Laszlo Vasa

The self-drive rental sector has witnessed exponential growth in recent years due to rising demand for long and short-distance drives among millennials. This study aims to investigate the quality of services in the self-driving rental sector and its impact on customer adoption or rejection of service in India. The conceptual framework was developed using the SERVQUAL model and other important factors affecting consumers’ service adoption. A quantitative research method was deployed, and data were gathered through a survey method using a structured questionnaire (based on a 5-point Likert scale). The sample size comprised 385 respondents, 23-38 years old millennials (with 69% of males and 31% of females). The population sample was chosen from Delhi, Mumbai, and Bangalore, India. The data were collected in March 2023. The factor and regression analyses were applied along with chi-square and SEM analyses to test the research hypotheses. The results indicated that the absence of low prices (42%), customer assistance (28 %), and security issues is responsible for consumer rejection. The factors leading to dissatisfaction are the absence of consumer schemes and discounts, a lack of staff interaction and assistance, and poor service quality. The brands must focus on the negative impact arising from the absence of these factors and effectively address the areas of improvement to regain customer trust and garner customer loyalty.

The current green agenda, the climate change, and sustainability frameworks are closely linked to the successful transition to renewable energy. The study purpose is to estimate the influence of economic and environmental drivers of renewable energy promotion in the EU-27, using the 2013–2021 data for member states. Breusch and Pagan Lagrangian multiplier test and Hausman specification test were performed to determine the proper model specification. Using random-effects GLS regression for selected data, the study found that the rise in the magnitude of the Land-Ocean Temperature Index by one unit contributes to an increase in renewable energy sources by 10-16 percentage points. The rise in natural gas prices in the EU by USD 10 per MMBtu is associated with an average growth of renewable energy sources by 2.1-2.6 percentage points and three percentage points for growth in renewable electricity. An increase in GDP per capita of USD 1,000 led to an average increase in renewable electricity by 0.2 percentage points. An increase in CO2 per capita by one ton is associated with an average decrease in renewable electricity by 0.85 percentage points. This study proves that the critical point of GDP per capita within the “economic growth/renewable energy” nexus when economic stimulus starts to decline was estimated at USD 121,227-148,623. Thus, for countries that have reached the break-even point in GDP per capita, the incentives for introducing renewable energy sources are reduced when the effect of wealth prevails over the impact of environmental awareness and responsibility.

Acknowledgments
This paper is supported by a grant “Formation of Economic Mechanisms to Increase Energy Efficiency and Provide Sustainable Development of Renewable Energy in Ukraine’s Households” (No. 0122U001233), funded by the National Research Foundation of Ukraine.

The COVID-19 outbreak has underscored the importance of strengthening an organization’s resilience and adaptive capability. In emerging and uncertain conditions, firms must adopt new capabilities to develop and survive unstable and unforeseen crises. The purpose of this study is to examine the difference between organizational resilience and the antecedents that are validated using a quantitative survey. The respondents consist of 157 top employees from 21 private service firms at the managerial level in Bangladesh. The proposed relationship is measured using the partial least squares structural equation modeling (PLS-SEM), a symmetric approach, using SmartPLS 4 software. The findings help to produce the path coefficient with organizational resilience that can lead to sustainable environments in highly turbulent conditions. The PLS-SEM analysis indicates that the antecedents of flexibility, agility, and redundancy have a strong and meaningful association with organizational resilience in response to disruptions. Therefore, this paper shows evidence that the measurement scales more effectively account for uncertainty in achieving resilience, supporting the role of the dynamic capability view.

Bank deposits are vital for the economy, serving as a primary source of funding for banks that facilitate lending, investment, consumption, and overall economic growth. This article aims to examine how oil price fluctuations and inflation, two critical macroeconomic variables, influence bank deposits in Azerbaijan, an energy-exporting country. The primary purpose is to reveal the extent to which these factors, particularly in the context of Azerbaijan’s role as an energy exporter, affect the stability and liquidity of the banking sector. Using the Autoregressive Distributed Lag (ARDL) model and Granger causality testing, the study analyzes the dynamic relationships among these variables. The findings demonstrate a significant long-term relationship and causal effects between oil prices, inflation, and bank deposits. Specifically, a one-unit increase in oil prices results in a 0.057-unit rise in bank deposits, underscoring the positive impact of oil price increases on banking sector liquidity. Conversely, a one-unit increase in inflation decreases bank deposits by 0.812 units in the long term, highlighting inflation’s detrimental effect on financial stability.

