Issue #2 (Volume 16 2025)

A transition toward sustainable logistics is crucial for Hungary’s automotive industry, which remains a main contributor to environmental degradation through its reliance on carbon-based supply chains. This study aims to examine how green technology, policy regulation, and infrastructure availability influence sustainability outcomes for the industry, with a focus on reducing carbon emissions and improving operational efficiency. Partial least squares structural equation modeling with 2015–2023 empirical data was employed. The model examined direct and moderate effects of such factors on lowering carbon footprint and sustainability performance, as well as on implementation cost, firm size, and demand.
The results suggest a significant impact on carbon footprint reduction (path coefficient = 0.32) and sustainability performance (0.38) through the adoption of green technology. Availability of regulatory frameworks (0.29 for reduction of carbon footprint; 0.25 for sustainability performance) and infrastructure (0.35 and 0.40, respectively) also have a significant impact. High implementation costs (–0.22 and –0.18) and the complexity of the supply chain (–0.15 and –0.17) have a negative impact, particularly for small and medium-sized enterprises. Moderation analysis shows that firm size (0.22) and strong demand (0.26) enhance the benefits of adopting green technology.
The indications are toward enhancing regulatory enforcement, raising financial aid schemes, and upgrading logistics infrastructure as a solution for Hungary’s accelerating adoption of sustainable logistics practices. Public-private partnerships are put forward as a strategic solution for bridging infrastructure and investment gaps and enabling long-term economic and environmental advantages for the automotive logistics industry.

This study investigates the role of green marketing in addressing Jordan’s environmental and economic challenges, focusing on barriers and drivers of adoption. Using a quantitative research approach, data were collected from 504 respondents (67.5% were customers and 32.5% were SME owners) and analyzed through partial least squares structural equation modeling to evaluate the relationships between socio-economic factors, financial incentives, and infrastructural challenges. The results reveal that financial incentives significantly drive the adoption of renewable energy (coefficient: 0.85, p = 0.010) and sustainable agriculture (coefficient: 0.80, p = 0.014). Stakeholder engagement is high, with customer awareness scoring a mean of 4.1 (standard deviation: 0.5) and environmental sustainability at 4.2 (standard deviation: 0.5). Key barriers include infrastructural limitations (mean: 3.7, standard deviation: 0.8) and socio-economic disparities (mean: 3.8, standard deviation: 0.7), restricting access to eco-friendly products. Model fit indices, including a standardized root mean square residual of 0.054 and a normed fit index of 0.92, confirm the robustness of the framework. The findings suggest that overcoming these barriers requires targeted financial support, infrastructure investment, and inclusive policies to scale green marketing effectively. This paper provides actionable insights into advancing sustainable practices in Jordan, offering valuable strategies for resource-constrained economies worldwide.

The paper investigates the causal interaction between renewable energy consumption and manufacturing value added in Kazakhstan, a relationship of growing importance in the context of sustainable industrial development. The aim of the study is to assess the direction and nature of causality between these variables over the period from 2000 to 2021. To this end, the Toda-Yamamoto Granger causality test is applied, offering robust results regardless of the order of integration of the time series data. The empirical analysis identifies a statistically significant bidirectional causal relationship. Specifically, renewable energy consumption has a significant impact on manufacturing value added (p = 0.003), while manufacturing value added also significantly influences renewable energy consumption (p = 0.006). These findings reveal a reciprocal mechanism in which the expansion of renewable energy supports industrial growth, and industrial development, in turn, enhances renewable energy usage. The results underscore the strategic importance of integrating renewable energy policies with industrial development plans. From a policy perspective, the study provides practical insights into fostering sustainable economic growth by aligning environmental and industrial objectives in Kazakhstan.

