Frontiers in Economics and Management (FEM) is a monthly online, international, peer-reviewed journal. All articles published are rigorously and fast reviewed meeting the Journal Quality standards. FEM is dedicated to publish empirical, academic, theoretical and review research articles that contribute to the practice in economics, management, and related topics. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
From the Simulacral Head to the Everyday Field: The Media Turn and Affective Mechanism in Tony Oursler's Video Installations
This paper examines the development of Tony Oursler’s video installation practice since the 1990s, focusing on how the artist persistently detaches the moving image from the fixed screen and relocates it onto effigies, readymade objects, everyday environments, and urban surfaces, thereby transforming the image from a flat pictorial entity into a spatial, material, and affective event. Analysing three major phases-Object Projection, Video Installation, and Outdoor Imaging-the study identifies four core creative strategies that evolve across these stages: head-centred projection, the integration of video and found objects, the installation of everyday materials in quotidian space, and the sound-driven construction of personified emotion. By tracing how these strategies shift from object adherence to spatial narration and ultimately to environmental intervention, the paper argues that Oursler develops a distinctive affective installation language marked by uncanny plausibility, proportional dislocation, virtual–real interpenetration, dark humor, and sensorial absurdity, reshaping the viewer’s perceptual behavior by transforming viewing from a stable act of looking into an embodied process of encounter, adjustment, and emotional negotiation. The study concludes that Oursler’s practice exemplifies a broader post-medium transformation in contemporary video art, wherein the moving image acquires material presence, spatial agency, and environmental permeability, and suggests that as the image increasingly intervenes in public space and everyday experience, Oursler’s work offers a crucial lens through which to understand how contemporary visual culture redefines the boundaries of image, object, emotion, and reality.
Tony Oursler; Video Installation Art; Affective Installation; Object Projection; Post-Medium Condition.
Copyright (c) 2025 Frontiers in Economics and Management https://creativecommons.org/licenses/by-nc/4.0
Research on the Impact of Geopolitical Risk on the Value of Chinese Listed
China has entered a stage of high-quality development. With the continuous advancement of high-level opening-up, the external environment increasingly exerts a substantial impact on China's economic development. Geopolitical risk stands as a significant factor among these influences. Given the important role that geopolitical activities play in corporate financial decisions-such as cash reserves, investment and financing, and research and innovation-this paper analyzes the impact of geopolitical risk on the value of Chinese listed enterprises and its underlying mechanisms. Using annual data from Chinese A-share listed companies from 2006 to 2024, this study examines the effect of the geopolitical risk index on corporate value in China and explores the mechanisms involved. The empirical results indicate that: (1) There is a significant negative correlation between the geopolitical risk index and the value of Chinese listed companies, suggesting that an increase in geopolitical risk significantly reduces corporate value. (2)The mediation mechanism test results show that geopolitical risk suppresses corporate value by exacerbating financing constraints.
Geopolitical Risk; Corporate Value; Financing Constraints.
Is ESG Rating an Effective Tool for Addressing Mispricing of Corporate Assets?
This study employs a multi-period difference-in-differences model to empirically examine the impact of ESG ratings on asset mispricing, utilising data from Chinese A-share listed companies between 2009 and 2023 and treating ESG ratings as an exogenous shock variable. Findings indicate that ESG ratings significantly mitigate the degree of asset mispricing within firms. The research not only provides fresh empirical evidence for understanding the relationship between ESG ratings and asset pricing.
ESG Ratings; Asset Mispricing; Multi-period Double Difference.
Research on the Quality of Performance Evaluation Report of Third Party Organizations
With the deepening of budget performance management reform in China, the role of third-party organizations in performance evaluation is increasingly prominent. This paper focuses on the quality problems of performance evaluation reports of third-party organizations, systematically analyzes the main problems existing in the current reports in terms of index design, index empowerment, analysis process, countermeasures and suggestions, and format specification, such as the disconnection between indicators and targets, subjectivization of empowerment, lack of in-depth analysis, lack of operability of suggestions, etc., and proposes to build a path to improve the quality of reports from four dimensions: institutional standards, institutional capacity, entrustment relationship and application of results. The research shows that improving the quality of third-party evaluation reports requires both internal and external repair, improving external supervision and incentives, and strengthening internal quality control and professional ability of institutions, so as to achieve the goal of serving high-quality budget performance management with high-quality evaluation.
Performance Evaluation; Third-Party Organizations; Quality Evaluation; Budget Performance Management.
