This study takes the US-China trade frictions in 2018 and 2025 as the research background, comparing the characteristic differences between the two frictions, and analyzing the transmission effects of the two frictions on the prices of four types of assets: stocks, bonds, gold, and foreign exchange. At the same time, a basic regression model is employed for quantitative testing of influencing factors. The study finds that during the two periods of friction, the responses of various assets exhibited systematic differences, and variables such as policy intensity, panic index, interest rates, US-China Treasury yield spread, and the level of economic prosperity showed changes in direction or magnitude in their impact on asset prices in both frictions. Finally, based on the research findings, the paper provides corresponding asset allocation recommendations.

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This paper mainly examines whether artificial intelligence (AI) can really improve the efficiency of financial accounting work, and why accountants are still required to verify its outputs and provide necessary supervision. To address these issues, this study reviews academic papers and reports published by professional institutions. Based on these studies, AI has been shown to perform repetitive tasks that follow fixed procedures. In addition, it can process large volumes of transactions, detect potential errors, and use historical data to forecast future sales or cash flows. Thus, AI reduces the time accountants spend on manual processing, thereby enabling them to allocate more time to analyzing financial information and generating valuable business insights. However, if the data provided by the company is incorrect or incomplete, the results may also be inaccurate. Moreover, financial records may contain private information, such as bank details, employee salaries, and customer data. As a result, AI should assist accountants rather than replace them. In this process, accountants still need to verify AI-generated results, review relevant information, make judgments based on the company's actual situation, and take responsibility for final decisions.

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The rapid development of generative artificial intelligence (AI) has created new opportunities for digital marketing, particularly in short video advertising. However, consumer acceptance of AI-generated advertisements remains uncertain because of the concerns over authenticity, trust and emotional connection. This study investigates how consumers respond to short video advertisements created by AI and humans through comparing evaluations and identifying factors that influence engagement intention and purchase intention. A quantitative survey was conducted with 179 participants, where respondents evaluated both advertisement formats. Reliability analysis, multiple linear regression models, paired samples t-tests, and qualitative analysis of open-ended responses were applied. The results show that human-created advertisements received much higher evaluations in authenticity, trust, visual appeal, professionalism, engagement intention, and purchase intention, while informativeness showed no significant difference. Regression results further indicate that trust is the strongest factor influencing consumer responses towards AI-generated advertisements. These findings indicate that businesses should balance AI efficiency and human creativity to improve consumer acceptance and advertising effectiveness.

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With the full implementation of the Rise of Central China strategy, foreign investment in the region has shifted beyond traditional manufacturing and expanded into services, emerging as a notable driver of provincial economic growth. Even so, how far foreign capital can lift the service industry depends on local conditions, above all infrastructure and service industry employment levels. Whether these conditions translate into tangible effects in Hubei Province, however, remains an open empirical question. This paper selects statistical data of Hubei Province from 2007 to 2021, and constructs an Ordinary Least‑Squares (OLS) model to study the impact of Foreign Direct Investment on the development of service industry in Hubei Province. The results show that foreign direct investment has a significantly positive effect on the growth of service industry in Hubei Province when the infrastructure variable is not controlled. The positive effect of foreign capital remains statistically stable when controlling for the service industry employment scale. In the full specification model, after the infrastructure variable is incorporated, the independent contribution of foreign direct investment becomes insignificant, and infrastructure turns out to be the core driver of service industry development. Therefore, Hubei Province should further expand opening-up, rationally introduce foreign direct investment, increase investment in transportation infrastructure, optimize the employment structure of service industry, and promote the high-quality development of service industry.

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