World Journal of Economics and Business Research
World Journal of Economics and Business Research (WJEBR) is an international peer-reviewed, open access journal.
HOW DOES THE GOVERNMENT GUIDANCE FUND DRIVE THE UPGRADING OF CORPORATE HUMAN CAPITAL? — BASED ON THE PERSPECTIVE OF EMPLOYEE EDUCATION LEVEL
As a pivotal policy-based financial instrument, whether government guidance funds (GGF) can facilitate human capital upgrading is essential for assessing the efficiency of fiscal capital allocation. Utilizing a sample of A-share listed companies in Shanghai and Shenzhen from 2006 to 2023, this study employs a two-way fixed effects model to examine the impact of GGF investment on employees’ education level and its underlying mechanisms. The empirical results demonstrate that GGF investment has significantly increased the proportion of highly educated talent within enterprises, a finding that remains robust across various sensitivity tests. Mechanism analysis reveals that this promotional effect stems from a certification effect prior to investment, which bolsters corporate reputation through government endorsement to attract talent. Post-investment, the funds exert resource and governance effects, indirectly optimizing human capital structures by mobilizing policy resources and incentivizing long-term innovation. Heterogeneity analysis further indicates that this effect is more pronounced among high-tech enterprises, firms with executives possessing overseas backgrounds, and those located in regions with lower market potential. This research moves beyond traditional financial performance metrics, providing micro-level evidence for optimizing the performance evaluation of GGF and advancing human capital-driven development strategies.
Copyright (c) 2026 HaoRan Weng https://creativecommons.org/licenses/by/4.0
A COMBINED EWM AND MULTIVARIATE STATISTICAL APPROACH FOR EVALUATING GREEN FINANCE AND ECONOMIC SUSTAINABILITY
Unraveling the nexus between financial allocation and ecological performance demands a framework capable of dismantling complex spatial heterogeneities. This study constructs a multidimensional statistical pipeline analyzing cross-sectional data across thirty Chinese provinces. Following objective dimension reduction via the entropy weight method, spatial clustering strictly partitions the landscape into distinct developmental tiers. Canonical correlation analysis subsequently extracts orthogonal structural equations, yielding a systemic coupling coefficient of 0.976. The derived loadings explicitly quantify a dual-edged transition mechanism: ecological sustainability relies heavily on capital friction against high-energy sectors (loading: -0.869), running parallel to targeted capitalization that accelerates industrial emission reductions (loading: 0.784). Beyond immediate operational insights, this research provides a mathematically rigorous blueprint for macroeconomic restructuring. By mapping these exact directional constraints, the framework equips policymakers to abandon homogeneous interventions, facilitating precision green resource allocation across highly polarized regional economies.
Copyright (c) 2026 HongYue Deng https://creativecommons.org/licenses/by/4.0
SPATIOTEMPORAL EFFECTS OF DIGITAL FINANCIAL INCLUSION AND FISCAL DECENTRALIZATION ON THE URBAN–RURAL INCOME GAP
This study investigates the joint impact of digital financial inclusion and fiscal decentralization on the urban–rural income gap in China within a unified spatiotemporal analytical framework. Using provincial panel data and employing both two-way fixed effects and spatial econometric models, the analysis reveals that digital financial inclusion significantly narrows the urban–rural income gap by improving financial accessibility, reducing transaction costs, and promoting rural entrepreneurship, while fiscal decentralization tends to widen the gap due to local governments’ bias toward urban-oriented resource allocation. Importantly, the interaction between the two shows that fiscal decentralization strengthens the inequality-reducing effect of digital financial inclusion, suggesting a moderating role through enhanced incentives for local investment in digital infrastructure. Furthermore, spatial results indicate significant positive spatial dependence and spillover effects, whereby digital financial inclusion generates beneficial cross-regional impacts, whereas fiscal decentralization may intensify regional disparities through competitive dynamics. These findings are robust across alternative model specifications and variable measurements, offering important insights into the mechanisms of income distribution in the digital economy and providing policy implications for optimizing fiscal systems and promoting inclusive financial development.
Copyright (c) 2026 Yan Zhai https://creativecommons.org/licenses/by/4.0
INVESTIGATION AND COUNTERMEASURES ON THE PROBLEM OF INCREASED LITCHI YIELD BUT NOT INCREASED INCOME: TAKING CHINA MAOMING LITCHI AS AN EXAMPLE
The 2025 litchi harvest in Maoming, Guangdong achieved record yields, however, increased production didn’t translate into proportional profit growth. This study investigates the phenomenon of “increased production without corresponding income growth” from both supply-side and demand-side perspectives. From the supply side, the findings indicate that factors such as concentrated market entry, oversupply, labor shortages, rising production costs, limited regional brand premium capacity, and insufficient product quality and technological innovation have constrained income growth. From the demand side, Consumer survey results reveal a general preference for low-priced litchis. However, a considerable proportion of consumers are willing to pay premium prices for higher quality, strong brand, and specific consumption scenarios. Most consumers accept a regional brand premiums of up to 10% for Maoming litchis, while demonstrating strong repurchase intention. Notably, 44.3% of respondents reported never having purchased Maoming litchis, highlighting the coexistence of high repurchase potential and significant untapped market segments. A comprehensive supply–demand analysis identifies several core contradictions: rigid supply structures versus weak demand upgrading; high channel dependency versus diversified consumption patterns; misalignment between weak brand awareness and rising quality expectations; and technological limitations combined with evolving consumption experiences that create “last-mile” barriers.Based on these findings, this study proposes targeted policy recommendations to address these structural issues and promote sustainable development in the litchi industry.
