Utilizing data from Chinese A-share listed companies, this study investigates the effects of digital transformation (DT) on total factor productivity (TFP) and the moderating function of ESG performance. The results indicate that DT boosts TFP, but ESG performance negatively moderates this effect, revealing the green paradox. A dynamic model of factor allocation efficiency shows that DT improves capital allocation by reducing financing constraints, information asymmetry, and enhancing operational capacity. However, ESG weakens the positive link between DT and operational capacity, thus diminishing its impact on TFP. Similarly, DT increases labor productivity, but ESG undermines this effect by weakening the link between DT and labor efficiency. The positive impact of DT is stronger when firms focus on ‘Practical Application Technologies’ rather than ‘Underlying Technologies’. This effect is especially evident in smaller, asset-intensive, non-state-owned firms, and those located in the Beijing-Tianjin-Hebei region. Additionally, ESG’s negative moderation is more pronounced where DT exerts a stronger positive influence. A notable distinction emerges: asset-intensive firms gain more from DT in terms of TFP, whereas ESG’s adverse effect is stronger in labour-intensive firms. This study offers a novel perspective on the interplay between DT, ESG performance, and productivity. It provides valuable insights for firms seeking to align digital strategies with ESG goals, thereby fostering technological innovation alongside sustainable development.

This paper investigates how institutional investors’ site visits affect firm productivity by using a dataset of China’s A-share listed firms. The findings reveal that site visits have a constructive effect on firm productivity. Moreover, mechanism analysis indicates that reducing information asymmetry and improving stock price informativeness are two channels through which site visits influence firm productivity. Heterogeneity analysis demonstrates that the nexus between site visits and firm productivity is more pronounced for non-state-owned firms and firms with intenser product market competition. Overall, this study brings new insights into the benefits of site visits and highlights the importance of investor activism.

The impact of Artificial Intelligence (AI) on firm performance is an emerging issue in both practice and research. However, discussions surrounding the effect of AI on productivity are enshrouded in a paradoxical quandary. This study examines the relationship between AI implementation and total factor productivity (TFP), considering the moderation effects of digital infrastructure quality, business diversification, and demand uncertainty. Using data from 2155 Chinese firms over 2016-2021, our empirical analysis reveals a nuanced pattern: while moderate AI implementation achieves the best TFP, excessive and insufficient implementation yields diminishing returns. The curvature of this inverted U-shaped relationship flattens with higher levels of digital infrastructure quality but steepens when firms undertake diversified businesses and face heightened demand uncertainty. The findings suggest that the impact of AI on TFP is not universally beneficial, and the relationship between AI and TFP varies across different contexts. These findings also provide implications on how firms can strategically implement AI to maximize its value.

This study examines how housing purchase restrictions (HPRs) affect firms' robotics adoption through labor cost increases. Exploiting policy-driven housing price shocks across Chinese cities, we find firms significantly accelerate robot adoption in response to higher labor costs. Effects are pronounced among financially unconstrained firms, state-owned enterprises, and firms with skilled or educated workforces. Automation investments subsequently improve firm productivity, profitability, and market positions. Our findings highlight unintended spillovers from housing regulations to firm-level technological decisions and suggest policymakers consider these indirect effects when designing local market interventions.

We study the effect of China’s inland-favoring land policy on firm-level productivity by employing a research design combining difference-in-differences and regression discontinuity at the policy border. We find that the inland-favoring land policy decreased the firm productivity gap between developed (eastern) regions and underdeveloped (inland) regions. The relative changes are mainly due to slower eastern firm productivity growth rather than faster inland firm productivity growth. Eastern firms reduced their R&D expenditure and capital usage as a response to the policy.

This study analyzes the network structures of institutional shareholders and examines the influence of institutional investor cliques on corporate innovation. Our empirical results reveal that institutional investor cliques significantly enhance both innovation input and output. To mitigate endogeneity concerns and establish causality, we adopt multiple empirical strategies. Further evidence suggests that the beneficial impact of institutional investor cliques on firm innovation can be attributed to increased innovation investment efficiency, enhanced employee productivity, reduced information asymmetry, and decreased managerial myopia. Additionally, we find that the positive effect of institutional investor cliques on firm innovation is more pronounced in non-state-owned enterprises and is particularly evident in firms with severe agency conflicts, CEO duality issues, highly competitive product markets, and for firms that have low stock liquidity.

Fintech has significantly influenced the traditional financial industry by introducing advanced technologies and innovative business models with profound impacts. We aim to study the effect of Fintech development on labor allocation efficiency, and to explore its underlying mechanisms. Using a set of companies on Chinese A-share market over the years of 2011- 2020, we find that Fintech development plays a positive role in labor allocation efficiency, mainly through suppressing labor overinvestment. This positive effect is further reinforced by market competition. In addition, our investigation reveals that the primary pathways through which Fintech enhances labor allocation efficiency are lowering information asymmetry, mitigating agency issues and substituting low-skilled labor. Moreover, we show that the dimensions of depth and digitalization are particularly important in improving labor allocation efficiency among the three dimensions of Fintech development. Lastly, we find that Fintech development enhances total factor productivity by improving labor allocation efficiency.

The literature has extensively explored the relationship between trade and envi-ronment, with most studies focusing on how trade affects the environment. However, our research takes a different approach by examining how air pollution affects firms’ exports. We use Chinese export and pollution data from 2000 to 2007 at the firm and county levels. By using fine particulate matter (PM2.5) concentrations as a proxy for air pollution and employing thermal inversion as an instrumental variable, we ffnd that a 1% increase in PM2.5 leads to a 0.89% reduction in firms’ exports. We also observe this negative effect of air pollution on entry and exit (i.e., extensive margins). Our mechanism analysis identiffes two channels through which air pollution affects exports. First, air pollution decreases exports by reducing firm productivity. Second, air pollution induces stringent environmental regulations, which reduces exports as firms need to increase abatement costs or reduce production to meet the environment standards.

Forming diversified global supply chains (GSC) is an important approach to improving economic resilience. When firms expand their oversea suppliers for such purposes, information friction is a major challenge, and internetization may help firms cope with it by more efficient communication of information. We introduce a dynamic discrete choice model for firms’ searching for new supplier sources estimated with structural methods, and construct counterfactual studies to analyze the internetization effects on Chinese firms’ GSC diversification. Our quantitative studies reveal that internetization relieves information friction, which reduces firms’ searching costs by 13.4%, and thus significantly diversifies firms’ GSC. It also raises firms’ productivity by 0.5% through efficient communication of information. Reductions in searching costs are revealed as the main channel of such effects of internetization, while the productivity channel is less significant. Moreover, the internetization effects on diversifying GSC are persistent over time, and are biased towards high-productivity and importing firms.

Facing external shocks, maintaining and stabilizing imports is a major practical issue for many developing countries. We first document that sourcing market switching (SMS) is widespread for Chinese firms (For 2000-2016, SMS firms account for 76.29% of all import firms and 96.30% of total import value). Then we use Chinese firm-level data to show that SMS can significantly mitigate the negative impacts of international uncertainty on imports, which further stabilizes firm employment and innovation, leading to increases in national and even world welfare. Possible motivations for SMS include stabilizing import supply, lowering import tariffs, raising the real exchange rate, and increasing product switching. We also find that the effects of SMS vary by the type of uncertainty, firm ownership, productivity, credit constraints, trade mode, and product features.