Achieving food security through improved agricultural technology is one of the greatest challenges of our time. Indeed, it is one of the elements explicitly mentioned in the Sustainable Development Goals (SDGs). One factor that can lead to improved production and distribution systems is the availability of data of all kinds on the sector. In this paper we study what is happening in this respect in two Mediterranean olive oil producing countries, and show how available data can facilitate the coordination and communication of technical developments and improve the competitiveness of producers.

The study analyses the long growth rate period contribution to human development in West African Economic and Monetary Union (WAEMU) from 1996 to 2019 introducing time and institutional indicators effects analyses. Time and institutional effects both greatly improve model's diagnostics statistics. Time effects reduce growth variable coefficient and its significance, but not institutional effects. Combined effects inhibit growth contribution to human development. It appears essential to increase the resiliency of growth and the efficiency of government institutions.

The precise prediction of carbon emissions trading prices is the foundation for the stable and sustainable development of the carbon financial market. In recent years, influenced by a combination of factors such as the pandemic, trading regulations, and policies, carbon prices have exhibited strong random volatility and clear non-stationary characteristics. Traditional single-perspective prediction methods based on conventional statistical models are increasingly inadequate due to the homogenization of features and are struggling to adapt to China's regional carbon emissions trading market. Therefore, this paper proposes a multi-perspective fusion-based prediction method tailored to the Chinese market. It leverages carbon emissions trading information from key cities as relevant features to predict the price changes in individual cities. Inspired by the development of artificial intelligence, this paper implements various time series models based on deep neural networks. The effectiveness of the multi-perspective approach is validated through multiple metrics. It provides scientific decision-making tools for domestic carbon emissions trading investors, making a significant contribution to strengthening carbon market risk management and promoting the establishment and rational development of a unified carbon market in China.

The low-carbon city pilot is an important policy for promoting sustainable development and addressing climate change. The level of green technological innovation is a significant driving force for China's transition to high-quality development and the realization of carbon peaking and carbon neutrality goals. This essay takes the panel data of 30 provinces in China from 2008 to 2020 as the research sample, regards the number of urban green invention patent applications as a quantifiable indicator of the level of urban green technological innovation, and takes the policy of low-carbon city pilot as a quasi-natural experiment, and uses the difference-in-differences model to test the impact of low-carbon city pilot on the level of urban green technological innovation, and to investigate the mechanism of action within. The main conclusions are as follows: (1) The policy of low-carbon city pilot has an outstanding promotion effect on the level of urban technological innovation. (2) Using the mediating effect to analyze, it is found that the low-carbon city pilot policy can improve the level of urban green technological innovation through the development of green finance.

The integration of digital technology and traditional finance has further achieved the goal of low-cost and sustainable financial services and contributed to high-quality economic development. Based on the data from 31 provinces in China from 2011 to 2021, this paper empirically analyzes the impact of digital finance on the urban-rural income gap. The results show that digital finance can significantly narrow the income gap between urban and rural residents. The quantile test shows that the greater the urban-rural income gap, the stronger the role of digital finance in narrowing the urban-rural income gap. The threshold effect test shows that the narrowing effect of digital finance on the urban-rural income gap will first increase and then weaken with the continuous improvement of the development level. Heterogeneity analysis shows that the secondary indicators of digital finance can significantly narrow the urban-rural income gap, and the effect of depth of usage is the most obvious. Moreover, digital finance has a significantly stronger effect on narrowing the urban-rural income gap in the eastern region than in other regions. Therefore, we should vigorously promote the development of digital finance and give full play to its effectiveness in narrowing the urban-rural income gap.

The objective of this study is to explore the link between the financial sector, macroeconomic fluctuations, and sustainable energy production in South Asia. It evaluates existing research, identifies gaps, and suggests future directions. The study emphasizes the need to understand how economic activities influence the environment and how environmental factors impact economic and financial outcomes. It also examines financial market responses to understand the manifestation of economic and environmental factors, using data from Bangladesh, India, Pakistan, and Sri Lanka spanning 1987 to 2022. The results show that investment in green energy is essential for developing countries. The study suggests that the relationship between the region's stock market, GDP, carbon emissions, and green energy is complex, with a negative response to domestic credit indicating potential obstacles to investment, such as policy barriers or insufficient incentives. Mixed responses highlight the need for credit directed towards sustainable projects. Variations in responses across economic indicators may indicate policy challenges or structural issues, necessitating a reassessment of government policies to incentivize sustainable investments and promote green technology adoption. These results imply that policymakers should precisely assess the environmental ramifications of economic growth and stock market activities. This presents an opportunity to craft policies that guide investments toward cleaner technologies and industries, aligning economic growth with sustainable practices. Policymakers and financial institutions should explore ways to incentivize green energy investments and promote sustainable economic growth.

