International Journal of Finance and Investment
International Journal of Finance and Investment (IJFI) is a peer-reviewed journal published by Darcy & Roy Press. The mission of the journal is to provide an academic forum for discussing the issues of finance, business and investment across the world. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
Exploring Pathways for Guangxi to Help ASEAN Enterprises Use China's Futures and Derivatives Markets for Risk Management
As the Protocol upgrading the China–ASEAN Free Trade Area (CAFTA) to Version 3.0 takes effect and the dividends of the Regional Comprehensive Economic Partnership (RCEP) continue to be released, the need to manage price risk in bilateral commodity trade has become more urgent. ASEAN's domestic futures and derivatives markets remain immature, and a persistent "institutional mismatch" separates ASEAN industry from the European and American markets it has traditionally relied on for hedging, while China's futures market is increasingly well placed to absorb this demand. This paper examines how Guangxi, as a land-and-sea hub linking China and ASEAN, can help ASEAN enterprises manage risk through China's futures market. It finds that Guangxi enjoys policy, industrial and geographic advantages that make it a natural "test field" and "bridgehead" for extending Chinese futures services to ASEAN, but still faces gaps in dedicated policy and funding, weak industrial clustering, cross-border infrastructure shortfalls, and slow futures–spot integration. To address these constraints, the paper proposes a pathway built on four pillars: cross-border cooperation rules, market infrastructure and services, technical and talent support, and outreach and promotion — together aimed at systematically empowering ASEAN enterprises to manage market risk, and offering a reference for a "Guangxi platform + Chinese futures + ASEAN industry" paradigm that supports a closer China–ASEAN community of shared future.
Copyright (c) 2026 International Journal of Finance and Investment https://creativecommons.org/licenses/by-nc/4.0
A Study on the Impact and Transmission Channels of New-Quality Productive Forces in Driving a Leap in the Competitiveness of China’s Manufacturing Exports Impact and Transmission Channels
Against the backdrop of deepening globalisation and digital integration, new-quality productive forces are reshaping the global industrial division of labour, creating key opportunities for China’s manufacturing export competitiveness to leap forward. Based on 2010–2023 panel data of 31 Chinese provinces, this paper examines the impact effects and transmission paths of new-quality productive forces on manufacturing export competitiveness. The results confirm that new-quality productive forces exert a significant positive effect on manufacturing export competitiveness, with industrialisation level playing a mediating role. The effect is significantly positive in eastern and central regions but insignificant in the western region. A threshold effect of urbanisation is identified: below the threshold, the positive impact is significant; above the threshold, it turns significantly negative, presenting a non-linear feature of diminishing marginal effect. Targeted recommendations are put forward accordingly.
Organizational Change and Strategic Integration in Disney’s Acquisition of 21st Century Fox
This study critically examines the post-merger integration process of Disney’s acquisition of 21st Century Fox, focusing on strategic change management. The analysis applies the Waterman 7S framework, Kotter and Schlesinger’s resistance-to-change strategies, and dynamic capabilities theory to assess structural realignment, cultural integration, talent retention, and skill reconfiguration. Disney successfully implemented a Direct-to-Consumer strategy and expanded its IP portfolio. However, its centralized control model constrained creative autonomy, weakened cultural integration, and created operational overlaps. Path dependency in content development, top-down cultural imposition, and insufficient skill synergy mechanisms are also identified. This study offers practical insights for media industry managers navigating large-scale M&A transformations, with strategic recommendations including rebalancing content portfolios, establishing symbolic leadership roles, and diversifying revenue streams beyond streaming subscriptions.
The Application Value of Option Instruments in Risk Management within Corporate Finance
Option instruments are frequently used in corporate finance to reduce the risk of a decline in price asymmetrically and do not restrict the upward movement of the price. Research on the application of options in enterprise risk management. The above options are relatively more suitable for handling the firms' uncertain exposures and non-linear risks and demand for strategic flexibility. Options are relatively precise hedging instruments for foreign exchange risk, commodity price risk and interest-rate risk, etc., and can be used to manage equity exposure of a company. Based on the study of corporate option use and real options and option incentives, the four dimensions of value in this paper are downside protection, flexible hedging, strategic real-option value, and risk governance. In short, options are for speculation; however, if they are well-managed by the company, the risk can be reduced and firm value increased at the same time.
