Journal of Education, Humanities and Social Sciences
Journal of Education, Humanities and Social Sciences is an open access, peer-reviewed publication series published by Darcy & Roy Press. It aims to publish conference proceedings dealing with all areas of education, sociology, economics, psychology, history, geography, linguistics, etc.
A study on China's "silver economy" based on SHAP interpretability modeling
This paper aims to explore the development models of China's provincial silver economy, identify their core influencing factors and interaction effects, so as to provide a basis for formulating targeted policies. To achieve this goal, it selects the panel data related to the silver economy from 2014 to 2023 in 31 provinces, municipalities and autonomous regions across the country, constructs a measurement index system including population structure, uses the EWM-CRITIC coupled weight system to measure the development level of the provincial silver economy, divides three types of models through spectral clustering and analyzes their characteristics and causes, and then uses random forests and SHAP method in explainable machine learning to identify the influencing factors and interaction effects. The results show that the provincial silver economy can be summarized into three types of models: high population structure-high consumption capacity type, low consumption capacity-medium pension security type, and low population structure-low elderly service resources type. Pension security and elderly service resources are the core influencing factors of the silver economic development model, and the population structure and consumption capacity constitute the demand base, and policy subsidies play a regulating role. The research innovation combines EWM and CRITIC methods to determine weights, and uses SHAP algorithm to analyze nonlinear effects and interaction effects, which can provide a basis for local governments to formulate policies, enterprises to tap potential, and the elderly to enhance consumer confidence.
Silver Economics, EWM-CRITIC coupled weight system, Spectral Clustering, SHAP.
Copyright (c) 2026 Journal of Education, Humanities and Social Sciences https://creativecommons.org/licenses/by-nc/4.0
Research on the impact of e-commerce on county economic resilience -- A quasi-natural experiment based on the policy of "comprehensive demonstration of e-commerce into rural areas"
Against the backdrop of high-quality county economic development and advancing e-commerce initiatives, the mechanism through which e-commerce drives county economic resilience has become a research focus. Current challenges include unbalanced development and inter-provincial disparities in resilience. Using balanced panel data of 265 counties from 2001 to 2021, this study employs the “Comprehensive Demonstration of E-Commerce in Rural Areas” policy as an exogenous shock, applying multi-time DID and mediating effect models. Results show the policy significantly enhances economic resilience, especially within two years of implementation ,the influence coefficient of which rises from 0.724 to 1.379. Industrial scale expansion mediates 2.37% of this effect via agglomeration and innovation. Heterogeneity analysis reveals stronger effects in non-Yangtze River counties and eastern regions. The study provides empirical references for digital-era county development, advocating strengthened e-commerce-industry synergy and location-based differentiated policies to boost resilience.
E-Commerce, Economic Resilience, Influence Mechanism, Multi-Time DID, Mediating Effect.
Theoretical Research on the Integration of multi-level Governance and Project Management of Engineering Ethics in the Development of Complex Systems
This paper focuses on the integration of engineering ethics and project management in complex systems development and proposes a multi-level governance framework to address the ethical challenges brought about by current technological advancements. Due to the rapid development of emerging technologies such as artificial intelligence and big data, ethical issues in complex systems development have become increasingly prominent, and traditional project management methods have difficulty effectively addressing these challenges. This study systematically explores the governance mechanisms of engineering ethics at the micro individual, meso organization, and macro society levels through literature review and case analysis, and proposes the "Ethical Embedded Project Management" (EEPM) theoretical model. The model incorporates ethical considerations into the requirements analysis, design, implementation, testing and maintenance stages of the project life cycle to achieve the organic integration of ethical governance and technology development. The research shows that the multi-level ethical governance framework can effectively improve project management efficiency, reduce ethical risks and promote the harmonious development of technology and society. Based on this, this paper constructs an engineering ethics evaluation index system for complex system development and proposes corresponding ethical review processes and tools. The research results have important theoretical significance and practical value for guiding engineering practice, improving project management methodology and promoting responsible technological innovation, and provide new ideas and methods for solving ethical dilemmas in complex system development.
Engineering Ethics; Complex systems; Multi-level governance; Project management; Ethical embedding.
Data Element Marketization and the Shift in Green Innovation: From Symbolic to Substantive
Promoting substantive green innovation is critical for sustainable economic growth. However, the “double externality” of environmental protection often incentivizes firms to prioritize symbolic innovation for image management over high-quality substantive innovation. This paper investigates whether Data Element Marketization (DEM) can correct this distortion and optimize the structure of corporate green innovation. Treating the establishment of data trading platforms as a quasi-natural experiment, this study employs a staggered difference-in-differences (DID) design using a sample of Chinese A-share listed companies from 2009 to 2023. By differentiating between substantive and symbolic innovation, the research rigorously tests the impact of DEM. The empirical results demonstrate that DEM significantly promotes substantive green innovation while having a limited and statistically insignificant impact on symbolic innovation. Mechanism analysis reveals that DEM drives this shift by reducing information asymmetry, alleviating financing constraints and enhancing management efficiency. Furthermore, heterogeneity analysis indicates that the positive effect is more pronounced in high-tech industries, firms with lower environmental awareness, and regions with under-developed digital finance. This study contributes to the literature by uncovering the unique role of DEM in enterprise green innovation. The findings suggest that policymakers should integrate DEM into environmental governance frameworks to encourage firms to move from symbolic to substantive environmental advancements.
