As a leading brand of tea drink chain in China, in recent years, MIXUE Ice Cream Tea (MIXUE Bingcheng) has completed its industrial layout by rapidly expanding its stores by virtue of its advantages in the market. In the process of brand operation also based on price, supply chain management, franchise mode, and brand IP quickly become one of the important brands in China's milk tea beverage industry. Therefore, this paper analyzes MIXUE Ice Cream and Tea's strategic decisions (including price, supply chain, franchise model, and IP management) to find out the unique business model of MIXUE Ice Cream and tea and discusses the key factors that make it stand out in the fierce market competition. The analysis shows that MIXUE Ice Cream & Tea 's low price and efficient supply chain play an important role in its rapid expansion and market share growth, while effectively reducing operational risks and costs.

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This study explores the influence of investor behavior and market sentiment on asset pricing mechanisms in both developed and emerging market economies. By comparing markets such as the United States, Japan, Brazil, and India, the research investigates how psychological factors, including overconfidence, loss aversion, and sentiment, affect asset returns and market volatility. Data spanning 10 years (2010-2020) is analyzed, incorporating traditional financial indicators, macroeconomic factors, and sentiment data derived from social media, news platforms, and sentiment indices. The empirical findings reveal significant heterogeneity across markets. In emerging markets, investor sentiment demonstrates a more pronounced effect on asset pricing, with sentiment fluctuations contributing significantly to volatility. In contrast, developed markets like the U.S. and Japan exhibit more stability, with investor behavior driven largely by fundamentals. A new sentiment resonance model is developed to capture the spillover effect of sentiment from developed to emerging markets, while behavioral finance models are enhanced to account for the emotional transmission between investor decisions and asset prices. The study suggests that incorporating behavioral insights into traditional asset pricing models can improve their explanatory power, particularly in emerging markets where investor sentiment plays a pivotal role in shaping asset prices.

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In recent years, the digital economy has been booming, and digital transformation has become an important development model for enterprises. In the automotive field, BYD's digital transformation has been advancing steadily. Through various channels and strategies, it has achieved the efficient construction of a new management data governance system. This article uses case analysis to analyze the problems encountered in BYD's digital transformation process and its problem-solving ideas, and explores the possible future development paths of BYD. Thus, six advantages of BYD after its digital transformation are concluded: improving the operational efficiency of the enterprise, optimizing products and services, enhancing the enterprise's competitiveness, promoting the coordinated development of the industry, achieving mutual assistance and interconnection within the industry, and facilitating sustainable development. Moreover, the transition from electrification to intelligence is also an important turning point for BYD's future development. It is necessary to actively seek transformation approaches based on the industry characteristics and resource conditions of the automotive manufacturing industry, and formulate a digital transformation strategic plan suitable for the long-term development of the enterprise, so as to achieve the digital and intelligent transformation of the value chain.

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This study analyzes the effects of collective investor behavior on systemic risk in financial markets using principles from behavioral finance. The research investigates how investor sentiment and emotional reactions together with herding behavior affect market instability during different stages of financial crises. Data analysis from the 2007-2009 Global Financial Crisis (GFC) lets us investigate the effect of irrational investor behavior on market volatility and systemic risk. The study analyzes important financial indicators such as stock market returns and volatility indices along with credit default swap spreads which are compared with sentiment data gathered from social media networks. Investor herd actions combined with overreactions to news events create market instability because stock market behavior moves away from economic fundamentals according to our analysis. This research advances understanding of how collective actions of investors create irrational market patterns and worsen financial crises. The study suggests ways to manage systemic risk with regulatory policies that include behavioral insights within financial regulation structures.

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