Traditional decision tree models, which rely exclusively on numerical variables, often encounter difficulties in handling high-dimensional data and fail to effectively incorporate textual information. To address these limitations, we propose the Integrated Multivariate Segmentation Tree (IMST), a comprehensive framework designed to enhance credit evaluation for small and medium-sized enterprises (SMEs) by integrating financial data with textual sources. The methodology comprises three core stages: (1) transforming textual data into numerical matrices through matrix factorization; (2) selecting salient financial features using Lasso regression; and (3) constructing a multivariate segmentation tree based on the Gini index or Entropy, with weakest-link pruning applied to regulate model complexity. Experimental results derived from a dataset of 1,428 Chinese SMEs demonstrate that IMST achieves an accuracy of 88.9%, surpassing baseline decision trees (87.4%) as well as conventional models such as logistic regression and support vector machines (SVM). Furthermore, the proposed model exhibits superior interpretability and computational efficiency, featuring a more streamlined architecture and enhanced risk detection capabilities.

Purpose The study investigates the impact of government intervention policy of capital markets (“National Team”) on firms’ sustainable management, i.e., green mergers and acquisitions (GMAs) in China, aiming to understand how such interventions influence corporate investment activities amidst a growing focus on green transition. Design/methodology/approach The research employs a dynamic analysis of quarterly data from Chinese companies (2014 Q1 to 2022 Q4), utilizing identified strategies, such as double machine learning-DID and multiple panel data regressions to assess the effects of government intervention on GMAs, and examines potential economic channels like liquidity, market stabilization, and informativeness. Findings The study finds that increased government intervention via direct stock purchases significantly boosts both the number and amount of GMAs, with economic significance of 23% and 45%, respectively. It identifies liquidity, market stability, and informativeness efficiency as underlying economic channels for this effect. Practical implications The findings suggest that government interventions can enhance corporate investment in green sectors, guiding firms to align strategies with sustainability goals. This can inform policymakers regarding the effectiveness of direct stock purchases in fostering a green economy, especially for large emerging countries. Social implications By promoting GMAs, government interventions contribute to green innovation and energy transition, ultimately benefiting society through enhanced environmental sustainability and compliance with eco-friendly regulations. Originality/value This research uniquely documents the direct effects of government stock purchases on corporate green financial activities, particularly GMAs, in a Chinese context characterized by tight credit, thereby expanding the understanding of government intervention in emerging markets.

This study investigates the impact of RegTech adoption in the M&A regulatory review process on deal performance. Leveraging the staggered implementation of the SOEs Online Supervision System (SOSS) by China’s State-Owned Assets Supervision and Administration Commission (SASAC) across its central and 31 provincial offices from 2018 to 2021, we find that SOSS directly enhances SASAC’s decision-making efficiency and improves its capacity to screen and approve higher-quality M&A deals. More importantly, SOE-led M&A transactions exhibit higher announcement returns as well as improved long-run stock and operating performance following the system’s implementation. The positive impact of SOSS is more pronounced for acquirers with stronger technological infrastructure, in transactions characterized by low transparency and weak governance, and in provinces with more stringent external scrutiny. Overall, by addressing regulator-firm information asymmetry and reinforcing managerial accountability, SOSS improves regulatory effectiveness in overseeing major investment activities among SOEs.

This paper examines how auction design can unintentionally facilitate bidder collusion in land market. Departing from the dominant view that attributes low land concession revenues to corruption, we highlight how features of auction structure enable bidder-side collusion, suppressing sale prices. Using a dataset of land auctions from 15 Chinese cities (2006–2016), we find that two-stage (listing) auctions are significantly more susceptible to collusion than one-stage formats. Empirical evidence shows that sales concluding at the (secret) reserve price occur disproportionately in two-stage auctions, even after controlling for land and market characteristics. We argue that the transparency and sequencing of two-stage auctions, while designed to enhance fairness, inadvertently reduce monitoring costs and facilitate tacit bidder coordination. Our findings underscore the need to jointly consider auction format and reserve price policy in designing land sales to enhance market efficiency and mitigate collusion risks.

We construct the most comprehensive bankruptcy database of Chinese firms to date and document significant real effects arising from the establishment of specialized bankruptcy courts. Specifically, the recovery rate for unsecured creditors increases by 38.6 percentage points after the reform. This improvement is not driven by shorter case durations or lower direct bankruptcy costs, as intuition might suggest. Instead, it results primarily from greater efficiency in the discovery and disposal of assets during bankruptcy proceedings. The reform also increases the likelihood of reorganization and promotes capital infusion in such cases. Higher recovery rates generate broader spillovers: reductions in non-performing loans, expansion of unsecured lending by local banks, relaxation of firms’ financial constraints, shifts in capital structure and investment, and greater public willingness to file for bankruptcy when distressed.

