Exploring Science Academic Conference Series
The Conference Proceedings Series publishes peer-reviewed papers presented at the Exploring Science conferences. These proceedings are a valuable resource for the scientific community, providing access to the latest research findings, innovative methodologies, and interdisciplinary studies. Key Features of the Proceedings: Peer-Reviewed Content – All submitted papers undergo a rigorous peer-review process to ensure academic quality and validity. Multidisciplinary Scope – Covers a wide range of fields, including but not limited to: Physical Sciences (Physics, Chemistry, Materials Science) Life Sciences (Biology, Biochemistry, Medicine) Engineering & Technology (AI, Robotics, Renewable Energy) Environmental Sciences (Climate Change, Sustainability) Social Sciences & Humanities (Psychology, Economics, Education) Open Access & Indexing – Many proceedings are published open access, ensuring wide visibility. Some are indexed in major databases like Scopus, Web of Science, Google Scholar, and others. Digital & Print Formats – Available in both digital (PDF/eBook) and print versions for accessibility. Benefits for Authors & Participants: Publication Opportunity – Presenters can publish their work in a recognized proceedings series. Networking – Connect with global experts and potential collaborators. Career Advancement – Enhances academic profiles for researchers and students. Impactful Research Dissemination – Contributes to the global scientific discourse. Submission Guidelines: Abstracts and full papers must follow the conference’s template. Submissions should present original, unpublished research. Deadlines and review timelines are announced on the official conference website. For more information, visit the official Exploring Science Conference website or contact the organizing committee.
Research on the Impact of Digital-Real Industrial Technology Integration on the Development of New Quality Productive Forces in Enterprises
This study, based on data from 2015-2024 regarding digital-real industrial technology integration and samples of new quality productive forces in Shanghai and Shenzhen A-share listed enterprises, systematically examines the impact effects, influencing mechanisms, and heterogeneity characteristics of digital-real industrial technology integration on the development of new quality productive forces in enterprises. The research finds that digital-real industrial technology integration can significantly promote the development of new quality productive forces in enterprises; this impact is primarily achieved through three mechanism pathways: alleviating corporate financing constraints, enhancing innovation efficiency, and improving operational efficiency. Heterogeneity tests further reveal that the influence of digital-real industrial technology integration on the development of new quality productive forces in enterprises exhibits distinct differences at the enterprise, regional, and industry levels. At the enterprise level, technology-intensive, labor-intensive, and high-profit enterprises are more likely to foster the development of new quality productive forces through digital-real industrial technology integration. At the regional level, enterprises in the southern region and economically underdeveloped areas derive greater benefits from digital-real industrial technology integration. At the industry level, enterprises in high-tech sectors and those with high degrees of monopoly are better positioned to achieve the development of new quality productive forces through digital-real industrial technology integration. The study demonstrates that digital-real integration can promote the development of new quality productive forces in enterprises by alleviating financing constraints and elevating innovation and operational efficiency, while exhibiting heterogeneity effects at the enterprise, regional, and industry levels. These findings expand the theoretical connotations of the digital economy and high-quality development, providing empirical evidence and decision-making references for enterprises’ differentiated transformations, governments’ targeted policies, and optimized resource allocation.
digital-real industrial technology integration, new quality productive forces in enterprises, financing constraints, innovation efficiency, operational efficiency
Copyright (c) 2026 Lu Xie (Author) https://creativecommons.org/licenses/by/4.0
Causes and Regulation Strategies of English Listening Anxiety Among Non-English Major College Students: An Analysis Based on Literature Review
English listening anxiety is one of the core affective barriers that constrain the effectiveness of second language acquisition among non-English major college students. Based on relevant studies published in domestic and international core journals and dissertations from 2011 to 2025, this paper systematically reviews the current status, causes, and regulation strategies of English listening anxiety in this population. The findings indicate that listening anxiety levels in this group are generally moderate or higher, with significant differences across dimensions such as grade level and place of origin. The causes can be attributed to the interaction between subjective factors related to individual learners and objective factors such as teaching and materials. Existing regulation strategies encompass two main dimensions: learner autonomous regulation and teacher instructional intervention. However, limitations persist, including restricted research samples and insufficient practicality of strategies. Future research should broaden perspectives, strengthen analyses of multi-factor interactions, and enhance empirical validation of strategies, thereby providing theoretical and practical references for alleviating listening anxiety among non-English major college students and improving the quality of listening instruction.
non-English major college students, English listening anxiety, causes of anxiety, regulation strategies, second language acquisition
Copyright (c) 2026 Yuhan Tang (Author) https://creativecommons.org/licenses/by/4.0
Design of a Multimodal Virtualization PTSD Therapy Interactive System Based on AIGC
Currently, VR exposure therapy for Post-Traumatic Stress Disorder (PTSD) remains primarily based on single modalities, which struggles to deliver sufficient immersive experiences and emotional responses, leading to certain limitations in treatment efficacy. To simulate multi-sensory channels in human natural interactions and overcome the single-sensory constraints of traditional exposure therapy, this paper explores the application of AIGC technology in the personalized generation of virtual scenes to enhance immersion and engagement in treatment. By systematically dissecting the intrinsic mechanisms of VR exposure therapy, this study proposes a personalized content adaptation method driven by patients’ real-time states and integrates thermal control arrays, muscle electrical stimulation, and user visual behavior analysis technologies to construct a multimodal interaction framework, encompassing coordinated multi-channel synergies such as haptic feedback, auditory resonance, and visual immersion. Building on this foundation, a multimodal virtualized PTSD therapy interactive system based on AIGC is designed and implemented. This research offers new perspectives for PTSD treatment, advancing exposure therapy toward multimodality, intelligence, and universality, while holding significant engineering application value in fields such as neurorehabilitation and psychological therapy.
