Based on a sample of 487 rural elderly people from five counties (cities and districts) in Chengdu City, this paper investigates the main demand drivers affecting rural home-based elderly care service consumption willingness based on structural equation modelling. The results of the study show that (1) the overall satisfaction level of the demand for rural home-based elderly care services in Chengdu is 40%, with insufficient service relevance and low cost-effectiveness; at the same time, the service functions of the basic facilities for the elderly are not sufficiently fulfilled, and the resources are not effectively utilised. (2) The willingness to participate in home care services in rural Chengdu is mainly driven by spiritual and cultural, medical and health care and other demand factors. (3) Life care has a positive effect on rural elderly's participation in home care to a certain extent, but it is not significant. Safety and security indirectly affect rural elderly's willingness to age in place by influencing medical and health care. Therefore, the government, enterprises, communities, and families should work together in an orderly and coordinated manner to form a family-centred, community-based, and professional service-dependent socialised service for the rural elderly living at home, with the main content of solving daily life difficulties, and supplemented by spiritual and cultural services, in order to guard the rural elderly in their later years of happiness.

In the digital era of the economy, digital transformation has become an important path for high-quality development of Corporates. This article is based on the Guotai An database and uses Chinese companies from 2010 to 2021 as research samples to empirically examine the impact of the proportion of female executives on corporate digital transformation. The study found that: (1) The proportion of female executives can enhance a company's level of digitalization. (2) This effect is mainly achieved through increasing the company's research and development intensity, thereby improving its digitalization level. (3) The role of female executives in promoting digitalization is more pronounced in non-state-owned, large companies with dispersed equity ownership.

This paper aims to provide a comprehensive analysis of the near future of the Russian ruble, with a particular focus on its potential profitability as an investment asset. Amidst a backdrop of political tensions, economic sanctions, and ineffective forex interventions by the Russian Central Bank, the ruble has experienced significant volatility. The paper examines key factors influencing the ruble’s value, including political climate, inflation, interest rates, and main exports. The study analyzes the causes and solutions of Russia’s three major devaluations since the dissolution of the Soviet Union in 1992. By analyzing historical exchange rate and other economic indicators, the paper scrutinizes the internal and external indicators of ruble’s devaluation and evaluates the various policy measures taken by the Central Banks of Russia to stabilize the currency, including redenomination and shifts in exchange rate mechanisms. The paper concludes that, given the current political and economic landscape, the profitability of investing in the Russian ruble is questionable and unrecommended. Through this multi-faceted approach, this paper aims to provide a nuanced understanding of Ruble’s past and present, thereby offering valuable insights for policymakers, investors, and scholars interested in the foreign exchange market of Ruble.

This paper constructs a comprehensive index system, measures China’s provincial G-FINANCING INDEX using the VIKOR algorithm, explores the spatial and temporal distribution pattern of green financial development, hotspot regional migration and discrete trends by establishing a Markov spatial transfer matrix, and predicts the future pattern of green financial development in China’s three major economic belts based on the machine-learning algorithm ADABOOST, which finds that: (1) the central region maintains a strong development momentum. The development of green finance in the region shows a scale effect, and there is a positive transmission trend of development momentum between cities. The right side of the nuclear density curve in the western region has a clear trailing trend, and the overall degree of improvement is high. The phenomenon of multi-polarisation exists among city clusters. The city clusters in the eastern region as a whole show extremely high development momentum. (2) Geographic background plays an important role in the process of transferring G-FINANCING INDEX in Chinese cities, and the level of regional G-FINANCING INDEX is the result of the joint action of desired outputs and non-desired outputs, which is dominated by the economic activities in the region, and is specifically expressed in the spatial spillover effect of regional G-FINANCING INDEX is the spatial spillover effect of regional economic activities. (3) The evolution of the G-FINANCING INDEX in the study region has obvious spatial spillover effects, and is synergistic with the type of regional G-FINANCING INDEX, showing the phenomenon of “club convergence”.

The proliferation of short video applications and platforms has paralleled the growing popularity of this media format. In the increasingly competitive landscape of short-form video, companies have adopted numerous strategies to expand their market share, retain active users, and ensure sustainable platform operations. Among these strategies, one of the most pivotal is the utilization of recommendation mechanisms and algorithms to personalize video suggestions for users. For platform users, the additional traffic and exposure facilitated by recommendation mechanisms present a valuable opportunity for their videos to reach a wider audience. This paper delves into the characteristics and commonalities of user-generated content on video platforms influenced by recommendation algorithms, and examines the strategies employed by video creators to harness the increased traffic and exposure provided by these mechanisms, as well as the dynamics between users and the platform. We have randomly selected video data from the "Beeping Beeping" pop-up website for analysis. The study also scrutinizes the actions taken by video producers to exploit the resources and opportunities provided by the recommendation mechanism. Furthermore, it explores the interactions between users and the platform. To carry out this research, we selected a sample of twenty random videos from each of the ten video producers who boast a substantial fan base on the "Bleeping.com" website. While the recommendation mechanism simplifies the user experience, it simultaneously offers varying resources and opportunities to different users. Users who comprehend the platform's recommendation guidelines and underlying algorithms can proactively leverage the mechanism to aid in video creation and dissemination. This approach enables them to actively promote high-quality user-generated content on the video platform during the video creation and upload phases.