Research on the Effectiveness and Innovative Pathways of Financial Support for Green Transformation in the Steel Industry
Under the dual carbon goals, the steel industry-as a high-carbon core sector-requires substantial capital for transformation. However, enterprises struggle to bear these costs independently, making financial support crucial. This study aims to examine the characteristics and contradictions of financial demand in the steel industry's transition, quantitatively analyze the effectiveness of financial support, and explore innovative pathways. It employs a methodology combining theoretical analysis, case studies, and data-driven evidence. Findings reveal that the current transformation faces challenges such as mismatched capital supply and demand, as well as limited financing tools. Nevertheless, notable successes have been achieved in regions like Tangshan, Hebei, and Xinyu, Jiangxi, where policy-guided and market-driven finance has effectively reduced financing costs and enhanced emission reduction benefits. Based on these insights, this paper proposes pathways from three dimensions: establishing policy standards, empowering financial institutions through technological innovation, and strengthening industry-finance synergy within enterprises. Future efforts should focus on refining standards to accelerate the green transformation of the steel industry.
Steel Industry; Green Transition; Financial Demand.
Research on S&P 500 Forecasting During High Volatility Periods
This paper investigates the predictive performance of ARIMA and LSTM models for the S&P 500 index under different market conditions. Using daily data from 1990 to 2024, the study also downloaded VIX and computed ATR as potential volatility indicators; however, the forecasting models were primarily based on closing prices and their log returns. High-volatility days were defined as those with daily returns exceeding 3%. The results show that in the overall sample, LSTM tends to underestimate and smooth the trend, performing similarly to ARIMA; however, during high-volatility periods, ARIMA provides more robust directional forecasts, while LSTM lags behind the real market. The findings suggest that deep learning models are not always superior to classical time-series models, and linear models remain competitive in extreme market conditions.
S&P 500; High Volatility; ARIMA; LSTM; Time Series Forecasting.
Cross-Cultural Variations in Gendered Marketing for Male Grooming Products Through Digital Strategies in Chinese and Western Markets
Against the backdrop of global integration, the market for male beauty products is growing rapidly, and digital marketing has become the core competitiveness of brands. However, due to the cross-cultural differences between China and the West, there are also significant differences in marketing models. This research aims to analyze the cross-cultural differences in the impact of digitalization on male beauty products in China and the West, explore the market shares occupied by male beauty products in China and the West under the cross-cultural background differences, and conduct a comparative analysis of the digital marketing strategies implemented by different brands for male beauty products. Through case studies, it compares the impact of digitalization differences on marketing strategies. Furthermore, innovative marketing strategies have been proposed for the digital marketing of male beauty products, with the aim of providing new ideas and references for research in this area.
Exploring Pathways for Digital Technologies to Advance Sichuan Province's Modern Energy System Towards Achieving Dual Carbon Goals
Against the backdrop of global energy transformation and the deepening advancement of the dual carbon goals, digital technologies have emerged as a pivotal force driving the energy system towards cleaner and smarter transformation. This paper systematically elucidates the defining characteristics of a modern energy system – namely, ‘secure and efficient, clean and low-carbon, diverse and synergistic, intelligent and inclusive’ – based on the current development status of Sichuan Province's modern energy system. It further delves into the intrinsic mechanisms through which digital technologies empower the low-carbon transition of modern energy systems. Research findings indicate that digital technologies exert synergistic effects across the supply, demand, and management sides of the energy system through three mechanisms: optimising energy structures, fostering technological convergence and innovation, and driving industrial integration and upgrading. This propels the energy system from a physics-dominated paradigm towards information-physical synergy, and from chain-based innovation towards networked symbiosis. Building upon this foundation, the paper constructs an implementation pathway centred on ‘optimising smart energy systems, deepening technological convergence applications, and establishing a modern industrial digital ecosystem.’ Drawing upon Chengdu's practical experience in virtual power plants, smart energy management, and data platform development, it summarizes transformation insights driven by the synergistic advancement of ‘technology-institutional-market’ dimensions. This research not only provides theoretical foundations and practical references for accelerating modern energy system development and achieving carbon peaking and carbon neutrality goals in Sichuan Province, but also offers a systematic framework for other regions across China to advance the digitalisation of modern energy systems alongside coordinated green and low-carbon development.
Digital Technology; Modern Energy System; Dual Carbon Goals; Pathway Exploration; Sichuan Province.