AIGC, multimodal, virtual reality, PTSD, interaction design, digital therapeutics
Copyright (c) 2026 Yinan Shang (Author) https://creativecommons.org/licenses/by/4.0
A Study of the “Two-Way Interaction” Governance Model in Ethnic Region
Grassroots governance in ethnic regions is a crucial part of the national governance system, facing the core challenge of reconciling the structural tension between the standardized logic of bureaucracy and local knowledge systems. Existing research, often trapped in the dichotomy of “state-centrism” and “society-centrism,” fails to adequately explain the cultural adaptation dilemmas in policy implementation. Drawing on Giddens’ “Structuration Theory,” this paper constructs an analytical framework of “Symbiotic Interactive Governance” to elucidate the complex mechanism of “bidirectional interaction” between the state and society at the grassroots level. The study argues that effective governance in ethnic regions is not a process of one-way embedding or passive adaptation, but rather an active process of institutional innovation and strategic evolution. Through the synergistic advancement of three pathways, “institutional integration,” “strategic innovation,” and “elite consolidation,” grassroots actors can transform external tensions into endogenous drivers, ultimately achieving a “symbiotic” order that moves from tension balance to value co-creation. This research offers a new theoretical perspective for understanding the mutually constitutive evolution of state-society relations in contemporary China and provides a reference for advancing the modernization of governance in ethnic regions.
ethnic regions, grassroots governance, bidirectional interaction, symbiotic governance, structuration theory
Copyright (c) 2026 Boxi Wang (Author) https://creativecommons.org/licenses/by/4.0
A Review of Real-Time Risk Detection for Adolescent Cybersecurity: Technological Advances, Challenges, and Prospects
Amid the wave of digitization, the internet has become a core context for adolescents’ lives and learning. The scale of underage netizens in China has reached 193 million, with an internet penetration rate of 97.2%, essentially achieving saturated coverage. The prevalence of short-form video platforms and smart devices has rendered online risks more concealed, prevalent among younger children, and cross-contextual. Reports indicate that 34.7% of adolescents have encountered cyberbullying, and 28.3% have been exposed to harmful information, urgently necessitating the construction of precise and efficient real-time risk detection systems. This study aims to systematically review the research, core technologies, and existing bottlenecks in the field of real-time risk detection for adolescent cybersecurity, providing references for theoretical deepening and practical implementation. The research method adopts a literature review, conducting in-depth analysis around the sample characteristics, technical methods, and governance mechanisms in domestic and international research. The findings indicate that the field has formed a “technology development-governance coordination-literacy cultivation” framework. Traditional technologies suffer from imbalances between timeliness and accuracy. Dual frameworks combining “reinforcement learning + deep learning” and multimodal fusion technologies offer effective paths to resolve core contradictions, yet research gaps remain in areas such as adaptation for younger age groups, cross-context migration, and human-computer collaboration. The conclusion points out that future efforts need to focus on technological innovation, scenario expansion, and governance coordination to build a refined and intelligent protection system.
adolescent cybersecurity, real-time risk detection, reinforcement learning, deep learning, collaborative governance, multimodal fusion, digital literacy
Copyright (c) 2026 Wanrou Guo (Author) https://creativecommons.org/licenses/by/4.0
Decoding Youth Buzzwords: “Transmutation” in Contemporary Ideologies and Marxist Perspective
With the advent of the new era, numerous social ideologies have surged, exerting significant influence on the value systems of the youth demographic. The phenomenon of “transmutation,” exemplified by popular youth slang such as “lying flat” and “involution,” is widely disseminated, reflecting underlying shifts in ideological values and raising concerns over the security of mainstream ideological consensus. The Party and the state prioritize guiding youth values, with General Secretary Xi Jinping emphasizing the importance of fostering correct ideological development during adolescence. It is urgent to critically analyze the genesis of these ideological trends from a theoretical standpoint. This paper adopts a Marxist perspective to critically examine the “transmutation” phenomenon, dissecting the mechanisms of semantic substitution, value preconditioning, and propagative fracturing, ultimately revealing the intrinsic nature of capitalist ideology. It proposes a holistic approach comprising de-commodification of concepts, discourse power contention, and innovative communication strategies. Through theoretical critique, this study aims to fill gaps in analyzing the material base of social relations, thereby clarifying ideological safeguards within pedagogical practice and youth ideological dissemination endeavors.