Data Element Marketization, Green Innovation Structure, Substantive Innovation, Symbolic Innovation.
Amidst the global emphasis on sustainable development and the deepening.The incorporation of Environmental, Social, and Governance (<!-- [if gte msEquation 12]><m:oMath>ESG</m:oMath><![endif]--> ) considerations into a company's strategic framework, this study examines The correlation between a company's ESG (Environmental, Social, and Governance) performance and its market standing/performance valuation using Shanghai and Shenzhen firms from 2013 to 2024. Empirical evidence confirms a statistically significant positive effect of robust <!-- [if gte msEquation 12]><m:oMath>ESG</m:oMath><![endif]--> practices on enhancing corporate market value.Key findings are summarized as follows:Baseline Regression Analysis: A significant positive correlation exists between <!-- [if gte msEquation 12]><m:oMath>ESG</m:oMath><![endif]--> performance and corporate market value (measured by <!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr>Tobin's Q</m:r></m:oMath><![endif]--> ) at the 1% significance level.Robustness Validation: The positive linkage persists under rigorous testing conditions, including one-period lagged <!-- [if gte msEquation 12]><m:oMath>ESG</m:oMath><![endif]--> variables and substitution of dependent variables (e.g.,alternative market value metrics).Heterogeneity Insights:<!-- [if gte msEquation 12]><m:oMath>ESG</m:oMath><![endif]--> performance positively influences market value for both state-owned enterprises (<!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr>SOEs</m:r></m:oMath><![endif]--> ) and non-state-owned enterprises (<!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr>non-SOEs</m:r></m:oMath><![endif]--> ).The impact is markedly stronger for <!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr>non-SOEs</m:r></m:oMath><![endif]--> compared to <!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr>SOEs</m:r></m:oMath><![endif]--> , likely attributable to differences in resource flexibility and stakeholder responsiveness.This research extends Research on the economic impacts stemming from <!-- [if gte msEquation 12]><m:oMath>ESG</m:oMath><![endif]--> factors performance, offering actionable insights for:Corporations: Optimizing <!-- [if gte msEquation 12]><m:oMath>ESG</m:oMath><![endif]--> integration into long-term strategic planning;Investors: Enhancing decision-making frameworks through <!-- [if gte msEquation 12]><m:oMath>ESG</m:oMath><![endif]--> risk-return assessments;Policymakers: Designing incentives to accelerate sustainable business practices.
Optimal Crop Planting Scheme Based on Linear Programming Model and Particle Swarm Optimization
With population growth and climate change, crop planting optimization has become increasingly critical in modern agriculture. The core challenge lies in maximizing economic benefits while satisfying planting constraints. This paper utilizes actual planting data from a rural area in North China Mountains to propose an optimized solution for enhancing land resource utilization and achieving sustainable rural economic development. By integrating particle swarm optimization (PSO) with a linear programming model, this paper establish a multi-constrained optimization framework focusing on annual, plot-specific, and seasonal planting area allocation. The objective function prioritizes total revenue maximization under considerations such as plot type restrictions, continuous cropping avoidance, and legume planting frequency constraints. Results demonstrate that the optimized scheme achieves a 15% and 12% increase in total revenue under two distinct sales strategies (2024–2030), respectively. This research not only provides actionable insights for agricultural optimization in North China but also serves as a reference for similar regions globally.
Optimal Planting Scheme, Linear Programming, Particle Swarm Optimization, Economic Efficiency, Agricultural Sustainability.
Study on Influencing Factors of Brand Building of Agricultural Products in Western Guangdong
Brand building of agricultural products in western Guangdong is related to farmers' income. In order to explore the influence of brand building on the brand development of agricultural products, this paper uses the theory of public goods and stakeholders, and uses questionnaire survey to carry out research. The results show that regional factors, industrial factors, brand factors and public factors all have positive influence on the brand development of agricultural products. Accordingly, the countermeasures are put forward: relying on regional advantages to extend the value chain of agricultural products; Strengthen industrial construction and integrate industrial resource allocation; Dig deep into the connotation of brand culture and expand market share; Promote multi-stakeholder coordination and achieve coordinated development. This study hopes to provide useful reference for brand building of agricultural products in western Guangdong.