ESG Performance, New-QualityProductive Forces, and Corporate Carbon Emission Reduction
Drawing on data from Chinese A-share private listed enterprises covering the period 2011–2022, this research investigates the interrelationships between ESG performance, new-quality productive forces (NQF), and carbon emission reduction through the integrated application of dynamic threshold modeling, instrumental variable two-stage least squares (IV-2SLS), and the Generalized Method of Moments (GMM) approach. Benchmark regression results demonstrate that NQF exerts a suppressive effect on carbon emission growth. Notably, this inhibitory impact is more pronounced when a firm’s ESG performance lies within the high-threshold interval compared to the low-threshold range. In other words, once a company’s ESG performance surpasses the identified threshold value, it reinforces the carbon emission reduction effect of NQF. The findings of this study not only deepen the understanding of how the "technology-powered nation" strategy-epitomized by the development of NQF-influences carbon emissions but also offer theoretical underpinnings for enterprises aiming to enhance their ESG performance. Additionally, they provide actionable insights for local governments to improve environmental outcomes, capitalize on the development opportunities presented by NQF, and unlock new avenues for low-carbon development.
Corporate ESG; New-Quality Productive Forces; Carbon Emission Reduction.
Financial Time Series Data Forecasting based on CEEMDAN-BiGRU-BO Model
In the quantitative investment and risk management system, financial data prediction, as a core link, its accuracy directly determines the efficiency of asset pricing and the return level of the investment portfolio. However, under the combined influence of multiple factors such as macroeconomic fluctuations, heterogeneity of investor behavior, and unexpected events, the financial market exhibits significant nonlinearity, non-stationarity, and high noise characteristics, posing severe challenges to traditional prediction models. To address this issue, this paper develops a hybrid model integrating Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Bidirectional Gated Recurrent Unit (BiGRU) and Bayesian Optimization (BO) to boost the forecasting accuracy and resilience of financial time series data. This model first introduces CEEMDAN in the feature engineering stage to adaptively decompose the data, extract the intrinsic mode function (IMF) and residual components, effectively alleviating the non-stationarity and complexity of the data. Subsequently, in the prediction stage, a BiGRU is adopted to enhance the model's capacity to model long-term trends and sequence structures. Finally, BO is utilized to determine the optimal parameter combination under different datasets. Based on the above methods, this paper takes the index of the Shanghai stock exchange (SSEC), the index of the stock exchange of Thailand (SET) and the Korea composite stock price index (KOSPI) as empirical data for verification. The findings demonstrate that the hybrid model achieved mean absolute percentage error (MAPE) indicators of 0.188%, 0.291% and 0.185% respectively, which were significantly lower than those of other control models, verifying its stability and adaptability in the complex financial environment.
CEEMDAN; BiGRU; Bayesian Optimization; Time Series Forecasting.
Research on Performance Evaluation of University Science and Technology Achievement Transformation based on DEA Method
As the core subject of scientific and technological innovation, the efficiency of university scientific and technological achievement transformation is an important indicator for measuring the allocation of innovation resources and the level of social development. Based on the scientific research input and output data of universities in 25 provinces in China from 2019 to 2023, this study adopts the Super-efficiency CCR-DEA model and the Super-efficiency CCR-Malmquist index model to conduct a dual measurement and evaluation study on the short-term static and long-term dynamic efficiency of university scientific and technological achievement transformation in various provinces. The study finds that: (1) There is a certain correlation between the level of regional economic development and the efficiency of university achievement transformation, but the two are not a simple linear relationship. The actual performance of transformation efficiency depends more on the rationality of scientific research resource allocation and the practical effect of innovation output. (2) The total factor productivity of university achievement transformation in the 25 provinces continues to rise. The efficiency presents a pattern of “superior in the East, inferior in the West; strong in the South, weak in the North”. It is suggested that universities should improve policies, attach importance to technology, introduce talents, promote transformation, and promote the optimized development of scientific research management.
Higher Education Institutions; Super-efficiency CCR-DEA Model; Transformation of Scientific Research Achievements.