Exploring the Path of Digital Transformation Empowered by Financial Technology for Traditional Financial Institutions
Deepening digital economic expansion has laid bare chronic operational flaws across traditional finance. Many firms run inefficient daily operations, deliver inconsistent client services, and stick to outdated risk control structures unable to match frequent market changes. Under such circumstances, digital upgrades become a practical choice for these financial players to remove growth barriers and boost overall operating performance. Technologies including artificial intelligence, big data and cloud computing form the core of modern fintech, which supplies essential technical resources to renovate conventional financial services. This paper draws on China’s real financial market conditions, with research materials sourced from official regulatory documents, CNNIC statistical releases, listed commercial banks’ annual filings and firsthand industry cases. The five-aspect analytical framework it establishes covers technical foundation construction, on-site business promotion, internal institutional adjustment, full-range risk governance and inter-industry partnership. Following a step-by-step logic from basic facility setup, practical business launch, institutional matching rules, risk precaution to industrial ecosystem expansion, the article sets clear work focuses for every single part. Empirical results prove synchronous advancement of all five parts guarantees smooth digital renovation, satisfies development requirements for financial organizations of diverse sizes and drives sustained high-quality growth of China’s financial industry.
The Interplay between Financial Development and Urbanization: Evidence from Wuhan
This paper investigates the correlation between financial economic power and urbanization economy through the case study of Wuhan City. First, it elaborates on the conceptual framework of financial economic power, analyzing its core components, influencing factors, and specific functions. Subsequently, the urbanization economy is described by defining its essence, examining its origins and operational mechanisms, and identifying four key manifestations of its development, thereby deepening the understanding of urbanization economy. The paper then explores the concrete forms of financial economic power in urbanization economy through four dimensions: temporal patterns, spatial dimensions, operational mechanisms, and market structures. It highlights the specific impacts of financial economic power on urbanization economy and clarifies their intrinsic connection. Finally, using Wuhan City as a case study, the paper proposes strategies for leveraging financial economic power in urbanization economy. This study provides theoretical insights into the synergistic mechanism between financial development and urbanization, offering valuable practical guidance for similar cities in China and developing countries to optimize resource allocation, enhance economic efficiency, and achieve sustainable urbanization. The findings contribute to the academic discourse on regional financial economics while serving as a reference for policymakers in formulating inclusive financial strategies and urban development plans.
Analysis of the Role of Big Data in Shaping Banks' Risk Appetite and Risk-Taking Behavior
Against the background of the deep integration of digital economy and financial technology, big data technology is reconstructing the risk management paradigm of commercial banks from the bottom level, exerting systematic and sustained impacts on the formulation, transmission, implementation of banks’ risk appetite and the choice of risk-taking behavior. Traditional banks’ risk appetite and risk-taking behavior rely heavily on empirical judgment, sampling data and static indicators, which are generally plagued by problems such as information asymmetry, delayed risk identification, poor transmission of risk limits, excessive risk-taking or excessive risk aversion. Relying on the capabilities of multi-dimensional data collection, real-time processing, intelligent modeling and dynamic early warning, big data can effectively alleviate information asymmetry, improve the accuracy of risk measurement, optimize the allocation of risk limits, perfect the risk pricing mechanism, promote the transformation of banks’ risk appetite from experience-driven to data-driven, and risk-taking from passive response to active management. Based on risk management theory, information asymmetry theory and behavioral finance theory, this paper systematically combs the theoretical logic and transmission path of big data’s influence on banks’ risk appetite and risk-taking behavior, analyzes the specific mechanism of big data from the dimensions of risk appetite system construction, credit decision-making, asset allocation, risk early warning, internal control and compliance, reveals the application effectiveness and practical constraints combined with the practice of domestic commercial banks, and puts forward countermeasures and suggestions such as improving data governance, optimizing model algorithms, strengthening compliance risk control, and improving governance mechanism. Studies show that big data can significantly enhance the scientificity, consistency and enforceability of banks’ risk appetite, reasonably guide risk-taking behavior, and enhance the robustness of the banking system while improving operational efficiency and the ability to serve the real economy. The conclusions of this paper can provide theoretical reference and practical guidance for the digital transformation of commercial banks, the upgrading of risk management and the improvement of regulatory rules by regulatory authorities.