Agricultural Products, Brand Building, Influencing Factors.
Research on the Impact of Digitalization and Intelligentization on Regional Innovation Capability Based on Provincial QCA Configuration Analysis
Against the backdrop of digitalization and intelligentization, the linkage between regional innovation capabilities and economic development has grown closer and more complex. An in-depth exploration of the multi-dimensional influencing factors of regional innovation capabilities is a prerequisite for accurately grasping the intrinsic link between regional innovation and economic development. However, existing studies are mostly confined to single-dimensional explanatory variables and lack analysis of multi-factor synergistic mechanisms. Using cross-sectional data from 31 Chinese provinces and municipalities in 2023, this study applies the fsQCA method to construct a digital-intelligent factor system with seven core variables and identifies the formation paths of high-level regional innovation capabilities. The study confirms two findings: (1) No single antecedent condition is necessary for fostering high-level regional innovation capabilities. (2) Four typical paths for these capabilities are identified, including the infrastructure-deficient path, the high-level development path, the infrastructure-digital industrialization path, and the digital industrialization-industrial digitalization linkage path, and these conclusions remain robust after robustness tests. This study transcends the traditional single-factor analytical framework and uncovers the dynamic combinatorial logic of digital-intelligent factors through the lens of configurational theory. It provides decision-making implications for "province-specific" regional innovation policies and guidance on resource allocation for enterprises.
Regional Innovation Capability, Digitalization, Intelligentization, fsQCA, Configurational Paths.
Crop planting strategies under robust linear programming based on constrained approximation
In the context of rural revitalization and agricultural modernization, the optimization of crop cultivation strategies is crucial to enhancing farmers' incomes and promoting sustainable economic development. Although the existing strategies are continuously optimized, the consideration of crop, land management and climate factors is still insufficient. Therefore, this paper proposes a crop planting strategy under robust linear programming based on constrained approximation, aiming at combining rural reality, scientifically allocating crop and plot resources, and formulating an optimal planting plan to maximize the planting income in the next seven years. Firstly, different crops and their planting plot types are summarized and processed, and the constraints are constraint-approximated and equated, and secondly, according to the distribution of crops, a variety of plot types are subdivided and the constraints are reduced accordingly.Finally, set the decision variable for the plant's planting area, for a certain quarter of a plant's planting per acre profit, for different chunks, consider and select the appropriate constraints, introduce a linear programming model, bring in the objective function, for more than part of the stagnant sales, resulting in a waste of the situation through the MATLAB to establish a linear programming model to maximize the total return, develop the optimal planting program and to find the maximum sales to get the first case the maximum total profit from 2024 to 2030 is $37008056. Due to multiple uncertainties in climate and market, multiple attributes of the crop will generate uncertainty, consider the fluctuation intervals of uncertain parameters, determine the boxed uncertainty set, and build a robust linear programming model to simulate the uncertainty scenario. The maximum total profit of $35,906,995 is obtained for the years 2024 to 2030 for this scenario.The results show that the robust linear programming model, after considering the uncertainty factors, the maximum total profit, although lower than the deterministic model, is still within the acceptable range, and can effectively improve the robustness and reliability of the planting program and reduce the impact of uncertainty factors on agricultural production, which has a high practical application value.
Research on the Intercultural Leadership of Chinese Enterprises Based on Hofstede’s Cultural Dimension Theory
As Chinese enterprises expand globally, their leaders face significant challenges due to cultural differences. These differences in communication styles, management expectations, and work values can lead to misunderstandings and inefficiencies, necessitating the development of intercultural leadership capabilities. This paper explores the impact of cultural differences on the global leadership of Chinese enterprises and proposes corresponding strategies. Using Hofstede’s cultural dimension theory as the theoretical foundation, the study analyzes how Chinese enterprises can adapt their leadership approaches to different cultural contexts. The findings indicate that Chinese enterprises can enhance their global leadership effectiveness by understanding and adapting to cultural differences. However, it is crucial to be aware of the limitations of cultural theories and continuously innovate to adapt to the evolving cultural landscape. The future demand for intercultural leaders is expected to increase, and intercultural leadership will become an increasingly valuable asset. The study suggests that Chinese enterprises should integrate traditional wisdom with modern innovation to develop unique leadership styles. They should also focus on cultivating cultural intelligence among employees and creating inclusive organizational cultures to support their global operations.
Intercultural Leadership, Chinese Enterprises, Hofstede’s Cultural Dimension Theory.
The Influence of Debt Financing Structure on Corporate Financial Risk
The consistent increase in corporate leverage ratios in China has raised concerns about systemic risks. Using A-share non-financial listed companies from 2015 to 2024 as a sample, this paper empirically examines the impact of debt financing structure on corporate financial risk and its variation across industries. The study finds that: First, debt financing structure is positively correlated with corporate financial risk, meaning an increase in the debt financing ratio significantly exacerbates corporate financial risk; Second, compared to asset-heavy industries, the positive impact of the debt financing structure on corporate financial risk is more pronounced in asset-light industries. This research provides a theoretical basis for differentiated corporate leverage control policies.