The Impact of Generative AI Development on Unemployment in the Financial Industry in China and the United States
The rapid development of generative artificial intelligence is triggering far-reaching structural changes in the labor market in the global financial industry. This paper aims to study the differentiated impact of generative AI on the unemployment rate in the financial industry in China and the United States and its response strategies. Generative AI, with its creative content generation, complex decision simulations, and unstructured data processing capabilities, is reshaping the employment landscape in the knowledge-intensive industry of finance. China and the United States have shown completely different influence paths due to different financial structures, technological foundations, and policy orientations: China's bank-led financial system is facing a large number of low- and middle-skilled job transformation pressures, but through strong government intervention and "stable employment" policies, the impact is buffered; The United States is market-led, with prominent risk of replacing mid-range analytical positions and relying on market regulation mechanisms to cope with technological shocks. This study not only reveals the alternative mechanism and creative effect of generative AI on financial employment, but also proposes a differentiated strategic response framework for the two countries, providing an important reference for the global financial industry to achieve a smooth transformation in technological change.
Generative AI; China-US Comparison; Finance; Unemployment.
Coordination Path of Fiduciary Duty and Representative Duty of Employee Directors under Dual Identity
The employee director system aims to balance employees' rights and interests with corporate interests through employee directors' participation in board decision-making. However, in practice, this system often faces the predicament of functional emptiness and insufficient effectiveness. The reason lies in that under the dual identity of employee directors, their fiduciary duty and representative duty are inevitably in conflict, but there is a lack of corresponding coordination systems, making it difficult for employee directors to perform their duties in accordance with the original intention of the system. Focusing on two major issues-how to choose when fiduciary duty and representative duty conflict, and how to handle situations where the performance of special representative duty leads to a breach of general fiduciary duty-this paper proposes to divide the gradient of duties, construct differentiated liability standards, establish a sound supporting mechanism for the performance of duties, optimize judicial adjudication, and establish rules such as the "Dual Rationality Test", thereby constructing a coordination path for the fiduciary duty and representative duty of employee directors.
Employee Director; Fiduciary Duty of Directors; Representative Duty; Corporate Governance; Democratic Management of Enterprises.
Performance Evaluation Analysis of Gree Electric Appliances based on Economic Value Added
In today's fiercely competitive business environment, scientifically and accurately assessing a company's true value creation capability is crucial. Traditional accounting profit indicators, which do not account for the cost of equity capital, struggle to reflect the real value creation. Economic Value Added (EVA), as a modern performance evaluation tool, more accurately reflects a company's value creation ability by measuring the portion of its after-tax operating profit that exceeds the total cost of capital. This study takes Zhuhai Gree Electric Appliances Inc. (000651.SZ) as a case study, systematically evaluating its operating performance from 2020 to 2023 using the EVA model. Employing case study and quantitative analysis methods, and based on the company's annual report data, the study calculates Net Operating Profit After Tax (NOPAT), Total Capital (TC), and Weighted Average Cost of Capital (WACC) to derive the EVA values for each year and conducts an in-depth analysis. The results show that Gree Electric Appliances demonstrated strong value creation capability between 2020 and 2023. EVA grew continuously from RMB 6.053 billion in 2020 to RMB 25.839 billion in 2023, a cumulative increase of 327%; NOPAT reached RMB 36.192 billion in 2023, with a capital cost rate of 5.48%. This indicates that the company not only created economic profits exceeding the cost of capital for shareholders for four consecutive years but also continuously improved its value creation efficiency. The growth in EVA is primarily attributed to the stable profitability of its core air conditioning business, continuous R&D investment, and excellent operational efficiency. Compared to the traditional net profit indicator, EVA more rigorously reveals the company's true profitability level: the 2023 EVA was lower than net profit, indicating that net profit includes a portion of the necessary return on shareholder capital. Notably, the growth rate of EVA exceeded that of net profit, suggesting improved marginal returns on newly invested capital and enhanced capital allocation efficiency. This study validates the applicability of the EVA indicator in large manufacturing enterprises, provides a theoretical basis and practical reference for Gree Electric Appliances to optimize resource allocation and improve capital efficiency, and also offers valuable insights for performance evaluation in other manufacturing companies.
Economic Value Added (EVA); Gree Electric Appliances; Performance Evaluation.
