers: Mediating role of self-efficacy and stress perception
Publication Name: Journal of International Studies
Publication Date: 2024-01-01
Volume: 17
Issue: 4
Page Range: 163-178
Description:
This study examines the mediating role of self-efficacy and stress perception in the relationship between work-family conflict and emotional exhaustion in healthcare workers. The study's primary purpose is to reveal the effect of work-family conflict on the emotional exhaustion levels of healthcare workers and to understand how individual factors such as self-efficacy and stress perception affect this process. The study's central question is, “Is there a significant relationship between work-family conflict and emotional exhaustion, and what role do self-efficacy and stress perception play in this relationship?” The study was designed as a cross-sectional design with a quantitative approach. The study sample consisted of 313 healthcare workers working in public and private hospitals in Turkey. The data were determined using the convenience sampling method. The data were analysed using structural equation modeling (SEM) to examine direct and indirect relationships between variables. According to the analysis results, a significant and positive relationship was found between work-family conflict and emotional burnout. It was determined that the perception of stress strengthened this relationship, while the perception of self-efficacy weakened it. While the work-family conflict was observed to cause less burnout in individuals with high self-efficacy levels, it was determined that emotional burnout levels increased even more in individuals with a high perception of stress. These findings emphasize the effect of individual factors on the professional and personal balance of healthcare professionals. This study confirms the adverse effects of work-family conflict on the emotional burnout levels of healthcare professionals. The research findings show that self-efficacy is a protective factor, while perception of stress is a risk factor. Increasing self-efficacy is critical in ensuring work-family balance and reducing the risk of emotional burnout in healthcare professionals. These results indicate that institutional strategies should be developed to reduce the emotional burnout levels of employees in the healthcare sector. Additionally, flexible working hours and family-friendly policies are recommended to reduce work-family conflict.
Open Access: Yes
SOCIAL EXPENDITURE MULTIPLIER: ASSESSMENT OF ECONOMIC EFFECT AND OPTIMAL VALUES
Publication Name: Economics and Sociology
Publication Date: 2024-01-01
Volume: 17
Issue: 1
Page Range: 182-195
Description:
The main aim of the study is to test the hypothesis that social expenditures are not only a source of social support and budgeting of the social sphere, but can be a significant lever of economic development, provided proper planning of their share and volume. In this regard, the authors have adapted the open-economy multiplier to assess the economic effect of social expenditures. Based on the correlation analysis of the relationship between the share of social expenditures (% of GDP) and the multiplier of social expenditures, conducted on the example of EU countries, two groups of countries are identified depending on the impact of social expenditure multiplier on GDP: the first one embraces those countries that are characterized by a growing economic return from social expenditures; the second one is where the return is declining. To determine the optimal levels of social expenditures, which can be expected to have a positive economic effect in the form of GDP growth, we have identified critical limits of the multiplier of social expenditures according to the principle: the maximum value is seen in the group of countries with positive impact; the minimal one is experienced in countries with inverse dependence of the share of social expenditures and their multiplier. As a result, the experience of financing social expenditures in the EU leads to the conclusion that the optimal share of social expenditures in GDP ranges from 28% to 30% – within these limits multiplier values exceed 1.0, i.e. there is a positive impact of social expenditures on GDP in the form of the growth of economic results over the resources consumed.
Open Access: Yes
Assessing the impact of artificial intelligence on project efficiency enhancement
Publication Name: Knowledge and Performance Management
Publication Date: 2024-01-01
Volume: 8
Issue: 2
Page Range: 109-126
Description:
The study explores the impact of artificial intelligence (AI) technologies on project management (PM) across different industries. It aims to assess how AI adoption in PM affects project efficiency. The study surveyed 159 project supervisors and specific project managers implementing projects from 7 industries in the Republic of Kazakhstan: software, green energy, engineering, construction, science, transport, and tourism. The research used variance and linear regression analyses to evaluate the relationship between AI adoption and project efficiency level measured by the Likert scale from 1 to 5 and test the associated hypotheses. The results show that AI adoption varies among industries, with software, construction, and scientific projects being the most active users. The study also found that the use of AI differed across eight project performance domains, with the stakeholder domain using voice technologies and process automation and the uncertainty domain using fewer tools. Projects with higher AI adoption rates showed higher efficiency scores (for example, in Software projects, the AI adoption rate is 3.2; the efficiency rate is 3.3), while those with lower efficiency levels (for example, in the Tourism industry, the AI adoption rate is 1.9; the efficiency rate is 2.2) showed the worst results. Decision-making systems, process automation, and voice technologies are the three most critical AI technologies PM professionals use to improve project efficiency.
Open Access: Yes
“Tourist attitudes towards SDGS and sustainable development: Evidence from Armenia”
Publication Name: Innovative Marketing
Publication Date: 2025-01-01
Volume: 21
Issue: 3
Page Range: 155-170
Description:
The paper aims to explore tourists’ perceptions and behaviors regarding sustainable tourism and sustainable development in Armenia. An online survey method was employed to collect data from 385 domestic tourists in Armenia from July to October 2024, enabling effcient and cost-effective access to a diverse respondent group. The sample size was determined based on a 95% confidence level and 5% margin of error, ensuring statistical reliability. The online format allowed for a broader reach and ano-nymity, making it suitable for exploring tourists’ knowledge of the SDGs, comprehen-sion of sustainable tourism, and willingness to embrace sustainable behaviors. Interestingly, despite only 46% of respondents being explicitly familiar with the SDGs, a significant proportion (64%) demonstrated knowledge of sustainable development, 62% understood sustainable tourism, and 64% believed tourism could positively impact sustainable development. Statistical analysis, specifically the Pearson Chi-Square test, revealed a strong correlation between knowledge of sustainable development and awareness of sustainable tourism, and tourists’ willingness to modify their travel habits and invest in eco-friendly options. Additionally, a sense of environmental responsibility was found to significantly influence the adoption of sustainable practices. Moreover, prioritizing sustainable tourism when selecting destinations strongly correlated with support for sustainable tourism initiatives. While many tourists acknowledged the importance of sustainable tourism, challenges such as limited information and higher costs hindered the adoption of eco-friendly behaviors. To promote sustainable tourism and contribute to achieving the SDGs, the study emphasizes the need for intensified awareness campaigns, accessible sustainable options, and collaborative efforts between the tourism industry, government, and tourists.
Open Access: Yes
