Volume 180

Against the backdrop of rapidly accelerating digital transformation, corporate performance in the areas of Environment, Social and Governance (ESG) has become a key indicator of corporate sustainability and long-term competitiveness. This paper explores the intricate mechanism of digital transformation on corporate ESG performance, utilizing the data of Chinese A-share listed companies from 2013 to 2023. By constructing a two-path analytical framework and a panel regression model, this study finds that corporate digital transformation significantly enhances the overall corporate ESG performance through the mediating channels of alleviating financing constraints and strengthening government regulation. The impact is particularly prominent among state-owned enterprises and firms with relatively low market competitiveness. The results provide a theoretical basis for policy makers to optimise the efficiency of resource allocation. They also offer practical guidance for enterprises to implement differentiated digital transformation strategies, which is of practical guidance value for regions with high financing constraints and policy-supported industries.

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In the information age, the impact of news media and social media on the stock market is becoming increasingly significant. This paper analyzes the influence of news and social media on the stock market from the perspectives of the information transmission chain, emotional differences, sentiment analysis techniques, and AI applications. Through a review of the literature, it is proved that the inventors’ behavior will be influenced by their emotions, which will be easily affected by the information they receive from the news and social media. It is found that by utilizing AI models and sentiment analysis techniques, emotions can be transformed into quantifiable data, which can be applied to more accurate stock price prediction systems, resulting in more precise stock price and trend forecasts. However, there are still many issues, such as information overload and overreaction to information, which can influence inventors’ behavior and cause redundancy in the accuracy of predictions. It is suggested that future research can focus on mitigating these factors and improving prediction accuracy.

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Consumption is both the starting point and ultimate driver of economic growth. Against the backdrop of invigorating domestic demand and intensified market competition, the importance of consumer behavior research has become increasingly prominent. Within this field, the POM model highlights the combined influence of Personal Perception (P), Others' Evaluation (O), and Marketing (M) on purchasing decisions. To explore the dynamic mechanisms of these influences, this study integrates Qualitative Comparative Analysis (QCA) with Generalized Structural Equation Modeling (GSEM), conducting empirical analyses using small-sample questionnaire data and large-sample e-commerce platform data, respectively. QCA results reveal three matching configurations in smartphone purchase decisions: rational decision-making type, brand-influenced type, and comprehensive consideration type. The GSEM regression further confirms the significant and nonlinear positive impact of personal perception on purchase behavior, while the direct effects of others' evaluation and corporate marketing are not statistically significant. The findings indicate that in generalized scenarios, consumers tend to rely more on their own information processing abilities, forming a rational decision-making dominant pattern. Based on this, it is recommended that companies optimize core product performance and enhance information accessibility pathways, while also exploring the synergistic effects between marketing strategies and user perception. This research offers new perspectives for both consumer behavior theory and practical application.

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