Amid the rise of the digital economy, online attention has emerged as a novel factor shaping urban development. Grounded in media function theory-particularly its surveillance function-this study conceptualizes online attention (OA) as an informational signal that influences urban economic behavior. A panel dataset covering 286 Chinese cities from 2011 to 2023 is employed, together with System GMM, quantile regression, mediation, and threshold models, to examine the effects of OA on urban economic performance. The empirical results indicate that OA exerts a significant and robust positive impact on GDP, with stronger effects observed in less developed cities. Firm location decision (FLD) serves as a mediating channel, while communication barriers and transportation connectivity act as contextual moderators conditioning the strength of this relationship. The findings provide empirical evidence and policy-oriented insights, extending the application of media function theory to the domain of urban economics.
This paper examines how import spillovers affect innovation efficiency across different innovation contexts in China by using a Chinese regional panel dataset from 2001 to 2020. The results indicate the coexistent of two opposing mechanisms of import spillovers: learning effects and adverse crowd-out effects. The import spillovers positively affect R&D efficiency and IPR protection positively moderates the relationship between import spillovers and R&D efficiency. Moreover, IPR and R&D efficiency present an inverted U-shaped relationship. By contrast, import spillovers negatively affect commercialization efficiency and IPR protection negatively moderates the relationship between import spillovers and commercialization efficiency. There is significant heterogeneity impact in different regions. These findings contribute to understanding the impact of IPR protection on innovation in emerging markets.
The relationship between Top management team (TMT) and corporate violations has long been a focus of both academic and practical attention. Using a sample of 4,671 listed companies from 2012 to 2024 in China, this paper examines the internal governance role of TMT faultlines in reducing corporate violations. The results show that TMT faultlines significantly impede corporate violations. In addition, corporate risk-taking level and managerial shareholding significantly moderate the relationship between TMT faultlines and corporate violations. High corporate risk-taking level further strengthens the moderating effect of managerial shareholding. This paper explores the internal governance role of TMT faultlines in controlling corporate violations and contributes to corporate governance literature by highlighting the importance of top management team configuration in reducing corporate violations.
We propose a novel hybrid framework that integrates stochastic volatility modeling with deep learning. The main contribution is a dual neural network architecture combining convolutional and LSTM networks (CNN-LSTM). This architecture learns and corrects pricing errors from the Heston model, and can optionally be enriched with GARCH-based time-varying volatility forecasts. The methodology involves three stages. First, the Heston model is calibrated using a genetic algorithm. Second, a GARCH model captures volatility dynamics over time. Third, a hybrid parametric model is built by integrating the CNN-LSTM network with the Heston framework (with or without GARCH predicted volatility). Results show that the hybrid Heston - CNN-LSTM model significantly lowers pricing errors and corrects systematic bias. Adding GARCH further enhances performance, especially for deep out-of-the-money options and under turbulent market conditions.
This paper investigates the impact of the 'Made in China 2025' pilot city policy on entrepreneurship, treating it as a quasi-natural experiment. The results show that the policy significantly boosts entrepreneurship in key sectors, with its effects being more pronounced in cities characterized by stronger institutional conditions and more developed financing environments. Heterogeneity analysis indicates that the effects are more pronounced in southern regions, areas with high manufacturing agglomeration, and cities with advanced industrial intelligence. Further analysis reveals that the policy enhanced entrepreneurial quality in key sectors and stimulated entrepreneurship in related industries. These findings provide empirical evidence on the effectiveness of 'Made in China 2025' and highlight the role of targeted industrial policies in developing economies.
Despite managing $3.8 trillion in assets, Islamic finance has failed to convert capital abundance into universal energy access across Muslim-majority countries. This PRISMA-based systematic review analyzes 89 peer-reviewed publications using bibliometric methods, socio-technical systems theory, and Multi-Level Perspective (MLP), evaluated against energy justice dimensions (distributional, procedural, recognition). Findings reveal critical publication-implementation gaps: academic output grew 347% while project financing increased only 23% (2015-2024), with no significant Granger causality (F = 1.82, p = 0.18). Citation concentration (Gini = 0.73) favors ESG correlations over energy access outcomes. Implementation analysis documents systematic failures across all justice dimensions: 73% urban project concentration despite 89% rural energy poverty; only 22% meaningful community participation; and average household reach of 1,200 versus 4,500 for conventional finance (p < 0.01). These patterns constitute a reproduction pathway producing symbolic responses without fundamental system change, carrying significant implications for SDG 7 financing reform.