Coastal tourism is a growing segment of the global tourist business. Nonetheless, the careless environmental behavior of travelers has precipitated significant problems. Thus, the purpose of this study is to examine the influence of visitors’ environmental knowledge and recreational experience on their environmental commitment and attitude, which subsequently impacts their pro-environmental behavior. It uses cognitive-affective-conative theory to deepen the comprehension of the factors affecting tourists’ pro-environmental behavior in the realm of coastal tourism in Vietnam. The proposed model was validated by partial least squares analysis with data collected from 303 online individuals with prior experience in coastal tourism in Vietnam, retrieved via Google Forms in April 2024 through convenience sampling. The findings reveal that environmental knowledge positively affected environmental commitment (β = .250, p = .000), environmental attitude (β = .331, p = .001), and travelers’ pro-environmental behavior (β = .220, p = .000). Moreover, the recreational experience positively impacted environmental commitment (β = .629, p = .000), environmental attitude (β = .385, p = .000), and travelers’ pro-environmental behavior (β = .259, p = .000). The research findings indicated a positive effect of environmental commitment on travelers’ pro-environmental behavior (β = .268, p = .000). Finally, visitors’ environmental attitudes positively influenced their pro-environmental behavior (β = .155, p = .006).

Acknowledgment
The author acknowledges the Industrial University of Ho Chi Minh City, which supported this study.

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.

Acknowledgments
The authors would like to acknowledge the Behavioral Laboratory at Sumy State University for providing the essential facilities and resources that enabled the successful completion of this research. Additionally, sincere appreciation is extended to all study participants for their valuable time, commitment, and contributions, which significantly enriched our understanding of consumer behavior related to waste management and the perception of advertising content.
The research is supported by the International Visegrad Fund: Visegrad Fellowship Program. Project № 62410031, “Marketing research consumer behaviour in the waste management system”, and by the budget of the Ministry of Education and Science of Ukraine (research topic 0123U100112 “Post-war recovery of the energy industry of Ukraine: Optimization of waste management taking into account the health of the population, environmental, investment, tax determinants”.

The study examines the long-term relationships between human development, economic growth, and environmental conditions in South Korea from 1996 to 2021. Understanding these interactions is crucial for shaping policies that balance economic progress, social well-being, and environmental sustainability. The analysis employs cointegration techniques, including the Fully Modified Ordinary Least Squares (FMOLS) and Canonical Cointegration Regression (CCR) methods, to estimate long-run relationships among GDP per capita, the Human Development Index (HDI), and carbon dioxide emissions per capita. Empirical findings confirm a stable long-term equilibrium between GDP and HDI, as demonstrated by significant Engle-Granger and Phillips-Ouliaris test statistics (p-values ≤ 0.0245). The results suggest that economic growth consistently enhances human development, while improvements in HDI contribute to sustained economic progress. The relationship between HDI and carbon emissions per capita, however, yields mixed evidence. The Engle-Granger test supports a long-term association (p-values ≤ 0.015), but the Phillips-Ouliaris test does not confirm cointegration (p-values ≥ 0.112). The covariance matrix test indicates that the negative relationship between HDI and carbon emissions per capita is stronger and more variable compared to the more stable inverse association between HDI and GDP per capita. Additionally, Granger causality analysis reveals a significant causal relationship between HDI and GDP per capita, supported by a Chi-square value of 20.627 and a p-value below 0.001. These findings highlight the complexity of integrating environmental considerations into development policies. South Korea’s experience underscores the necessity of a balanced policy framework that ensures sustainable economic growth while advancing human development and mitigating environmental impacts.

This study empirically examines the cross-border environmental and health impacts of mineral fertilizer use in European countries by applying spatial panel models. Specifically, it evaluates how nitrogen and phosphate fertilizers affect public health expenditures and water quality within national borders and adjacent countries. To accurately capture transboundary influences, the analysis uses a spatial weights matrix based on shared land borders constructed from geospatial data (Natural Earth shapefiles), enabling the assessment of spillover effects between neighboring countries. The models cover the timespan 2006–2021 for 29 European nations, except those that do not have common land borders (island countries), with available and comparable data. The results confirm significant spatial effects. The spatial lag model revealed strong direct and spillover effects for health expenditure, particularly for nitrogen and pesticide use, indicating that increased agricultural intensity in one country can raise health costs in neighboring states. Phosphate and potash use were associated with reductions in health expenditure, though the interpretation may reflect regional differences in environmental management. In contrast, the spatial error model best explained unsafe drinking water outcomes, highlighting the role of unobserved, spatially correlated environmental pressures. Nitrogen and pesticide use were linked to increased water contamination, while phosphate showed a strong but context-dependent negative association.