transmutation, youth, internet buzzwords, ideology
Copyright (c) 2026 Ningxin Ji (Author) https://creativecommons.org/licenses/by/4.0
Investigation and Analysis about Multimodal Fatigue Detection
Fatigue driving accounts for a significant proportion of traffic accidents. Multimodal fatigue detection offers a new effective way to detect fatigue. This article selected six articles by some criteria and reviewed them carefully. The improvements of the method include using lightweight YOLOv8 networks to process complex images; others process multimodal EEG signals via non-smooth non-negative matrix factorization (nsNMF) and Gramian angular field imaging. Attention-based networks like MMA-Net and TMU-Net are designed to fuse EEG, EDA, PPG, and EOG signals. Additionally, LSTM-based models analyze PPG and facial features, while enhanced MTCNN and PFLD algorithms improve detection accuracy and reduce individual variability. Based on the methods, the article summarizes some challenges in the multimodal fatigue detection and proposes the future of the multimodal fatigue detection. In general, the article provides a comprehensive review to guide further research about multimodal fatigue detection.
multimodal, fatigue driving, fatigue detection, EEG multimodal, multimodal improvement
Copyright (c) 2026 Keran Huang (Author) https://creativecommons.org/licenses/by/4.0
The Impact of Overseas Backgrounds of Directors, Supervisors, and Senior Executives on the Green Innovation Ability of Enterprises: Based on Empirical Analysis of Listed Company Data from 2014 to 2023
In the face of the dual background of the national green development strategy and the difficulty of implementing enterprise green innovation, whether and how the overseas background of directors, supervisors, and senior executives, as the core decision-makers of corporate governance, can and how their overseas background can affect enterprise green innovation has become an important issue. The purpose of this study is to empirically test the impact of the overseas background of the directors, supervisors and senior management teams on the green innovation ability of enterprises, and to explore the moderating role of whether the enterprise is a key pollution monitoring unit in the external policy situation. The research method of this study is to select the data of China’s A-share listed companies from 2014 to 2023 and construct a two-way fixed effect model for empirical analysis. Based on the company’s green innovation ability, whether directors, supervisors and senior executives have overseas backgrounds are the core variables, and a series of corporate financial and governance variables are controlled. The research hypothesis was verified by benchmark regression, moderating effect test, heterogeneity analysis and robustness test. The study found that the overseas background of directors, supervisors and senior executives has a positive but not significant impact on enterprise green innovation. Key pollution monitoring policies have a significant positive moderating effect and can strengthen the promotion of green innovation from overseas backgrounds.
overseas background, corporate green innovation, key pollution monitoring, corporate governance
Copyright (c) 2026 Yufan Wang (Author) https://creativecommons.org/licenses/by/4.0
SMIC’s Dual Listing in A-Shares and Hong Kong Shares: Differences and Valuation Drivers from Institutional, Financial, and Market Performance Perspectives
Against the backdrop of global semiconductor supply chain restructuring and intensifying China-US tech competition, Semiconductor Manufacturing International Corporation (SMIC), a flagship of China’s semiconductor industry, implemented a dual-listing strategy with listings in Hong Kong in 2004 and on the STAR Market in 2020. This study explores differences in listing mechanisms, financial signal interpretation, and valuation logic between the two markets using a mixed-methods approach that integrates case analysis, comparative study, and empirical testing with data from 2020 to 2025. Key findings include three core aspects. First, institutional divergence is evident as the STAR Market’s registration-based system prioritizes policy support for R&D-intensive firms, while Hong Kong’s Chapter 18C emphasizes disclosure and global capital access, leading to differences in listing efficiency and financing flexibility. Second, financial interpretation bias exists where A-share investors focus on "growth scale" while Hong Kong investors prioritize "profit quality". Third, valuation drivers such as investor structure-with retail-dominated A-shares versus institutional-dominated Hong Kong shares-and policy sensitivity explain the long-term A/H premium, while technological gaps and global cycles suppress Hong Kong valuations. This study enriches the literature on dual listing for strategic tech firms and provides insights for cross-border financing, regulatory coordination, and global asset allocation.
SMIC, dual listing, institutional difference, valuation premium, financial signal, international finance
Copyright (c) 2026 Jun Ge (Author) https://creativecommons.org/licenses/by/4.0
The Impact of Strengthening Legal Liability on the Effectiveness of Internal Control in Listed Companies
This paper utilizes the implementation of the new Securities Law in 2020 as a quasi-natural experiment, drawing on data from Chinese A-share listed companies spanning 2018-2022. It employs a multi-period difference-in-differences approach to investigate the impact of strengthening legal liability on the effectiveness of internal control in listed companies, along with the underlying mechanisms. The findings reveal that, in the full sample, the enhancing effect of the new Securities Law is not significant. However, it exhibits a significant positive impact on super-large enterprises in the top 75th percentile of asset size. Mechanism tests indicate that financial risk constraints serve as the core channel: the policy significantly reduces the leverage ratios of small and medium-sized enterprises, while in super-large enterprises, financial risks exert a significant negative influence on internal control. This study provides crucial evidence for understanding the conditional effectiveness of “harsh laws and stern punishments” style regulation, offering important theoretical and practical implications for advancing differentiated regulation and optimizing capital market governance.