Research on the Path to High-Quality Integrated Development of the Sports Tourism Industry under the Background of "Green and Beautiful Ecological Construction"
Green and beautiful ecological construction represents a significant practical endeavor for ecological civilization in the new era, providing a new value coordinate and development opportunities for the high-quality development of the sports tourism industry. Based on elucidating the theoretical logic of integrating green and beautiful ecological construction with the sports tourism industry, this paper systematically analyzes the practical foundation and major problems of the integrated development of China's sports tourism industry, constructing an analytical framework of "dynamic mechanism—integration mechanism—realization path." The research indicates that the integration of green and beautiful ecological construction and the sports tourism industry exhibits a bidirectional interactive relationship characterized by "ecology empowering industry, industry feeding back to ecology." However, prominent challenges remain, including imbalances between ecological protection and development, insufficient depth of industrial integration, institutional barriers, and underdeveloped market entities. This paper proposes that, guided by ecological priority as the value orientation, industrial integration as the core path, and institutional innovation as the fundamental guarantee, a practical path for high-quality integrated development of the sports tourism industry should be constructed from four dimensions: spatial restructuring, product innovation, industrial chain integration, and governance optimization. This aims to provide theoretical reference and practical guidance for achieving synergistic and mutually beneficial ecological and economic benefits.
Green and beautiful ecological construction
Intelligent Transformation of Non-bank Mortgage Loan Business: Application of AI in Process Optimization and Risk Identification
As Australia’s non-bank mortgage sector expands under the combined pressures of broker-led distribution, stricter compliance expectations and rising document fraud risk, artificial intelligence is being adopted in lending operations in more practical and targeted ways. This article examines how AI can be deployed across document intake, fraud screening, credit assessment support and compliance traceability in Australian non-bank mortgage lending. Rather than treating AI as a substitute for human credit judgment, the article argues that its most credible role is to improve operational efficiency, strengthen anomaly detection, enhance consistency in preliminary assessment and support auditable decision processes. Using Australian market structure and regulatory settings as the institutional background, the article develops an applied framework that links lending stages, AI functions, risk constraints and points of human intervention. A scenario involving self-employed and non-standard income borrowers is used to illustrate both the operational value and the governance limits of AI deployment. The analysis shows that AI creates the greatest value when it is embedded within a human-in-the-loop operating model that preserves accountability, interpretability and regulatory defensibility. For journals such as IJFI, the contribution of the article lies in showing that the key issue is not whether AI can automate more lending tasks, but whether non-bank lenders can govern AI in a commercially usable and risk-aware way.
Analysis of the Impact of Tax Transparency on International Investment Behavior of Enterprises and the Role of Corporate Governance
Economic globalization is evolving in depth, and the international tax governance system is becoming increasingly perfect. Tax transparency has become a core institutional endowment that affects the cross-border resource allocation of enterprises. Based on three major theories of information asymmetry, this article deeply deconstructs the deep coupling logic between tax transparency and international investment decision-making, location selection, scale, and efficiency of enterprises, and explores the regulatory and intermediary effects of corporate governance. Research has found that tax transparency injects positive empowerment into international investment by reducing financing costs, easing cross-border tax exposure, and building a foundation of investor trust; Improved corporate governance can not only improve the quality of tax information disclosure, but also establish a sound compliance framework, significantly amplifying this positive effect. In addition, the impact of tax transparency shows distinct heterogeneity among different enterprise sizes, industry attributes, and investment regions. The BEPS Action Plan provides theoretical and practical guidance for enterprises to deepen tax transparency, governments to promote international tax management, and create a fair and efficient cross-border investment environment by improving global tax information exchange and reducing compliance risk exposure.
Research on Price Discovery in Major International Crude Oil Futures and Spot Markets
This paper focuses on the price discovery function of the international crude oil futures and spot markets. Against the backdrop of intensified volatility in the global energy market and the gradual rise of Shanghai crude oil futures' influence, it aims to explore the price discovery efficiency and structural breakpoint impact effect of crude oil futures and spot markets in different countries and regions. Selecting data from Shanghai crude oil futures and gasoline, diesel spot markets in 5 countries/regions (China, Singapore, the Netherlands, the United States, and the Mediterranean) from 2018 to 2024, the study employs methods such as dynamic Copula, Bayesian structural breakpoint test, and dynamic Granger causality test. The results show that the price discovery function of crude oil futures is significantly stronger than that of spot markets; the price discovery efficiency of European and American markets (the Netherlands, the United States, the Mediterranean) is far higher than that of Asian markets (China, Singapore); and the intensity of price discovery is highly consistent with structural breakpoints. This research reveals the temporal and spatial characteristics of price discovery in international crude oil futures and spot markets, provides arbitrage references for market participants, and offers a basis for policymakers to optimize the regulatory mechanism of the Asian crude oil market.