Ongoing urbanization presents significant environmental challenges, which can be addressed through targeted investments in green infrastructure. Such investments not only mitigate ecological impacts but also enhance a city’s brand value and attractiveness to investors and residents. This study evaluates how green infrastructure, along with environmental, social, and economic indicators, influences the formation of a “green” image of the capitals of European countries. The “green” image is conceptualized as the perception of a city as environmentally friendly and sustainable, increasing its appeal to various stakeholders. Using k-means cluster analysis based on 10 indicators across 29 capitals of European countries, four distinct clusters were identified according to their potential for sustainable development. The second Cluster (Berlin, Helsinki, Ljubljana, Madrid, Riga, Sofia, Tallinn, Vilnius, and Zagreb) showed the strongest “green” image, with extensive green areas and low pollution levels balanced by solid socio-economic indicators. The first Cluster (London, Luxembourg, and Paris) had a high quality of life but relatively limited green space. The third Cluster (Amsterdam, Copenhagen, Dublin, Lisbon, Prague, Rome, Stockholm, and Vienna) combined high living costs and life expectancy with moderate green coverage. Most remaining cities, including Athens, Brussels, and Kyiv, were placed in the fourth Cluster, indicating a need for more robust environmental policies. The findings highlight that expanding green spaces, maintaining low pollution levels, and supporting high life expectancy is key to enhancing a city’s green image, thereby boosting its investment appeal and overall quality of life.

Acknowledgment
This study was partially supported by the project of the European Union Program ERASMUS+ Jean Monnet, under grant agreement № 101085435. This article reflects only the authors’ views, and the European Commission is not responsible for any use that may be made of the information it contains.

The study analyzes the implementation of responsible production practices in Kazakhstan’s manufacturing sector, an area of growing importance for sustainable development in emerging economies. The aim is to examine how environmental, operational, and social factors influence production processes and community contributions. Data were collected through an online survey conducted between May and August 2024, using a voluntary response sampling method. To enhance the representativeness of the findings, the sectoral distribution of the responding enterprises was analyzed post-collection. The survey captured top, middle, and line management responses to comprehensively assess sustainability practices. Structural equation modeling (PLS-SEM) was employed to evaluate the relationships between ecological operational efficiency, environmental protection, resource efficiency, waste management, social factors, product manufacturing, and community contribution. The findings reveal that environmental protection, efficient resource use, and effective waste management significantly strengthen manufacturing performance and enhance companies’ contributions to community development. In contrast, improvements in ecological operational efficiency and workplace social initiatives do not directly impact production outcomes. The study concludes that integrating sustainable environmental and resource management practices into production processes is crucial for enhancing both manufacturing performance and broader societal outcomes. The findings offer practical implications for industrial managers, policymakers, and stakeholders aiming to promote sustainability transitions in manufacturing sectors.

Acknowledgment
This study was funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP19576593).

The circular economy is increasingly recognized as a crucial solution to environmental and economic challenges, gaining significant attention from the government, businesses, and citizens in Vietnam. As urban waste management becomes urgent, understanding the factors influencing sustainable waste management practices is essential. This study aims to assess the impact of circular economy awareness on the actual waste management behavior of market vendors in Hanoi. A total of 324 valid responses were collected directly from vendors in 2024. The paper applies an extended version of the theory of planned behavior framework, incorporating key variables such as circular economy awareness, willingness to pay, government policies, and behavioral barriers. Using the PLS-SEM method, the findings indicate that circular economy awareness has a positive influence on vendors’ waste management behaviors, with significant effects through attitudes (β = 0.425), subjective norms (β = 0.473), perceived behavioral control (β = 0.539), and willingness to pay (β = 0.462). However, behavioral barriers negatively impact actual waste management behavior (β = –0.179). Notably, government policies, despite existing national strategies, do not appear to affect vendors’ behavioral intentions (β = 0.031; p-value = 0.520). This suggests that such policies have yet to effectively reach or influence the target group. These findings emphasize the necessity for more targeted policy interventions to enhance circular economy awareness and foster sustainable waste management behaviors among market vendors. Strengthening engagement with vendors and improving policy effectiveness will be critical in promoting long-term environmental sustainability in Vietnam.

Acknowledgments
This study was funded by the Ministry of Education and Training of Vietnam, grant number B2023-NTH-02.