As one of the world's largest digital entertainment providers, Netflix plays a crucial role in the entertainment and streaming industry. This article analyzes the main strategies for Netflix's success by using market research data, financial data, and user behavior data. Through analysis, it was found that high-quality original works are the key weapon for Netflix to win. With the help of big data and algorithm analysis, Netflix is deeply loved by consumers. In addition, Netflix's globalization strategy has gained market recognition and allowed it to maintain a competitive advantage in the global streaming media market. This article also reveals some key insights and elaborates on the challenges Netflix is currently facing from competitors and changes in user behavior patterns. Despite facing increasing competition, Netflix is still able to maintain its leading position as a streaming platform, relying on its unique strategy and continuous changes based on users and the market.

As the cornerstone of China's engineering construction, the construction machinery industry plays an important role in the process of foreign trade and export. This fully reflects the important demand for China's construction machinery industry, but also shows the important position of the industry in the international market. At present, China's construction machinery market is open to the outside world, the domestic and foreign construction machinery market competition is fierce, many scholars on China's construction machinery export trade situation and ways to improve the enterprise's global market share to do in-depth research. In this paper, we find that Sany Heavy Industry is ranked in the top of the global construction machinery manufacturers, brand, scale, technology than other domestic construction machinery enterprises have advantages, from the perspective of Sany Heavy Industry through cross-border mergers and acquisitions to improve the level of internationalisation, through a combination of quantitative and qualitative methods, to provide assistance to the international development of China's small and medium-sized construction machinery enterprises.

The internet celebrity effect is a newly emerging effect in the era of big data on the internet, which exerts a unique influence on economic development. Several aspects of the internet celebrity effect align with certain marketing strategies in the modern tourism industry, making it undoubtedly one of the significant drivers of economic development in this sector. Building upon this premise, this paper takes the case of Ding Zhen, a young man from Litang who gained popularity. We conduct an in-depth study through qualitative analysis and comparative analysis, comparing it with Yajiang County to explore the significance and value of the internet celebrity effect. The internet celebrity effect can enhance social attention to tourist destinations, boost regional tourism industry development, and achieve economic growth in the tourism sector.The analysis explores how to leverage the internet celebrity effect to advance the modern tourism industry. It underscores the interconnectedness between the internet celebrity effect and the modern tourism industry, emphasizing the full utilization of the internet celebrity effect's role to enhance economic development in the modern tourism industry catalyzed by this phenomenon.

This study, based on panel data from 30 provinces in China from 2007 to 2020, employs the Super Efficiency SBM model to measure the green total factor productivity of each province. By constructing mediating effect models and spatial econometric models, it conducts an empirical investigation into the mechanisms and spatial characteristics of how green investments promote China's green development. The results reveal that, at an overall level, green investments play a positive role in influencing China's green development. Regarding the influence pathways, innovative green technology advancements, both in terms of inventions and improvements, are important mediating channels through which green investments promote green development, with inventions having a stronger mediating effect. In terms of regional heterogeneity, green investments significantly promote green development in the eastern and central regions, while their promotion effect in the western regions is less pronounced. Concerning spatial spillover characteristics, green investments not only drive local green development levels but also stimulate the green development in surrounding areas through spatial spillover effects.

The accurate prediction of inflation is of utmost importance in informing economic policy formulation and guiding private investment choices. Enhancing the precision of inflation prediction through the utilization of univariate models continues to present difficulties. Inspired by the hybrid methology that has emerged in the field of time series forecasting, which seeks to enhance forecasting accuracy by integrating linear and nonlinear approaches, the author employs a hybrid model that combines Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA) techniques. The objective is to forecast the non-seasonally adjusted monthly US Consumer Price Index (CPI) inflation. The hybrid model employed in this study incorporates the utilization of wavelet transform, namely the discrete wavelet transforms (DWT), for the purpose of breaking the time series data into its constituent components of details and approximation. The subsequent application of LSTM and SARIMA models aims to capture both nonlinear and linear patterns present in the data. The findings of this research indicate that the DWT-based LSTM-SARIMA model outperforms both the solo SARIMA and LSTM models in a one-step rolling window forecast over a period of five years. This superiority is particularly evident during periods characterized by severe levels of inflation.