Mispricing Detection in the S&P 500 ETF Options Market Based on an XGBoost Model
Based on high-frequency data for S&P 500 index options (SPX) obtained from the WRDS database, this paper builds an empirical framework for identifying option pricing mismatches. First, taking the Black–Scholes model as the theoretical pricing benchmark and combining it with actual market quotes, we introduce a relative mispricing measure and adopt a quantile standardization strategy to construct mispricing labels, which are divided into three categories: overpriced, underpriced, and fairly priced. Then, we construct a mispricing identification model using an XGBoost multiclass classifier, trained and predicted with multidimensional features including contract attributes, trading indicators, and volatility. In data preprocessing, we clean both option and underlying information and strictly align them using a dual primary key of trading date and contract identifier to ensure the accuracy and consistency of label construction. The empirical results show that the model achieves good identification performance in the out-of-sample test period (2023), with an overall accuracy of 77.6%. The precision and recall for the underpriced category are particularly strong, indicating that the model can effectively identify pricing deviations with potential arbitrage value. At the same time, the results reflect the existence of certain structural inefficiency in the options market. Although the Black–Scholes framework relies on idealized assumptions, it still has important reference value in mispricing identification. This study not only verifies the feasibility of using machine learning to identify option mispricing, but also provides a methodological foundation for subsequent quantitative trading strategy design.
Can the Low-Altitude Economy Pilot Policy Promote the Upgrading of Urban Industrial Structure?
The low-altitude economy serves as a vital engine for cultivating new quality productive forces. Based on panel data covering 291 prefecture-level cities in China from 2017 to 2023, this study utilizes the introduction of national-level planning in 2021 as a quasi-natural experiment to empirically examine the impact of low-altitude economic policies on urban industrial upgrading using a Difference-in-Differences (DID) approach. The findings indicate that these policies significantly promote industrial upgrading in pilot cities, a conclusion that remains robust after addressing endogeneity via the instrumental variable (IV) method and conducting a series of robustness checks. Regarding the underlying mechanisms, the policy exerts its influence primarily by improving resource allocation efficiency rather than through technological innovation. Heterogeneity analysis further reveals that the promotional effect is more pronounced in the central and western regions compared to the eastern region. This research provides micro-level evidence for evaluating the macro-economic effects of the low-altitude economy.
Research on the Radiation Effect and Collaborative Path of Xi'an as a Central City's Innovation Function against the Background of High-Quality Development
Against the backdrop of high-quality development, this paper focuses on the radiation effect and collaborative paths of innovation function of Xi’an as a national central city. The study systematically summarizes the four-stage evolutionary characteristics of Xi’an’s innovation function from single-core polarization to networked collaboration, and identifies three major collaborative obstacles: administrative barriers, industrial isomorphism and innovation chain rupture, as well as gradient gaps in the innovation ecosystem. On this basis, a three-dimensional mechanism framework of “space-industry-institution” is constructed to reveal the spatial friction caused by topographic barriers and transportation infrastructure, the bonding effect formed by industrial complementarity, and the barrier-breaking role of institutional coordination. In response to the above obstacles and mechanisms, this paper proposes a collaborative path system that optimizes spatial carriers through the “米”-shaped transportation network and zonal layout, promotes the in-depth integration of innovation chain and industrial chain with the Qinchuangyuan platform, and breaks down administrative barriers via cross-regional governance mechanism innovation. The results show that the systematic promotion of spatial restructuring, industrial collaboration and institutional innovation can effectively improve the innovation radiation efficiency of Xi’an, and provide theoretical support and practical paradigm for the high-quality development of urban agglomerations in western China.
Research on Pricing Decisions for Battery Swapping Mode Based on Different Power Structures in Staged Utilization of Power Batteries
To address challenges in power battery recycling, the integrated application of battery swapping and secondary utilisation technology enhances both economic efficiency and environmental performance, providing crucial support for the sustainable development of new energy vehicles. Accordingly, this paper constructs separate Stackelberg game models for supply chains under distinct power structures—one for battery manufacturers and another for battery swapping operators. It examines the cascading utilisation of power batteries under these varying power structures, making decisions regarding the technical level of cascading utilisation, pricing of cascaded products, and consumer battery leasing rates. The study delves into how parameters such as battery leasing duration, cascading sensitivity coefficient, and cascading R&D cost coefficient influence both parties' profits and technical advancement. Findings reveal: (1) Extending consumer battery leasing durations reduces leasing costs while simultaneously increasing profits for both swapping operators and manufacturers. (2) At elevated re-use sensitivity coefficients, profits remain relatively high even with substantial re-use R&D cost coefficients, though sensitivity coefficients exert greater influence on profitability. (3) Battery manufacturers leading secondary technology R&D enhances secondary technology standards and reduces secondary product prices, whereas battery swapping operators leading such efforts benefits supply chain system profitability. (4) A battery manufacturer-dominated supply chain proves more advantageous for consumers in both the battery swapping and secondary markets.
