The Impact of Economic Corridor and Tourism on Local Community's Quality of Life under One Belt One Road Context

Understanding life satisfaction among the original inhabitants in the suburbanized areas at the outskirts of a major city: a qualitative study

PURPOSE

Suburbanization has become a major characteristic of urban development in sub-Saharan Africa, and shifting from agricultural-based areas modus vivendi to urban lifestyles affects subjective wellbeing of the original settlers. While there is lack of evidence in the literature of wellbeing in these areas, this study examines life satisfaction of these populations by means of individuals' own appreciation and evaluation of quality of life.

METHODS

The study uses interpretionist and reflexive approaches, and analyses 76 interviews conducted through snowball sampling in two major suburbanized areas. Thematic analysis was used to analyse the data.

RESULTS

Generally, the findings show that respondents are satisfied with material living conditions due to improvement of availability of economic opportunities, roads and other transport services, social and community support. However, income inequality and urban poverty result in the inability to afford modern and high-quality urban living conditions, which creates feelings of vulnerability while limiting social relationships.

CONCLUSIONS

There is a need to strenghten existing frameworks to fully respond to urban life requirements that relate to transport, education, hygiene, and sanitation services. It is also important to develop support systems that mitigate issues of gender discrimination, human rights, household decision-making, fashion, and cultural norms.

Analyzing psychological resilience in college students: A decision tree model

In the evolving landscape of higher education, particularly in the post-pandemic era, it is crucial for college students to face societal challenges and achieve success by understanding and predicting psychological resilience. To deepen our understanding of psychological resilience, this study used a decision tree model to explore influencing factors. We surveyed 776 college students and collected data on demographic information, self-esteem, sense of school belonging, pro-environmental behavior, subjective well-being, internet game addiction, life autonomy, and academic procrastination using several scales. The decision tree model identified eight key predictors of psychological resilience, which are as follows in order of importance: self-esteem, sense of school belonging, pro-environmental behavior, subjective well-being, academic procrastination, life autonomy, internet game addiction, and academic achievement. This model's accuracy reached 73.985 %, emphasizing its potential utility in educational settings. The findings not only provide a novel and data-driven perspective to understand psychological resilience in college students compared to existing research but also provide practical guidance for educational practitioners and policymakers on how to develop psychological resilience in college students.

Predicting air pollutant emissions of the foundry industry: Based on the electricity big data

Industrial enterprises are one of the largest sources of air pollution. However, the existing means of monitoring air pollutant emissions are narrow in coverage, high in cost, and low in accuracy. To bridge these gaps, this study explored a predicting model for air pollutant emissions from foundry industries based on high-accuracy electricity consumption data and continuous emission monitoring system (CEMS). The model has then been applied to the calculation of air pollutant emissions from foundries without CEMS and the optimization of air pollutant emission temporal allocation factors. The results reveal that electricity consumption and PM emissions during the 2022 Beijing Winter Olympics have the same ascending and descending relationship. Furthermore, a cubic polynomial model between electricity consumption and flue gas flow is established based on the whole year data of 2021 (R2 = 0.85). The relative errors between the PM emissions calculated by the model and the emission factor method are small (-17.09-24.12 %), and the results from the two methods revealed a strong correlation (r = 0.93, p < 0.01). In addition, the monthly PM emissions from foundries are mainly concentrated in spring and winter, and the daily emissions on weekends are significantly lower than those on workdays. These results can be useful for environmental regulation and optimization of air pollutant emission inventories of foundry industry.

Investments in basic public infrastructure and their effects on economic growth in a developing country: The case of Cameroon