internal control, legal liability, difference-in-differences
Copyright (c) 2026 Jiayi Shi (Author) https://creativecommons.org/licenses/by/4.0
ARIMA-GARCH and ARIMA-EGARCH-t Models in Fitting and Forecasting Volatility of the Shanghai Composite Index
Stock market volatility lies at the heart of risk management. Existing research indicates that A-share returns exhibit fat-tail characteristics, yet further refinement is required in balancing the model’s depiction of fat tails and asymmetry with predictive robustness. This paper utilises daily data from the Shanghai Composite Index spanning January 2010 to June 2025 as its sample. It compares the Autoregressive Integrated Moving Average-Generalised Autoregressive Conditional Heteroskedasticity (1,1)-Normal (ARIMA-GARCH (1,1)-Normal) and Autoregressive Integrated Moving Average-Exponential Generalised Autoregressive Conditional Heteroskedasticity (1,1)-t (ARIMA-EGARCH (1,1)-t) models in terms of volatility fitting and forecasting performance. Methodologically, the mean correlation was first filtered using ARIMA (2,0,2). Maximum likelihood estimation was employed for modelling, with performance evaluated through rolling forecasts. The research encompasses sequence stationarity testing and model construction, evaluating in-sample fit through metrics such as the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and log-likelihood values. Out-of-sample forecasting performance is measured using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Quantile Likelihood (QLIKE) values. The results indicate that the EGARCH-t model exhibits superior in-sample fit with a higher log-likelihood value (10,606.9), successfully capturing fat tails (ν=4.7236) and the leverage effect (γ=-0.0216). However, the GARCH model demonstrated greater robustness in out-of-sample forecasting, with lower error metrics such as MSE (0.000000) and RMSE (0.000523). Research indicates that model selection requires balancing goodness-of-fit with generalizability, while EGARCH-t is well-suited for capturing historical volatility mechanisms, GARCH holds greater predictive utility.
Shanghai composite index, GARCH model, EGARCH model, fitting, forecasting
Copyright (c) 2026 Qinming Yao (Author) https://creativecommons.org/licenses/by/4.0
Fintech Empowering the Real Economy: The Key Pathway to Driving High-Quality Development of China’s Economy
In the context of the transformation toward high-quality development of China’s economy in the new era, fintech, leveraging core technologies such as artificial intelligence and blockchain, reconstructs the financial ecosystem and serves as a key engine in addressing the dilemmas of “difficult financing, high costs, and narrow coverage” faced by small and medium-sized enterprises in the real economy. This article systematically delineates the internal mechanisms through which fintech empowers the real economy. By constructing a fintech index via integrated text mining methods and drawing on multi-dimensional empirical evidence, it reveals three core empowerment pathways-corporate financing, consumption investment, and resource allocation-while analyzing the specific roles of fintech in promoting economic development. It provides theoretical references for establishing a virtuous cycle of “technology-finance-industry” and holds strategic significance for cultivating new quality productive forces.
fintech, real economy, high-quality development
Copyright (c) 2026 Xinze He (Author) https://creativecommons.org/licenses/by/4.0
Consumption Behavior of the Silver-Haired Population and Market Demand Prediction
With the acceleration of global population aging, the silver economy has emerged as a crucial engine driving social and economic development. This study, based on market data for China’s silver economy from 2016 to 2024, constructs a multifaceted statistical modeling system. From dual perspectives of society and individuals, it uncovers the developmental patterns and market characteristics of the silver economy. Multiple linear regression, K-Means clustering, and random forest methods are employed to form a multidimensional analytical framework, overcoming the limitations of traditional studies that rely on single methodologies. The findings reveal that the scale of the silver economy market is positively correlated with the digital economy market size and the national proportion of the elderly population, while negatively correlated with the year-end number of participants in basic medical insurance. Similarly, from an individual perspective, the silver economy market scale is positively correlated with residents’ health literacy levels and per capita disposable income. For health-oriented consumer groups, emphasis should be placed on strengthening the layout of medical and health product lines; for era-oriented consumer groups, age-appropriate content marketing strategies need optimization; and for market-oriented consumer groups, the supply of cost-effective goods should be enhanced. Health needs and age-appropriate services are core drivers of elderly consumption behavior, suggesting that enterprises should prioritize layouts in these areas. The digital economy and the proportion of the elderly population are key drivers of the silver economy, whereas basic medical insurance exhibits a negative effect by suppressing demand for market-oriented services.