Contextualized Identification of the Asset Structure-Earnings Relationship: The A-share Evidence of Industry/Size Moderation and Working Capital Mechanisms (2018–2024)
This paper examines how a firm’s asset structure-disaggregated into current, fixed and intangible assets-relates to profitability and how this relationship varies by context. Using Chinese A-share non-financial listed firms from 2018–2024, we estimate two-way fixed-effects models, then validate with system-GMM and panel quantile regressions. We further test a mediation channel via working-capital efficiency (proxied by the cash conversion cycle), and moderation by industry attributes and firm size. Results show that intangible-asset intensity is positively associated with ROA/ROE, whereas high shares of current and fixed assets are associated with lower profitability. The positive effect of intangibles is stronger in high-tech industries and for larger firms. Mechanism tests indicate that approximately two-fifths of the negative effect of current-asset share operates through reduced working-capital efficiency (a lengthened cash conversion cycle). Findings are robust to alternative measures and sample restrictions. The study advances contextual identification of the asset structure–earnings link and provides actionable implications: firms should manage liquid-asset buffers and fixed-asset commitments prudently, while building intangible capital where it can be effectively commercialized, especially in technology-intensive sectors and at larger scales.
Asset Structure; Profitability; Moderation; Working-Capital Efficiency; A-share.
Frontier Assessment of Green Economic Efficiency in China’s High-quality Development Stage: An Empirical Comparative Study based on Non-parametric, Parametric and Semi-parametric Methods
Green economic efficiency is a core quantitative indicator of high-quality development, and the scientific nature of its evaluation methods directly determines the accuracy of development quality diagnosis. This paper constructs a four-dimensional evaluation framework of "traditional input-digital input-expected output-unexpected output," using 30 provinces, autonomous regions, and municipalities of China from 2014 to 2024 as research subjects. It systematically compares the theoretical characteristics and empirical performance of non-parametric data envelopment analysis (DEA), parametric stochastic frontier analysis (SFA), and semi-parametric stochastic non-smooth semi-parametric data envelopment method (StoNED). This study mainly focuses on testing StoNED adaptability under stochastic environments and multidimensional constraints during the high-quality development stage. The study reveals that StoNED constructs a non-parametric frontier through convex regression and incorporates composite error terms, addressing the shortcomings of DEA in being sensitive to outliers and neglecting shocks from new elements such as the digital economy, while also overcoming SFAs dependence on the form of production functions. Its measurement results show significantly higher consistency with the high-quality development evaluation system compared to DEA and SFA. From 2014 to 2024, China's provincial green economic efficiency exhibited a "U-shaped recovery-steady improvement" trend. The StoNED average value reached 0.763 in 2024, an increase of 18.7% compared with 2014, and the regional gap between the eastern, central and western regions showed a convergence trend. This paper provides methodological references for evaluating green economic efficiency during the high-quality development stage and supports regional coordination under the "dual carbon" goals.
Green Economic Efficiency; Stochastic Frontier Analysis; Data Envelopment Analysis; Stochastic Non-Smooth Semi-Parametric Data Envelopment Analysis; High-quality Development.
Can New Quality Productive Forces Promote Green and Low-Carbon Agricultural Development? Evidence from China
Green and low-carbon agricultural development is an important pathway for achieving the “dual carbon” targets and sustainable development. New Quality Productive Forces (NQP) play a key role in promoting green and low-carbon agricultural development. Based on provincial panel data for China from 2014 to 2023, this study constructs comprehensive evaluation index systems for NQP and green and low-carbon agricultural development (GLCA) and employs fixed-effects and mediation-effect models to systematically examine the mechanisms through which NQP affects GLCA. The results show that: (1) NQP has a significant positive impact on GLCA; (2) NQP can further promote GLCA by enhancing the educational attainment of the labour force; and (3) the effects of NQP on GLCA vary across regions. Accordingly, this study recommends promoting the deep integration of NQP with agriculture, enhancing the educational level of the agricultural labour force, and advancing regionally differentiated development to establish a multi-stakeholder governance system for green and low-carbon agriculture.
New Quality Productive Forces; Green and Low-Carbon Agricultural Development; Fixed Effects; Mediating Effects.
Digital Financial Performance Analysis of Listed Companies in the Smart Security Industry: A Case Study of Hikvision
Under the profound influence of digital technology, numerous manufacturing enterprises have adopted digital transformation strategies to optimize and upgrade production processes. This enhances their ability to address both internal and external challenges, thereby improving their competitive position in the industry. Taking Hikvision as a case study, this research aims to thoroughly explore the current status of its digital transformation, including driving forces and specific implementation measures. Building on this foundation, the paper evaluates Hikvision's post-transformation profitability, operational efficiency, and growth potential using three key financial indicators: return on equity (ROE), total asset turnover ratio, and net profit growth rate. Ultimately, the study summarizes Hikvision's successful digital transformation experience and provides actionable recommendations for other enterprises implementing similar initiatives.