Financial Strategies and Practices of Start-Up Companies at Different Stages of Development
This article studies the impact of financing constraints on investment and expenditure of enterprises in different life cycles that are negatively impacted. Previous studies have mostly focused on static analysis of corporate financing, while this article focuses on the dynamic financial performance differences between start-up and growing enterprises in different life cycles. Using panel data from Chinese ChiNext listed companies to measure financing constraints, the stage of the company's lifecycle, and negative impacts. The empirical results also confirm this conclusion, that is, higher information asymmetry and higher financing constraints lead to earlier companies being more sensitive to negative shocks and experiencing greater investment contraction effects. This article intends to use the double difference method to identify causality using exogenous negative shocks at the macro or industry level, examine the heterogeneity of the response of enterprise investment (such as capital expenditure) and operating expenditure (such as research and development investment) to such shocks at different stages among enterprises, and explore the moderating effect of external financing availability. The research found that it is expected to deepen the understanding of the interaction mechanism between the lifecycle of enterprises and financing constraints, and make theoretical contributions to understanding the financial behavior of innovative enterprises in emerging markets.
Research on the Realization Path of Low-carbon Economy Assisted by Waste Classification under the Background of Ecological Civilization
Under the strategic guidance of the construction of ecological civilization and the goal of "double carbon", waste classification has become an important link to promote green and low-carbon development, and the evaluation of its environmental and economic benefits has been paid more and more attention. Based on this, this study aims to systematically explore the realization path of waste classification to help low-carbon economy from the perspective of environmental accounting, so as to provide a basis for government policy-making. This study uses the analytic hierarchy process (AHP), focusing on the four dimensions of environmental benefits, economic feasibility, management effectiveness and social sustainability, and sets up three typical paths: policy-driven, technology-incentive-driven and comprehensive cooperation-driven. The results show that the implementation path of comprehensive synergy driving is the optimal solution of waste classification under the current background, especially in terms of environmental benefits and social sustainability. Accordingly, this study puts forward relevant policy recommendations to encourage the government to provide technical empowerment, economic incentives and community co-construction while focusing on policy guidance, so as to carry out diversified collaborative governance.
The Impact of Data Assetization on Stock Price Crash Risk
Data assetization significantly impacts stock price crash risk by optimizing corporate information disclosure systems and enhancing information supply quality. Based on data from A-share listed companies covering 2007-2023, this study finds that data assetization significantly suppresses stock price crash risk, with this inhibitory effect being more pronounced in asset-light firms, companies with lower audit quality, and those with greater regulatory distance. Mechanism analysis reveals that data assetization reduces crash risk by improving stock price informativeness, while institutional ownership weakens this effect. This research enriches the literature on data assetization and stock price crash risk, providing theoretical guidance for regulatory authorities, enterprises, and investors in advancing data assetization practices.
How Does Public Environmental Concern Affect Corporate Green Innovation?
This study investigates the impact of the rising public environmental concern on cooperate green innovation in China using a firm-level fixed effects model. It includes 41,881 Chinese A-share listed firms from 2010 to 2024. Data are obtained from the Baidu search index and the CNRDS green patent database. The results show that public environmental attention can promote corporate green innovation. Heterogeneity analyses show that this positive impact is substantially stronger for financially constrained firms. This indicates that environmental attention serves as a critical external pressure that motivates green innovation under financing constraints. Also, state-owned enterprises respond more strongly to environmental attention than non-state-owned firms.
