With the rapid development of financial technology, the liquidity of commercial banks has undergone tremendous changes. Based on this, this paper comprehensively combs through a number of relevant core literature at home and abroad, discusses the impact of financial technology on the liquidity risk of commercial banks, the mechanism of financial technology on the liquidity of commercial banks, summarizes relevant research conclusions and puts forward corresponding suggestions. The results show that most scholars believe that fintech can increase the liquidity of commercial banks, improve the level of liquidity creation and reduce risks. The mechanism includes the effect of debt structure optimization and the effect of asset allocation efficiency improvement. These mechanisms reshape the liquidity and risk flow of commercial banks. A few scholars believe that the development of financial technology will bring liquidity challenges to commercial banks. The research conclusion provides a decision-making reference for the management of liquidity risk of commercial banks and the regulatory authorities to improve the supervision of financial technology.
With the rapid development of population aging and the increasing demand for elderly care services, China’s elderly care services are facing unprecedented challenges. As an economically underdeveloped region, Guangxi is characterized by a growing aging population and a prominent urban-rural inversion. For the majority of elderly people with low incomes and insufficient savings, access to affordable, accessible, and quality-assured elderly care services has become a major issue in contemporary elderly care. This paper briefly describes the current situation of inclusive elderly care services in Guangxi Zhuang Autonomous Region and explores the path of inclusive elderly care in the region. The study points out that the government needs to strengthen its leading role, break the hard constraints of elderly care operation costs, continuously promote the improvement of the basic elderly care service system, and ensure that the basic needs of China’s growing elderly population for care, support, and protection are met.
Taking visual grammar of multimodal discourse analysis as the core theory, this paper chooses three cross-era Yunnan border cultural symbols: anti-colonial archives, stone monuments and native folk songs. It combines field investigation, annotated thick translation and cross-media effect evaluation as mixed research methods. Analysis proves text-only English translations without audio-visual aids fail to build complete three-layer multimodal meanings, causing severe cultural bias among overseas audiences. Combining translated texts with on-site footage and ethnic audio can fully interpret the history of border ethnic solidarity against foreign invasion. This paper establishes a four-dimensional closed research path of cultural excavation, annotated translation, multimodal creation and effect assessment, and forms a replicable paradigm applicable to southwest frontier texts, facilitating global understanding of China’s pluralistic national development and international dissemination of ethnic unity stories.
Against the backdrop of the burgeoning digital economy, this paper investigates the impact of residents’ digital financial literacy on the efficiency of household financial asset allocation and its underlying mechanisms. Using micro-survey data from the China Household Finance Survey (CHFS) for 2017 and 2019, we conduct an empirical test. The findings reveal that an improvement in digital financial literacy significantly enhances the efficiency of household financial asset allocation. This effect is achieved by increasing household financial accessibility and promoting social interaction. Moreover, these results remain robust and significant after replacing the measurement indicators of the explanatory variable and accounting for potential policy interference. The heterogeneity analysis indicates that the positive effect of digital financial literacy is larger for rural households, those in non-key urban agglomerations, and non-financially vulnerable households. This study holds significant implications for enhancing the digital financial literacy of residents in China and promoting the rationalization of household financial asset allocation.
This study takes Chinese A-share listed firms in the Shanghai and Shenzhen stock markets from 2015 to 2024 as the research sample, constructs a panel data model, and empirically examines the impact of new quality productive forces on firms’ short-term operating performance and long-term value performance. It further analyzes the underlying mechanisms, robustness, and heterogeneity characteristics. The results show that, first, new quality productive forces have a significantly positive effect on firm performance, and this conclusion remains robust after a series of robustness tests, including the use of instrumental variable approaches and alternative measurements of core variables. Second, mechanism analysis indicates that R&D investment and digital capability serve as important transmission channels through which new quality productive forces affect firm performance. Specifically, new quality productive forces improve firm performance by promoting increased R&D investment and enhancing digital technological innovation capability. Third, heterogeneity analysis reveals that the performance-enhancing effect of new quality productive forces is particularly pronounced in non-heavily polluting industries. At the regional level, a clear gradient pattern is observed: the promoting effect is stronger for firms located in regions with higher levels of economic development than those in less developed regions, and it is more significant for firms in the eastern region than in the central and western regions. This study extends the literature on the microeconomic consequences of new quality productive forces to a certain extent and provides new empirical evidence for understanding the mechanisms through which technological innovation and the optimized allocation of production factors contribute to firm value creation. Meanwhile, it offers practical implications for guiding firms to accurately seize development opportunities associated with new quality productive forces and for assisting governments in implementing differentiated policies.