Debt Financing Structure, Corporate Financial Risk, Industry Characteristics, Fixed Effects Model.
Directors' and Officers' Liability Insurance and Specific Volatility in Corporate Stock Prices
Directors and Officers Liability Insurance (D&O insurance), as a vital tool for corporate risk management and operational stability, exerts a profound influence on the development of share price volatility. This study employs panel fixed-effects models and instrumental variable methods, utilising data from listed companies between 2004 and 2023, to validate the mediating effect of information transparency. Findings reveal that D&O insurance exerts a positive effect on stock price volatility, a conclusion upheld through multiple robustness tests. From an internal corporate governance perspective, this promotional effect is more pronounced in firms characterised by overlapping board and executive functions, high executive compensation incentives, and concentrated share ownership. Regarding external environmental factors, the promotion of stock price volatility by directors' and officers' liability insurance is more pronounced in firms facing high performance pressure, high media attention, and high marketisation. Mechanism analysis indicates that purchasing directors' and officers' liability insurance enhances stock price volatility by improving corporate information disclosure quality and transparency. This conclusion holds significant implications for regulating the development of directors' and officers' liability insurance business and guiding enterprises to enhance information disclosure efficiency.
D&O Insurance, Information Transparency, Stock Price Volatility.
The Impact of Green Factory Rating on Corporate ESG Performance
Against the backdrop of the "dual carbon" goal and the deepening of the green development concept, this paper adopts the data of China's A-share listed companies from 2012 to 2023, and takes the green factory rating policy as an entry point to test the impact of this policy on the ESG performance of firms and its internal mechanism. The results show that firms awarded with green factories are conducive to enhancing their ESG performance. Mechanism analysis shows that green factory rating can promote corporate ESG performance through two paths: alleviating financing constraints and stimulating green innovation. Heterogeneity analysis finds that the policy has a more significant effect on the ESG performance of enterprises in low-carbon pilot cities and eastern regions. This paper provides empirical evidence and decision-making reference for improving the green industrial policy system and promoting the practice of corporate sustainable development.
Green factory rating, ESG performance, Financing constraints, Green innovation.
Mechanism of the Impact of Enterprise Digital Transformation on ESG Performance from Internal and External Perspectives
With the full arrival of the digital economy era and the growing prominence of sustainable development concepts, Digital Transformation and ESG have garnered widespread attention across society. This study uses A-share listed companies from 2013 to 2023 as its research sample, adopting an Internal Control and External Supervision perspective to construct a dual fixed-effects model. It empirically investigates the relationship and underlying mechanisms between DT and ESG Performance. The findings reveal: (1) DT can help companies improve their ESG Performance, and this finding withstands an extensive battery of robustness checks. (2) Internal Control and External Supervision play a partial mediating role between DT and ESG Performance, indicating that DT promotes corporate sustainability through both internal and external pathways. (3) Heterogeneity analysis shows that the promotional effect of DT on ESG is more pronounced in eastern regions and non-state-owned enterprises, while the marginal effects in central and western regions and state-owned enterprises are relatively limited. The article provides theoretical basis for understanding the intrinsic mechanisms driving ESG improvement through digital technology and offers decision-making references for policy formulation and corporate practice.
Digital Transformation, ESG Performance, Internal Control, External Supervision, Intermediary Effect.
Dynamic Evolution and Driving Mechanisms of Green GDP: Provincial Evidence from China
This study constructs a comprehensive Green GDP accounting framework encompassing economic, resource, and environmental dimensions. Based on data from 2010–2022 for 31 provinces in mainland China and using an entropy weighting method to determine indicator weights, provincial Green GDP values are calculated. The results indicate that Green GDP and conventional GDP rise in tandem, with the former expanding at a marginally faster rate; meanwhile, the environmental-cost component exhibits a gradual decline over time. A structural inflection is observed around 2015–2016, after which growth patterns shift, and significant regional disparities in Green GDP are apparent. An ARIMA model forecast shows the gap between Green GDP and conventional GDP narrowing gradually from 17.4% in 2022 to 12.9% in 2028. Panel fixed-effects analysis reveals that economic scale is the primary driver of Green GDP growth; industrial structure upgrading exhibits a short-term “decline-then-rise” effect on Green GDP, and rapid urbanisation exerts additional environmental pressure. By integrating economic, resource, and environmental factors, this research offers a holistic and innovative approach to evaluating sustainable development. The entropy-based weighting and the combination of time-series forecasting with panel analysis represent methodological advances, and the findings not only enrich the theoretical understanding of Green GDP dynamics but also carry practical implications.