Increased production without income growth
Copyright (c) 2026 XiaoPing Tan; ZhongYi Zhu; WeiCheng Chen; RuiQi He; GaoXue Wei https://creativecommons.org/licenses/by/4.0
ALGORITHMIC GOVERNANCE AND THE RECONFIGURATION OF GLOBAL VALUE CHAINS: A CASE STUDY OF SHEIN’S ON-DEMAND MANUFACTURING MODEL
This paper examines how algorithmic governance reshapes global value chains (GVCs) in the context of platform-based fast fashion. While prior research has explored platform governance and GVC organization separately, less attention has been paid to how algorithmic systems intervene in production processes at an operational level. Drawing on a qualitative case study of SHEIN, this study uses multiple sources of secondary data, including company disclosures, industry reports, and third-party analyses. A process-tracing approach is adopted to reconstruct the development of SHEIN’s on-demand manufacturing model. The findings suggest that algorithmic governance operates through three interrelated mechanisms: real-time demand sensing, small-batch production, and dynamic supply chain coordination. Together, these mechanisms enable a shift from a forecast-driven “push” model to a data-driven “pull” model, reducing inventory risk while improving responsiveness. By linking platform governance with GVC analysis, this paper provides a mechanism-based explanation of how data capabilities reshape production organization. It also highlights digital embedding as an alternative pathway for firms to participate in global value creation.
Copyright (c) 2026 YiWen Gao https://creativecommons.org/licenses/by/4.0
BIG DATA IN INCLUSIVE FINANCE AND FINANCIAL ECOSYSTEMS CHALLENGES AND FUTURE DIRECTIONS
With the explosive growth of data volume in the financial sector, big data technologies are transforming the accessibility and inclusiveness of financial services, particularly for populations traditionally excluded from formal financial systems. This paper analyzes how big data facilitates financial inclusion through alternative credit assessment, identity verification innovation, and customized products, while exploring from a financial ecosystem perspective the challenges faced by multi-stakeholder collaboration (banks, fintech companies, regulatory authorities) in technical infrastructure, data governance, regulatory compliance, and ethics. Through systematic analysis of current research, this paper proposes future pathways including the integration of big data technologies with emerging technologies such as artificial intelligence and blockchain, expansion of real-time analytical capabilities, and evolution of platform-based business models, providing reference for researchers, policymakers, and financial practitioners.
Copyright (c) 2026 BiJie Li; ChangEr Liu https://creativecommons.org/licenses/by/4.0
FROM "BROWSING" TO "PURCHASING": BARRIERS AND ENHANCEMENT STRATEGIES FOR CONSUMERS' PURCHASE INTENTION IN INTANGIBLE CULTURAL HERITAGE E-COMMERCE
The deep integration of intangible cultural heritage (ICH) and e-commerce provides a new path for the transmission of traditional culture. However, this development process faces numerous challenges, and the formation mechanism of consumers' purchase intention in this context requires further in-depth investigation. Based on 358 consumer questionnaires, this study diagnoses issues in ICH e-commerce across five dimensions: Product Information and Presentation, Cultural Perception and Trust, Price and Value Perception, Logistics and After-Sales Service Experience, and Service and Interaction. It employs cluster analysis, multiple regression, and group heterogeneity analysis to reveal the obstacles and promotion paths for purchase intention. The study finds that logistics and after-sales service experience, along with product information and presentation, are the most significant positive factors influencing purchase intention, while price perception has no direct significant effect. Consumers can be segmented into four groups: Mature and Steady, Generation Z Novelty-Seeking, Potential Wait-and-See, and Sophisticated Quality-Conscious, each with significantly different pain points and drivers.
Copyright (c) 2026 XiYu Cai; Peng Liu; XuanJie Lu https://creativecommons.org/licenses/by/4.0
THE OPTIMISATION OF SYNERGISTIC MECHANISMS FOR THE LOW-ALTITUDE ECONOMY TO EMPOWER NEW-QUALITY PRODUCTIVE FORCES IN SHENZHEN
As a prime example and key vehicle of new-quality productive forces, the low-altitude economy is emerging as a new engine driving high-quality economic and social development. As a pioneering demonstration zone for the development of China’s low-altitude economy, Shenzhen saw the added value of its low-altitude economy and aerospace industry clusters exceed 35 billion yuan in 2025, representing a year-on-year increase of 31% and demonstrating robust growth momentum. This study examines how Shenzhen’s low-altitude economy empowers new-quality productive forces, systematically analysing its current development status, underlying logic and coordination mechanisms. The research finds that Shenzhen’s low-altitude economy empowers new-quality productive forces through multi-dimensional pathways, including technological cluster innovation, deep industrial integration, spatial resource development and green, low-carbon transformation; however, it still faces systemic challenges in areas such as airspace management, infrastructure, market cultivation and safety regulation. Based on this, the paper constructs a five-pronged collaborative mechanism optimisation framework comprising ‘policy, industry, technology, application scenarios and ecosystem’. It proposes collaborative optimisation pathways such as prioritising institutional innovation, upgrading industrial clusters, driving development through application scenarios, weaving a network of infrastructure, and fostering an innovation ecosystem. This provides theoretical support and practical guidance for Shenzhen’s ambition to become the world’s leading city in the low-altitude economy and to establish itself as a benchmark for high-quality development in this sector.