This paper uses Chinese A-share listed firms on the Shanghai and Shenzhen stock exchanges from 2007 to 2024 as the research sample to investigate the effect of regional cultural diversity on corporate cost stickiness. The findings show that regional cultural diversity heightens cost stickiness, as validated by extensive robustness tests. Mechanism analysis reveals that cultural diversity amplifies cost stickiness by increasing adjustment costs, fostering managerial optimism, and raising agency costs. Moderation analysis demonstrates that digital transformation, social trust, and appointing local CEOs alleviate the detrimental impact of cultural diversity on cost stickiness. These results clarify the role of regional culture in shaping firm behavior, advance research on cultural diversity and cost stickiness, and offer practical recommendations for enhancing corporate cost management.
Company Law of the People's Republic of China 2023 represents the statute's most comprehensive overhaul to date. With respect to director liability, this amendment further elaborates the duty of loyalty and diligence. However, this reform is largely incremental: many provisions track earlier formulations and still leave key terms indeterminate. This article builds an original dataset of 2,021 cases alleging that directors harmed corporate or shareholder interests. It adopts a Regression Discontinuity Design, examining whether successive changes of statutory contexts have produced discernible influences in judicial outcomes. The empirical evidence reveals that the amendments of corporate law do not to strengthen the director accountability over time, which is reflected in win rate, compensation ratio, and explanation depth. These findings indicate that legislation, by itself, is insufficient to generate enough influence on director accountability. A more multifaceted regulatory strategy is required to establish a robust mechanism of director liability.
This study examines the impact of the Emission Trading System (ETS) on firms' cash flow volatility, using China's ETS pilot as a quasi-natural experiment. We employ difference-in-differences regressions on a sample of 3,714 listed Chinese firms in high carbon emission industries. The results show that the ETS significantly increases firms' cash flow volatility. However, this effect is heterogeneous across cohorts: firms in the 2013 pilot regions (Guangdong, Shanghai, Tianjin, and Beijing) exhibit no significant change, whereas those in the 2014 (Hubei and Chongqing) and 2016 (Fujian) cohorts experience significant, delayed, and positive effects. Further analyses indicate that research and development expenditure, environmental, social, and governance (ESG) performance, and board gender diversity (female on board) significantly and negatively moderate this relationship. Overall, the findings suggest that sustainability practices and gender diversity can help mitigate ETS-induced cash flow fluctuations, thereby providing important implications for policymakers and corporate managers.
This paper explores the promotion patterns of Qing dynasty officials using a manually constructed dataset based on the Draft History of Qing. It finds that older age at first appointment positively affects promotion likelihood, reflecting a bureaucratic preference for maturity and experience. The study also reveals that non-examination entry paths, Manchu identity, and political context significantly shaped promotion outcomes. These findings shed light on the institutional logic of Qing officialdom and offer insights for contemporary governance in developing countries.
This paper examines how AI-driven hiring can reconcile efficiency with fairness and social welfare by embedding ethical and ESG principles directly into economic optimisation. We develop an equilibrium model in which firms minimise recruitment costs and maximise match precision through a multi-stage algorithmic screening process. In the baseline, efficiency gains arise from shifting screening and adjustment costs onto applicants, which reduces participation, increases inequality, and lowers welfare. We introduce an ethical extension that incorporates three constraints. These are a firm cost-sharing floor, an applicant time cap, and a demographic parity condition. These preserve equilibrium uniqueness and tractability while aligning private optimisation with social objectives. The results show that ethical design transforms AI hiring from a narrow efficiency mechanism into a system of shared and sustainable value creation. The model provides a quantitative foundation for ESG-aligned governance and practical guidance for designing AI systems that are efficient, inclusive, and accountable.
This study aims to map the growth and trends of AI research in the financial sector over the past ten years through a bibliometric approach. Data were collected from Scopus and Web of Science, including as many as 2272 documents, and analyzed using bibliometric software to identify publication patterns, author collaborations, dominant keywords, and the evolution of research themes. The results show a significant increase in the number of publications since 2016 to peak in 2024. Countries such as China, India, the United States, and the United Kingdom dominate scientific contributions, while global collaboration continues to grow. This study also reveals research gaps, especially related to aspects of AI ethics, regulation, economic transformation, finance, business, technological innovation, sustainable development, and the adoption of AI by MSMEs. These findings provide a comprehensive picture of the dynamics of AI research in finance and serve as an important basis for future research and policy development.