Understanding the impact of economic factors on bank lending is crucial in Kazakhstan’s modern economy, characterized by volatile inflation and fluctuations in real wages. This paper aims to investigate the link between bank lending and economic factors such as inflation, real wages, and consumer expenditure in a regional context. Data from the Bureau of National Statistics and the National Bank, covering the period from 2012 to 2022, were used to uncover how economic factors influence bank lending. For the analysis, various economic indicators were integrated through normalization and averaging. Analysis reveals significant regional disparities in real wages and consumer expenditures, which impact the demand for bank credit. The results of the correlation matrix showed that both real wages (P-value < 0.001) and inflation (P-value < 0.001) significantly impact bank lending, with an R² value of 0.998, indicating that the model explains 99.8% of the variation in bank lending. The regression analysis highlights that regions with higher real wages, such as Astana, Almaty, and Atyrau, provide the most favorable conditions for banking sector growth, demonstrated by a strong relationship between wages and bank lending. In contrast, regions with lower wage levels, such as Turkestan and Zhambyl, show a significantly weaker connection (around 0.65), reflecting their lower attractiveness for banking investment and emphasizing the need for policies to address social inequality. The Durbin-Watson test confirmed no autocorrelation in residuals (DW = 1.89), although heteroscedasticity was detected, suggesting the need for further model adjustments. The study emphasizes the importance of developing economic policies that can balance regional development and improve financial stability.

Acknowledgments
This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant “Development of mechanisms for reducing social inequality and improving the welfare of the population of Kazakhstan” AP19174744).

This study aims to investigate the relationship between environmental sustainability, social development, and governance within Kazakhstan’s agro-industrial complex. The paper applies econometric modeling and statistical analysis to assess these relationships and provide strategic recommendations for sustainable development. A dataset from 2013 to 2023, sourced from the Bureau of National Statistics of the Republic of Kazakhstan, was utilized to assess the influence of transit routes and agriculture on ESG performance. Principal component analysis (PCA) and regression modeling identified three key components – environmental (84.3%), social (98.4%), and governance (88.33%) – as significant contributors to ESG variability. The results demonstrate that transit flows positively affect environmental and governance indicators (β = 0.266, p = 0.050), while agro-industrial activity has mixed effects: improved social sustainability but increased environmental pressure. The combined impact of transit corridors and the agro-industrial complex provides a more comprehensive explanation of ESG variability (R² = 0.998), reinforcing the need for integrated policy approaches. The findings highlight the strategic importance of aligning transit infrastructure and agro-industrial development with ESG frameworks. This paper contributes to the discourse on sustainable development by offering practical insights for policymakers on optimizing logistics and agricultural strategies to promote ESG adoption, particularly in agriculture-dependent economies.

Acknowledgments
This study is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant “Strategy of structural and technological modernization of the basic sectors of the economy of the Republic of Kazakhstan based on ESG: criteria, mechanisms and forecast scenarios” BR24993089).

The impact of different types of capital flows on China’s economic growth has been widely studied to determine whether the type of capital significantly affects the Chinese economy. The purpose of this study is to investigate the relationship between long-term capital flows and economic growth in China, considering factors such as Foreign Direct Investment (FDI), portfolio equity, portfolio bonds, and external debt. All secondary data were collected from the World Bank database. The paper also investigates which type of capital flow has the most significant relation with the economic growth of China. A quantitative approach was chosen for the study. Moreover, to overcome the bias output of ordinary least squares, this paper deployed a Two-Stage Least Squares (2SLS) estimation method. This study has found a relatively stable positive relationship between FDI and growth, where the coefficient of 0.9699 indicates that a 1% increase in FDI is associated with a 0.97% growth in Gross Domestic Product (GDP). Similar to FDI, portfolio equity has a positive impact on GDP growth, with a coefficient of 2.1419. In contrast, portfolio bond and debts have a negative coefficient of –1.7752 and –0.2831. These findings contribute to a deeper understanding of China’s development experience, particularly regarding the role of capital flow. The paper explores two key limitations that need to be explored in the future, i.e., the causal relation between each type of long-term capital flow and economic growth, and the impact of COVID-19 on the economic growth relationship.