Copyright (c) 2026 Ji Li https://creativecommons.org/licenses/by/4.0
THE IMPACT OF ESG PERFORMANCE ON ENTERPRISE PERFORMANCE: BASED ON THE MEDIATING EFFECT OF GREEN INNOVATION
This paper conducts an empirical study on Chinese A-share listed companies from 2009 to 2024 using Huazheng ESG rating data, focusing on how ESG performance affects corporate performance and its underlying mechanism. The empirical results show that the improvement of ESG performance has a significant positive effect on corporate performance, and this impact has a three-period lag effect. In the relationship between ESG performance and corporate performance, green innovation shows a significant partial mediating effect, indicating that the optimization of ESG performance can be transformed into the growth of corporate operating performance through stimulating green innovation. Heterogeneity analysis indicates that the promoting effect of ESG performance on corporate performance is more significant in enterprises in the eastern region and in the manufacturing industry. The research conclusions provide empirical evidence for enterprises to optimize ESG practices and carry out green innovation, as well as for the government to improve ESG supervision and green finance policies.
Copyright (c) 2026 ManNi Zhuang; Pei Wan; YaXin Li https://creativecommons.org/licenses/by/4.0
YOUNG AND MIDDLE-AGED ADULTS' AWARENESS OF DOMESTIC BRANDS AND THEIR CONSUMPTION INTENTIONS
As cultural confidence and appeal within China's consumer market grow, the Z-generation consumer group has rapidly emerged. New consumption models centered on digital consumption and confidence-driven spending continue to expand, observing and attracting consumers to purchase domestic brands. Domestic brands are developing rapidly, and the consumer market is continuously expanding. This study aims to explore the understanding and consumption intentions of domestic brands among young and middle-aged adults in Shandong Province. Through a questionnaire survey targeting young and middle-aged individuals in Shandong Province across different age groups, genders, occupations, and income levels, data was collected regarding their awareness, usage patterns, and future outlook toward domestic brands. This information provides insights into the current domestic brand market. The study addresses six key research questions and offers recommendations for the future development of domestic brands. After validating the questionnaire's reliability and validity and completing both online and offline surveys, the collected data was analyzed using cross-tabulation, one-way ANOVA, clustering analysis, and linear regression models. The primary objectives are to assess the consumption willingness and satisfaction levels of Shandong's young and middle-aged population toward domestic brands, propose substantive recommendations for the future development of domestic brands, enhance consumer confidence in domestic brands, and contribute to the vigorous growth of the domestic market and industry, thereby sustaining the momentum of the domestic brand trend.
Copyright (c) 2026 XinRui Liu; YiXin Liang; WenXi Zhang; HuiZhong Geng https://creativecommons.org/licenses/by/4.0
THE BCPE FRAMEWORK AND THE CONSTRUCTION OF AN AUTONAMOUS KNOWLEDGE SYSTEM FOR CHINA’S ECONOMIC DEVELOPMENT
This article proposes a dynamic “Basic–Constraint–Purpose–Effect” (BCPE) framework to explain China’s paradox of “stability through transformation” over seven decades. Moving beyond theories that treat the state as a passive market corrector, BCPE operationalizes CCP’s leadership as institutionalized political integrative capacity—manifested in strategic planning, organizational penetration, nationwide coordination, and self-correction. This capacity sustains a dual-loop learning system: an experience-elevation loop that scales local innovations into national policy, and a risk-correction loop that recalibrates goals and institutions in response to systemic failures. Development purposes are not exogenously given but endogenously shaped through the CCP’s evolving diagnosis of the principal societal contradiction, blending normative values (e.g., equity, sustainability) with instrumental concerns. Four middle-range propositions follow: (1) political integrative capacity enhances collective action in large societies; (2) constraints, when cognitively reframed, drive innovation; (3) a strategic state dynamically optimizes multiple, often competing goals; and (4) effective markets and promising government co-evolve through complementary institution-building. Rooted in China’s governance practice yet articulated with generalizable mechanisms, BCPE draws on indigenous epistemic traditions—particularly practical rationality and holistic thinking—while offering testable, boundary-specified claims. It thus advances a path toward an autonomous, globally engaged political economy, providing analytically rigorous tools for understanding adaptive governance in complex developing contexts.
