Corporate digital transformation, primarily driven by data and leveraging digital technologies and mathematical algorithms such as Internet+, big data, cloud computing, artificial intelligence, and blockchain, is a crucial enabler of sustainable development. This transformation integrates various aspects of corporate production and operations, enhancing the level of digital operations and ultimately contributing to high-quality and sustainable development. This paper, based on data from listed companies in China’s A-shares from 2007 to 2021, theoretically articulates the intrinsic mechanism between corporate digital transformation and corporate governance level, with a focus on sustainability. It empirically finds that a higher degree of digital transformation correlates with an improved level of corporate governance, fostering sustainable practices. Further investigation reveals that digital transformation elevates corporate governance by enhancing innovation capabilities, reducing information asymmetry, and promoting sustainable strategies. This paper provides policy insights for promoting corporate digital transformation as a means to achieve sustainability goals and optimizing management’s corporate governance level for long-term sustainable success.

The authors investigate the link between noninvestors and financial returns using data from a social media platform.

This study investigates the integration of non-economic policies into the framework for assessing macroeconomic coherence as applied by the Chinese government, with a particular focus on green policies. We examine the impact of non-economic factors on social disagreement and investor disagreement (expectations), and how these influences interact with macroeconomic regulation, employing both empirical evidence and dynamic stochastic general equilibrium (DSGE) theoretical models. In the basic analysis section, we merge statistical data on social divergence with policy implementation, utilizing multiple regression and deep neural network models. Our findings provide direct evidence that non-economic policies significantly regulate social sentiment. Additionally, theoretical analyses using contagion models, grounded in real textual data on social and investor divergence, demonstrate that expectations of social sentiment can ultimately affect economic variables. In the extended analysis, we enhance the classic DSGE model to delineate the pathways through which non-economic policies impact the macroeconomy. Drawing from our analyses, we propose specific optimization measures for non-economic policies. The results indicate that targeted policy optimization can effectively manage social disagreement, thereby shaping expectations and harmonizing non-economic with economic policy initiatives. This alignment enhances the coherence of macroeconomic policy interventions. The innovative contribution of this study lies in its provision of both theoretical and empirical evidence supporting the formulation of non-economic policies for the first time, alongside specific recommendations for improving the consistency of macroeconomic policies.