Research on the Advantages of Hybrid Forecasting Method and Its Performance Under Different Forecasting Spans
Prediction technology is the key support for decision-making in the fields of economy, energy, environment and so on, but there are obvious limitations in a single prediction method: ARIMA and other statistical models are difficult to fit nonlinear data, and LSTM and other machine learning models rely on large samples and are easy to over fit. Through literature analysis and method comparison, combined with typical scenarios such as power load, GDP growth, population planning, this paper focuses on the core advantages of the hybrid forecasting method, and explores its performance in the short-term (1-3 months), medium-term (3-12 months), and long-term (more than 1 year) forecasting span. The results show that the hybrid method breaks through the accuracy bottleneck and enhances robustness by "basic model complementarity+fusion strategy optimization": it is good at capturing real-time fluctuations in short-term forecasting, and can balance stability and dynamic adaptability in medium and long-term forecasting. The research provides practical reference for the selection of prediction methods in different scenarios, and effectively avoids the scene adaptation defects of a single method.
Research on Identification and Prevention Measures of Financial Risks in Enterprises under the New Situation
The current economic environment presents "new situation" characteristics such as deepening digital transformation, global supply chain restructuring, and stricter policy supervision. The transmission speed of corporate financial risks is accelerating, and their manifestations are becoming more complex. This article focuses on the four major risk dimensions of enterprise financing, investment, operation, and liquidity through literature analysis and logical sorting. It identifies the specific manifestations and causes of financial risks under the new situation, points out the problems of incomplete system, weak data integration, and lagging early warning in risk identification of enterprises, and proposes targeted preventive measures such as improving the identification system, strengthening internal control, and optimizing financing structure. The research aims to provide practical reference for enterprises to cope with financial challenges in the new situation, help enterprises improve their financial risk control capabilities, and ensure business stability. The full text is based on economic policies, public operational reports of enterprises, and academic research results from core journals published by official institutions such as the National Bureau of Statistics and the Ministry of Industry and Information Technology, with no false data or cases.
Analysis of the Formation Path of Investors' Risk Perception Bias and Its Impact on Decision-Making Efficiency
In the capital market, the efficiency of investor decision-making is directly related to the efficiency of resource allocation and the smooth operation of the market. Risk perception bias, as a common systemic phenomenon in investor decision-making, is not an accidental product, but the result of the interaction between individual cognitive traits and external environmental factors. This article is based on the theoretical frameworks of behavioral finance and cognitive psychology, systematically deconstructing the formation logic and evolutionary path of this bias, analyzing the core driving mechanism from the dual dimensions of individual cognition and external environment, and exploring its multidimensional impact on decision-making timeliness, accuracy, and rationality. Research has shown that individual cognitive limitations, information asymmetry, and social interaction effects are the core driving factors for bias formation, and this bias significantly weakens investor decision-making efficiency by distorting the risk assessment system, interfering with the internal logic of decision-making, and exacerbating market irrational behavior. The research conclusion of this article provides theoretical reference and practical inspiration for investors to optimize decision quality and regulatory authorities to improve market mechanisms.
From Instrumental Rationality to Value Symbiosis: Logical Rationale and Practical Mechanism of Generative AI Empowering Content Production of Internet Ideological and Political Education in Universities
Currently, Generative Artificial Intelligence (AIGC) technologies, represented by ChatGPT and Sora, have triggered a profound transformation in the paradigm of information production, bringing a historic opportunity for the digital transformation of Internet ideological and political education in universities. However, existing practices are largely confined to the one-dimensional perspective of "instrumental rationality," regarding AI merely as a technical means to improve efficiency. This has led to dilemmas in content production, such as homogenized supply, emotional deficit, and the alienation of subjectivity. Based on Marxist philosophy of technology and the principles of ideological and political education, this paper proposes a theoretical proposition of transitioning from "instrumental rationality" to "value symbiosis." The study argues that the empowerment of Internet ideological and political education by generative AI should not stop at technical application but should move towards the ecological reshaping of human-machine collaboration. By constructing a closed-loop mechanism of "intelligent perception—collaborative creation—value alignment—dynamic feedback," a deep coupling of technological logic and value logic can be achieved. Based on this, the paper systematically elucidates the practical paths for generative AI to empower content production in university Internet ideological and political education from three dimensions: constructing vertical domain knowledge graphs, optimizing interaction paradigms through prompt engineering, and governing ethical risks across the entire chain. The aim is to provide theoretical support and action references for resolving "structural contradictions on the supply side" and enhancing the effectiveness of online ideological and political education.