Green GDP, Entropy Weight Method, Environmental Benefits, Regional Heterogeneity, Fixed-Effects Model.
The Impact of ESG Performance on Corporate Competitiveness
With sustainable development emerging as a global consensus and China’s “dual carbon” goals advancing in depth, Environmental, Social, and Corporate Governance (ESG) performance has become an increasingly critical benchmark for assessing a firm’s long-term value and competitiveness. This study investigates the effect of ESG performance on corporate competitiveness by examining Chinese A-share listed firms from 2013 to 2023 through a two-way fixed effects model. The results demonstrate that ESG performance significantly enhances corporate competitiveness, with the effect being particularly pronounced among large-scale and state-owned enterprises. These findings provide valuable insights for firms seeking to embed ESG principles into their core strategies to strengthen competitiveness, as well as for policymakers aiming to refine ESG-related regulatory frameworks.
ESG performance, corporate competitiveness, firm size, ownership structure, fixed effects model.
The Coupling of Green Finance and Economic Growth: An Empirical Study of Shenzhen under Low-Carbon Policy Using CCDM and PVAR Models
Confronting global climate change and China's "Dual Carbon" goals, Shenzhen, a national low-carbon pilot city, presents a valuable case for studying the synergy between green finance and economic growth. Despite existing studies on green finance, the synergistic mechanisms within integrated policy frameworks remain underexplored. This study addresses this gap by utilizing Shenzhen's macroeconomic, green finance, and carbon emissions data (2015-2024), this study employs a Coupling Coordination Degree Model (CCDM) and a Panel Vector Autoregression Model (PVAR) to analyze their dynamic coupling mechanism. Key findings include: (1) Exponential expansion of Shenzhen's green finance sector, evidenced by an 18% average annual growth in green credit balance and a 14-fold increase in green bond issuance. (2) Policy support and institutional innovation, identified through a "policy-market-technology-region" framework, are the primary drivers of coupling development, accounting for 42.3% of the effect. (3) Significant regional synergy, with the Qianhai Green Finance Reform Pilot Zone exhibiting a technology spillover coefficient of 0.78 to surrounding areas. This research offers a replicable policy paradigm for high-density cities pursuing high-quality, low-carbon economic development.
Green Finance, Economic Growth, Coupling Coordination Model, Vector Autoregression Model, Low-Carbon Policy.
The Impact of Green Credit on Bank Risk-Taking: Based on the Moderating Effect of FinTech
Based on panel data from 20 representative listed commercial banks in China between 2015 and 2023, this study conducts an empirical analysis of the effect of green credit on bank risk-taking, with a specific focus on the moderating function of FinTech. The results indicate that green credit plays a significant role in reducing risk exposure among commercial banks. Furthermore, FinTech is found to strengthen this risk-alleviating impact. The inhibitory influence of green credit on risk-taking is also more substantial in large state-owned commercial banks compared to their non-state-owned counterparts. By examining the interplay between green credit and bank risk-taking from a risk-bearing perspective, this research elucidates the facilitatory role of FinTech and offers novel insights and a theoretical foundation for commercial banks to evaluate green credit risks, develop evidence-based risk management frameworks, and optimize policy support systems for green finance.
Green credit, Commercial bank risk-taking, FinTech, Moderating effect.
Supply Chain Resilience Impact on Enterprise Digital Technology Innovation: Dual Perspectives of Absorptive Capacity and Adaptability
Under the impact of multiple uncertainties such as geopolitical conflicts and financial risks, the construction of supply chain resilience has become a primary strategic goal​ for the survival of enterprises, but an acute paradox is increasingly prominent: when enterprises strive to build a risk-resistant "resilient armor", this protection system may become a hidden shackle that stifles digital technology innovation. Utilizing panel data from Chinese listed firms (2013-2023), this research examines how supply chain resilience (SCR) shapes enterprise digital innovation through the integrated lens of dynamic capability theory, dissecting transmission mechanisms at the capability-microstructure nexus. The study finds that supply chain resilience enhances the enterprise's digital technology innovation level by improving its absorption capacity and adaptive capacity, thereby strengthening the enterprise's ability to respond quickly to environmental changes and coordinate the configuration of resources. Behaviorally, patient capital holders exhibit a neglect of innovation risk premium and demand excessive returns for digital innovation exposures, leading to an equilibrium of underfunding. When enterprises obtain more patient capital, they tend to invest in projects with stable returns, thereby reducing the enterprise's firm digital innovation capability. In addition, this study breaks through the limitations of traditional single-dimensional indicators and constructs a comprehensive index through resistance, recovery, operations, supply and demand matching, and renewal capabilities to more accurately capture supply chain resilience, while also revealing the influencing factors of innovation and development in the manufacturing industry.