There are significant regional disparities in the consumption expenditure levels of urban residents in China. Scientifically identifying the regional differentiation characteristics of consumption structure is of great significance for formulating differentiated regional development policies. Based on the data of per capita consumption expenditure of urban residents across eight major categories in 31 provinces, autonomous regions, and municipalities from the China Statistical Yearbook 2024, this study conducts an empirical analysis of regional differences in consumption expenditure levels in China using the systematic clustering method, specifically the within-cluster sum of squares method and squared Euclidean distance. First, descriptive statistics and boxplots are employed to identify the distribution characteristics of variables and detect outliers. Second, Pearson correlation coefficients are used to examine the relationships among variables. Subsequently, systematic clustering based on the within-cluster sum of squares method is performed, and the optimal number of clusters is determined with the aid of scree plots and dendrograms. Finally, one-way analysis of variance (ANOVA) is applied to test the statistical significance of the clustering results. The empirical results indicate that the 31 provinces in China can be classified into three consumption tiers. The first category is characterized as “high consumption–comprehensive development,” including Beijing, Shanghai, and Zhejiang, where the consumption structure has shifted toward development- and enjoyment-oriented consumption. The second category is defined as “moderate consumption–structural optimization,” covering Tianjin, Inner Mongolia, Jiangsu, Fujian, Guangdong, and Tibet, where the consumption structure is in a transitional stage of upgrading. The third category is described as “relatively low consumption–survival-oriented,” comprising the remaining 22 provinces, where consumption remains concentrated on essential goods. Significant inter-group differences are observed across all eight categories of consumption expenditure among the three groups (p < 0.01), and the clustering results are highly consistent with China’s regional economic development patterns. This study provides empirical evidence for understanding regional differences in consumption structure in China and for formulating differentiated consumption promotion policies.
Under the guidance of the “dual carbon” strategic goals, high-energy-consuming industrial parks, as the main carriers of industrial energy consumption and carbon emissions, are confronted with multiple challenges such as low energy utilization efficiency, increasingly strict carbon emission constraints, and slow policy responses. Traditional single governance approaches are unable to effectively coordinate the complex relationships among government regulation, power resource allocation, and carbon market mechanisms, thus there is an urgent need to establish a multi-dimensional mechanism coupling system optimization model. This paper focuses on the three-dimensional synergy of “government-electricity-carbon”, and constructs a collaborative optimization mechanism centered on the management organization layer, power system layer, and carbon flow network layer, exploring the path to achieve the maximization of resource allocation efficiency and the coordinated attainment of carbon emission control targets in high-energy-consuming industrial parks. To verify the feasibility of the mechanism, this paper takes the high-energy-consuming industrial park of Henan Luoyang Petrochemical as a case, and conducts simulation and comparative analysis based on on-site energy consumption and emission data. The research results show that this mechanism strengthens the dynamic regulatory role of government policies, enhances the response flexibility of the power system and the price discovery function of the carbon market. It not only provides theoretical support and practical paths for the low-carbon development of high-energy-consuming industrial parks, but also has significant practical significance and promotion value for achieving the carbon peak and carbon neutrality goals within the regional scope.
In the context of global sustainable development strategies and China’s “dual carbon” goals, green innovation has become a critical driving force for the transformation and development of agricultural enterprises. This study takes Chinese A-share agricultural listed companies from 2016 to 2024 as the research sample and systematically examines the impact mechanism of green innovation on corporate profitability. It particularly introduces green patents as a mediating variable to reveal the transmission path between green innovation and profitability. The study employs the entropy weight method to construct a comprehensive corporate profitability score. Green innovation is measured from two dimensions: R&D intensity and financing constraints. Empirical tests are conducted using multiple regression models. The results show that R&D intensity has a significant negative impact on corporate profitability, while financing constraints exert a significant positive impact. Green patents play a positive mediating role between R&D intensity and profitability, but a negative mediating role between financing constraints and profitability. Heterogeneity analysis indicates that the above relationships are more pronounced in the northern regions and in the post-epidemic period. The findings provide empirical support and policy implications for agricultural listed companies to optimize green innovation resource allocation and enhance profitability, and offer experience and path references from the Chinese capital market for global agricultural green transformation and sustainable development.