The sustainable development of the agri-food industry has become increasingly critical in the face of rising food insecurity, climate change, and recent global disruptions such as the COVID-19 pandemic and geopolitical conflicts. This study aims to perform a bibliometric analysis of global research concerning the sustainable development of the agri-food industry and its implications for food security across nations. Drawing on 1,704 Scopus-indexed publications from 1993 to the first quarter of 2025, the study identifies four distinct phases of research growth, ranging from an exploratory stage to a recent surge in interdisciplinary and technology-focused studies. Keyword co-occurrence analysis reveals five major thematic clusters: agri-food supply chains, environmental sustainability, public health and nutrition, technological and product innovation, and systemic food security. Thematic evolution demonstrates a clear progression from fragmented early research to integrated, systems-based approaches, with a growing emphasis on digital technologies (e.g., AI, blockchain, and IoT) and circular economy principles. Despite rapid thematic expansion, the study highlights ongoing gaps in connecting sustainability research to actionable food security strategies in low- and middle-income regions. 

The transition to a sustainable energy economy requires substantial public investment, with government spending playing a crucial role in driving the adoption of renewable energy and achieving environmental outcomes. This study investigates the impact of India’s budgetary allocations on renewable energy consumption, carbon emissions, and economic growth. The analysis covers annual data from 1990 to 2024. It employs the autoregressive distributed lag (ARDL) bounds testing approach and the Granger causality test to examine long-term equilibrium relationships and directional causality among the variables. The results indicate a statistically significant long-run relationship between government expenditure, renewable energy usage, and carbon emissions. Specifically, a 1% increase in renewable energy consumption (REC) results in a 1.14% decrease in carbon emissions, demonstrating the environmental benefits of clean energy deployment. The ARDL model also shows that past government disbursements significantly contribute to emissions reduction, with coefficients of –2147.41 (p < 0.001) and –997.36 (p < 0.05) at lags one and two, respectively. Granger causality results confirm an unidirectional causal relationship between renewable energy expenditures (REE) and carbon emissions, as well as between government spending and gross domestic product (GDP), highlighting the dual impact of such investment on environmental sustainability and economic growth. The findings underscore the effectiveness of public financial support in accelerating the transition to renewable energy while advancing macroeconomic goals. Strengthening and sustaining government investment in renewable energy is essential for achieving India’s long-term development targets, reducing carbon intensity, and promoting green economic growth.

This study examines the impact of renewable energy consumption, CO₂ emissions, and renewable electricity generation on the Sustainable Development Index in Uzbekistan over the period 1990–2023. Using an autoregressive distributed lag (ARDL) model, the study estimates the short- and long-run relationships between these variables. The Sustainable Development Index is constructed using indicators of primary school enrollment, life expectancy at birth, and female labor force participation using a min-max normalization method. The results indicate a long-run positive impact of renewable energy consumption (β = 0.0552, p < 0.05), underscoring its significant contribution to sustainable development. Conversely, renewable electricity generation has a significant negative impact in the long run (–0.0153, p < 0.01), which may be due to initial high transformation costs and short-term economic adjustments. CO₂ emissions did not have a statistically significant impact on the Sustainable Development Index. The model is robust, with no autocorrelation or heteroscedasticity issues, indicating reliable results. This study underscores the importance of strategic investments in renewable energy and offers valuable insights for policy development, thereby enhancing Uzbekistan’s sustainable development trajectory.

The paper deals with the growing importance of understanding energy consumption patterns and their relationship with export performance in developing economies. The study aims to analyze the bidirectional relationship between commodity exports and energy consumption in Uzbekistan from 1992 to 2023. A vector autoregression (VAR) model is employed as the primary methodology, incorporating four main variables: commodity exports, GDP per capita, renewable energy consumption, and renewable electricity generation. Unit root tests (ADF and PP) were conducted, revealing that all variables are stationary in their first differences, which necessitated cointegration analysis. The Johansen test results confirm the existence of a single long-run cointegration vector among the variables. Granger causality tests identify a bidirectional causal relationship between GDP per capita and exports, with changes in GDP per capita having a significant impact on exports (p < 0.001) and vice versa. The results demonstrate that renewable electricity has a positive effect on exports (coefficient = 0.055, p = 0.01), while GDP per capita shows a negative effect on exports (coefficient = –0.0002, p = 0.039). Additionally, VAR analysis reveals that past values of exports significantly influence current export levels, with a lagged coefficient of 0.883 (p < 0.05). These findings have practical implications for policymakers in Uzbekistan seeking to balance economic growth objectives with sustainable energy development strategies.