Copyright (c) 2026 Wei Xin https://creativecommons.org/licenses/by/4.0
EXECUTIVES’ ENVIRONMENTAL BACKGROUNDS AND GREEN INNOVATION BUBBLES: EVIDENCE FROM CHINESE LISTED FIRMS
The study examines the impact of executives’ environmental backgrounds on corporate green innovation bubbles, analyzing a sample of Chinese listed firms from 2010 to 2022. The findings indicate that appointing executives with environmental expertise significantly mitigates green innovation bubbles, a phenomenon characterized by the decoupling between the quantity and quality of green innovation. Mechanism analyses reveal that such executives operate through two key channels: by enhancing the green cognition of the management team and by improving government–enterprise communication. Furthermore, cross-sectional tests show that the restraining effect is more pronounced under specific conditions—particularly in firms facing higher performance pressure, those with higher resource allocation efficiency, or those receiving fewer government green R&D subsidies. Overall, the results suggest that executives with environmental backgrounds help firms shift their focus from short-term innovation metrics toward substantive green innovation. These insights offer meaningful implications for corporate governance and for policy design aimed at fostering high-quality green transitions.
Copyright (c) 2026 Nan Yang; WenXi Sun https://creativecommons.org/licenses/by/4.0
CONSTRUCTION OF JUNEAU’S TOURISM SOCIAL COST-ECONOMIC BENEFIT MODEL AND KEY FACTOR ANALYSIS BASED ON AHP AND MULTIVARIABLE ADJUSTMENT
In 2023, Juneau, Alaska, received a record 1.6 million cruise visitors, bringing significant revenue but severe overcrowding. To address this, this study develops a sustainable tourism model prioritizing economic benefit maximization. It uses linear fitting/trigonometric functions for visitor numbers, logarithmic/linear functions for tourism revenue, differential equations for environmental pressure, and the Analytic Hierarchy Process (AHP) for a constrained social cost model. Analysis shows Juneau’s total economic benefit peaks at ~1,026,453 visitors, with an income-expenditure plan and feedback mechanism proposed. A multivariable adjustment approach further quantifies impacts of variables (e.g., visitor spending, tax rates) and identifies key factors (e.g., visitor numbers, glacier melting rate) to support tourism decision-making.
Copyright (c) 2026 Min Zeng; LvJie Fan; XinYu Zheng https://creativecommons.org/licenses/by/4.0
NEW-QUALITY PRODUCTIVE FORCES AND AGRITOURISM INTEGRATION: INSIGHTS FROM GREENFOOD FARM
Taking Yantai Greenfood Farm as a case study, this research explores the integration mechanisms between new-quality productive forces and the agritourism industry in areas such as green and low-carbon development, digitalization, mechanization, and intelligentization. It focuses on analyzing practical applications of new-quality productive forces, including how intelligent breeding technologies enhance agricultural production efficiency, how ecological circulation models support low-carbon development, and the value creation pathways of integrated agritourism business formats. It identifies key challenges in industrial practice, such as ambiguous definitions of new-quality productivity technology applications and insufficient integration depth between agritourism formats and technologies, while proposing optimization directions and improvement suggestions. The technology application models and industrial integration pathways presented in this article can provide practical references for the high-quality development of the agritourism industry, thereby contributing to rural revitalization.
Copyright (c) 2026 YuQing Qiu https://creativecommons.org/licenses/by/4.0
DEVELOPMENT COUNTERMEASURES FOR THE CONSTRUCTION OF ZHENGZHOU NATIONAL LOGISTICS HUB
Under the new development paradigm, addressing the critical issue of the "Construction of Zhengzhou National Logistics Hub," this paper deeply analyzes the current status of logistics development in Zhengzhou, discusses the strategic significance of constructing the Zhengzhou National Logistics Hub, clarifies the strategic direction, and proposes implementation strategies for its construction.The construction of the Zhengzhou National Logistics Hub is an important part of the logistics network system construction. It is conducive to promoting logistics network construction, reducing total social logistics costs, improving logistics service levels and quality, optimizing the economic spatial layout and economic system construction of Zhengzhou and Henan Province, and promoting the rapid and healthy development of Zhengzhou's logistics industry and national economy.
Copyright (c) 2025 YuQing Fan; BoYe Zhang; YuXin Luo https://creativecommons.org/licenses/by/4.0
THE DETECTION OF HOUSEHOLD ECONOMIC ANOMALIES BASED ON THE CFPS2022 DATABASE: AN EXAMPLE OF INCOME-CONSUMPTION DEVIATION PATTERN ANALYSIS
In recent years, China's household debt has witnessed explosive growth, increasing financial vulnerability and posing a potential threat to economic stability. Based on the China Family Tracking Survey 2022 database, this study innovatively synthesizes three algorithms, namely the statistically based 3-criteria, Isolation Forest, and Local Outlier Factor (LOF), to detect anomalies with higher accuracy, and further applies a variety of data analysis techniques, such as cluster analysis, association rule mining, and Random Forest algorithm, to conduct a systematic and in-depth study of household economic anomalies. We also utilize various data analysis techniques such as cluster analysis, association rule mining, and random forest algorithm to conduct a systematic and in-depth study of household economic anomalies. Consequently, the study proposes policy recommendations such as strengthening financial education, providing precise support, and establishing a risk warning mechanism. These measures are expected to assist high-risk households, foster healthy economic development, and contribute to national economic stability.