Internet Ideological and Political Education
Copyright (c) 2025 International Journal of Finance and Investment https://creativecommons.org/licenses/by-nc/4.0
Construction and Optimization Strategy of Regional Sports Industry Financial Ecosystem from the Perspective of New Quality Productive Forces
In the new journey of comprehensively building a modern socialist country, new quality productive forces, as a concrete manifestation of advanced productive forces, are becoming the core engine promoting industrial structure transformation and high-quality economic development. The sports industry, possessing attributes of greenness, health, and consumption upgrading, is undergoing a transition from traditional factor-driven to innovation-driven development, which urgently requires a matching financial support system. However, traditional single financial instruments or loose investment and financing models can no longer adapt to the characteristics of "high technology, light assets, long cycle, and high risk" of new quality productive forces in sports. There is a serious "ecological niche mismatch" between financial resources and industrial needs. Constructing a regional sports industry financial ecosystem characterized by multi-subject symbiosis, all-factor coordination, and environmental friendliness has become the key to solving this problem. Based on financial ecology and industrial organization theory, this paper constructs an analytical framework for the sports financial ecosystem driven by new quality productive forces, analyzing its reshaping mechanism on financial species evolution, ecological environment reconstruction, and energy flow mechanisms. Taking Guangzhou as an example, this paper deeply analyzes the realistic pain points existing in its sports industry financial ecosystem in terms of species diversity, community structure, ecological environment, and energy flow, such as the dilemma of "credit standing alone," the scarcity of patient capital, the "island effect" of credit data, and the rigid mechanism of industry-finance integration. Based on this, this paper proposes constructing a composite ecosystem architecture of "government guidance + market leadership + technology empowerment" and puts forward optimization strategies from five dimensions: enriching financial species communities, optimizing ecological environment matrix, dredging capital energy circulation, strengthening technological nervous systems, and improving risk immune mechanisms. The aim is to provide a continuous stream of financial living water and institutional guarantees for Guangzhou to build a world-famous sports city and cultivate new quality productive forces in the sports industry through the benign succession of the financial ecosystem.
Reconstruction Logic and Practical Path of "Sports+" Composite Talent Training Model Oriented to Industrial Demand: An Examination Based on OBE Education Philosophy
With the high-quality development of the sports industry and the in-depth advancement of the "New Liberal Arts" construction, traditional sports talent training under a single-discipline paradigm can no longer meet the urgent demand for composite and innovative talents in new business formats. The long-standing separation between sports disciplines and economics/management disciplines has led to a structural misalignment between the supply side of talent training and the demand side of the industry. Based on the Outcome-Based Education (OBE) philosophy, this paper examines the realistic dilemmas in current "Sports+" talent training, such as disciplinary barriers, lagging teaching paradigms, and single evaluation systems. Following the logic of "reverse design and forward implementation," this study reconstructs a composite talent training objective covering knowledge, ability, and literacy. It builds a three-layer progressive interdisciplinary curriculum system of "Theory-Integration-Practice." On this basis, it proposes an innovative path of "Case + Project" dual-driven teaching mode and constructs a deep school-enterprise collaborative mechanism and a whole-process value-added evaluation system. This study aims to provide theoretical compliance and practical paradigms for solving the pain points of "Sports + Economics/Management" composite talent training and to promote the connotative development of higher sports education.
A Study on Intelligent Decision-Making and Risk Management for Cross-Market Bidding via Integrated Federated Learning and R Language Modeling
Cross-market bidding across energy, finance, and supply chain sectors faces significant challenges due to data privacy constraints and commercial confidentiality, which hinder effective collaborative decision-making and risk management. This work proposes an integrated FL-R framework that synergistically combines Federated Learning for privacy-preserving collaborative modeling with the R language for statistical analysis and reproducible research. Through simulated case studies in electricity markets and supply chain finance, this work demonstrates that the proposed approach achieves an average reduction in prediction error of approximately 18% and an improvement in risk-adjusted returns of about 12%. The framework provides decision-makers with an effective tool for enhancing forecasting accuracy and strengthening risk control capabilities in complex multi-market environments.