In the current society, the field of artificial intelligence is developing rapidly. In the field of artificial intelligence, OpenAI can be said to be one of the best, which promotes technological progress and market dynamic changes. This article discusses OpenAI's marketing strategy in depth, with the aim of understanding its formulation, evolution, and impact on the artificial intelligence industry. Through analysis, this paper examines the company's initial marketing efforts, branding and messaging strategies, and the role of collaborations and partnerships in expanding its market presence. The paper also discusses ethical considerations intertwined with OpenAI's marketing messages and statements, emphasizing the importance of transparency in this field. The findings of this paper highlight the importance of well-designed marketing strategies to shape industry perceptions, drive technology adoption, and promote ethical considerations in AI development. This research serves as a basis for looking at the complex relationship between marketing strategies and their wider implications for the AI industry.

This study investigates how SMEs' creative activities are impacted by digital financial inclusion. Small and medium-sized businesses face severe funding constraints, and scientific and technical innovation struggles to advance quickly due to information asymmetry, regional development imbalance, and other issues. The dominating element of the current growth of inclusive finance, digital inclusive finance, may address these concerns through theoretical and empirical research. Despite the fact that digital inclusive finance is still in its infancy and that there are issues with the law, risk management, trust, and other areas, accelerating the development of digital inclusive finance, easing the financial restrictions on SMEs, and enhancing the drive for scientific and technological innovation can all help to promote the innovative development of SMEs. Based on the influence of SMEs' technology innovation from the perspective of digital inclusive finance, this paper analyzes the influence of technology innovation by using the multiple linear regression model of time series. Empirical analysis shows that the digitalization of digital inclusive finance has a significant positive impact on small and medium-sized enterprises' scientific and technological innovation, significantly the higher the digital support and coverage breadth index, the more pronounced the incentive of scientific and technological innovation. Considering the impact of regional differences, the paper puts forward relevant policy suggestions, including improving laws and supervision, establishing a mature credit investigation system, and strengthening risk management and the digital divide. Through these measures, digital inclusive finance can better support the financing and development of SMEs and promote scientific and technological innovation and the development of the national economy.

Firstly, tax management is an important aspect of financial management, which involves the selection and calculation of taxes. However, tax management also carries various risks, and we need to adopt different approaches to avoid these risks. In this article, we will discuss the definition of tax management, the different stages involved in the tax management process, and the differences in tax management in different countries. Secondly, this article also conducted case studies on tax management and tax risk prevention strategies, in order to deepen the understanding of these issues and their impact on the company's financial health. This article first provides the definition of tax management and tax risk prevention strategies, and then delves into the different stages involved in the tax management process. At the same time, this article emphasizes the importance of tax risk prevention strategies in enhancing the financial health of companies, and conducts in-depth analysis of cases.

This paper examines whether the loose monetary policy was a key factor in the 2006 housing bubble and then led to the financial crisis of 2008. It analyses the situation of the US economy during the early 2000s. It presents how the role of the Federal Reserve’s Monetary strategies such as the Expansionary Monetary Policy created an easy credit environment and investors' overconfidence in the US. Furthermore, this paper delves into the Taylor rule and explores the principle for adjusting nominal interest rates based on economic fluctuation and inflation. This framework is crucial in understanding the policy decisions of that time. In addition, this paper outlines the different perspectives on the Monetary Policy from the John B. Taylor and Bernanke who was defend for the Federal Reserve that fears of deflation and the restrictions brought about by the liquidity trap during that time. The paper also reveals labour market, including unemployment and output gaps, indicated economic strength but also inflationary pressure. In conclusion, this paper emphasizes the importance of a multifaced approach to monetary policy analysis in understanding the intricate factors that led to this pivotal event in economic history.

This paper explores the principles and practice of value investing deeply, tracing its origins and analyzing its fundamental ideas. The basic principle of intrinsic value is examined, along with how it influences investment choices, emphasizing the reasons why it can have an effect when investigated and appraised. The limitations of value investment, such as long-term commitment, are also discussed in the article. It is determined that Microsoft, Apple, Pfizer, and Merck's long-term changes are related to the investment technique after integrating their yearly returns, total revenues, and earnings per share over the past four years. After calculating the growth rate of their total revenue and earnings per share, the changes of the four companies are more clearly seen in the chart. It is found that the returns of value investing correspond to the events experienced by the four companies, proving once and for all the usefulness of value investing. Finally, the article considers how value investing, a well-known and established financial technique, may help investors meet their objectives and generate profits.

