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.

This study applies the generalized dynamic factor model (GDFM), TVPVAR-DY framework, and pattern causality to investigate spillover effect from international commodity idiosyncratic volatility co-movements to China's financial market risk, as well as the impact of a series of macroeconomic factors on such spillover effect. The empirical results indicate that the idiosyncratic volatility co-movements of energy, industrial metals, precious metals, soft commodities, and agricultural products all have significant spillover effects on China's financial market risk. The influence of commodity idiosyncratic co-movements on China’s financial market risk is relatively stable under normal economic conditions but intensifies significantly during periods of deteriorating economic fundamentals. Macroeconomic factors such as international capital flows, investor sentiment, geopolitical risks, economic conditions, and international freight rates predominantly exhibit a positive causal effect on the dynamic spillover effect.

With the accelerating global aging population, the prevalence of cognitive impairments, particularly Alzheimer’s disease and related dementias, is rising steadily, giving rise to a substantial and rapidly expanding market for memory services. This review aims to systematically examine the core development trends, driving factors, innovative service models, and challenges within the memory services market in the context of the aging economy. It provides a comprehensive analysis of the entire industry chain, spanning early screening, diagnosis, non-pharmacological interventions, long-term care, and technological support. By integrating the latest business models, policy directions, and evolving consumer demands, this article explores future development trajectories and investment potential in the memory services sector. The insights offered herein are intended to support practitioners, policymakers, and researchers engaged in this critical field by delivering an in-depth understanding of current market dynamics and emerging opportunities.

While observational studies have long suggested a positive correlation between social relationships and online transactions, surprisingly little research demonstrates a causal link. Effects identified in observational data generally conflate the Information effect, which bears the counterfactual causal interpretation, with the Homophily/environment effect. Against this background, this study conducted a pioneering a randomized field experiment design to isolate the Information effect of friendship disclosure from confounding homophily factors. We exploit a rare opportunity to conduct a field experiment on a large Chinese online second-hand platform, in which we manipulate buyer and seller’s awareness of their preexisting friendship ties. We provide the first empirical evidence that the effect of revealing friendship information between transaction parties turns out to be insignificant. We demonstrate that reliance on observational estimates of the “total effect” of friendship significantly overstates the benefits of providing friendship information in online marketplaces. Our findings contribute to a better understanding of social commerce and highlight the potential fallacy of relying on observational data in business studies.

This study examines how firm-specific characteristics and monetary tightening influence the composition and dynamics of trade credit received by Chinese listed firms. Using panel data, the analysis distinguishes among three sources of trade credit: related parties, non-related parties, and controlling shareholders. The findings reveal a clear asymmetry in firms’ financing responses to monetary tightening: while trade credit from non-related parties declines, credit from related parties—especially controlling shareholders—increases. This underscores the strategic role of intra-group financing in buffering firms against external financial shocks during periods of constrained liquidity. Moreover, firm-specific factors such as size, profitability, market power, and ownership have differing effects depending on the source of trade credit. These effects are most pronounced when the credit is extended from controlling shareholders, reflecting the influence of intra-group trust and reduced information asymmetries. The results also highlight a substitute relationship between bank credit and trade credit, which weakens when trade credit is sourced from related parties and disappears entirely in the case of controlling shareholders. By shedding light on the distinct mechanisms of intra-group trade credit in China’s underdeveloped financial system, this study contributes to a deeper understanding of corporate financing strategies of Chinese firms.

