The current study examines the impact that technological innovation, foreign direct investment, economic growth, and globalization have on tourism in top 10 most popular tourist destinations in the world. The information on the number of tourists, foreign direct investment, growth in gross domestic product, GFCF, use of FFE, and total energy consumption were extracted from the World Development Indicators. The United Nations Conference on Trade and Development (UNCTAD) database was used for collecting the statistics about technological innovation.  The source ETH Zurich has been utilized to gather panel data for the time period 2008 to 2022 to calculate the KOF Index of Globalization. Theoretically, FDI and Economic growth are the endogenous variables for the Tourism model. Whereas, TI, Glob, Energy Consumption, and GFCF are the exogenous variables. Hence, the analysis is based on the System Equation—Simultaneous equations, after checking identification that confirms the problem of simultaneity in system of 3 equations. The empirical outcomes suggest that TI, FDI, globalization index, GDP growth, and energy consumption are the most important factors that contribute to an increase in tourism. Likewise FDI as the endogenous variable is favorably impacted by globalization, technological innovation, fossil fuel energy consumption, gross fixed capital formation, and tourism. Nevertheless, the coefficient of GFCF is only insignificant in the study. While, globalization, TI, and FFE are also favorably affecting the FDI. GDP growth is the second endogenous variable in this research, and it is positively influenced by globalization, FDI, and tourism in the case of the top 10 nations that are most frequently visited by tourists.

As urbanisation increases, questions arise about the desirability of further urban growth, as it was not accompanied by corresponding economic growth, and social and environmental problems began to grow in the largest cities in the world. The objective of the article is to substantiate the limits of urbanization growth in Kazakhstan based on the study of theoretical views on this process, analysis of the dependence of social and economic parameters of 134 countries on the urbanisation level and calculation of the urbanisation level that contributes most to economic growth and social well-being. To achieve the goal, the following tasks have been set and solved: theoretical views on the process of urbanization have been generalized; a hypothesis has been put forward about the emergence of an “urbanization trap” in which the growth of large cities is not accompanied by economic growth and improvement of social well-being; an analysis of the dependence of socio-economic indicators on the level of urbanization has been carried out on the example of 134 countries of the world; the level of urbanization that maximizes economic growth and social well-being is calculated; the necessity of the development of small towns in Kazakhstan is substantiated. To solve the problems, the methods of logical analysis, analogies and generalizations, economic statistics, index, graphical, Pearson correlation analysis, Spearman and Kendall rank regression based on models in SPSS were used. As a result, the following conclusions are made: the hypothesis of a possible deterioration of socio-economic indicators in large cities is confirmed; the best positive result is demonstrated by the level of urbanization of 50%–59%. The recommendations are justified: in Kazakhstan, it is necessary to adhere to the level of urbanization no higher than 59%; the growth of urbanization should be ensured through the development of small towns; it is necessary to improve the methods of managing the process of urbanization and develop individual city plans.

COVID-19 has amplified existing imbalances, institutional and financing constraints associated with a development strategy that did not take sufficient account of challenges with emissions, environmental damage and health risks associated with climate change in a number of countries, including China. The recovery from the pandemic can be combined with appropriately designed investments that take into account human, social, natural and physical capital, as well as distributional objectives, that can also address commitments under the Paris agreement. An important criterion for sustainable development is that the tax regimes at the national and sub-national levels should reflect the same criteria as the investment strategy. Own-source revenues, are essential to be able to access private financing, including local government bonds and PPPs in a sustainable manner. Governance criteria are also important including information on the buildup of liabilities at all levels of government, to ensure transparent governance.
Despite differences in political systems, the Chinese experiences are relevant in a wide range of emerging market countries as the measures utilize institutions and policies reflecting international best practices, including modern tax administrations for the VAT, and income taxes, and benefit-linked property taxes, as well as utilization of balance sheets information consistent with the IMF’s Government Financial Statistics Manual, 2014. The options have significant implications for policy advice and development cooperation for meeting global climate change goals while ensuring sustainable employment generation with transparency and accountability.

To achieve sustainable development, detailed planning, control and management of land cover changes that occur naturally or by human caused artificial factors, are essential. Urban managers and planners need a tool that represents them the information accurate, fast and in exact time. In this study, land use changes of 3 periods, 1994-2002, 2002-2009, 2009-2015 and predictions of 2009, 2015 and 2023 were assessed. In this paper, Maximum Likelihood method was used to classify the images, so that after evaluation of accuracy, amount of overall accuracy for images of 2013 was 85.55% and its Kappa coefficient was 80.03%. To predict land use changes, Markov-CA model was used after assessing the accuracy, and the amount of overall accuracy for 2009 was 82.57% and for 2015 was 93.865%. Then web GIS application was designed via map server application and evoked shape files through map file and open layers to browser environment and for design of appearance of website CSS, HTML and JavaScript languages were used. HTML is  responsible for creating the foundation and overall structure of webpage but beautifying and layout design on CSS. 

COVID-19 has presented considerable challenges to fiscal budget allocations in developing countries, significantly affecting decisions regarding number of investments in the transport sector where precise resource allocation is required. Elucidating the long-term relationship between public transport investment and economic growth might enable policymaker to effectively make a decision in regard to those budget allocation. Our paper then utilizes Thailand as a case study to analyze the effects on economic growth in a developing country context. The study employs Cointegration and Vector Error Correction Model (VECM) techniques to account for long-term correlations among explanatory variables during 1991–2019. The statistical findings reveal a significantly positive correlation between transport investment and economic growth by indicating an increase of 0.937 in economic growth for every one-percent increment in transport investment (S.D. = 0.024, p < 0.05). This emphasizes the potential of expanding the transport investment to recover Thailand’s economy. Furthermore, in terms of short-term adjustments, our results indicate that transport investment can significantly mitigate the negative impact of external shocks by 0.98 percent (p < 0.05). These findings assist policymakers in better managing national budget allocations in the post-Covid-19 period, allowing them to estimate the duration of crowding-out effects induced by shocks more effectively.

This study considers the relationship between investment in the manufacturing and processing industries and economic growth in Vietnam. This study applies an autoregressive distributed lag (ARDL) model to reassess the long- and short-term relationships between industrial investment and economic growth from 1998 to 2023. It has been found that in both the long and short term, investments in this sector have a positive and significant effect on economic growth. The results further show that labor negatively affects growth in the long run, but is favorable in the short run. The verdict for the role of exports is that more evidence is required before any conclusive analysis can be conducted. Reinvestment in the manufacturing and processing industries for further economic growth is evident in the foregoing analysis. On the other hand, this research provides insight into the optimization of the utilization of resources and future sustainability by the government.