The driving forces behind stock price increases are twofold: investor expectations for the future and market sentiment. Investors prefer stocks with growing performance as they are essentially investing in the future. Market sentiment, characterized by heightened enthusiasm for buying and selling stocks, contributes to remarkable gains in stock prices, with some sectors experiencing multiple consecutive limit-up movements. Against this backdrop, this study formulates an investment strategy that combines market trends and performance growth as dual factors. The research outlines the logic, specific implementation, timing of transactions, and risk management measures associated with this strategy. Using the optical communication sector as an example, the study tests the investment strategy and concludes that stocks with strong performance or anticipated growth, situated in trending sectors with sustained market conditions, are worth purchasing. Additionally, timing transactions strategically can yield favorable returns.

The number of small and medium enterprises (smes) in a country is huge, their impact on national development is also incalculable, is an important component of the rapid growth of GDP and a strong foundation, but the financing problem has been restricting the development of small and medium-sized enterprises, the analysis of small and medium-sized enterprises in the era of economic downturn financing difficulties how to solve, We should upgrade our financing capacity while improving our own construction. The government should also increase support for financing projects of smes, and introduce certain policies to help smes provide financing services, so as to enhance the financial influence of smes and improve the social environment while developing the economy, through several practical examples, this paper analyzes some problems that small and medium-sized enterprises may encounter in financing in real life, so as to help small and medium-sized enterprises improve the success rate of financing,finally, analyze the future development trend of small and medium-sized enterprises.

The COVID-19 pandemic has posed a severe threat to global public health, particularly in New York City, where the impact has been substantial. Against this backdrop, understanding the relationship between hospitalization and mortality, as well as how this relationship is influenced by the economic and healthcare conditions of different regions, becomes an urgent and important research topic. This study aims to explore the relationship between hospitalization and mortality in different administrative districts of New York City (Brooklyn, Bronx, Manhattan, Queens, and Staten Island) during the COVID-19 pandemic, and further analyze how economic development and healthcare conditions affect this relationship. Utilizing data provided by the New York City Department of Public Health, two differently configured regression models are employed for analysis. Model 1 solely considers the impact of hospitalization numbers on mortality numbers, while Model 2 further incorporates area and time as control variables. These findings not only provide significant insights into the geographical and socio-economic differences in the pandemic but also offer targeted suggestions for policy-making.

This study seeks to explore and elucidate the economic repercussions of the COVID-19 pandemic on Japan and China. By comparing these two prominent Asian economies, the paper aims to offer insights into how different economic structures, policies, and external relations can influence the economic impacts of a global health crisis and determine what each country should do in the post-pandemic era economy. This research delves into various economic indicators such as GDP growth, employment rates, number of bankruptcies, and sectoral analyses. Using quantitative analysis shown in graphs, the paper concludes that the COVID-19 pandemic significantly impacted Japan and China's economies, affecting SMEs, supply chains, unemployment, and government finances; the study suggests both nations need a multifaceted approach from government and society to boost their post-pandemic economies. The study found that Japan faced a surge in SME bankruptcies despite financial support measures; aggregate supply experienced disruptions, and aggregate demand declined due to service restrictions, exacerbating fiscal challenges. China, facing a supply-side shock, should prioritize domestic demand, SME support, digital transformation, and healthcare investment, leading to the study's conclusion that strengthening supply chains and aligning recovery with sustainability is vital for recovery and growth in the post-pandemic era.

This article aims to empirically examine the impact of internal fintech investment on operational performance using both a two-way fixed effects model and a mediation effect model. Take banks in China as research target. Through manually collected unbalanced panel data from 42 listed commercial banks spanning the years from 2010 to 2022. The key findings are as follows. First, investments in fintech significantly enhance the operational performance of banks. However, compared to state-owned banks and share-owned banks, the positive effect of fintech investments on the performance of urban commercial banks and rural commercial banks is more significant. Secondly, mediation tests on operational costs and business scope channels have revealed that fintech could achieve "cost reduction and efficiency enhancement" for urban and rural commercial banks by enhancing operational efficiency and expanding their business scope. Nonetheless, this effect is not significantly evident in state-owned banks and share-owned banks. Thirdly, further empirical testing on market share indicates that fintech investments significantly boost the market share of joint-stock commercial banks, corroborating the notion that fintech could augment the competitiveness of commercial banks. The insights garnered from this study contribute to understanding and augmenting existing research on the microeconomic consequences of the strategic fintech investment undertaken by commercial banks. Furthermore, it offers valuable references for future policies aimed at propelling the digital transformation of traditional banking industries.