Purpose: High investment efficiency is a key dimension of high-quality enterprise development. As critical nodes embedded in supply chain networks, corporate investment behaviors are profoundly shaped by the structural characteristics of their supply chains. Concentrated supply chain configuration, as one of the core structural features, has not yet been systematically examined in terms of its impact on corporate investment efficiency and the underlying mechanisms, leaving an important research gap. Design/methodology/approach: Based on a sample of China’s A-share listed enterprises from 2007 to 2023, this study empirically examines the effect of concentrated supply chain configuration on corporate investment efficiency. Findings: First, concentrated supply chain configuration exerts a significant inhibitory effect on corporate investment efficiency, a conclusion that remains robust after a series of tests. Second, mechanism tests indicate that this influence operates primarily through three channels: exacerbating financing constraints, crowding out working capital, and deteriorating the information environment. Third, heterogeneity analysis shows that both supplier concentration and customer concentration inhibit investment efficiency, with the latter having a slightly stronger negative effect. The adverse impact is more pronounced in over-investing enterprises, non-state-owned enterprises, smaller firms, and those in growth or decline stages. Furthermore, regional factor market development, external market power, and internal control quality are found to effectively mitigate the negative effect of concentrated supply chain configuration on corporate investment efficiency. Originality: This study extends the research on determinants of corporate investment efficiency from a supply chain structure perspective, providing new theoretical insights and empirical evidence for understanding corporate investment behavior in China.

This paper examines the role of institutional investors in shaping pricing dynamics within China’s nascent infrastructure Real Estate Investment Trust market. Introduced in 2021, China’s REITs have rapidly gained policy and market attention as a tool for financing large-scale infrastructure projects through equity-based securitisation. Unlike mature REIT markets, China’s infrastructure REITs are characterised by a high concentration of institutional ownership dominated by state-owned financial institutions. Using panel data on first 9 REITs from May 2021 to April 2024, we find that institutional ownership significantly boosts the premium to net asset value. This effect operates primarily through two channels: reduced market liquidity and increased idiosyncratic return volatility, likely reflecting institutions’ trading activity and informational advantages. The findings highlight how institutional capital serves as a confidence signal in China’s emerging REITs ecosystem. The study contributes to the global REITs literature by offering insights from an emerging market context and provides policy recommendations to guide China’s REITs market development toward greater transparency, diversity, and long-term resilience.

This study employs a Triple-Difference (Triple-DID) model, utilizing balanced panel data at the district level from Beijing, Shanghai, Shenzhen, and Hangzhou between 2018 and 2024, to critically evaluate the effectiveness of the Multi-School Zoning Policy (MSZP) in suppressing the capitalization of educational resources into housing prices and promoting educational equity. The research explicitly accounts for spatial and institutional heterogeneity as well as household strategic behavior.The results indicate that: (1) MSZP significantly reduced the average housing price premium associated with elite school districts by 15.2%, with the strongest effect observed in Beijing and the weakest in Hangzhou; (2) The policy's effectiveness diminishes as the spatial concentration of high-quality educational resources increases, highlighting persistent structural inequalities; (3) In areas characterized by resource monopolization and strong institutional inertia, the policy's suppressive effect on educational capitalization and its gains in educational equity are both constrained.The findings suggest that MSZP alone cannot fully overcome the "spatial lock-in" effect of high-quality educational resources. Achieving lasting equity requires complementary deeper institutional innovations, such as robust cross-district teacher rotation, transparent resource allocation mechanisms, and adaptive zoning algorithms. This research offers quantitative evidence for optimizing policy and institutional tools in the pursuit of comprehensive urban education reform.