Supply chain resilience, Digital technology innovation, Absorptive capacity, Adaptability, Patient capital.
Green Finance Empowering Corporate Green Innovation Based on the Dual Mechanisms of Resource Allocation and Market Signaling
This study empirically examines the impact of green finance on corporate green innovation, its regional heterogeneity, and underlying mechanisms using a sample of A-share listed companies in Shanghai and Shenzhen stock exchanges from 2010 to 2023. The findings reveal three key insights: First, green finance significantly promotes corporate green innovation, a conclusion that remains robust in both one-period lag tests and alternative sample interval robustness checks. Second, the effect exhibits distinct regional heterogeneity - the western region demonstrates the strongest and most significant positive impact, while the eastern region shows a positive but statistically insignificant effect, and the central region displays no significant impact. Third, the study identifies two primary mechanisms through which green finance influences green innovation: alleviating financing constraints by providing specialized financing instruments, policy endorsements, and synergistic effects that enhance capital accessibility for green innovation projects; and transmitting market signals through improved information disclosure, third-party evaluations, and increased market attention that channels resources toward green innovation initiatives. These findings provide micro-level evidence for understanding the green finance-innovation nexus and offer theoretical foundations for optimizing green finance policy design.
Green finance, Corporate green innovation, Financing constraints, Market signaling
Foreign Direct Investment and China's Employment Structure Transformation: An Empirical Analysis Based on Urban Panel Data
Against the backdrop of high-quality development and an employment-first strategy, how foreign direct investment (<!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr>FDI</m:r></m:oMath><![endif]--> <span lang="EN-US" style="font-size: 10.5pt; mso-bidi-font-size: 11.0pt; font-family: 等线; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; position: relative; top: 2.5pt; mso-text-raise: -2.5pt; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;"> ) shapes urban employment structures is of significant practical importance, as it relates to industrial upgrading and the well-being of the people, contributing new insights from three aspects: research perspective, data granularity, and heterogeneity analysis. This paper uses panel data from 283 prefecture-level cities and four municipalities in China from 2010 to 2023 to construct a two-way fixed effects model and analyze the impact of <!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr>FDI</m:r></m:oMath><![endif]--> <span lang="EN-US" style="font-size: 10.5pt; mso-bidi-font-size: 11.0pt; font-family: 等线; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; position: relative; top: 2.5pt; mso-text-raise: -2.5pt; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;"> on the proportion of employment in the secondary industry. The findings reveal that <!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr>FDI</m:r></m:oMath><![endif]--> <span lang="EN-US" style="font-size: 10.5pt; mso-bidi-font-size: 11.0pt; font-family: 等线; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; position: relative; top: 2.5pt; mso-text-raise: -2.5pt; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;"> significantly increases the share of employment in the secondary sector, and this conclusion holds under a series of robustness tests. Heterogeneity analysis indicates that the effect is stronger in ordinary prefecture-level cities and central-western regions, while it is insignificant or negative in eastern regions, municipalities/sub-provincial cities, and northeastern regions;<!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr> FDI </m:r></m:oMath><![endif]--> <span lang="EN-US" style="font-size: 10.5pt; mso-bidi-font-size: 11.0pt; font-family: 等线; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; position: relative; top: 2.5pt; mso-text-raise: -2.5pt; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;"> has a certain “crowding-out” effect on the tertiary sector and a weak impact on the primary sector; its role is more pronounced in cities with relatively underdeveloped digital inclusive finance. Based on these findings, the study proposes differentiated investment attraction and employment coordination strategies to enhance the structural employment spillover effects of <!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:scr m:val="roman"/><m:sty m:val="p"/></m:rPr>FDI</m:r></m:oMath><![endif]--> <span lang="EN-US" style="font-size: 10.5pt; mso-bidi-font-size: 11.0pt; font-family: 等线; mso-ascii-theme-font: minor-latin; mso-fareast-theme-font: minor-fareast; mso-hansi-theme-font: minor-latin; mso-bidi-font-family: 'Times New Roman'; mso-bidi-theme-font: minor-bidi; position: relative; top: 2.5pt; mso-text-raise: -2.5pt; mso-ansi-language: EN-US; mso-fareast-language: ZH-CN; mso-bidi-language: AR-SA;"> .
Foreign Direct Investment, Employment Structure, Secondary Industry, Tertiary Industry, Reform and Opening-up.
Life-course Perspectives on Childhood Inequality: Understanding Its Contemporary and Long-term Impacts
Socioeconomic inequality in childhood has become a core challenge for global public health and social equity. This article reviews the socio-economic inequality experienced in childhood, which is reflected not only in physical and mental health and education, but also in social performance. These early disadvantages continue to accumulate and develop in the long term, affecting career development and individuals’ capacity for economic accumulation in adulthood, and eventually widen the physical and mental health gap in middle and old ages. The persistence of this predicament highlights the necessity of multi-faceted interventions during the critical period of children's growth and development. This study emphasizes the need for a comprehensive policy approach and early interventions that integrates educational investment, health system reform and social security enhancement. Understanding the impacts of and interventions for socioeconomic inequality in childhood is of great significance for achieving sustainable social equity and breaking the intergenerational cycle of poverty.