Prefabricated buildings(PBs) have significant advantages in improving construction efficiency, saving resources, and reducing environmental pollution. They have become an important direction for transforming and upgrading the global construction industry. However, the high construction costs have severely restricted their large-scale adoption. To systematically explore the key influencing factors and the mechanism of the construction cost of PBs, this study uses the method of combining interpretative structural model (ISM) and structural equation model (SEM), identifies the main influencing factors by synthesizing literature and data analysis, analyze hierarchical relationships between these factors via ISM, and quantifies the influence intensity and mechanism of the construction cost by SEM method. The results show that the driving factors of the construction cost of PBs can be divided into several levels. The core factors, such as the assembly rate, the production scale of prefabricated components, the integration of design management, the technical level of designers, and the specialization of prefabricated components in the factory, play a crucial role in cost optimization. In conclusion, this study deeply reveals the impact mechanism of the construction cost of PBs, offers practical guidance for reducing construction costs and optimizing resource allocation, and provides a scientific basis for government policy-making and enterprise strategic decision-making.

Climate change presents a global threat, prompting nations to adopt low-carbon development pathways to mitigate its potential impacts. However, current research lacks a comprehensive framework capable of integrating multiple variables and providing dynamic optimization capabilities. This article focuses on designing pathways for developing a low-carbon economy to tackle climate challenges. Specifically, we construct a low-carbon economy model that incorporates economic, environmental, social, energy, and policy factors to analyze the drivers of economic growth and carbon emissions. We utilize economic model predictive control and tracking model predictive control to optimize development pathways aligned with various low-carbon targets, creating and validating a comprehensive framework for low-carbon policy design using historical data from China. This study highlights significant advantages in analyzing low-carbon pathways through advanced techniques like hierarchical regression and model predictive control, providing a robust framework that enhances our understanding of causal relationships within the LCE system, captures system feedback, dynamically optimizes pathways, and accommodates diverse policies within a comprehensive low-carbon economy system.

We revisit cross-asset time-series momentum (XTSM) and single-asset time-series momentum (TSM) in China's stock and bond markets. With a fixed-effects model, we find a positive momentum from bonds to stocks and a negative momentum from stocks to bonds, with both momentum persisting for no more than six months. By employing a cross-grouping method, we find that the choice of lookback periods and asset signals impacts the performance of XTSM and TSM. A comparison between XTSM, TSM, and time-series historical (TSH) portfolios reveals that XTSM outperforms in small/midcap stocks and government bonds, while its performance is weak in large-cap stocks and corporate bonds. A spanning test confirms that XTSM generates excess returns that other pricing factors can not explain. XTSM is more prone to momentum crashes. Increased market stress has similarly adverse effects on XTSM and TSM. Furthermore, Market illiquidity, IPO counts, new investor accounts, and consumer confidence index positively correlate with the returns of XTSM and TSM portfolios, while IPO first-day return and turnover rate correlate negatively. The effects of these sentiment indicators exhibit heterogeneity.

This paper examines the impact of Chinese local government hidden debt on corporate ESG greenwashing. Extending fraud theory, we reveal that hidden debt shifts the boundary between government and market that drives the factors behind ESG greenwashing. Using the ESG greenwashing indicator of listed firms in the A-share market and the hidden debt-to-GDP ratio of 31 provinces from 2012 to 2023, we find that local government hidden debt is positively correlated with corporate ESG greenwashing. The impact is more significant for firms that are state-owned, without active primary-level Party organizations, or not on China’s key pollution supervisory list. Mechanism analysis indicates that expansion of local government hidden debt brings firms with higher LGFVs’ share-holding for the SOEs, heavier environmental tax burden, and less social responsibility preference, all of which are related with ESG greenwashing. Reducing local government special debt and improving tax compliance can help alleviate this impact. These findings highlight the necessity of fiscal risk management in achieving genuinely sustainable corporate development.

The relationship between ESG factors and corporate performance is contentious, partly due to the literature's neglect of organizational demographic differences. Using data from 5,127 Chinese companies (2009-2022), we empirically analyze ESG's impact on corporate performance, factoring in the demographic heterogeneity of executive teams. Our findings indicate that although ESG indeed enhances corporate performance, its conversion effect is significantly influenced by the vertical dyads of gender and education within the top management teams (TMT). Additionally, our extended analysis reveals that these two types of vertical dyads exhibit distinct structural characteristics.