We construct a Housing Purchase Intention Index (HPII) using the Baidu Search Index, which captures online search behavior directly reflecting households’ housing purchase intentions. We assess the predictive power of the HPII for the growth rate of housing transaction volume and further examine factors influencing housing purchase intention. The results show that the HPII has significant predictive ability and enhances real-time forecasting accuracy, highlighting the role of search behavior as a behavioral signal in the housing market. We also find that housing purchase intention is shaped by policy, economic, demographic, and supply factors. Specifically, purchase restriction policies exhibit an inverted U-shaped effect; moderate mortgage-rate hikes dampen purchase intention, while persistent increases may induce anticipatory buying. In addition, rising wages, increasing population concentration, and expanded residential land supply consistently strengthen housing purchase intention. These findings provide new behavioral evidence on the drivers of housing demand and underscore the value of search-based indicators for understanding household decision-making in the real estate market.

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.

Based on the sample data of Chinese listed companies, this paper finds that the increase in customer concentration significantly reduces the level of enterprise employment. The research results are robust to a series of tests. Further analysis shows that the increase of financing constraints, the increase of enterprise risk and the decrease of profitability are the mechanism of customer concentration affecting enterprise employment. In addition, the negative correlation between customer concentration and enterprise employment is stronger for enterprises with small size, fierce industry competition, and increasing economic policy uncertainty.

Recently, the Chinese Government has strengthened the enforcement of bankruptcy laws to protect creditors’ rights. This study shed light on the effect of creditor protection on asset-debt maturity mismatch by employing a quasi-natural experiment in China. The results show that creditor protection mitigates maturity mismatch, and the effect is more pronounced among financially constrained firms. Results remain robust after the dynamic effects test, placebo test, propensity score matching approach, entropy balancing method, and controlling for COVID-19 shocks. Mechanism tests show that creditor protection decreases the cost of debt and reduces over-investment. The effect of creditor protection is pronounced in private companies, financially independent companies, and companies with secured loans. Creditor rights can alleviate maturity mismatch in firms with medium ownership concentration and managerial ownership levels. Economic consequences studies suggest that creditor protection reduces corporate default risk. This study reveals the mechanism and effect of creditor protection on asset-debt maturity mismatch in emerging markets, providing recommendations to policymakers for assessing and improving bankruptcy law regimes.

We examine the relationship between customer concentration and capital structure adjustment speed using a sample of US listed firms from 1977 to 2020. We found that the customer-concentrated firms have a lower speed of leverage adjustment. Customer concentration affects leverage adjustment speed mainly through increased cash flow volatility and asset specificity. The negative association is more pronounced in firms with high relationship-specific investments and low switching costs for their customers. Stock market reacts to leverage deviation strongly for firms with concentrated customers. Our findings highlight the vital role of customers as key stakeholders in capital structure decisions.

We study how investor composition is related to future return, trading volume, and price volatility in the cross- section of the music-content non-fungible tokens (music NFTs). Our results show that the breadth of NFT ownership negatively predicts weekly collection-level median-price returns and trading counts. In contrast, ownership concentration and the fraction of small wallets are positive predictors. The fraction of large NFT wallets is a bearish signal for future collection floor-price returns. Investor composition measures have weak predictive power on price volatility. Further analysis indicates that an artist’s Spotify presence moderates the predictive power of investor composition for future NFT returns and trading volume, consistent with the notion that reducing information asymmetry helps improve price efficiency.

Comprehensive evaluation and identification of the critical regulatory determinants of carbon emission efficiency (CEE) are very important for China’s low-carbon transition. Accordingly, this paper first employs an undesirable global super-hybrid measure approach to calculate the CEE of China’s iron and steel industry (ISI). We then further use spatial error and threshold regression models to examine the spatial and non-linear effects of heterogeneous environmental regulations on CEE, respectively. Our empirical results show that (1) CEE varies significantly across China’s regions, with the eastern region having the highest CEE score, followed by the western and central regions, with the northeast region ranking the lowest; (2) command-and-control and market-incentive regulations both promote CEE, whereas the public participation approach does not significantly contribute to performance gains; (3) all three types of environmental regulations exhibit a non-linear threshold effect on CEE; (4) openness level, technological progress, and industrial concentration enhance efficiency gains, while urbanization level exerts a negative impact on CEE. Our findings have important implications for the design of environmental regulations.