Stablecoins facilitate large volumes of on-chain payments, raising urgent questions about stability and regulation. This paper reviews recent studies on the economic design of stablecoins and the determinants of their price stability. It also introduces a cross-country dataset covering 40 jurisdictions. Using hand-collected documents and an LLM-assisted evaluation, we score legislation, licensing, reserve requirements, disclosure, and currency restrictions. Then, we construct composite indicators of openness and risk containment. By linking these measures to institutional-quality data from the Quality of Government database, we discovered that stronger rule of law, protection of rights, and higher order and security are associated with more comprehensive and enforceable frameworks. This study expands the law-and-finance literature to include digital assets, providing global policy insights and lessons for sustainable financial development.
China's debt has surged significantly since the Global Financial Crisis (GFC), raising concerns about its long-term impacts. Numerous studies have examined various facets of China's debt. To better understand this issue, we reviewed over 120 scholarly papers from EconLit, published after the GFC, and categorized findings into five key areas: determinants, effects, costs, levels and sustainability, and other aspects. This review examines the key determinants and economic effects of China's three main debt components: corporate, government, and household debt. By synthesizing existing research, we aim to enhance understanding of China's debt landscape, provide actionable insights for Chinese policymakers and future researchers, and offer valuable lessons for other nations.
This paper investigates the effect of CEO overconfidence on corporate financialization and examines whether internal and external governance mechanisms moderate this relationship, using a sample of Chinese A-share listed firms from 2009 to 2019. The results show that firms led by overconfident CEOs exhibit significantly higher levels of financialization. Further analysis indicates that product market competition strengthens the positive influence of CEO overconfidence on financialization, whereas financing constraints weaken it. In contrast, corporate governance quality does not moderate this relationship. These findings deepen the understanding of managerial behavioral drivers of corporate financialization and offer implications for guiding firms toward real-sector investment and reducing financial risk.
Facing challenges in meeting its 2030 carbon peak goal, China's multifaceted dilemmas and hopes are revealed through data envelopment analysis (DEA), and panel data analysis, etc. Results show a positive correlation between CO2 emissions/electricity consumption and GDP. Electricity surges boost GDP but complicate carbon control. Pursuing GDP Granger-causes emissions growth, yet de-carbonization is feasible. Expanding green power in (semi-)deserts can maintain minimum economic growth while enhancing environmental payment capacity, offering a 'win-win' solution. Empirical findings support the environmental Kuznets curve (EKC) hypothesis, with proposed measures aiding its formation. Reforms may help foster a 'virtuous cycle' model between economic growth and emissions reduction.
This study examines how convertible bond issuance affects the stock performance of small-cap listed companies in China. By employing a multi-period Difference-in-Differences (DID) model and network analysis, it demonstrates the application of a diversified methodological framework in data science. We find that issuance significantly boosts returns and reduces volatility. This effect is attributed to eased financing constraints, heightened market attention, and improved transparency, with heterogeneity analysis revealing that factors including convertible dilution, financing costs, and capital intensity significantly moderate the stock performance. Non-state-owned and eastern-region firms are more sensitive. Network analysis shows that the correlation between convertible bonds and stocks in the same industry is the strongest, showing significant two-way spillover, and there are significant differences between different industries. In terms of spillover transmission effects, the two variables exhibit not only obvious time-varying characteristics but also strong correlations and systemic risks.
This study examines how spatial context influences the relationship between environmental performance (lower carbon emission intensity) and financial performance (higher profitability) in real estate investment trusts (REITs). Analyzing 375 REITs across 21 economies during 2017-2023, we identify a negative, non-linear relationship between carbon emission intensity and profitability. However, this relationship is significantly weaker for REITs headquarted in major urban agglomerations. We attribute this to three mechanisms: reduced environmental differentiation in dense markets, elevated operational costs, and systemic environmental externalities. In contrast, REITs outside agglomerations show a stronger negative relationship, driven largely by Scope 2 emissions. Our findings reveal the importance of geographical context in shaping green financial outcomes and highlight the need for spatially sensitive policy design. We also discuss how AI can enhance emission monitoring, hotspot identification, and resource optimization, strengthening the environmental-financial link in future real estate management.
This paper examines the moderating role of environmental, social, and governance (ESG) performance in the relationship between CO2 and greenhouse gas emissions and sovereign credit ratings in G20 countries. Our findings indicate that higher ESG performance is associated with lower emission levels and improved creditworthiness, suggesting that sustainability practices help mitigate environmental risks while strengthening rating credibility. The study contributes to the literature by highlighting ESG as a key channel through which environmental performance influences sovereign risk assessments. Empirically, ESG performance emerges as a positive signal for investors, encouraging more responsible behavior. From a policy and managerial perspective, the results emphasize the strategic importance of integrating ESG considerations into national and institutional frameworks to enhance sustainability and financial credibility.