silver economy, cluster analysis, random forest, multiple linear regression
Copyright (c) 2026 Yuhang Li, Chengyu Lai, Siqi Liao (Author) https://creativecommons.org/licenses/by/4.0
This paper focuses on the impact of digital technology on inclusive finance in China. By reviewing existing literature, it systematically analyzes the current development status, specific impacts, and challenges of digital technology (including big data, artificial intelligence, and mobile payments) empowering inclusive finance. This review of existing literature and current research reveals that digital technologies such as big data and artificial intelligence have significantly improved the coverage, convenience, efficiency, and risk management capabilities of inclusive finance by breaking through geographical limitations, optimizing service processes, and improving risk control systems. This has driven the transformation and innovation of traditional financial institutions and expanded their service coverage. However, the application of digital technology also faces certain practical challenges. These include the digital divide faced by some elderly and low-income groups due to device access barriers, uneven development across provinces and regions, and regulatory loopholes and user data security issues arising from the development and application of emerging digital technologies, which continue to hinder the further development of digital inclusive finance. By conducting a literature review, this paper systematically analyzes and summarizes the dual impacts of digital technology on inclusive finance and anticipates its trend toward precision and intelligent development. This paper provides theoretical references for promoting the high-quality development of digital inclusive finance.
digital technology, inclusive finance, digital inclusive finance, financial technology
Copyright (c) 2026 Jingchao Yang (Author) https://creativecommons.org/licenses/by/4.0
Study on the Differentiated Impact of Social Media Emotion Orientation on Corporate ESG Performance
With the popularization of ESG concepts in the capital market, the impact mechanism of social media on corporate ESG performance has become a current research highlight. This article aims to systematically review the relevant research in the past 5 years, from the perspective of the impact mechanism of positive and negative social media coverage on ESG performance, summarize the differentiated paths of social media on ESG ratings and corporate ESG practices in different industries (energy, finance, etc.) and analyze the limitations of existing research in areas such as “insufficient cross industry comparison” and “lack of long-term impact tracking”.Research has found that the social media focuses on the environmental impact of high-risk industries (such as energy), while the financial industry emphasizes social and governance supervision. In the future, it is necessary to further explore the dynamic interactive mechanism of “media-public-enterprise” in the era of social media, in order to provide theoretical reference for optimizing corporate ESG.
social media, ESG dimension, heterogeneity analysis
Copyright (c) 2026 Xiaowan Huang (Author) https://creativecommons.org/licenses/by/4.0
Optimization of the Tax Business Environment and Corporate Green Transformation: Empirical Evidence from the Tax “Streamlining Administration and Delegating Power” Reform
This paper employs the pilot reform of the “streamlining administration and delegating power” in the tax system as a quasi-natural experiment. Drawing on data from A-share listed companies spanning 2013-2023, it investigates the impact of optimizing the tax business environment on corporate green innovation. The findings reveal that optimizing the tax business environment significantly enhances the level of corporate green innovation. This conclusion holds robust after a series of robustness tests, including parallel trends tests, placebo tests, and controls for contemporaneous policy interferences. Mechanism analysis indicates that optimizing the tax business environment promotes corporate green transformation through two pathways: alleviating financing constraints and reducing agency costs. Heterogeneity analysis further demonstrates that this policy effect is more pronounced in state-owned enterprises, non-heavy polluting enterprises, and regions with higher levels of economic and financial development. This study provides important theoretical foundations and policy implications for deepening the “streamlining administration and delegating power” reform and optimizing the tax business environment to stimulate corporate green innovation momentum.
tax business environment, “streamlining administration and delegating power” reform, green innovation, financing constraints, agency costs
Copyright (c) 2026 Yingxin Yang (Author) https://creativecommons.org/licenses/by/4.0
Research on Stock Realized Volatility Prediction Using Multi-Models Incorporating International Macro Factors
Predicting realized volatility (RV) is crucial for asset allocation and risk management. Existing multi-factor research on predicting realized volatility in stocks has rarely incorporated international macroeconomic factors, and the comparison of machine learning models remains limited. This paper constructs a multi-factor framework combining technical and international macroeconomic factors using monthly data from the 50 most liquid stocks in the CSI 300 Index from 2018 to 2024. Three models-ridge regression, extreme gradient boosting (XGBoost), and a multilayer perceptron (MLP)-are used to predict the next period's RV. Results show that incorporating international macroeconomic factors improves the forecast accuracy of all models, with machine learning performing even better on the test set (R²≈0.43). The study finds that incorporating international macroeconomic factors significantly improves model forecast accuracy, with machine learning outperforming linear regression models. This research provides a reference for selecting methods for volatility forecasting in different market scenarios and offers theoretical insights for investors, asset pricing, and risk management.
realized volatility, multi-factor model, linear regression, machine learning, volatility forecasting
Copyright (c) 2026 Jiarui He (Author) https://creativecommons.org/licenses/by/4.0
Household wealth is a key determinant of food security; in particular, its impact is heterogeneous due to differences in entitlements, consumption smoothing, and the conversion of food into nutrition. This study develops a pathway framework that links asset stocks and income flows to the four FAO pillars, which include availability, access, utilization, and stability. The condition of India’s urban and rural setting would also be treated as evidence for analysis by adopting measurement approaches that are reviewed, including experience-based scales (HFIAS/FIES), coping indicators, dietary diversity indices, and anthropometric outcomes. The results indicate that wealth gradients in access-oriented indicators are generally steeper than those observed for long-term utilization outcomes. Weak asset buffers amplified the effects of income and price shocks, as demonstrated during the COVID-19 lockdown. While India has ample cereal supplies, the relative scarcity and high prices of nutritious foods limit the ability of poor households to upgrade their diets despite income growth. The policy recommendations include transforming social supply and demand dynamics, investing in distribution and transportation within the supply chain, and increasing infrastructure investment in livelihoods. Complementary interventions to strengthen health, water and sanitation, and nutritional knowledge may increase the efficiency of wealth in improving dietary quality.