The literature review conducted in this study indicates that there is no unanimity regarding the definition of infrastructure and its impact on growth. While some economists argue that focusing on logistical infrastructure, such as transportation, telecommunications, water, and energy, would be beneficial for governments, others emphasise the importance of social infrastructure, such as health and education. Given the diverse range of opinions, further investigation is required, particularly in the context of Cameroon's infrastructure. The objective of this article is to evaluate the impact of investing in fundamental public infrastructure on economic growth in Cameroon. The study compares the elasticities of various infrastructure types on growth and private investment. With data from WDI 2020, a generalized method of moments is utilised, revealing that the energy sector has the highest contribution. In the majority of studies relating to infrastructure; many are those who are limited to overall infrastructures without however specifying them. Furthermore, the particularity of our study is that we are not interested in the stock of infrastructure, but rather in the amount of investment actually allocated. We are therefore trying to jointly see their repercussions on economic growth and the behaviour of private investments, something which had not yet been done in Cameroon to our knowledge. Therefore we find that the impacts of investments actually allocated do not have the same effects on the growth and behaviour of private investments; for example, everything happens as if there is a crowding out effect between the telecommunications sector and the behaviour of private investments. Macroeconomic performance in Cameroon is positively influenced by investment in road and telecommunications infrastructure. A 1% increase in investment in this sector leads to a 0.0536% boost in economic growth and a 0.329% increase in the private sector. Compared to other forms of infrastructure investment, this sector has a strong impact on the country's economic development. A 1% increase in investment in this sector leads to a 0.0536% boost in economic growth and a 0.329% increase in the private sector. These results allow on the one hand to see the infrastructures which contribute the most to economic growth in a country like Cameroon which is still struggling to take off in its development process. But they will also further densify the public-private partnership which is very important for the quantity but also the quality of infrastructure.

Corporate capital structure effects on corporate performance pursuing a strategy of innovation in manufacturing companies

Within the sphere of finance, the concept of capital structure has long been a subject of intense debate, serving as a quantitative depiction of the balance between debt, preference shares, and common stock within a company. This structure serves a crucial role in optimizing the utilization of a company's existing resources while simultaneously elevating the revenue streams for stakeholders. This particular study delves into the intricate relationship between corporate performance and capital structure, focusing on 78 publicly listed firms within the Dhaka Stock Exchange (DSE). Bangladesh holds the 29th position globally in terms of purchasing power, lending significant weight to this investigation. To comprehensively analyze this correlation, panel data encompassing the span from 2017 to 2021 was collected for these 78 sample companies operating within the DSE. Several key determinants of capital structure were considered in this analysis, namely the debt-to-equity ratio, short-term leverage ratio, long-term leverage ratio, and total debt ratio. Meanwhile, the performance of these firms was gauged using key metrics such as Return on Assets (ROA), Return on Equity (ROE), and Earnings Per Share (EPS). To ensure a robust analysis, factors such as inflation, liquidity, growth rate, tax rate, and firm size were meticulously controlled for. The findings unveiled a compelling narrative: all forms of debt ratios-be it short-term, long-term, or the total debt ratio-exhibited a substantial negative impact on ROA at a significant level of 1 %. Conversely, specific debt ratios, like the short-term total debt and the total debt-to-total asset ratio, displayed a notable positive correlation with ROE at a 1 % significance level. Intriguingly, the long-term total debt ratio yielded a negative and insignificant effect on ROE. Moreover, within the spectrum of predictors influencing a firm's performance, the liquidity ratio emerged as a non-significant factor-a notable discovery that highlights the nuanced nature of the interplay between capital structure and performance within these companies.

Unveiling the global nexus: Pandemic fear, government responses, and climate change-an empirical study

This study examined the relationships between pandemic fear, government responses, and climate change using a time-series dataset from January 1, 2020, to December 31, 2020. By employing an auto-regressive distributed lag (ARDL) approach, the results revealed that pandemic fear significantly impacts climate change, while government responses to COVID-19 negatively influence climate change in the long run. Climate change and government responses significantly positively affect pandemic fear in the long run. Moreover, we found a bidirectional causality between government responses and climate change, unidirectional causality from government responses to pandemic fear, and no Granger causality between pandemic fear and climate change. Our findings have some important policy implications. Governments must encourage coordination, enhance crisis responses, and consider revising economic metrics to maintain environmental sustainability. The COVID-19 experience can inform strategies for reducing CO2 emissions and investing in green economies and healthcare to prepare for future challenges.

