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.

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).