India, food insecurity, economic access to food
Copyright (c) 2026 Nan Pan (Author) https://creativecommons.org/licenses/by/4.0
Geopolitical Risk Escalation and Traditional Safe-Haven Assets: The Dynamic Performance and Linkage Mechanisms of Gold, US Dollar, Japanese Yen, and Swiss Franc
This paper proposes and tests a “time-varying safe-haven hierarchy” theory by analyzing the market data during recent major geopolitical risk events. Using 20-day rolling correlations, event studies and narrative analysis, we show that the relative attractiveness of gold, the US dollar, the Japanese yen and the Swiss franc rotates predictably across crisis phases. During acute shocks, the dollar captures the liquidity panic premium, whereas gold dominates as the stalemate lengthens. Swiss-franc appreciation is actively managed by the central bank, while the yen repeatedly fails as a haven because of energy-linked macro vulnerabilities. Policy interventions act as exogenous shocks that instantaneously rewire cross-asset linkages. The findings offer phase-dependent allocation and hedging prescriptions for investors and highlight the market-impact implications of official FX operations for policymakers. High-frequency data and cross-case replication document a consistent leadership cycle: initial liquidity flight into the USD, transitional co-demand for USD and gold at peak panic, and protracted gold supremacy once energy-inflation risks dominate. Rolling correlations reveal the CHF as a “managed haven” instantly decoupled from gold whenever the SNB intervenes, while the JPY’s theoretical status is invalidated by oil-price shocks and current-account pressures. Despite differing systemic scope, both crises exhibit identical hierarchical sequencing, validating the dynamic framework and supplying investors with actionable, phase-contingent allocation rules while warning policymakers that FX operations can abruptly rewrite global correlation risk.
geopolitical risk, safe-haven assets, time-varying hierarchy, rolling correlation
Copyright (c) 2026 Jingyi Zhang (Author) https://creativecommons.org/licenses/by/4.0
Analysis of the Credit System of Internet Consumer Finance Companies
As an important part of consumer finance, Internet consumer finance plays a vital role in leading innovation and promoting consumption, and thus deserves great attention. Therefore, this paper focuses on the construction of the credit system of Internet consumer finance companies, adopting a research approach that combines theoretical analysis and case studies. Through theoretical analysis, we found that the credit scoring system has evolved from expert scoring cards and machine learning models to artificial intelligence; through case studies, we observed that in the process of constructing the credit system, not only technological innovations have emerged, but also the sources of credit information have undergone significant changes. This study systematically sorts out the development process of the credit system and compares the differences between Internet consumer finance credit risk and traditional credit risk, such as differences in information sources and technical levels. Meanwhile, this paper also identifies that the Internet consumer finance credit system, which relies on big data as its information source, carries certain risks.
internet consumer finance, credit risk model, WeChat loan
Copyright (c) 2026 Jiatong Liu (Author) https://creativecommons.org/licenses/by/4.0
International Talent Mobility under the Global Science and Technology Governance Framework: Challenges and Strategies for China
Under the profound transformation of global science and technology governance, international talent mobility has become a key arena of national competition. This paper builds a dual-drive model based on push‒pull theory and identity theory to explain China’s international talent flow. The model combines external factors such as institutional support and development opportunities with internal motivations such as emotional belonging and value identity, forming a mechanism of both attraction and cohesion. From the dynamic process of “outflow–inflow–circulation,” the study shows that China’s talent policies have evolved from quantity expansion to quality improvement and structural optimization. However, challenges remain, including intensified global competition, the trend of “decoupling,” and an insufficient domestic environment. To address these issues, the paper suggests enhancing institutional support, improving living conditions, and strengthening cultural identity to attract and retain high-level talent. Ultimately, China should move from a “policy-driven” approach to an “emotion-driven” approach in global talent competition.
global science and technology governance, international talent mobility, push-pull theory, dual-drive model, China’s talent strategy
Copyright (c) 2026 Rui Sun (Author) https://creativecommons.org/licenses/by/4.0
The Impact of ESG Performance on Corporate Financial Performance: Evidence from Listed Manufacturing Companies in Jiangsu Province
This study examines the impact of ESG performance on corporate financial outcomes using listed manufacturing firms in Jiangsu Province from 2013--2023 as the sample. Drawing on Huazheng ESG ratings and financial data, a two-way fixed effects model is employed to explore transmission mechanisms through innovation capability and debt financing costs. Heterogeneity analysis is conducted on the basis of ownership structure and regional differences within Jiangsu Province. The innovation of this study lies in its focus on provincial-level manufacturing sectors and its comprehensive examination of the overall effects across all three ESG dimensions. The results indicate that strong ESG performance enhances corporate performance, with more pronounced effects observed in nonstate-owned enterprises and in northern and central Jiangsu. These findings provide empirical support for enterprises and regulators to advance differentiated ESG practices.