Childhood; socioeconomic inequality; health; education.
From Hegemony to Transformation: The Institutional Logic of the Pound Sterling's Millennial Evolution
The pound sterling is one of the world's oldest currencies. Its evolutionary process from a global hegemonic currency to an important international currency provides a unique historical perspective for understanding the dynamic changes of the international monetary system. This paper adopts the analytical framework of historical institutionalism, reviews the nearly millennial evolution of the pound sterling through a literature review, and focuses on analyzing the institutional logic of its achievement of hegemony in the 19th century relying on the gold standard system, its hegemonic decline under the impact of the two World Wars in the 20th century, and its final post-war transformation into a modern international currency. This study shows that the essence of monetary hegemony is an extension of a nation's comprehensive strength, but its maintenance depends on a stable credit anchor and the ability to adapt to changes in the global economic landscape. The history of the pound sterling indicates that even a declining hegemonic currency can find its position in the new international order by virtue of its institutional resilience and historical accumulation. This process has practical implications for understanding the current trend of diversification in the international monetary system.
Pound Sterling; Monetary Hegemony; Gold Standard; International Currency; Hegemonic Decline.
The Influence of Social Media on Luxury Brand Communication Strategies: A Case Study of Gucci, Prada, Dior, and Chanel
The advancement of social media platforms has greatly impacted the manner in which luxury fashion brands interact with consumers. Social media platforms like Instagram, TikTok, and YouTube are a unique way for brands to reach out to the audience, especially the younger generation. Thus, this paper aims to explore the effects of social media on luxury brand communication, with a focus on Gucci, Prada, Dior, and Chanel. In the paper, the author examines the use of social media in increasing brand recognition, customer loyalty, and purchase intentions using case studies. The study also shows that social media has helped luxury brands to expand their reach, build brand experiences, and overcome the constraints of conventional advertising. The study also stresses on the need to strike a balance in the use of social media, where brands should keep their identity intact while at the same time reaching out to a larger and more engaged audience.
Luxury Brand Communication; Social Media Marketing; Brand Identity and Exclusivity; Influencer Marketing in Luxury Brands; Consumer Engagement on Instagram.
From "Cultural Understanding" to "Business Valuation": Analyzing the "Industrialization" Turn of the Humanities
Contemporary humanities are facing a profound "industrialization" turn, its core characteristic has already quietly slid from "cultural understanding" towards "business valuation." This article argues that this turn is not a scattered reform or a passive compromise, but rather a multi-dimensional systemic project driven by neoliberal "academic capitalism." This article aims to reveal the three major core mechanisms of this turn: First, at the teaching mechanism level, through the reorganization of "Applied Humanities" (such as the University of Arizona model) and "skills discourse" (such as the Georgia Tech "Robin Hood" case), humanistic "content" is instrumentalized into sellable "skills"; Second, at the technical mechanism level, using "Digital Humanities" as an accelerator (such as the "IP-ization" of "Digital Dunhuang"), it provides the technological foundation for industrializing humanistic "raw materials" and realizing "business valuation"; Finally, at the administrative mechanism level, through management tools such as the "impact agenda" (like the UK REF) and "academic portfolio review" (like UNCG hiring rpk Group), the logic of "business valuation" is "liquidated" and "enforced" from the top down. This article's conclusion is that this systemic turn is creating a "Faustian" paradox—the university on one hand sells the "product" of "critical thinking," and on the other hand eliminates its basis for existence in its management—ultimately potentially leading the humanities to slide into a "post-humanities," fragmented, and instrumental existence.
Humanities; Industrialization; Neoliberalism; Academic Capitalism; Digital Humanities.
Empowering Education in Western China with AI Technology: A Case Study from Gansu Province
The present study is an exploratory case study of the role of artificial intelligence (AI) in the digital transformation of education throughout Western China, resulting from a summer 2025 social practice project with the No.3 Middle School in Zhenyuan County, Gansu Province. The study analyses AI-based personalized teaching, teacher development, and resource-sharing programmes to argue that these technologies will be critical for providing a relatively fair allocation of teaching resources in an area with extreme imbalances in teaching resources. Such technologies, it is argued, can fulfil a dual role by not only providing a direct interface with the students but also serving as a very effective tool for the professional development of teachers, thereby offering a further mechanism for teaching fairness. The study also discusses certain arising difficulties, such as infrastructural deficiencies, teacher training deficiencies, and a lack of locally specific instructional resources. It concludes with suggestions for addressing these findings.
