This study focuses on the impact of trade in environmental goods (green trade) on the environment. We found that green trade can decrease pollution levels by exploiting a panel of 277 Chinese cities from 2004 to 2013 and using the instrumental variable (IV) strategy. However, total trade openness is far less favorable to the environment. We also found that both green imports and exports are conducive to the Chinese environment, while ordinary green trade performs better than green processing trade. Nevertheless, the effects of green trade are restricted by a city's purchasing power and absorptive capacity, as well as the classifications of environmental goods. Furthermore, green trade mainly promotes local green technological progress to benefit the environment.

The business world is a competitive place, and enterprises must cultivate sustainable relationships with their clients to gain customer loyalty. Concepts of relationship marketing (RM) are becoming vital in the service industry. Different RM strategies are used to attract customers, but some of these strategies do not achieve customer loyalty as easily as predicted due to customers’ changing behaviour patterns. This paper investigates the impact of RM strategies on customer loyalty through relationship qualities (customer satisfaction and trust) by concentrating on the high-end hairdressing sector in Auckland. Additionally, this research investigates the expectations of customers of high-end hair salons formed by RM strategies, which influence their satisfaction, trust, and customer loyalty to their service provider. The results indicate that brand image shows a significant relevance to trust, satisfaction, and customer loyalty claiming that brand image is an essential element of RM. Additionally, this investigations revels that, hair salons in Auckland are looking forward to ascertaining a sustainable relationship with their clients through a spectrum of strategies such as positive brand image, good service quality, reasonable price, and good value deals to earn optimistic relationship quality, which will ultimately escalate to customer loyalty. Findings of this research will be useful in supporting hair salons to gain a greater understanding of their customers by adopting effective RM strategies.

Technological advancements in the last few decades have created energy and cost-efficient power plants, but it is not a prominent feature in the electricity supply-chain. While many long-term and short-term energy alternatives are available, Pakistan still has a significant number of people who do not have access to electricity; as there are many areas that are neither connected to the national grid nor the provincial grids. This paper aims to find the reasons behind the energy crisis in Pakistan, keeping Islamabad as the focus of study, and to find the effect of use of renewable resources on the reduction of shortage of electricity. We will be focusing on the facts that how energy crisis has been affecting the economic growth of the country.  Our data collection will be based on primary sources and secondary sources along with which we will be conducting pilot study to check the feasibility of using the solar energy as an alternative form of electricity.

The claim that “there is no third way” besides the economic models of capitalism and communism has faced a challenge from a new and growing body of research into a “third way” economic paradigm known as democratic planning. In this paper, we explore one of these democratic planning models–Robin Hahnel and Michael Albert’s model of a participatory economy, focusing in particular on its allocation mechanism–a non-market, non-command-planning procedure known as “participatory planning.” This procedure has recently been implemented in computer programs to explore its feasibility, the encouraging results of which have been published elsewhere and which we summarize here. But I present here for the first time the detailed algorithms and related pseudocode powering all of these computer programs for others to consider, examine, and build as their own programs. I also describe future directions for this avenue of research.

Access to electricity, a fundamental element of contemporary life, is essential for economic success. Its impact extends to the fundamental foundations of industrial development and has the power to improve a wide range of industries, including healthcare, transportation, utilities, and education. This article aims to analyse the effect of electricity access on primary education in Central Africa over the period 1997-2019. To this effect, we employ data mainly from the World Development indicator on 9 countries of Central Africa. Using the pooled ordinary least squares estimation technique, the results indicate that access to electricity contributes positively and significantly to primary educational attainment in Central Africa during the study period. The results are Robust to the use of alternative estimation strategy and eventual endogeneity problems in the results are account through the two stage least square estimation techniques which confirm our baseline results as well as the nature of the relationship between access to electricity and primary education in Central Africa. These results have important implications for policies in overcoming barriers to electricity access.

The signing of RCEP has created new opportunities for the development of China's export trade, and international logistics capacity is an important factor affecting the conduct of international trade. This paper qualitatively describes and analyzes the LPI index and its sub-indicators of RCEP member countries, and empirically investigates the impact of logistics performance level on China's export trade through an extended gravity model. The study shows that there are large differences in logistics performance levels among RCEP member countries, especially in South Asia, where the quality of logistics infrastructure and customs efficiency are the most lagging behind, which are the key factors pulling down the logistics performance index; the signing of RCEP has effectively promoted China's foreign trade level, but there are great differences in export amounts to different countries, and the logistics performance levels of importing countries and China's export trade are significant positive correlation, the improvement of logistics performance is conducive to promoting China's export trade to RCEP member countries, and from the viewpoint of logistics links, the role of logistics infrastructure quality is the strongest, and the influence of cargo transportation timeliness is the weakest.