ESG performance, corporate financial performance, innovation capability, debt financing costs
Copyright (c) 2026 Zuxin Ge (Author) https://creativecommons.org/licenses/by/4.0
EVA Dynamic Valuation Model Embedded in Surplus Governance: Based on the Empirical Research of Tencent Holdings and the Value Reconstruction of Internet Enterprises
This study investigates the EVA-based enterprise value assessment model, employing a combined approach of normative research and empirical analysis and quantitative and qualitative methods. The paper first establishes theoretical foundations through a literature review, followed by an in-depth case study of Tencent Holdings Limited. A triadic chain framework-”earnings governance-EVA-enterprise value”-is proposed, defining earnings governance as strategies to curb earnings management, thereby reducing capital costs and increasing economic profits. Research findings demonstrate that EVA provides a more objective measure of corporate value creation, offering a rigorous valuation benchmark after total capital costs are deducted. Tencent Holdings maintained positive EVA values from 2020--2024, consistently generating incremental wealth for shareholders, with projected future growth showing stable momentum. Additionally, EVA has multiple applications in corporate governance systems, driving attention to capital allocation efficiency and promoting long-term sustainable development. Notably, earnings governance significantly improves the valuation accuracy of EVA. Finally, integrating EVA with the BSC establishes a closed-loop management system for comprehensive corporate performance evaluation.
EVA, earnings governance, TenCent holdings, enterprise valuation, Kw, governance premium; asset light companies
Copyright (c) 2026 Zhenhao Liang (Author) https://creativecommons.org/licenses/by/4.0
Valuation Analysis of Mindray Medical’s Acquisition of Huitai Medical
This study examines the 2024 acquisition of Huitai Medical by Mindray Medical for CNY 6.65 billion, with particular focus on assessing the reasonableness of the acquisition premium. The analysis begins with an overview of the two companies: Mindray Medical, a leading medical device manufacturer with 2023 revenues exceeding CNY 40 billion, and Huitai Medical, a competitive electrophysiology sector player generating CNY 1.65 billion in revenue in 2023. Historical financial data for Huitai Medical covering 2023-2024 are examined to establish baseline performance metrics. The valuation methodology employs a Discounted Cash Flow (DCF) framework, projecting Huitai’s revenue growth, net income, and Free Cash Flow to the Firm (FCFF) through 2030 and into the terminal period. Utilizing a Weighted Average Cost of Capital (WACC) of 8.21% as the discount rate and incorporating a perpetual growth assumption for the terminal value, the analysis yields an enterprise value of CNY 28.918 billion. After adjusting for net debt, the equity value is estimated at CNY 29.938 billion, corresponding to an intrinsic value of approximately CNY 309.55 per share. Sensitivity analysis establishes a valuation range of CNY 262-361 per share under varying assumptions. The study concludes that the 25% acquisition premium is justified, primarily attributable to substantial anticipated synergies and Mindray’s strong financial capacity to absorb the transaction costs. However, several risk factors warrant attention, including potential underperformance in domestic market substitution strategies. Ultimately, the acquisition’s success will depend critically on effective post-merger integration and the sustained operational development of the combined entity.
mergers and acquisitions, valuation analysis, intrinsic valuation model
Copyright (c) 2026 Liang Jin (Author) https://creativecommons.org/licenses/by/4.0
Evolution of Industry Momentum Factors Following the 2025 U.S. Midterm Elections: Analysis of Structural Differentiation and Policy Sensitivity
Even though the United States election finished in 2024, the first half of 2025 is critical for the incoming administration’s policies to transition from anticipation to action. In light of this, this essay predicts that during the first half of 2025, high-momentum sectors will exhibit substantial structural divergence. This disparity reflects the market’s perceptions about different industries’ ability to respond to policy changes. This article’s key statistic is a 9-day momentum factor, which captures short-term trend performance across sectors. With statistically significant t-test results, it explores the sectors with the greatest difference in policy events and creates discrete event analysis windows based on policy types. Finally, the findings reveal that policy events exacerbate the disparities in momentum between industries. Furthermore, the disparity is systematic, involving both the nature of the industry and the policy’s content. Building on these findings, it discusses five critical policies and the underlying variables that contributed to this outcome. It concludes that, while policy serves as an external catalyst for divergence, the primary cause of this divergence is changes in industry sensitivity.