This paper examines how Chinese public pension funds affect corporate governance and market risk in a state-capitalist setting. Using A-share firms from 2015 to 2024, we show that pension funds display an ESG screening effect ex ante and are followed by higher post-investment ESG scores. The effect, however, is concentrated in the governance pillar and is more than twice as large in SOEs as in private firms. Despite these governance gains, pension ownership is not associated with lower stock-return volatility. We interpret this pattern as governance-risk decoupling: pension funds appear to promote visible, compliance-oriented governance upgrades, but their small stakes and the retail-dominated market limit their ability to stabilize prices. The findings refine the universal-owner view by showing that, in transitional economies, state-backed patient capital may function more as administrative legitimacy than as a direct mechanism of market-risk reduction.
As the interconnection mechanism of Shanghai-Shenzhen-Hong Kong Stock Connect keeps improving, an increasing number of enterprises choose to go public simultaneously in the A-share and H-share markets. However, the long-standing problem of “same stock with different prices” and the persistent premium of A-shares still exist. Taking the valuation difference between A-shares and H-shares as the research object, this paper uses literature review, comparative analysis and case studies to explore the formation mechanism and fluctuation characteristics of AH share premium from the perspectives of market structure, trading system, liquidity, investor sentiment and exchange rate changes. It also focuses on the reverse premium anomaly of leading enterprises such as CATL. The results show that structural differences between the two markets are the main cause of AH share premium, and macro liquidity and capital flows significantly affect the trend of the premium. Meanwhile, industry leaders with strong fundamentals and high information transparency are more likely to show H-share reverse premium. This study can provide references for cross-market investment decisions, corporate capital operation and the institutional optimization of capital markets.
Against the backdrop of China’s dual-carbon targets and the pursuit of high-quality economic development, the synergistic relationship between ESG (environmental, social, and governance) performance and corporate governance mechanisms has become increasingly prominent. Using Chinese A-share listed companies from 2020 to 2024 as the research sample, this paper employs panel-data multiple regression and mediating-effect models to empirically examine both the direct impact of managerial incentives on corporate financial performance and the underlying transmission mechanisms. The results show that (1) both equity-based and compensation-based managerial incentives exert a statistically significant positive effect on corporate financial performance; and (2) ESG performance plays a significant partial mediating role in the relationship between managerial incentives and corporate financial performance—specifically, a transmission pathway exists in which managerial incentives improve ESG performance, which in turn enhances financial performance. These findings remain robust after a series of robustness checks, including variable substitution. By adopting a sustainable-development perspective, the study extends the literature on the economic consequences of managerial incentives. It also supplies empirical evidence that can help firms incorporate ESG metrics into executive evaluation systems, refine incentive contract design, and assist regulators in improving relevant institutional frameworks.
Against the dual background of a moderately aging society and digital consumption transformation, the consumption of the silver-haired group has shifted from function-oriented to emotion-oriented. Security anxiety, dignity pursuit, emotional loneliness, and communication barriers have become core emotional demands. Existing research insufficiently reveals the integrated mechanism among the silver-haired group’s emotional consumption, ESG social dimension practices, and brand competitiveness, making it difficult to explain the value transformation logic of technology enterprises’ silver-haired services. Taking Tencent's silver-haired service as a single case, this paper systematically analyzes the characteristics of the silver-haired group’s emotional consumption, the ESG practice system, and the competitiveness empowerment path by adopting literature research, exploratory case study, and grounded theory methods, based on stakeholder theory, social exchange theory, and signaling theory. The findings show that: (1) The emotional consumption of the silver-haired group centers on security, respect, companionship, and smooth communication, characterized by emotion priority, low trial-and-error tolerance, high intergenerational transmission, and strong trust dependence; (2) Tencent has formed an ESG practice system responding to the emotional needs of the silver-haired group with the senior care exclusive hotline, AI invisible caregiver, silver-aged service base, and product-wide aging-friendly adaptation as the core; (3) Tencent's silver-haired service ESG practices transform into brand competitiveness through three paths: trust empowerment, word-of-mouth empowerment, and reputation empowerment; (4) Silver-haired ESG practices can achieve synergy between social responsibility and market benefits. This paper expands the theoretical boundary of emotional consumption, enriches the research on ESG value transformation mechanism, and provides a reference for technology enterprises to layout aging-friendly services and build brand competitiveness.