Artificial Intelligence; Educational Equity; Rural Education (China); Digital Transformation; Case Study.
Analysis of the Business Strategy in the Banking Industry: A Case Study of JPMorgan Chase & Co
With the fast growth of the Internet, JPMorgan Chase is suffering more and more competition from old-fashioned banks and new fintech companies. At the same time, with the further development of technology to change the financial market dramatically, JPMorgan's old-fashioned strengths, such as its worldwide coverage and extensive range of services, are diminishing. Therefore, this paper discusses JPMorgan Chase's challenges and strategies regarding its challenges in investment banking, the adoption of fintech, and pressure from regulation. This study discovers that JPMorgan has to pay more attention to customer experience improvement, the adoption of new technology such as AI and blockchain, and market penetration to new markets. JPMorgan's future could be enhanced by digitizing its strength and acting on customers' evolving requirements. The conclusion from this study could be applicable to future JPMorgan Chase development and has some major implications to facilitate the healthy growth of the banking sector.
JPMorgan Chase; Competition; Fintech; Customer experience; Technology adoption.
The Impact of Artificial Intelligence on the Labor Market
In addition to industrial robots, machine learning, and generative artificial intelligence (AI), AI technology has advanced rapidly over the past ten years, infiltrating several industries, including manufacturing, services, finance, healthcare, and education. The rise in productivity has had a significant impact on the labor market. Through writing reviews and event studies, this post systematically examines the multiple effects of AI on general jobs, employment composition, and skill requirements, while recommending parliamentary and business strategies. According to studies, AI's impact on employment reveals complex characteristics of both movement and design. Low-skilled staff have the most serious issues, whilst the need for highly trained and multidisciplinary skills has dramatically increased. Instantly, local developmental disparities, inadequate retraining, and skill gaps have become significant issues that require immediate resolution. In order to accomplish an equitable transition and lasting expansion of the labor market in the framework of the AI boom, this study ultimately makes policy ideas at three levels: government, enterprise, and worker.
Artificial intelligence, labor market, employment structure, skill demand, policy reaction.
LSTM-Integrated Particle Swarm Optimization Model for Listed Companies
In the context of global economic integration, credit risk assessment of listed companies is crucial for maintaining capital market stability. However, traditional methods rely on static financial indicators, which are limited by timeliness and subjective parameter selection. While LSTMs excel at capturing long-term dependencies in financial time series data, they are limited by the difficulty in accurately determining key hyperparameters, such as the number of hidden layer neurons and the learning rate, which hinders their predictive performance. Therefore, this study proposes a credit risk assessment model for listed companies based on a combination of a long short-term memory network (LSTM) and a particle swarm optimization (PSO) algorithm. This model overcomes the core limitations of traditional methods in time series data processing and parameter optimization. Using deep learning techniques, the model automatically extracts features from time series data and effectively captures the dynamic impact of different financial indicators on credit risk. The particle swarm optimization algorithm is used to optimize the LSTM model's hyperparameters, thereby improving predictive accuracy and stability. Empirical results show that the proposed model outperforms traditional methods across multiple evaluation metrics, achieving an accuracy of 92.3% and a recall of 90.1%, validating its effectiveness and practical value in credit risk assessment. This model theoretically overcomes the bottleneck of LSTM parameter tuning. In practice, it can provide investors and regulators with a high-precision risk assessment tool, helping to improve capital market risk management.
Credit Risk Assessment, LSTM, Particle Swarm Optimization, Financial Health, Deep Learning
Research on the Value added Evaluation of Digital Competence of University Teachers from the Perspective of Education DigitalizationMotion
In the context of AI, Internet and big data technology accelerating the digital transformation of education, the digital competency of college teachers has become the core element to promote the modernization of higher education. Based on the industry standard of "Teacher Digital Literacy", the four primary indicators of digital basic ability and digital teaching ability are refined into 12 secondary indicators (such as hardware and network access ability, proficiency in online teaching platform operation, etc.). Using the fuzzy Delphi method to aggregate expert fuzzy judgments (five level language variables and triangular fuzzy number conversion), combined with the Analytic Hierarchy Process (AHP) to construct a fuzzy pairwise comparison matrix, and ensuring the rationality of weights through consistency testing (CR<0.1), ultimately forming a comprehensive weight system that integrates subjective and objective factors ( =0.7), achieving scientific quantification of indicator importance. Constructing a "static weighting+dynamic evolution" model, calculating the static competence score SS of universities through the weight vector W. Empirical evidence shows that the teacher competence of Double First Class universities ( 1=0.82) and the eastern region ( 1=0.75) has significantly increased, and policies such as digital training center coverage and intelligent teaching subsidies have a marginal effect of 48% on western universities.
College teachers, digital competence, value-added evaluation, fuzzy Delphi method.