As the underlying institutional design for enterprise risk management, it is important to study whether and how internal control affects enterprise technological innovation in the current context of increased economic policy uncertainty. Based on the principal-agent theory and information asymmetry theory, this paper explores the impact of internal control on corporate technological innovation using the listed company data from 2009-2019 CSMAR database, and obtains the following research conclusions: (1) the quality of internal control positively affects the corporate technological innovation. (2) The operational risk plays an intermediary role in the relationship between the internal control affecting the corporate technological innovation. (3) The degree of market competition positively moderates the impact of internal control on enterprise technological innovation. (4) Relative to non-stateowned enterprises and non-high-tech enterprises, the quality of internal control of state-owned enterprises and high-tech enterprises has a more significant impact on enterprise technological innovation. This paper enriches the consequences of the study of internal control on the one hand, and on the other hand, it provides a new perspective for improving technological innovation, and it provides certain guidance for further improving the level of corporate governance.

At present, global warming poses the greatest threat to the planet's ecosystem. China is the greatest CO2 emitter, expected to account for roughly 33% of overall emissions in 2021, and this has caused authorities to express significant concern in the most latest Paris accord, when they decided to cut global emissions to a particular level. In comparison, 55% of China's power in 2021 appears from coal. As a result, investigating the ecological elements that affect China's CO2 output is essential. This analysis utilizes the autoregressive distributed lag (ARDL) technique to investigate the relationships concerning fossil fuels, renewables, and economic growth from 1990 to 2021. According to the data, using fossil fuels to generate energy and increase GDP significantly increases CO2 emissions. Yet, the use of renewable energy reduces CO2 emissions both in the long run and in the short term. Overall, the outcomes imply that using renewable energy sources is key to reaching sustainable environmental goals and deters the usage of fossil fuels in the energy mix. This study suggests that China take into account empirical findings and undertake long-term initiatives to reduce carbon emissions in favor of sustainable environmental outcomes.

This paper examines the information content of selected US industries focusing on the dynamic linkages among these industries, the stock market and a number of fundamental variables. The period of investigation spans from January 1960 to December 2021. The empirical strategy includes several methodologies such as regressions, vector autoregressions and volatility models. The idea is to investigate the dynamic linkages among these series at both the mean and the volatility levels. The results point to significant industry returns’ explanatory power for many predictors of economic activity including the stock market. Further, time-varying analysis of the linkages among the industries and the stock market’s returns reveal that certain industries such as Oil and Financials provide consistent information leadership over other industries and across decades. Further, upon assessing the industry–market return volatility spillovers, it was found that a market risk–return profile may not always be economically significant and timely for investors. Finally, crises, financial or otherwise, affect industries but to differing degrees.

The Public Welfare Foundation of a listed company is a non-profit organization with independent legal personality. It is established and funded by a listed company. The purpose of establishing a foundation for a listed company is generally to carry out charitable activities and make important contributions to charitable causes. However, due to the special power separation model, the autonomy of the foundation is poor, and there may be serious agency conflicts, ultimately leading to listed companies becoming beneficiaries of the foundation's charitable activities. We have found from the perspectives of commercial credit, sales, and cooperative relationships that social responsibility initiating organizations (listed companies) can obtain potential benefits from social responsibility fulfilling organizations (listed company public welfare foundations) in supply chain commercial relationships, that is, listed companies that establish public welfare foundations have good supply chain commercial relationships. When a listed company and a public welfare foundation have a close relationship in terms of fund donation, decision-making, business, and naming, the public welfare foundation has a strategic preference in selecting project names, project service areas, project beneficiaries, and project service areas. It prioritizes the interests of the listed company, enabling the listed company to obtain better supply chain business relationships.