Using data from the Chinese General Social Survey (CGSS) from 2017 to 2023, this study employs a Probit model to examine the impact of digital economy development on informal employment among the labor force. The results indicate that the development of the digital economy significantly increases the probability of engaging in informal employment. Mechanism analysis shows that the digital economy improves individuals’ internet usage, which in turn enhances human capital, reduces information barriers and transaction costs in the labor market, and ultimately raises the likelihood of informal employment. Heterogeneity analysis further reveals that the employment effects of the digital economy are not universally inclusive: the impacts are more pronounced among individuals with non-agricultural household registration, higher educational attainment, and the self-employed. Moreover, regions with higher levels of economic development benefit more from the promotion effect of the digital economy on informal employment.
With the rapid development of the digital economy, artificial intelligence (AI) has become an important factor influencing international service trade. As the growth of traditional merchandise trade slows, digitally deliverable services have continued to expand, supported by the increasing role of data and AI technologies. Using a systematic literature review approach and drawing on recent macro-level trade statistics and micro-level empirical studies, this paper examines the mechanisms through which AI affects the scale and structure of service exports and reviews the related empirical evidence. Recent data show that digitally deliverable services account for more than half of global service trade. Existing studies suggest that AI can improve the technological sophistication of knowledge-intensive service exports by lowering cross-border search costs, increasing total factor productivity, and enhancing service tradability. In this sense, AI contributes not only to the expansion of service trade but also to its movement toward higher value-added activities. The findings of this study help explain recent developments in digital trade and provide policy implications for narrowing the global digital divide, particularly through improvements in digital infrastructure and increased investment in research and development.
Recent years, the game industry has developed continuously. Game Intellectual Property (IP), as an important element in the game, has a very high popularity in the market, which has attracted more and more companies to concentrate on game IP for investment. However, there is a lack of multi-dimensional empirical research on the impact of game IP holdings on the investment efficiency of enterprises. It is found that the positive impact of IP holdings on inefficient investment has not passed the significance test, indicating that simply increasing the scale of IP holdings cannot significantly aggravate or alleviate the problem of inefficient investment; Enterprise growth has a significant inhibitory effect on inefficient investment, and high-growth enterprises are more likely to realize rational allocation of resources. This paper proves that it is difficult to convert the value of game IP into investment income alone, and blindly hoarding IP can easily lead to information asymmetry and aggressive investment by management, which in turn leads to resource mismatch. Learning the results of enterprise IP investment through this empirical analysis can improve the vigilance of enterprises against IP bubble, which can help to avoid blind investment in IP and turn their investment eyes to other sustainable growth points.
While green finance reform policies channel capital toward green industries, can they effectively curb the green innovation bubbles caused by corporate “greenwashing”? This study examines Chinese A-share listed companies from 2010 to 2024, treating the establishment of green finance reform and innovation pilot zones as a quasi-natural experiment. Using a multi-period difference-in-differences method, the study systematically investigates the impact of green finance policies on corporate green innovation bubbles and their transmission mechanisms. The findings reveal: First, green finance reform policies significantly curb corporate green innovation bubbles. Second, a decomposition of the transmission mechanisms indicates that strategic green innovation is the core channel through which policies exert their “corrective” function; due to the short-term crowding-out effect of policies on substantive innovation, the contribution of the substantive green innovation channel is weak and runs in the opposite direction. Third, the policy effects exhibit heterogeneity: non-state-owned enterprises are more sensitive to policy responses; the moderating role of executives’ financial backgrounds is limited, with differences between groups failing to reach statistical significance. This paper reveals the underlying mechanism by which green finance policies improve innovation quality by curbing strategic innovation, providing empirical evidence for mitigating “greenwashing” risks and optimizing the institutional design of green finance.