Digital Transformation; Financial Performance; Hikvision.
Analyzing the Impact of Carbon Emission Trading Policies on Corporate Behavioral Responses and Supply Chain Co-opetition: A Literature Review
This paper reviews 245 articles from Peking University Core and CSSCI journals (CNKI, 2021-2025) on China’s carbon emission trading (CET) policy and its effects on corporate behavior and supply chain coordination. Results show that the national carbon market has significantly altered the corporate operating environment. At the micro level, CET spurs green innovation through three mechanisms: easing financing constraints, transforming cost pressures, and addressing institutional legitimacy, supporting the “Porter Hypothesis” in China. Effects on corporate performance are mixed: while CET can improve financial performance and debt structures via cost savings, trading revenue, and better financing, its impact on firm value and non-financial performance remains debated. At the meso level, research focuses on supply chain coordination. To mitigate "double marginalization" caused by uneven carbon regulation across supply chains, contract mechanisms-especially cost-sharing and revenue-sharing contracts-are designed to optimize emission reduction investments and boost efficiency. Blockchain technology also supports emission reduction by improving carbon data transparency, cutting compliance costs, and enabling new collaboration models. Future research should examine heterogeneous responses in newly covered industries (e.g., steel, cement, aluminum), low-carbon transitions for SMEs, and long-term ESG effects. Further innovation is needed in contract design under dynamic carbon pricing, multi-tier supply chain coordination, and blockchain cost-benefit analysis. Policy efforts should prioritize cross-regional carbon accounting, carbon revenue recycling, and carbon financial instruments.
Carbon Emission Trading Policy; Green Innovation; Supply Chain Coordination; Literature Review.
Analysis of the Mechanism by Which Corporate Social Responsibility Affects Corporate Performance in Manufacturing Enterprises under the Regulation of Corporate Governance
Against the backdrop of economic globalization and the growing acceptance of sustainable development concepts, China's economy has gradually transformed its development model. However, it still faces numerous challenges, with issues such as product quality and environmental protection becoming increasingly evident. In recent years, many enterprises have undergone transformations due to national policy adjustments, with their development models continuously evolving and internal management repeatedly tested by governance strategy adjustments. For the vast majority of enterprises, whether they can fulfill social responsibilities and ensure healthy, sustainable development remains the key to their long-term growth and profitability. Based on the above background, to further explore corporate social responsibility, this paper takes A-share companies listed in China between 2019 and 2023 as research samples. Based on the relationship between corporate governance and corporate performance, it is found that the degree of corporate social responsibility practices in listed companies is positively correlated with corporate performance. From the perspective of corporate governance, the increase in equity concentration can strengthen the positive correlation between corporate social responsibility and corporate performance. This indicates that a sound corporate governance system significantly promotes corporate operations and social responsibility, with various elements of corporate governance playing a key role in coordinating these two aspects. This paper proposes corresponding suggestions for the development and operation of listed companies regarding improving the social responsibility system, enhancing product competitiveness, and optimizing corporate governance structures.
Corporate Social Responsibility; Corporate Governance; Corporate Performance.
A Five-Level Synergistic Psychological Safety Network: A Case Study on Mental Health Education for a Student with Severe Depression
This paper summarizes the full process of psychological intervention for a student with severe depression at a vocational college. Through early screening and classification, intensive attention, real-time tracking, multi-party collaboration, and timely intervention, the crisis was effectively prevented, leading to the establishment of a comprehensive psychological safety network. Through comprehensive data analysis and market research, Such efforts are crucial for improving students’ psychological well-being and enhancing the overall quality of higher education.
Vocational College; Severe Depression; Mental Health; Five-Level Synergy.
Study on the Compatibility of Sharing Economy Platforms' Profit Models, Cost Structures, and Key Financial Performance Indicators
With the booming digital economy, the sharing economy has become a significant force driving the transformation of the service industry and optimizing resource allocation. However, amidst rapid market expansion, platform companies generally face challenges such as unclear profit models, unbalanced cost structures, and significant fluctuations in financial performance. This paper examines sharing economy platforms, constructing a "profit model-cost structure-financial performance" compatibility analysis framework and systematically exploring the inherent relationships among these variables. Using a sample of 12 listed domestic and international sharing economy platforms from 2019 to 2023, the study employs descriptive statistics, correlation analysis, and multivariate regression models to empirically examine key factors such as transaction commissions, advertising, value-added services, and user acquisition costs. The results show that: (1) the proportion of transaction commission income has a significant positive impact on net profit margin and is the main driving factor for platform profitability; (2) the user acquisition cost is significantly negatively correlated with the operating income growth rate, indicating that excessive subsidies weaken the efficiency of revenue growth; (3) the fixed asset investment ratio is negatively correlated with the asset turnover rate, and the light asset model has greater financial flexibility; (4) value-added services can effectively promote user growth, while excessive advertising revenue inhibits user expansion; (5) service and regulatory cost investment helps to reduce the asset-liability ratio and optimize the risk structure. The research conclusions provide quantitative basis and strategic inspiration for sharing economy platforms to balance profitability and sustainable development, which has important theoretical value and practical significance.