U.S. presidential election, policy impact, momentum effect
Copyright (c) 2026 Yunhan Xia (Author) https://creativecommons.org/licenses/by/4.0
Research on Green Supply Chain Construction Strategy from the Perspective of Sustainable Development: Taking JD Logistics as an Example
A green supply chain is an inevitable choice for enterprises pursuing high-quality development. This paper conducts a detailed analysis of JD Logistics, a leading company in China’s logistics industry. By exploring JD Logistics’ green supply chain construction strategy, implementation path, and coordination mechanism, this paper analyzes JD Logistics’ actual measures in five major areas: procurement, warehousing, transportation, packaging, and digitalization and technology collaboration. It finds that the main reason why JD Logistics has achieved breakthrough progress in both energy conservation and emission reduction, and resource recycling is that it has utilized scientific and technological empowerment methods and process reshaping measures. On this basis, it has integrated the forces of multiple parties within and outside the industry and supply chain, and actively promoted the energy- and resource-saving green supply chain system achieved through the “Green Flow Plan” and “Carbon Neutrality” actions. This practice has made positive contributions and provided useful reference for the green development and transformation of China’s logistics industry and even China’s manufacturing industry.
sustainable development, green supply chain, supply chain collaboration, JD Logistics
Copyright (c) 2026 Shanshan Hu (Author) https://creativecommons.org/licenses/by/4.0
Investors’ Risk Aversion Preference from the Perspective of Behavioral Finance
Behavioral finance breaks through the limitations of the “rational man” assumption in traditional financial theory, providing a more realistic perspective to explain irrational behaviors in the market (such as “herd behavior” and “disposition effect”) and abnormal phenomena like stock prices deviating from fundamentals. This discipline incorporates psychological factors such as cognitive biases and emotional fluctuations into its analytical framework, with investors’ risk-averse preferences being particularly crucial. These preferences directly influence their risk-return trade-offs and, through the aggregation effect of individual decisions, profoundly shape market volatility and operational efficiency. This paper systematically reviews the relevant theories and empirical studies on investor risk aversion preference in the field of behavioral finance, exploring the topic from multiple dimensions: at the level of influencing factors, it analyzes the effects of individual cognitive biases, emotional states, and market environments on risk aversion preferences; it also examines in depth how risk aversion affects investment decisions and the resulting market anomalies; finally, it investigates the behavioral finance explanations for fluctuations in risk aversion preferences, interpreting investors’ tendencies and changes in risk aversion from a behavioral finance perspective. The aim of this paper is to comprehensively analyze the significance and practical value of risk aversion preferences within the framework of behavioral finance, deepening the understanding of investors’ decision-making logic, and providing practical references for investors to optimize asset allocation and improve decision-making rationality, as well as for market participants to more accurately grasp market operating rules and maintain market stability.
behavioral finance, risk aversion preference, investment decision-making, market anomalies
Copyright (c) 2026 Xinyue Jia (Author) https://creativecommons.org/licenses/by/4.0
A Review of Social Media Sentiment Analysis in Financial Risk Control: Based on Natural Language Processing Technologies
This review examines the application of social media sentiment analysis, driven by Natural Language Processing (NLP) technologies, within financial risk control. It outlines the four-stage evolution of NLP, from traditional methods to pre-trained models. Using credit risk control as an example, it elaborates on its application across the entire loan lifecycle: pre-loan, in-loan, and post-loan. The study identifies limitations such as data scarcity, insufficient model generalization and interpretability, and high implementation costs. It also explores potential breakthroughs, including dataset construction and model optimization, aiming to provide a framework for related research and practice.
natural language processing (NLP), social media sentiment analysis, financial risk control, pre-trained language models, credit risk control
Copyright (c) 2026 Xinpeng Li (Author) https://creativecommons.org/licenses/by/4.0
Analysis of the Current Situation of the Aging Population and Differential Economic Impacts between China and Japan
Given that aging has become a common problem faced by China and Japan in terms of development paths, this article conducts a differentiated comparative analysis of the current situation and economic impact of aging in China and Japan. Both countries have gone through specific aging stages and will continue to experience aging with increasing and negative population growth. China has the largest elderly population, whereas Japan has the deepest degree of aging and a greater proportion of elderly people. In terms of economic impact, population aging has a detrimental effect on the quality of economic expansion in both countries, whereas interacting with technological innovation has a positive effect. The impact on consumption and the industrial structure has both positive and negative effects, which strongly influences the development of the tertiary industry. Finally, China can actively draw on Japan’s experience to promote technological innovation, postpone retirement, and guide elderly consumption to counteract the detrimental influence of aging on the development of both China and Japan.
Copyright (c) 2026 Jingyi Wang (Author) https://creativecommons.org/licenses/by/4.0
ESG Performance of Listed Companies and Labor Cost Stickiness
In the context of sustainable development and the “dual carbon” goals, the impact of corporate ESG performance on cost behavior has attracted increasing attention. This study employs a sample of Chinese A-share listed companies from 2010 to 2024 to examine the impact of ESG performance on labor cost stickiness. The findings show that overall ESG performance has no significant direct impact on labor cost stickiness. However, dimension-specific analyses indicate that the social responsibility (S) dimension significantly suppresses cost stickiness, while the environmental (E) and governance (G) dimensions have no significant effect. Further analysis reveals that the moderating effects of ownership type and regional development levels on ESG are heterogeneous, and ESG practices in state-owned enterprises and enterprises in the central and western regions of China have not effectively reduced labor cost stickiness. The findings suggest that the current structural limitations of ESG ratings and differences in institutional environments are key factors affecting the cost management effectiveness of ESG practices.
ESG performance, labor cost stickiness, corporate social responsibility, property rights heterogeneity
Copyright (c) 2026 Zeyu Ma (Author) https://creativecommons.org/licenses/by/4.0