Copyright (c) 2025 Jia Yu; JiaCong Jiang; BoRui Zhao https://creativecommons.org/licenses/by/4.0
A HOUSING PRICE PREDICTION MODEL BASED ON BACKPROPAGATION NEURAL NETWORK
The real estate industry serves as a crucial pillar of the national economy, playing an indispensable role in both national and local economic development. Analyzing and forecasting housing price trends can provide more reliable decision-making references for homebuyers, real estate agents, and market analysts. This study selects 150,000 data samples and addresses the complex non-linear characteristics of housing prices influenced by multiple factors by proposing a housing price prediction model based on a Backpropagation (BP) neural network. The model effectively simulates and predicts housing prices in the test set, achieving successful non-linear fitting,such as R is 0.8376, MAPE is 466873.78%%. This research not only offers a more reliable decision-making tool for homebuyers, real estate intermediaries, and market analysts but also provides a practical modeling approach for non-linear housing price prediction problems, thereby contributing positively to the rational development of the real estate market.
Copyright (c) 2025 ShiYu Jiao; Dong Wang https://creativecommons.org/licenses/by/4.0
AN EMPIRICAL INVESTIGATION INTO THE STRATEGIC IMPACT OF RECIPROCAL TRADE COUNTERMEASURES ON U.S. ECONOMIC RESILIENCE AND MANUFACTURING RE-INDUSTRIALIZATION
The 2025 U.S. “reciprocal tariff” policy has intensified global trade frictions, triggering retaliatory countermeasures that reshape supply chains and industrial dynamics. Whether such protectionist strategies can sustainably revive domestic manufacturing or instead undermine macroeconomic stability remains an open empirical question. This study investigates the nonlinear effects of reciprocal trade countermeasures on U.S. manufacturing performance and economic resilience using a 13-dimensional monthly panel dataset. We construct composite manufacturing and macroeconomic indices via the Entropy Weight Method (EWM), examine policy–economy linkages using Grey Relational Analysis (GRA) and Pearson correlations, and model dynamic impacts through a heterogeneous machine learning framework combining XGBoost and Support Vector Regression (SVR). Empirical results show that retaliatory trade measures significantly disrupt intermediate input supplies and raise domestic production costs, offsetting short-term gains from tariff protection. High-precision forecasts further indicate that international retaliation largely neutralizes the intended reindustrialization effects. The findings suggest that sustainable manufacturing revitalization requires structural investment and innovation-driven policies rather than reliance on tariff barriers alone.
Copyright (c) 2026 XinYi Chen; TianTian Liu https://creativecommons.org/licenses/by/4.0
THE IMPACT MECHANISM OF SMES’ PERSONALIZED TAX SERVICE DEMAND UNDER THE BACKGROUND OF DIGITAL ECONOMY
In the context of the digital economy, tax services are shifting from a management-oriented approach to a service-oriented one, and the demand for personalized tax services from small and medium-sized enterprises (SMEs) is increasingly prominent. This paper takes SMEs in City A as the research object, constructs a structural equation model based on questionnaire survey data, and empirically analyzes the influence mechanisms of tax-handling channel preference, tax policy awareness and information acquisition, and tax service satisfaction on the demand for personalized tax services. The results show that tax-handling channel preference, tax service satisfaction, and tax policy awareness all have significant positive effects on the demand for personalized tax services among SMEs, with the effect of tax-handling channel preference being the most prominent. The research conclusions provide empirical evidence for optimizing the supply of tax services to SMEs and improving tax administration efficiency in the context of the digital economy.
Copyright (c) 2026 Qian Zhang https://creativecommons.org/licenses/by/4.0
DYNAMIC DEPLOYMENT OF FINANCIAL PERSONNEL BASED ON THE HOLT-WINTERS ALGORITHM-PROPHET-LSTM PREDICTIVE MODEL
In the context of refined enterprise management, the dynamic optimal allocation of human resources has become the key to improving operational efficiency and reducing labor costs. Financial reimbursement, as a high-frequency and important business process, exhibits significant fluctuation in its workload due to influences from business cycles, project milestones, and other factors. A fixed number of finance personnel can easily lead to backlogs in expense review during peak periods, resulting in employee dissatisfaction, while creating idle human resources during off-peak periods. To resolve this contradiction, this paper aims to establish a dynamic adjustment mechanism for finance personnel based on predictive modeling. This study utilizes historical reimbursement claim volume time series data from enterprises, integrating the Prophet-LSTM predictive model based on the Holt-Winters algorithm to accurately predict future claim volumes for specific cycles (e.g., monthly, quarterly). Through this model, enterprise managers can proactively anticipate future workloads and dynamically adjust staffing levels for financial reimbursement positions accordingly, enabling flexible allocation of financial personnel. Empirical research demonstrates that this predictive model exhibits high accuracy, with an MSE of only 152.47, an RMSE as low as 12.35, an MAE of 7.89, a MAPE of just 6.58%, and an R2 as high as 0.948. The dynamic adjustment strategy based on this model effectively smooths workloads, significantly shortens reimbursement processing cycles, and enhances the overall utilization efficiency of corporate human resources. This study provides a feasible theoretical framework and practical pathway for enterprises to achieve data-driven human resource management in finance and other volatile business domains.