Based on China's 30 provincial panel data from 2006 to 2018, this paper uses the spatial Durbin model to empirically study the influence path and transmission mechanism of financial development on regional technological innovation, and introduce digital finance environment, marketization degree, and government environmental management as an adjustment variable to verify its regulating effect on financial development and regional technological innovation. The study found that the overall promotion of digital finance to local technological innovation is not significant. Besides, the characteristics of ownership discrimination and weak risk appetite in the bank's medium and long-term credit market have led to its failure to promote regional technological innovation. In contrast, the stock market and bond market in direct financing channels have enhanced local innovation capabilities. When the external environmental system is used as the adjustment variable, the results show that an excellent digital finance development, marketization degree, and government environmental management can effectively and positively regulate the effect of financial development and technological innovation.

Gravity Energy Storage (GES) systems are recently being considered as a viable solution for storing intermittent renewable energy power, specifically in high curtailment zones. While a few studies have analyzed the material costs of GES systems, there is a paucity of literature on analyzing the socioeconomic costs of GES systems. This study analyzes the location-dependent costs of GES plants using a multi-factor spatial parameterization model for evaluating the existence of a point of minimum cost in a suburban mountainous geography. A case study of 500x500 points in a 50x50km2 area in the suburban area of Fukuoka city in Japan is performed. It is found that the cost of material transportation and transmission is more dominant in determining the position of an optimal cost location than factors of excavation and land costs. The position of the minima is also related to the principal urban area in that the line connecting the Center Business District (CBD) and suburban flat areas (line 1) is where the potential minima lie. The intersection point of an orthogonal to the line connecting the CBD with a substation nearest to the flat area with line 1, is the potential zone of minima location. The findings of this study are critical for urban energy planners and reveals how socioeconomic cost factors can aid in geolocation a suitable GES installation site.

Economy has various stages which have been described as economic cycle and due to that the circulatory movement observed, some have faster cycle some have longer cycle which depends on numbers of factors and from that inflation is an important segment. Various terms have been described for inflation, in simple meaning when price of different commodities have been raised compared to previous stage due to depreciation of currency having lesser purchasing power. Perception of people towards inflation and its impact is the main crux of the study, because how the people think about technical terms is vital matter. The present study is based on primary data collected from 277 respondents through questionnaire from the Gujarat state India. The perception has been analysed from four statement have been asked in Lickert’s five scale form. The one-way ANOVA has been used to test the hypotheses and it has been found from that in first statement regarding price of commodity once increase then it will not decrease due to inflation has significant difference with place, education and age of the respondents and in rest three statement no significant differences have been observed.

Cancer is the leading cause of death in the world, throughout the global researches of cancer treatment, people have a deeper understanding of cancer, and the treatment methods are constantly breakthrough. Conventional surgery, chemotherapy and radiotherapy have serious adverse effects and patients' quality of life is not significantly improved. Now, photodynamic therapy, photothermal therapy andthermodynamic therapy based on nanotechnology and materials technology are booming, and the development of these novel cancer therapies and their combination therapies brings more possibilities for cancer treatment. This review summarizes the research progress of novel cancer therapies based on nano and material technology from the aspects of mechanism of action and therapeutic methods, hoping to provide reference for their clinical application.

The aim of this study is to solve the problem of labor allocation in cases where the company has fewer employees than the number of existing jobs based on the evaluation of work quality according to multiple objectives. Optimizing labor allocation not only benefits the company by maximizing the use of human resources, but also saves employees' energy. In addition, employees are assigned to tasks that match their skills and qualifications, maximizing their productivity. The research results show that the multi-objective decision-making algorithm based on the Hungarian algorithm is a suitable method to help leaders of companies solve the aforementioned problem text.

Speeding up digital development and building "digital China" is an important strategic deployment of the "14th Five-Year Plan" and a concrete measure to promote the high-quality development of China's sports industry and national health. Based on provincial data in China from 2011 to 2019, an empirical model is used to analyze the relationship between digital construction, sports industry development and national health investment. The results show that digitalization is instrumental for sports industry development and the improvement of national health in China. Digitalization has promoted the healthy development of sports industry and national health by increasing the input of public science and technology.