This study investigates the impact of Total Factor Productivity(TFP) growth in China's high-tech industry on household consumption, examining the distinct roles of labor and capital factor productivity from the perspective of biased technological progress. We innovatively construct a sequential proportional NDDF-Luenberger index. This index not only provides a theoretically consistent measure of TFP but also enables its precise decomposition into labor factor productivity and capital factor productivity, allowing for the quantitative identification of the degree and direction of technological bias. Our analysis yields three key findings. First, China's high-tech industry TFP evolved through a three-phase pattern of "surge–retreat–recovery," characterized by persistent capital-biased technological progress. Second, at the national level, improvements in overall TFP, labor factor productivity, and capital factor productivity all significantly promote household consumption, validating the theoretical pathway where supply-side efficiency gains stimulate demand. Third, significant regional heterogeneity exists: the Eastern region exhibits a "capital-led" growth pattern with weaker consumption effects from labor productivity; the Central and Western regions show "factor synergy," where both productivities contribute to consumption; whereas the Northeastern region suffers from a blocked transmission mechanism, where technological progress fails to significantly boost local consumption due to insufficient integration with the regional economy. By integrating supply-side TFP with demand-side consumption through the lens of biased technological progress, this research provides critical insights for fostering a virtuous cycle between innovation and domestic demand, offering valuable implications for industrial and regional policy design aimed at sustainable and inclusive growth.

This paper examines how economic policy uncertainty (EPU) affects mergers and acquisitions (M&As) between companies with different levels of financing constraints. Existing literature overlooks the interactive effect of EPU and financing constraints on M&As, and empirical evidence regarding EPU's influence on financially constrained firms remains limited. China's unique ownership structure provides a valuable context for this analysis, as state-owned enterprises (SOEs) face fewer financing constraints than private firms. Using a 2007-2021 sample of Chinese listed state-owned enterprises (SOEs) and private companies, we find that high EPU decreases the likelihood of private firms acquiring SOEs, while increases the likelihood of private firms being acquired by SOEs. These results suggest that under high EPU, financially constrained firms experience greater survival pressure, limiting their capacity to alleviate constraints by acquiring less-constrained targets. Conversely, less-constrained firms enhance their bargaining power and are more likely to acquire financially stressed counterparts. EPU facilitates control transfers from high-constraint to low-constraint firms, contributing to long-term market returns and improving financial market allocation efficiency. Our study contributes to the literature by shedding light on how EPU shapes divergent M&A behaviors based on firms’ financing constraints.

This paper investigates the causal impact of pre-trade transparency on the market liquidity of an over-the-counter-style market by leveraging a natural experiment in China’s interbank corporate bond market. We find that turnover, market liquidity, and aggregate bond returns significantly declined when the regulators unexpectedly suspended real-time quote dissemination in March 2023. Consistent with our expectation, these effects were mainly focused on interbank bonds, not exchange bonds, and bonds with lower credit ratings and longer maturities. This study contributes novel evidence to the transparency literature and provides insights for policymakers in emerging markets weighing the trade-offs between data governance and market efficiency.

To address the challenges posed by renewable energy integration in power systems, China is advancing the development of Pumped Hydro Storage (PHS). However, the rapid growth of PHS installations, coupled with strict regulations and a high reliance on capacity compensation, has led to increasing financial burdens on other utilities. One solution is to reallocate the capacity compensation through market-based approaches to implement the “beneficiary-pays” principle. To achieve this goal, an operational policy named ’partial-regulated dispatch’ is proposed in this study. The analysis of this policy encompasses two crucial dimensions: the dispatch mechanism and business models. The dispatch mechanism evaluates PHS’s capacity contribution to grid stability, while the business models focus on enhancing PHS profitability to reduce dependency on capacity compensation while ensuring long-term economic sustainability. Furthermore, the flexibility of PHS is introduced as a criterion for assessing system security contributions, considering both individual unit vibration characteristics and multi-unit commitment strategies. The case study shows that through partial-regulated dispatch, PHS can reduce its reliance on capacity compensation by nearly 50% while ensuring its regulation service via flexibility compensation. This policy effectively balances economic viability with system support capabilities. Moreover, flexibility compensation provides PHS operators with a risk mitigation strategy in the complex power market environment. Under an appropriate operational strategy and policy incentives, the flexibility can be enhanced by nearly 30% in a fully marketized scenario, contributing to both system stability and operational efficiency.

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.