The use of All-Terrain Vehicles (ATVs) has gained considerable attention within the recreation industry. The incorporation of ATVs into tourism and recreational activities has demonstrated substantial economic potential for local economies. However, there is a lack of comprehensive knowledge regarding the economic impact of ATV recreation. This paper conducts an extensive review of existing literature from 2004 to 2022, evaluating the economic impact of ATVs on local economies in the United States. The review aims to identify commonalities and disparities among existing economic impact studies and assess whether these studies have included costs associated with ATV-induced environmental, societal, and public health damages in their economic assessments. To this end, there is a scarcity of scientific peer reviewed journal articles that exclusively focus on the economic impact of ATVs. As such, we reviewed a total of seven publications comprising reports. The results of our analysis shed light on similarities and differences in aspects of resident and non-resident ATV spending, type of ATV expenditures, and the approaches used to evaluate economic impact assessment. The findings indicate that existing studies have assessed the economic impact of ATVs solely based on gross expenditures, lacking comprehensive inclusion of the costs associated with ATV damages to the environment, society, and human health. This study advocates for the need for a more comprehensive consideration of both benefits and costs in the economic impact of ATVs to assist ATV business managers, policymakers, and researchers in making informed decisions and planning future programs.

This paper examines impacts of China’s financial liberalization policy on income inequality, through three channels: financial scale, financial structure and financial efficiency, an empirical analysis based on panel data of 30 provinces in China from 1996 to 2013 is conducted. The results confirm the Kuznets effect between financial scale, financial structure and income inequality. As the size of the financial sector expands, the financial structure is tilted toward direct financing, and the income gap among residents will experience a "reverse U-shaped" trend that rises first and then falls. Most of China has not yet passed the turning point, and is still in the upper bound of the "inverted U-shaped" curve. Financial liberalization policies will continue to exacerbate income inequality. The impact of financial efficiency on income distribution is quite different in different regions of China. After dividing the whole China into three regions according to the degree of economic development, it is found that the financial efficiency of the eastern and western regions has a Kuznets effect on the income gap, but compared with the eastern region, more provinces and cities in the western region have entered the stage of reducing the income inequality, and the financial development has a great impact on the western region. The effects of financial development on central China are weak, and income inequality increases with financial efficiency.

The enactment of policies that bolster new research and development (R&D) institutions stands as a pivotal strategy to catalyze urban innovation and development. Adopting a strategic lens of innovation chain management and employing the Differences-in-Differences (DID) method to scrutinize panel data from 43 Chinese cities spanning 2008 to 2019, this study probes the efficacy and underlying mechanisms of policies designed to support nascent R&D institutions in facilitating urban innovation. Empirical findings reveal that policies in support of new R&D institutions have markedly enhanced the three integral stages of the urban innovation chain: research and development, transfer, and application. Furthermore, the innovation ambiance within cities and the innovative activities of enterprises emerge as significant mediators between support policies and the output of urban innovation across these stages. A regional heterogeneity analysis unveils that the impact of support policies on the output of urban innovation diverges across regions, with a notably more pronounced effect observed in the eastern region compared to central and western regions. An objective appraisal of the policy's impact on urban innovation not only aids in delving into the profound implementation effects of policy instruments but also furnishes policy-makers with decision-making references for optimizing the utilization of support policies for new R&D institutions to advance the edification of the national innovation system.

This study analyzes how the presence and the composition of nomination committees could influence innovation. Specifically, we focus on the committee size, the frequency of meetings, and the presence of independent and female members. Innovation is measured by (1) the firm’s ability to produce innovations such as new or improved products/processes and the number of patents, and (2) innovation expenditures (R&D spending and the number of scientists and experts per R&D teams). This study is drawn on firms listed on the SBF120 index, between 2002 and 2016. It provides the following results: First, the presence of nomination committees is negatively associated with the number of patent applications and the number of scientists and engineers in R&D teams. Furthermore, most of the nomination committee’s attributes (such as the presence of independent and women members) have no significant association with innovation proxies. We show, also, that large nomination committees are prone to increase innovation income (such as the R&D expenditures and the number of scientists and experts per R&D teams) as well as the number of filed patents. Turning to the committee functioning provides evidence that the frequency of meetings could reduce asymmetric information regarding innovation projects and lead to an increase of R&D expenses. This article brings practical insights to board structures issues. This study contributes to the current debate on how boards should be organized, specifically; the nomination committees. It shows that boards should pay attention to the nomination committee features as they could undermine innovation projects, specifically in innovation-sensitive industries.