Copyright (c) 2026 HuiJun Liang; ZiTian Sheng; ZhiJie Luo https://creativecommons.org/licenses/by/4.0
GREEN FINANCE POLICY AND TECHNOLOGICAL INNOVATION: EVIDENCE FROM 35 CHINESE AUTOMOTIVE FIRMS (2013–2023)
This study examines how China’s green finance development relates to corporate technological innovation in the automotive industry. Using firm–year observations from 2013–2023 for leading Chinese automotive firms, technological innovation is measured through patent applications and patent grants, expressed as logarithmic outcomes. Green finance is proxied by a national annual index, reflecting the macro policy-finance environment faced by firms each year. To address missing values in firm-level covariates, the analysis employs multiple imputation (m = 5) and reports pooled estimates. Across baseline models with standard controls, green finance is associated with lower patent applications, while the relationship with patent grants is weaker and generally statistically insignificant. Policy-timing analysis around the 2016 green finance policy shift provides limited evidence of differential effects, and additional robustness checks including alternative cutoffs (lead/placebo timing) and pre/post subsample regressions support the overall pattern. Lag models indicate that the negative association is more pronounced for patent applications with one- to two-year delays, whereas patent grants remain comparatively insensitive. Collectively, the findings suggest that macro green finance expansion does not translate mechanically into short-run increases in firm innovation outputs, and that firm fundamentals such as R&D, subsidies, and profitability remain central correlates of innovation performance. The results provide practical implications for policy design and corporate strategy in green transition contexts.
Copyright (c) 2026 Jean Jacques Yves Leslie Bottine Junior https://creativecommons.org/licenses/by/4.0
THE IMPACT OF TWO-WAY FDI INTERACTIVE DEVELOPMENT ON CHINA’S DIGITAL ECONOMY
Distinct from the existing literature that predominantly focuses on the economic impact of either FDI or OFDI in isolation, this study examines the synergistic effects and coordinated development of two-way FDI on the digital economy across Chinese provincial regions. The findings reveal that the coordination of two-way FDI exerts a positive influence on the digital economy. This impact mechanism exhibits a distinct threshold effect, moderated by two key threshold variables: the level of local trade openness and the characteristics of the industrial structure. Notably, the facilitative effect of two-way FDI coordination is more pronounced within the Yangtze River Economic Belt, whereas in regions outside the Belt, it still contributes to the growth of the digital economy but with statistically weaker significance. This research not only offers policy implications for China's foreign trade and digital economic development but also elucidates the underlying mechanisms and threshold conditions involved. It provides valuable insights for regional economic and digital advancement in China, while also serving as an important supplement to the literature on two-way FDI.
Outward Foreign Direct Investment (OFDI)
Copyright (c) 2025 JingYi Zhao https://creativecommons.org/licenses/by/4.0
NEW PRODUCTIVITY ENABLES HIGH QUALITY DIGITAL AGRICULTURE IN JILIN PROVINCE DEVELOPMENT LOGIC AND IMPLEMENTATION COUNTERMEASURES
As a pioneering model driving the transformation and upgrading of traditional agriculture, digital agriculture has long been prioritized by government authorities. The new quality productive forces, characterized by technological innovation, high efficiency, and superior quality, provide robust support for the high-quality development of digital agriculture. Under the impetus of these advanced productive forces, digital agriculture will fully embrace the development concepts of innovation, openness, coordination, green practices, and sharing, thereby comprehensively empowering the high-quality development of digital agriculture in Jilin Province. However, various challenges remain in the province that urgently require resolution. To achieve sustainable development in the new era, Jilin must focus on cultivating and advancing high-quality digital agriculture as its core objective, establishing distinctive local strategies for digital agricultural advancement.
Copyright (c) 2025 AiLing Zhu; Tao Ding; XinXin Liu https://creativecommons.org/licenses/by/4.0
TECHNOLOGY SELECTION OF ENTERPRISE JAVA WEB FRAMEWORKS BASED ON EVOLUTIONARY PATH ANALYSIS
In response to the rapid iteration of enterprise-level Java Web frameworks and the lack of systematic theoretical guidance for selection decisions, this study proposes an innovative selection methodology based on the analysis of technical evolution paths. The main innovations are as follows: First, it reconstructs the three-dimensional "scenario-driver-paradigm" analysis model for framework evolution, systematically revealing the internal logic and technological inflection points in the transition from monolithic to cloud-native architectures, going beyond traditional version-based reviews. Second, it proposes a quantitative selection framework based on the dual-track "steady-state-agile-state" adaptation, which for the first time comprehensively models core dimensions such as development efficiency, runtime performance (startup time, memory usage), and cloud-native compatibility, clarifying the Pareto boundaries of mainstream frameworks such as Spring Boot and Quarkus under different constraints. Third, it constructs a hybrid architecture decision-making model based on technical debt and transformation cost assessment, providing enterprises with path planning and risk assessment tools for the smooth evolution from legacy systems to cloud-native architectures. This study validates the effectiveness of the method through empirical case comparisons, offering systematic theoretical foundations and practical guidance for enterprises to make forward-looking, low-risk architectural decisions in complex technological ecosystems.