Sharing Economy; Profit Model; Cost Structure; Financial Performance; Regression Analysis.
Global Value Chain Activities in Host Country and Foreign Subsidiary Performance: The Role of Local Knowledge, Entry Model Strategies
This paper explores the extent to which the performance of foreign subsidiaries is affected by country, sector and company factors, using the company level panel of more than 61,000 foreign subsidiaries in 103 economies. We found evidence that the increase of GVC participation and GVC position of host countries improved the financial performance of foreign subsidiaries. This shows that the more active the host country is in the global value chain activities, the greater the market potential, so that foreign companies can obtain higher returns. The study also found that this positive return was also affected by the differences in local knowledge and entry mode strategies of foreign subsidiaries. In addition, this paper also conducted a variety of robustness tests and discussed the endogenous problem. Our findings support the basic principles of international production and division of labor and advocate that a country should participate more in global production in order to attract foreign investment.
Host Country Global Value Chain; Foreign Subsidiary Performance; Local Knowledge; Entry Mode.
Can Shorting Curb Major Shareholder Hollowing Out
This paper studies the external supervisory and restrictive role of short-selling deregulation, focusing on major shareholders' "hollowing out" in China's corporate governance. Theoretically, post-deregulation, small and medium shareholders can short to lower stock prices; when hollowing gains are less than price fall losses, major shareholders' behavior is restrained. Using 2008-2020 A-share data, empirical analysis shows short-selling deregulation significantly reduces major shareholders' fund occupation proportion, with more obvious effects in weakly governed companies like private enterprises and those with high shareholding concentration. This indicates the short-selling mechanism protects minority shareholders' interests via market-based supervision, providing empirical evidence for regulators to optimize short-selling policies and improve corporate governance.
Short-selling Mechanism; Major Shareholder Short-selling; Capital Misappropriation; Short-selling Deregulation; Corporate Governance; External Oversight.
Research on the Impact of the Digital Economy on Consumer and Producer Behaviour
Although extensive research has examined the influence of the digital economy, few studies have explored its impact on industrial organisation behaviour from a foundational theoretical perspective. Building upon existing theoretical frameworks, this paper constructs a theoretical model to analyse how the digital economy affects consumer choice behaviour, firm production and profit functions. The study seeks to encourage greater scholarly engagement among Chinese researchers in examining industrial organisation within the digital economy context of developing countries, thereby providing a theoretical foundation to guide and promote the sustainable and healthy development of the digital economy.
Digital Economy; Consumer Behaviour; Producer Behaviour.
Research on the Impact of Empowering Rural Revitalization with New Quality Productivity
As a new economic form, the new quality productivity provides a promoting role for the comprehensive revitalization of rural areas. Based on the connotation of the theory of new quality productivity, from the perspective of system theory elements, this paper analyzes the composition characteristics of the system elements of new quality productivity, formulates evaluation indicators, and uses balanced panel data from 30 provinces from 2012 to 2022 to calculate the development level of new quality productivity and rural revitalization using the entropy method, empirically testing the impact and mechanism of new quality productivity on rural revitalization. Research has found that: (1) New quality productivity has a significant promoting effect on the development of rural revitalization. After introducing a series of control variables such as instrumental variables for robustness testing, the results are still significant; (2) New quality productivity can promote the development of rural revitalization by advancing the level of urbanization and transportation infrastructure; (3) The empowering effect of new quality productivity on the development of rural revitalization exhibits spatial and dimensional heterogeneity. From a regional perspective, the promotion effect of new quality productivity on rural revitalization development is strongest in the central region, followed by the eastern region; (4) There is a threshold effect of new quality productivity on the development of rural revitalization, and excessive government intervention will weaken the promoting effect of new quality productivity on rural revitalization under certain conditions.