The digital economy based on digital technology is an important force for high-quality economic growth and industrial transformation, and has great potential for value creation. Based on the data of 30 provinces in China from 2007 to 2017, this paper uses entropy method to calculate the industrial green transformation (IGT), and empirically analyzes the impact of Digital economy on IGT. The DE can significantly reduce IGT of local and neighboring areas after excluding the influence of macro system factors and replacing the spatial weight matrix. The DE can indirectly reduce the IGT by accelerating the accumulation of human capital, and green technology innovation. The impact of digital economy on IGT is a non-linear relationship. With the further improvement of environmental regulation, financial development and intellectual property protection, the role of digital economy in IGT is more obvious. To this end, it is necessary to speed up the construction and improvement of digital infrastructure, build an integrated layout of "digital infrastructure", give full play to the radiating role of the digital economy, and implement differentiated development paths based on regional comparative advantages.

Under the background of digital economy, global tax governance has become one of the important topics in today's world development and change. In recent years, new challenges, such as tax base erosion and profit transfer, and the imbalance of cross-border tax source division, have become prominent, forcing the reform of international tax rules and the reshaping of international tax order. Based on this, the article first deeply digs into the scale and cross-border characteristics of the spatial-temporal aggregation of the digital economy, and comprehensively evaluates its impact on the global tax governance pattern. After that, the article combs out the realistic picture and challenges of the current digital tax reform from the aspects of theoretical basis, basic principles and governance mechanism. Finally, based on China's basic national conditions, the article puts forward some institutional ideas and policy suggestions, with a view to improving China's participation, voice and influence in global tax governance, and also enabling governments, enterprises and residents of various countries to enjoy the fruits of world economic development fairly and promote the construction of Community of Shared Future for Mankind.

Green innovation, as a sustainable development approach, can synergistically promote high-quality economic and social development. We select China's A-share-listed manufacturing corporations from 2011 to 2021 as the research sample to empirically study the impact of executive academic experience on green innovation in manufacturing corporations. Further, we test the relationship between executive academic experience and green innovation in manufacturing corporations under the mediating role of corporate social responsibility and the moderating role of heterogeneous environmental regulations. The study shows that (1) executive academic experience helps to promote green innovation in manufacturing corporations; (2) executive academic experience is conducive to promoting the fulfillment of social responsibility by manufacturing corporations; (3) corporate social responsibility plays a mediating role between executive academic experience and green innovation in manufacturing corporations; (4) environmental regulation positively moderates the relationship between executive academic experience and green innovation in manufacturing corporations, and both formal environmental regulation and informal environmental regulation positively moderated the promotion of green innovation in manufacturing corporations by executive academic experience.

With the continuous advancement of technological revolution and industrial transformation, digital finance supported by big data and artificial intelligence has become an important engine for promoting carbon neutrality. We measured the industrial structure transformation index (ISU) of 30 provinces in China, and discussed the spatial spillover effect and transmission mechanism between digital finance and ISU using the spatial Durbin model. The research results demonstrate that the digital finance development can significantly improve the local ISU. Interestingly, the impact of digital finance on the ISU of adjacent areas has a significantly negative spatial spillover effect, which still exists under the different spatial weight matrix. Digital finance can improve ISU by improving green technology innovation, upgrading industrial structure, and alleviating capital allocation. We also found that the higher degree of marketization and environmental regulation can increase the positive influences of digital finance on ISU. This research proves the effectiveness of the digital finance in improving energy efficiency, and it encourages policymakers around the world to rely on digital finance to promote ecological governance and achieve high-quality economic development.

Based on the provincial panel data of China from 2011 to 2019 for a total of 9 years, this paper uses the entropy method to construct a comprehensive measure of the digital economy and common prosperity. We theoretically analyzed the impact mechanism of the digital economy on common prosperity using the econometric model. The study found that the digital economy can significantly promote the realization of common prosperity. The digital economy has a significant impact on the development and sustainability of common prosperity. The results of the impact mechanism show that the digital economy promotes common prosperity by increasing entrepreneurial activity. Heterogeneity research shows that the role of digital economy in promoting common prosperity changes with different regions. Specifically, the digital economy in the central and western regions can significantly promote the realization of common prosperity, but this impact is not significant in the eastern region. From the regression results of the digital economy, we can see that industrial digitalization and digital infrastructure play a greater role in promoting common prosperity. Economic openness affects the promotion of digital economy to common prosperity. The conclusion of this work provides an important research reference for the development of digital economy and the realization of common prosperity.