In an increasingly competitive sportswear industry, where multiple brands are pursuing accelerated globalization, relying solely on financial metrics to evaluate corporate performance no longer suffices to support the effective execution of strategy. The Balanced Scorecard (BSC) integrates financial indicators with non-financial dimensions—such as customer satisfaction—enabling multi-brand conglomerates to more comprehensively balance short-term profitability against long-term sustainable development. This study selects ANTA Sports Products Co., Ltd. as its case, examining the practical implementation of the Balanced Scorecard across its four core perspectives. The analysis reveals that the BSC’s multidimensional evaluation framework aligns well with ANTA’s prevailing strategic orientation. Nevertheless, opportunities for refinement remain, particularly in the weighting and prioritization of individual performance indicators. The findings and related conclusions may offer valuable insights for other enterprises engaged in the manufacturing and distribution of sportswear as they develop or refine their own performance evaluation systems.
As China’s population aging accelerates, developing the third pillar of commercial pension insurance has become an important policy issue. However, the participation rate among urban residents remains persistently low. Existing studies mostly focus on static factors and overlook the dynamic impact of retirement—a critical life event. Based on data from the 2019 China Household Finance Survey (CHFS), this paper employs a fuzzy regression discontinuity design (FRDD), using the statutory retirement age as the policy cutoff, to precisely identify the causal effect of retirement on urban male residents aged 50–70 and their participation in commercial pension insurance. The study further examines the underlying mechanisms from three dimensions: income level, risk preference, and financial literacy. The results show that retirement significantly reduces the probability of urban residents participating in commercial pension insurance, decreasing the participation rate by 12.1 percentage points under the optimal bandwidth. Mechanism analysis reveals that retirement exerts a dual inhibitory effect by lowering residents’ income levels and risk preferences. Although increased leisure time after retirement improves financial literacy and generates a certain positive effect, this positive influence is offset by the negative effects of income constraints and increased risk aversion. This paper provides rigorous empirical evidence on the causal relationship between retirement and commercial pension insurance participation, offering important policy implications for improving the third pillar of the pension system.
Background: As a leading enterprise in China’s internet industry, Alibaba Group Holding Limited holds significant reference value for investors, competitors, and academic researchers in terms of valuation analysis. This study aims to evaluate its intrinsic value and assess the rationality of market pricing through multiple relative valuation models. Methods: This study selects Tencent Holdings, JD.com, and Meituan as comparable companies. It applies three trading multiples within the relative valuation framework—Price-to-Earnings (P/E), Price-to-Book (P/B), and Enterprise Value to EBITDA (EV/EBITDA)—to conduct a comprehensive valuation analysis of Alibaba for fiscal year 2025 and the forecast period. Results: The analysis indicates that among the three models, EV/EBITDA demonstrates the highest applicability for valuing Alibaba in fiscal year 2025, as it is not affected by capital structure, non-operating income, or substantial capital expenditures. The P/E ratio exhibits reduced reliability due to distortions in net profit, while the P/B ratio shows the lowest applicability because Alibaba’s core value lies in its asset-light structure and platform ecosystem, which are not well aligned with the assumptions of this model. Conclusion: The findings emphasize that the selection of valuation methods should be based on a firm’s specific operating conditions and financial characteristics at a given stage.
In the era of digital economy, 5G factories, as the core carrier of intelligent manufacturing, represent an important manifestation of the transformation and upgrading of the manufacturing industry. This paper takes the manufacturing listed companies in Shanghai and Shenzhen stock markets from 2020 to 2024 as the sample. Using the “5G Factory List” released by the Ministry of Industry and Information Technology as the experimental group, a multi-period difference-in-differences model is employed to empirically examine the impact of 5G factory construction on the financial efficiency of enterprises. The research found that the construction of 5G factories significantly enhanced the total factor productivity of manufacturing enterprises. This conclusion remained robust after undergoing Parallel Trend Tests, Propensity Score Matching–Difference-in-Differences Model, and Placebo Tests. The Mechanism Test shows that although individual production, inventory or innovation indicators did not show significant changes in the short term, the 5G factory improved overall efficiency through systematic resource allocation optimization. This study provides microeconomic evidence for understanding the empowerment of the real economy by digital technologies.