An advanced deep learning predictive model for air quality index forecasting with remote satellite-derived hydro-climatological variables

Forecasting the air quality index (AQI) is a critical and pressing challenge for developing nations worldwide. With air pollution emerging as a significant threat to the environment, this study considers seven study sites of the sub-tropical region in Bangladesh and introduces a novel hybrid deep-learning model. The proposed model, expressed as CLSTM-BiGRU, integrates a convolutional neural network (CNN), a long-short term memory (LSTM), and a bi-directional gated recurrent unit (BiGRU) network. Leveraging nineteen remotely sensed predictor variables and harnessing the grey wolf optimization (GWO) algorithm, the CLSTM-BiGRU model showcases its superiority in air quality forecasting. It consistently outperforms the benchmark models, yielding lower forecasting errors and higher efficiency (i.e., correlation coefficient ~1) values. Hence, this study underscores the feasibility and substantial potential of the hybrid deep learning model, which can provide precise forecasts of air quality index, and will be highly useful for relevant stakeholders and decision-makers. Furthermore, the adaptability and potential utility of this innovative model may be ascertained for air quality monitoring and effective public health risk mitigation in urban environments.

Impacts of external factors on Ethiopia's economic growth: Insights on foreign direct investment, remittances, exchange rates, and imports

This study conducts a rigorous examination of relationships that are often assumed but rarely tested within the context of Ethiopia's journey towards sustainable development. An autoregressive distributed lag model is employed using annual time series data from 1982 to 2021 to investigate the short- and long-term impacts of foreign direct investment (FDI), remittances, real exchange rates, and imports on Ethiopia's economic growth. By incorporating additional control variables, this study contributes nuanced insights that were previously lacking in the literature. The findings reveal intriguing patterns that both align with and deviate from existing frameworks. Contrary to some prior studies, foreign investment consistently emerges as a significant driver of economic growth over time. However, remittances demonstrate only transient significance, highlighting the need for cautious policy considerations. The influence of exchange rates on economic growth proves to be unexpectedly complex and nonlinear, challenging conventional assumptions. The empirical validation of these multifaceted realities underscores the importance of this analysis. Furthermore, robustness tests conducted in this study confirm the reliability of the findings while shedding light on additional intricacies. For instance, the relationship between imports and growth is context-dependent and exhibits ambiguities that call for careful consideration. The theoretical and practical implications derived from this research offer valuable insights for researchers and policymakers alike. The recommendations put forth emphasize the promotion of sustained prosperity through evidence-based strategies that prioritize community development.

Effect of the characteristic town policy on sewage treatment in mountainous areas: Evidence from Chongqing

The report to the 20th National Congress of the Communist Party of China highlighted the necessity of advancing a new type of urbanization with people at the core. Characteristic towns as an essential link between new urbanization and rural revitalization attach great importance to creating a beautiful environment. Sewage treatment is an indispensable foundation for a town's high-quality economic and social development; however, it may be hard to achieve through urban construction. Therefore, using data from 584 organic towns in Chongqing, a typical mountainous city in western China, this study empirically analyzes the effect of the characteristic town policy in China on mountainous sewage treatment and its mechanisms from 2014 to 2020. The results indicate that (1) the characteristic town policy helps enhance sewage treatment in small towns, which remains valid after a series of robustness tests. (2) Investment and human resource effects are mediators for the characteristic town policy to boost sewage treatment in small towns. Further analyses reveal that the boosting effect of the characteristic town policy on small-town sewage treatment is more significant for small towns with higher economic development levels suffering ecological and environmental pressures. These findings provide a basis for a broad recognition of the effect of the characteristic town policy and its impact. They also theoretically enrich the awareness of the Chinese government's urbanization policy concerning the economy and society.

Moderating the role of social progress with greenhouse gases to determine the health vulnerability in developing countries

Human activities have compelled massive environmental degradation, which causes climate vulnerability and that has emerged as a significant health issue. The present study assesses the role of social progress with greenhouse gases to determine the health vulnerability in 77 developing countries from 2011 to 2020. The empirical results are estimated by using the panel ARDL econometric approach. The study found that greenhouse gas emission proposes a U-shaped relationship to determine health vulnerability. In this study, social progress is used as the moderator variable, which shifts the turning point of the U-shaped curve. For this purpose, the interaction term of social progress with greenhouse gases shifts the turning point to the left side of the U-shaped curve and further flattens it. Furthermore, this study explores that urbanization, export openness, and government education expenditure negatively impact health vulnerability while industrialization increases health vulnerability. The study recommends that government should pay special attention to declining greenhouse gases and rising social progress to improve health vulnerability.Graphical abstact.