Since the 18th National Congress of the Communist Party of China, informatization initiatives have facilitated the stable and rapid transformation of China's tax administration. The "Golden Tax Phase III" project employs modern techniques to ensure the stability and sustainability of national fiscal revenue, progressively advancing the digitalization of tax administration. This study uses data from Shanghai and Shenzhen A-share listed companies between 2008 and 2020. Employing the Difference-in-Differences (DID) approach against the backdrop of the "Golden Tax Phase III" project, we examine the effect of digitalized tax administration on firms' stock price crash risk. The results indicate that digitalized tax administration significantly reduces the risk of corporate stock price crashes. This effect is particularly pronounced among firms with slower digitalization processes and those audited by non-"Big Four" audit firms. The paper enriches the existing literature on the economic consequences of the "Golden Tax Phase III" project and provides new insights for policy-making.

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The COVID-19 pandemic triggered one of the most severe global economic downturns since the Great Depression, marked by unprecedented uncertainty and widespread disruption. This paper examines the pandemic's economic impacts through key studies. COVID-Induced Economic Uncertainty highlights how surging uncertainty, measured by stock market volatility and business surveys, contributed to an estimated year-on-year U.S. GDP declines by late 2020, with half attributed to uncertainty alone. The Economic Impacts of COVID-19: Evidence from a New Public Database uses private sector data to show reduced spending by high-income individuals, leading to revenue losses for small businesses and job losses for low-wage workers, while finding traditional stimulus measures less effective than direct financial support. Macroeconomic Forecasting in the Time of COVID-19 projects prolonged declines in employment, consumption, and production, with a slow recovery. Based on these findings, this paper proposes strategic policies to mitigate the crisis and support economic recovery.

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As the importance of the sports industry in national health and economic development is increasing, the management problems of stadiums have gradually highlighted. This paper examines the current deficiencies in the use of stadiums in China and its causes, and proposes an informatization solution based on SaaS (Software as a Service) system. It is revealed that the current public facilities, such as sports stadiums, have inefficient management, difficulty in satisfying users' needs, and insufficient application of technology, which are not compatible with the development trend of informatization society. Through the introduction of SaaS system, the integrated management of stadiums and the optimization of resource allocation can be achieved, which contributes to the enhancement of user experience and there by promotes the information transformation of the sports industry. In addition, this paper argues the feasibility and necessity of SaaS system in the informatization management of sports venues from four aspects, political, economic, social, and technological, through PEST analysis, and offers actual cases to prove its effectiveness. Informatization is an inevitable choice for the sports industry to comply with the development of the times, which can effectively improve the operational efficiency and user participation of stadiums and promote the high-quality development of the sports industry.

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In the context of global economic integration and digital transformation, the financial industry is facing an increasingly complex and changeable risk environment. With its powerful data processing and analysis capabilities, big data technology provides a new solution for enterprise financial risk management. This paper provides an in-depth analysis of the application of big data technology in enterprise financial risk management. However, big data technology also faces many challenges, such as data security and privacy protection, data quality and reliability, technology and talent bottlenecks, and laws, regulations and supervision. To address these challenges, this paper puts forward corresponding coping strategies, including strengthening technical means and management measures to ensure data security and privacy, optimizing data processing process to improve data quality, increasing investment in technology research and development and talent training and introduction, and improving laws and regulations and innovating regulatory mode. This study holds important theoretical and practical guiding significance for enterprises to effectively use big data technology to improve the level of financial risk management, and provides a useful reference for the stable development of the financial industry.

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