Copyright (c) 2026 ZhengLin Wang https://creativecommons.org/licenses/by/4.0
IMPACT OF DIGITAL ECONOMY DEVELOPMENT ON POLLUTION REDUCTION AND CARBON REDUCTION
Exploring the impact and spatiotemporal characteristics of the digital economy on pollution and carbon reduction is of great significance in the context of the "dual carbon" goal and The digital economy is advancing at a fast pace. Currently, China is facing the dual task of reducing pollution and carbon emissions, and the "technological dividend" of the digital economy provides a new path for achieving environmental governance goals. However, there are still shortcomings in the systematic analysis of the spatial spillover effects, regional adaptation differences, and dynamic mechanisms of pollution and carbon reduction in the digital economy, which urgently require in-depth research from a multidimensional perspective. This study comprehensively utilized entropy weight method, benchmark regression model, mediation effect model, spatial-Durbin-model (SDM), spatiotemporal-geographically-weighted-regression (GTWR), and graph attention network (GAT) to construct a research framework covering impact effect assessment, mechanism identification, and spatiotemporal dynamic analysis. Firstly, This study utilized the entropy weight method for quantifying the development degree of the digital economy, and conducted an analysis on the spatiotemporal features of both pollutant emission intensity and carbon intensity of emissions, the fundamental correlation between the digital economy and environmental performance is revealed; Secondly, through the application of a fixed effects model, the digital economy exerts a direct influence on achieving the twin goals of reducing pollution and carbon emissions, and identifying indirect paths such as industrial structure upgrading, technological progress, and green finance through a mediation effect model; Finally, using spatial econometric models and GAT models, analyze the spatial dependence, regional heterogeneity, and the digital economy’s emission reduction effects: Spatiotemporal dynamic evolution characteristics.
Pollution reduction and carbon reduction
Copyright (c) 2025 WeiJie Lin https://creativecommons.org/licenses/by/4.0
THE IMPACT OF DIGITAL INCLUSIVE FINANCE ON URBAN INNOVATION AND ENTREPRENEURSHIP
Innovation and entrepreneurship are of great significance to enhance the overall national strength and promoting regional development. Promoting innovation and entrepreneurship is an inevitable requirement for China to enhance the internal driving force and high-quality economic development. Based on the panel data of 279 prefecture-level cities in China from 2011 to 2019, this paper constructs a fixed-effect model to verify the relationship between digital inclusive finance and urban innovation and entrepreneurship and its influence mechanism. The study found that digital inclusive finance can significantly affect the improvement of the level of urban innovation and entrepreneurship, and the conclusion is still valid after changing the measure of urban innovation and entrepreneurship and deleting the robustness test of the provincial capital cities. Secondly, through the construction of the intermediary effect model, it is found that digital inclusive finance promotes the level of urban innovation and entrepreneurship by improving the development level and marketization degree of the Internet.
Copyright (c) 2025 KaiWen Li; YanLin Ji; Min Liu; SuiYi Liao https://creativecommons.org/licenses/by/4.0
A HYBRID GA-PSO AND COUPLING COORDINATION FRAMEWORK FOR MULTI-OBJECTIVE OPTIMIZATION IN SUSTAINABLE TOURISM SYSTEMS
Rapid tourism growth has boosted local economies but also posed environmental and social challenges, highlighting the need for sustainable management. This study presents a hybrid optimization framework that integrates Genetic Algorithm with Particle Swarm Optimization (GA-PSO) with a Coupling Coordination Degree (CCD) mechanism to balance social, economic, and environmental subsystems. The model targets maximization of employment, tourism revenue, and glacier stability under statistical and coordination constraints. Regression analysis and the entropy weight–TOPSIS method were applied to quantify subsystem interactions. Results show that GA-PSO outperforms single GA and PSO, achieving an optimal coordination degree of 0.6254. Employment, tourism revenue (USD 147 million), and environmental sustainability all showed notable improvements. This research extends the use of hybrid evolutionary algorithms in sustainable tourism and provides quantitative support for policymakers seeking to balance economic growth, social well-being, and ecological resilience.