This study employs empirical analysis using an econometric model that examines the interdependence among environmental degradation, exports, and economic development with energy use. It also provides an environmental Kuznets curve (EKC) for selected South Asian economies utilizing time-series data. The findings reveal a long-term, stable equilibrium link between energy demand and pollution. There exists a positive relationship between structural factors and pollution. Moreover, this study constructs a model of exports and pollution from an interdependent perspective. The three perspectives are tested: the scale and structure of energy consumption considering the twin constraints of export-trade and pollution, and the scale of pollution in export-trade constraint. These results show that the increase in energy use leads to higher CO2 emissions amidst export volume. However, in the presence of income, the scale of effect lowers a little. The analysis also supports the presence of Kuznets curve for south-Asian economies. The results imply substantial scope for development in the energy use and pollution structure within South Asia's current export trade process. This development can be attained by regulating energy use and enhancing system efficacy without necessitating changes to the scale effect or structural effect.

The dawn of the Artificial Intelligence (AI) era presents a plethora of new possibilities for analyzing regional economic development. The present article provides an in-depth exploration of the methods employed in this field, highlighting the immense opportunities that AI offers while also addressing potential challenges. The role of AI is crucial in complex data handling, enabling efficient analyses of intricate regional economic patterns. This capacity is paramount in shaping economic policies and strategies that are reflective of each region's unique needs and potential. The article firstly explores various AI methods used in economic analysis, including but not limited to machine learning, deep learning, and natural language processing. It delves into the application of these methods in discerning development trends, predicting economic shifts, and identifying strategic economic drivers unique to various regions. Subsequently, the potential of AI to transform regional economic analysis is discussed, encompassing its capability to process large and complex datasets, its power to predict future trends based on past and present data, and its ability to aid in strategic decision-making. However, this new era of AI-driven economic analysis is not without challenges. The latter part of this article thus confronts the issues related to data privacy, ethical use of AI, and the necessity of interdisciplinary skills in AI and economics. This exploration contributes to a broader understanding of how AI is transforming the landscape of regional economic development analysis, illuminating both its present use and future implications. By understanding these dynamics, we can better harness the potential of AI to advance economic prosperity in various regions around the globe.

Population, as a fundamental element in urban development, often reflects a city's economic development pattern through its spatial distribution and dynamic changes. Studying population spatial distribution is pivotal for bolstering the economic activity capacity in urban agglomerations and guiding regional economic health. Using the Changsha-Zhuzhou-Xiangtan urban agglomeration as a case study, this paper analyzes its overall spatial structure and the spatiotemporal evolution of population at the district and county levels. This analysis utilizes population density, population redistribution index, and population geographic concentration as key indices. Additionally, a spatial econometric model is constructed to assess the impact of economic, social, and environmental factors on population spatial patterns. Findings reveal several key points: (1) Furong District serves as the primary central area, boasting a population geographic concentration of 25.1% in 2021. Tianxin District, Kaifu District, Yuhua District, Shifeng District, Yuelu District, and Hetang District constitute the secondary central areas, while Yutang District, Tianyuan District, Lusong District, Yuhu District, Wangcheng District, and Changsha County form the tertiary level areas. (2) Population density within the Changsha-Zhuzhou-Xiangtan urban agglomeration gradually decreases from Furong District outward. The first central area and sub-central areas experience increasing population density, highlighting a polarization trend in the population distribution. (3) The overall Moran's index for the spatial distribution of population in the Changsha-Zhuzhou-Xiangtan urban agglomeration is significantly positive, indicating a strong spatial autocorrelation and a deepening spatial agglomeration of population distribution. (4) Per capita disposable income, financial expenditure, and education level positively influence the geographical concentration of population in the urban agglomeration, while GDP per capita, road area per capita, and environmental quality exert a negative impact. Notably, the most influential factors shaping population spatial distribution are GDP per capita, disposable income per capita, and air quality.

This research focuses on the digital transformation of retail banking in New Zealand, focusing on the challenges and opportunities elderly customers face. The banking industry is undergoing unprecedented change as technology evolves and customer needs change. However, elderly customers face physical and security challenges associated with digital transformation and lower acceptance of new technologies. This paper analyses the characteristics and needs of elderly customers, investigates the different needs of elderly and young customers, and recommends relevant solutions and suggestions. This investigation is based on secondary data, and recently published articles from various sources were used to collect information. In the wave of digital transformation, banks not only need to strive to provide convenient, safe, and high-quality services, but also need to innovate continuously to meet the needs of all customers and enhance their trust and satisfaction. This report provides exclusive digital service suggestions and solutions to help banks better meet the needs of elderly customers.