New Quality Productivity; Rural Revitalization Urbanization Level; Degree of Government Intervention.
Vegetable Purchase and Pricing Strategy Combined with ARIMA, K-means, LSTM and Optimal Linear Programming
The shelf life of vegetables is short, and with the serious loss of time, it is important for supermarkets to make reasonable replenishment decisions and pricing. Based on the quantity control of single items and the minimum display quantity of each single item, this paper constructs an optimal linear programming model with the ultimate goal of maximizing the benefits of supermarkets and meeting the market demand. Based on ARIMA model, K-means clustering analysis, LSTM model training validation, brought into linear regression analysis to establish a prediction model. It is expected that the compound model will be widely used in supermarkets to make purchase decisions and pricing decisions.
Linear Regression Analysis; Optimal Linear Programming; ARIMA Model; K-means Clustering Analysis; LSTM Model.
Research on the Improvement of Professional Quality for University Academic Affairs Staff in the Context of Educational Digital Transformation
With the deepening advancement of the educational digital transformation, academic affairs personnel must quickly integrate into the digital teaching environment, actively explore and practice new management models, and maintain an attitude of continuous learning. university academic affairs staff are confronted with challenges in mastering and applying new technologies, handling data and ensuring information security, adapting to changes in work processes and communication methods, and coping with the pressure of training and self-improvement. To enhance the efficiency and quality of teaching management for academic affairs personnel, measures that can be taken include intensifying training and theoretical understanding to improve comprehensive competence; engaging in practical exercises and cross-boundary collaboration to broaden competency boundaries; honing professional skills and communication abilities to build efficient teams; and fostering psychological quality and constructing incentive mechanisms to stimulate work enthusiasm.
Educational Digital Transformation; University Academic Affairs Staff; Professional Quality Improvement.
How Cultural Industry Policies Promote Urban Space Transformation: A Case Study of Beijing 798 Art District
Against the dual backdrop of accelerated post-industrial development and the continuous evolution of urban governance concepts, the cultural industry has gradually transcended the traditional service sector, becoming a core force driving urban renewal and reconstructing spatial value. Globally, cases such as London's South Bank Arts District, New York's SoHo, and Berlin's Kudam Art District demonstrate that peripheral areas once dormant due to the decline of traditional industries can fundamentally transform from "production spaces" to "cultural consumption spaces" through the intervention of cultural and creative industries. In this process, government cultural industry policies are not merely "administrative directives," but rather establish an ecosystem of deep integration between cultural resources and urban space through coordinated institutional design, resource allocation, and spatial planning, thereby reshaping the social structure, functional layout, and cultural identity of cities. As a landmark case of China's cultural and creative industry development, the 30-year evolution of Beijing's 798 Art District not only comprehensively presents the iterative logic of urban space under cultural industry policy guidance, but also reflects the complex and dynamic interactions between policy orientation, market forces, and social entities, providing a typical sample for understanding China's distinctive urban renewal path (Bianchini & Parkinson, 1993).
Cultural Industry; Policy-driven; Mode Exploration.
The Impact of Recent US Tariff Hikes on the Stock Market
Since early 2018, the U.S. government's tariff hike policy has triggered multiple rounds of global trade tension, with profound implications for financial markets. This paper investigates the impact of U.S. tariff policy on global stock markets between 2017 and 2025, focusing on S&P 500, CSI 300, and STOXX 50 indices. Using event study methodology and panel regression analysis, this work examines both short-term market reactions and long-term transmission mechanisms. The model incorporates macro control variables (U.S. bond yields, dollar index, and VIX), as well as industry-level trade sensitivity metrics. Results indicate that tariff announcements and implementations significantly depress market returns, especially in China’s A-share market, which shows heightened sensitivity to policy uncertainty. Over the medium to long term, tariffs influence market expectations via earnings forecasts, export dependence, and volatility sentiment. Industries with high trade exposure suffer sustained valuation discounts, even after controlling for fundamentals. Moreover, fluctuations in VIX and the dollar index amplify policy-induced risks across markets. This paper demonstrates that tariffs serve not only as trade instruments but also as key exogenous shocks to global capital markets. The findings offer important insights for investors managing risk under geopolitical uncertainty and for policymakers aiming to balance protectionism with financial stability.
Tariff Policy; Trade War; Stock Market Reaction; Event Study; Panel Regression; Macroeconomic Variables; Risk Transmission.