Parkinson’s Disease (PD) is a prevalent progressive neurodegenerative condition affecting millions globally. Research has found that individuals with PD have a reduced risk of certain cancers, such as colon, lung, and rectal cancers, but an increased risk of brain cancer. Therefore, there is an urgent need for the development of advanced PD diagnostic methods and for investigating the relationships between risk factors, such as lifestyle due to handedness associated with various types of cancers. Recent ad- vancements in magnetic resonance imaging have enhanced PD diagnosis, reducing misdiagnosis and facilitating more accurate disease progression monitoring. Nevertheless, challenges exist, particularly in the distinction of PD between left-handed and right-handed patients over time. This survey provides an overview of contemporary deep learning-based imag- ing analysis methodologies, encompassing both non-longitudinal and lon- gitudinal contexts. We also explore existing limitations and prospects for refinement to gain deeper insights. These insights are poised to inform the development of personalized treatment strategies for PD patients while elucidating the current disparities between deep learning models and their efficacious implementation in clinical practice.

As the COVID-19 epidemic swept the world in early 2020, it is worth watching how it affects the total factor productivity of enterprises. Based on the theory of information asymmetry and the data of A-share listed companies from 2014 to 2021, this paper conducts an empirical study on the relationship between COVID-19 and the total factor productivity of enterprises. The results show that the impact of the COVID-19 epidemic can significantly reduce the total factor productivity of enterprises, and the conclusion is still true after a series of robustness tests. Taking the financing constraint as an intervening variable, it clearly reveals a transmission mechanism, that is to say, the impact of the COVID-19 epidemic exacerbates the financing constraint of the enterprise, thus it makes the total factor productivity of the enterprise reduce. It is further found that the above effects are more obvious for small and medium-sized enterprises and non-intelligent enterprises. Based on this, the government should implement some active economic development policies to create a free, relaxed and orderly market environment for enterprise financing. At the same time, enterprises should not only pay attention to digital and intelligent development, and transform into technology-intensive enterprises, but also strengthen the awareness of worry. Enterprises should store "more grain" for preparing for the cold winter.

Given the rapid development of live streaming commerce in China, this study focuses on the interactivity and sociability of live streaming shopping activities and explores online consumers’ real-time interaction intentions and trust-building behaviours with online merchants. To discover the real-time interaction between online consumers and online merchants, this study builds a research model based on the Theory of Planned Behaviour (TPB). Through the data analysis based on the partial least squares path modelling and variance-based structural equation modelling (PLS-SEM), the key findings state that, three factors, including attitude, subject norm, and perceived control, positively affect online consumers’ real-time interaction intentions and lead them to build trust with online merchants. Meanwhile, control variables, including gender, age, and educational background, demonstrate insignificant effects across the model. Unlike existing literature, the current study pays much attention to the interactive characteristics of live streaming shopping activities and can provide some valuable suggestions both for online consumers and online merchants, which can promote the co-development of the commercial and social aspects of live streaming platforms.

Entrepreneurs are important actors in economic activities and creators of social wealth. Excellent entrepreneurs contribute their wisdom to the accumulation of social wealth and the promotion of high-quality economic and social development. The business environment is the main manifestation of the soft power of cities and regional economic development, and a better business environment can effectively attract enterprises and promote their sustainable growth. Using data from Chinese A-share listed companies from 2009-2019 as a research sample, the following research conclusions were drawn: (1) A better business environment helps enhance entrepreneurship. (2) A better business environment promotes entrepreneurship by reducing rent-seeking expenses and corporate credit costs. (3) Compared to traditional enterprises, high-tech enterprises are better able to enjoy the benefits brought by business environment optimization and further enhance entrepreneurship. When competition is low, entrepreneurs face lower rent-seeking expenses, which is conducive to stimulating entrepreneurship. The businessenvironment can promote fairness and bring more equal financing opportunities for enterprises, which has a higher impact on entrepreneurship for the group facing higher financing constraints. This study meticulously analyzes the impact ofthebusiness environment on entrepreneurship, providing references for the next steps of optimizing the business environment and enhancing entrepreneurship.

In the statistical standard of population aging adopted by the United Nations in 1956, the UN only focused on age, which is no longer a good statistical indicator in the context of deepening global population aging. To some extent, population aging is also the embodiment of social progress. This paper suggests improving the existing statistical standards of population aging to better adapt to the reality of social development.