Copyright (c) 2025 DingYi Ma; KeYin Zhu; Lei Zang https://creativecommons.org/licenses/by/4.0
EMPIRICAL ANALYSIS ON THE EFFECT AND MECHANISM OF GREEN FINANCE RELATING TO REDUCTION AND CARBON EMISSION REDUCTION RELYING ON THE EMPIRICAL EVIDENCE FROM CHINESE LISTED COMPANIES
In the process of implementing the "dual-carbon" strategy, research on whether green finance can truly translate into emission reduction effects and its conversion mechanism is crucial for testing green finance policies. The present study takes A-share listed non-financial enterprises in China from 2011 to 2022 as samples, matches enterprise emission data of sulfur dioxide (SO 2 ), nitrogen oxides (NO x ), and soot, and constructs a "firm-year" green finance index built on seven types of tools including green credit and green bonds to systematically examine the impact of green finance on corporate pollution reduction and carbon emission reduction. Baseline regression results show that for each 1-unit rise in the green finance index, the logarithm of total corporate pollutant emissions decreases by an average of 0.366, and this conclusion stays robust after instrumental variable and robustness examinations. Mechanism analysis reveals that green finance exerts its effects through a dual-pathway of alleviating financing constraints and promoting green technological innovation: on one hand, it significantly reduces the SA index, providing low-cost funds for corporate green investments; on the other hand, it significantly increases the quantity of applications submitted for green utility model patents, facilitating process upgrading and end-of-pipe treatment. Heterogeneity tests reveal that the emission reduction effect of green finance stands out more in non-state-owned enterprises (non-SOEs), eastern regions, and the manufacturing industry, presenting a pattern of "non-SOEs outperforming SOEs, eastern regions outperforming central and western regions, and manufacturing outperforming non-manufacturing". This study provides micro-level evidence for constructing a precise and efficient green finance support system, and also offers actionable policy references for accomplishing the "dual-carbon" goals.
Pollution control and carbon emission reduction
Copyright (c) 2025 ZiMo Chen https://creativecommons.org/licenses/by/4.0
FROM DUAL-CARBON MANAGEMENT TO GREEN INNOVATION: THE SYNERGISTIC PATHWAYS OF CARBON ACCOUNTING AND CARBON FOOTPRINT IN TECHNOLOGY ENTERPRISES
Under the national dual-carbon strategy, technology enterprises face increasing pressure to reduce carbon emissions resulting from intensive energy use, complex supply chains, and long product life cycles. Identifying effective pathways for achieving green innovation under carbon constraints has become an essential issue for sustainable corporate development. This study establishes a “dual-carbon management” theoretical framework that integrates organizational-level carbon accounting with product-level carbon footprint assessment. Drawing on existing literature, the study examines the roles of carbon accounting in carbon governance, strategic planning, and internal incentive mechanisms, as well as the contributions of carbon footprint analysis to life-cycle assessment, material optimization, and product Eco-design. It further explores the synergistic mechanisms between the two, including data complementary, governance alignment, strategic coordination, and value-chain integration. Based on these insights, the study proposes key principles for constructing green innovation paths, emphasizing data integrity, systemic thinking, innovation-oriented governance, life-cycle perspective, value-chain collaboration, and dynamic adjustment. A representative case of a technology enterprise is analyzed to illustrate how dual-carbon management supports the development of low-carbon technologies, process improvements, and green product innovation. The results show that carbon accounting provides a foundation for organizational carbon governance, while carbon footprint offers detailed life-cycle insights. The integration of these two mechanisms forms a multi-level system that enhances strategic decision-making, operational transformation, and supply-chain-wide collaboration. This study contributes theoretical insights and practical guidance for technology enterprises seeking green innovation pathways under carbon constraints.
Copyright (c) 2025 Na Lei; XinZhi Wang https://creativecommons.org/licenses/by/4.0
BILATERAL DIPLOMATIC RELATIONS AND CROSS-BORDER M&AS: EVIDENCE FROM CHINA
Cross-border mergers and acquisitions (M&A) are one of the most important ways for countries to participate in the global economy. China's bilateral diplomatic relations with other countries are flawed and the data are mainly from the Chinese media, which may lead to omissions in diplomatic events, lack of objectivity and insufficient information, which may lead to miscalculations. Therefore, it is necessary to select a measure that reflects the high level of recognition between the two countries in international affairs or bilateral affairs. Using unbalanced panel data (including cross-border M&A data and United Nations General Assembly (UNGA) voting data) for 181 countries (or regions) from 1992-2017, the paper empirically examines the impact of bilateral diplomatic relations on China's cross-border M&A completion rate and its mechanism of action, by building an estimation model, mediation effect models, and conducting a robustness test. The mediating effect in the mechanism test finds that bilateral diplomatic relations affect the completion rate of cross-border M&As between Chinese and foreign firms through both formal (i.e., the signing of BITs and the establishment of bilateral partnerships) and informal mechanisms (i.e., exchanges among senior bilateral leaders and the establishment of Confucius Institutes). For formal institutions, bilateral diplomatic relations can increase the completion rate of cross-border M&As from and to China by facilitating the signing of BITs and the establishment of bilateral partnerships. For informal institutions, bilateral diplomatic relations increase the completion rate of cross-border M&As from and to China by facilitating exchanges between high-level leaders of the two countries and the establishment of Confucius Institutes. The results of the study show that bilateral diplomatic relations can help improve formal and informal systems to facilitate successful cross-border M&As, and the Chinese Government can draw on the successful experience of political diplomacy to create more opportunities for bilateral political, economic and cultural exchanges. In addition, both China and other countries can actively explore bilateral and multilateral cooperation mechanisms and promote the establishment or formulation of new cooperation rules and agreements.
Copyright (c) 2025 YueChun Xu; ChenXi Liu; YuYing Wei; Min Liu https://creativecommons.org/licenses/by/4.0