The article analyzes the process of formation of research universities as one of the elements of a strong innovation economy. The formation of a new university model is a global trend, successfully implemented in English-speaking countries. In Russia, the educational system is not yet ready to ensure the country’s effective competition in the innovation market. The Strategic Academic Leadership Program “Priority-2030” is designed to carry out the functional transformation of the entire infrastructure of human capital reproduction in a short period of time in Russia. The article presents an analysis of the main conditions for the development of a university with a research strategy, as well as an assessment of the implementation of this strategy by Moscow Polytechnic University. The methodological basis of the study was formed by qualitative methods: included observation and benchmarking of universities’ activities, which allowed to generalize the current global trends and best practices in the field of education. For the analysis we used the data of monitoring the activities of higher education organizations, data of official statistics, as well as data from reports and presentation materials of universities and online publications participating in the “5-100” and “Priority-2030” programs. The results of the study may be useful for researchers and practitioners engaged in the transformation of the Russian higher education system.
This study critically examines the relationship between Total Quality Management (TQM) and Service Quality (SQ) within Dubai’s housing sector, with a specific focus on the moderating influence of blockchain technology (BT) in this relationship. Employing a quantitative approach grounded in a deductive research strategy and positivist epistemology, data were gathered from a sample of industry professionals and subjected to rigorous analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that the deliberate deployment of TQM methodologies leads to significant improvements in SQ metrics, and the catalytic role of BT further enhances these service quality improvements. The study highlights the transformative potential of BT in recalibrating conventional paradigms of service delivery within the housing sector. Specifically, the analysis reveals that BT plays a pivotal moderating role in the relationship between TQM practices and SQ outcomes, thereby enriching our comprehension of the intricate interplay between these constructs. The study concludes by furnishing nuanced insights into the multifaceted dynamics shaping SQ within the housing sector, while also delineating avenues for future inquiry.
The paper proposes a methodology for the analysis and evaluation of the traffic scheme of Bulgarian cities. The authors combine spatial, network, and socio-economic analyses of cities with transport operators’ financial-economic evaluation, sociological studies of transport habits, and the possibilities of new information technologies for transport modeling (such as geographic information systems). The model proposes several approaches to optimize the municipality’s transport scheme. It results from a new need to improve urban traffic, the quality of transport services, and the integration of urban transport into the regional economy of Stara Zagora municipality. It presents a description, analysis, and outline of the opportunities for developing urban transport connectivity and mobility in Stara Zagora municipality. The research results show a deficit of transport connectivity between the different parts of the city, reflecting on the regional economy’s development and the efficiency of the environment and the population.
This research aims to assess the impact of bargaining power on budget implementation while also considering the deviation in capital expenditure as a moderating factor. The research sample included 34 provincial governments in Indonesia between 2019 and 2022. The sample determination method used purposive sampling, so the final sample size was 134 observations. The research employed panel data regression to test the hypotheses and continued with the Chow, Lagrange multiplier, and Hausman tests. The study results indicate that bargaining power has a positive and significant effect on budget implementation, with the deviation in capital expenditure not diminishing its impact. The research’s practical implication is that regional governments must effectively manage their revenues to finance regional spending needs through regional tax intensification and extensification policies. The study contributes to signaling theory by highlighting that regional governments can finance regional spending needs through fiscal independence and society’s involvement. It also contributes to agency theory by demonstrating that capital expenditure deviation in the form of information asymmetry in regional governments does not reduce their ability to finance regional expenditure needs. Nonetheless, the study suggests that the proxies used in this research are limited, and further exploration of other proxies to measure tested variables. This research provides new knowledge for stakeholders regarding the dynamics of regional budgeting, especially regarding assessing the impact of bargaining power on budget implementation and considering deviations in capital expenditure as a moderating factor.
Low enrollment intention threatens the funding pools of rural insurance schemes in developing countries. The purpose of this study is to investigate how social capital enhances the enrollment of health insurance among rural middle-aged and elderly. We propose that social capital directly increases health insurance enrollment, while indirectly influences health insurance through health risk avoidance. We used data from the China Health and Retirement Longitudinal Study (wave 4) dating the year of 2018, instrumental variable estimation was introduced to deal with the endogeneity problem, and the mediation analysis was used to examine the mechanism of social capital on insurance enrollment. The results show that social capital is positively related to social health insurance enrollment, and the relationship between social capital and social health insurance enrollment is mediated by health risk avoidance.
Accurate demand forecasting is key for companies to optimize inventory management and satisfy customer demand efficiently. This paper aims to Investigate on the application of generative AI models in demand forecasting. Two models were used: Long Short-Term Memory (LSTM) networks and Variational Autoencoder (VAE), and results were compared to select the optimal model in terms of performance and forecasting accuracy. The difference of actual and predicted demand values also ascertain LSTM’s ability to identify latent features and basic trends in the data. Further, some of the research works were focused on computational efficiency and scalability of the proposed methods for providing the guidelines to the companies for the implementation of the complicated techniques in demand forecasting. Based on these results, LSTM networks have a promising application in enhancing the demand forecasting and consequently helpful for the decision-making process regarding inventory control and other resource allocation.
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