Field Reconstruction and Collaborative Governance: Modern Transformation of the Activation and Utilization of Urban Red Cultural Heritage in the Era of Digital Intelligence
Against the dual backdrop of the in-depth implementation of the national cultural digitization strategy and the modernization of the governance system, red cultural heritage, as a key carrier of urban collective memory and an important space for political socialization, faces the epochal proposition of transforming from "static protection" to "dynamic inheritance." The rapid development of digital intelligence technology has provided technological empowerment for this transformation, but it has also triggered profound structural changes in the existential state and communication field of heritage. As the source of the modern Chinese democratic revolution and a pioneer of reform and opening up, Guangzhou possesses extremely unique and rich red cultural resources. However, under the traditional administrative-led governance model, it still faces deep-seated contradictions such as "data islands" caused by low digitization levels, "meaning fracture" triggered by obsolete narrative methods, and "subject absence" resulting from insufficient social participation. Based on Pierre Bourdieu's sociological "Field" theory and the "Collaborative Governance" theory of modern public management, this paper constructs an analytical framework of "Technology-Field-Governance." The study deeply analyzes how digital intelligence technology acts as a "meta-medium" to promote the transformation of red culture from a closed physical field to a virtual-real symbiotic composite field through the virtual extension of physical space, the embodied reorganization of social relations, and the semantic reconstruction of historical meaning. The paper further points out that simple technological embedding is insufficient to solve the inheritance crisis; it is necessary to transcend technological determinism and build a multi-subject collaborative governance pattern featuring "government meta-governance, university knowledge supply, enterprise technological innovation, and public presence participation." Finally, the paper proposes specific paths such as establishing a blockchain-based trusted data space, an integrated innovation ecosystem of industry-academia-research-application, and a localized emotional identification network, aiming to provide theoretical support and institutional solutions for Guangzhou to polish the brand of "Source of Revolution" and realize the modern transformation of red cultural heritage activation and utilization.
Embodiment, Empathy, Identification: Mechanisms of Red Finance Digital Narrative Empowering the Cultivation of Family-Country Sentiment
Against the dual backdrop of the digital transformation of education and the construction of "Comprehensive Ideological and Political Education," Red Finance resources, as historical witnesses to the economic struggles led by the Communist Party of China (CPC), possess unique educational value. However, the static display of historical materials under traditional educational models has led to a separation of body and mind and the concealment of emotions among students. Grounded in Embodied Cognition Theory and Narrative Ethics, this paper proposes that Red Finance digital narrative is a practice of physical return and spiritual reshaping mediated by technology. The article deeply analyzes the triple mechanisms by which digital narrative empowers the cultivation of Family-Country Sentiment: First is the "Embodiment" mechanism, which reconstructs a historical "sense of presence" through multimodal perception, breaking spatio-temporal barriers and transforming disembodied symbols into embodied experiences. Second is the "Empathy" mechanism, which leverages narrative transportation and mirror neuron mechanisms to drive students from "spectators" to "participants" through role empathy, achieving a resonance between individual emotions and historical destiny. Finally, the "Identification" mechanism sublimates transient emotional experiences into stable Family-Country Sentiment and political beliefs through meaning negotiation and value reflection. Based on this, the paper constructs a complete educational logic ranging from sensory immersion to spiritual internalization, providing profound theoretical support and practical direction for the digital innovation of ideological and political education in universities in the new era.
Technological Disenchantment and Value Anchoring: Ethical Scrutiny and Teacher Role Reshaping in AI-Embedded University Physical Education
As Artificial Intelligence (AI) technology embeds itself into the field of university physical education (PE) with an irreversible trend, PE is undergoing a profound transformation from "corporeal presence" to "data twinning." While this transformation significantly improves teaching precision and efficiency, it also triggers a crisis of technological rationality overstepping humanistic values. Based on the dual perspectives of philosophy of technology and educational ethics, this paper conducts a deep "disenchantment" scrutiny of the process of AI embedding into university PE. The research points out that the excessive application of AI technology in PE faces ethical dilemmas such as bodily alienation, privacy surrender, algorithmic bias, and the dissolution of subjectivity, exposing PE to the risk of "dehumanization." In the face of the assertion of technological rationality, the article proposes that PE must return to its value origin of "becoming human," reaffirming the unique educational functions of sports in moral discipline, will tempering, and emotional interaction. On this basis, this paper reconstructs the role map of university PE teachers in the intelligent era: teachers should transform from simple "skill transmitters" to "interpreters of data wisdom," "gatekeepers of technological ethics," and "builders of a human-machine symbiotic ecosystem," finding a new educational balance in the tension between technology and value, and realizing the dialectical unity of technological empowerment and value anchoring.
Technological Embodiment and Value Return: The Logical Path of Generative AI Empowering Scenario-based Teaching in University Ideological and Political Courses
In the deep water zone of digital transformation in education, Generative Artificial Intelligence (Generative AI), with its powerful content generation capabilities, multimodal interaction characteristics, and human-like logical reasoning abilities, provides a new technological embodiment field for the reform of scenario-based teaching in university ideological and political theory courses (Civics Courses). Traditional teaching in these courses often faces a rupture between abstract theory and concrete experience. Generative AI, by constructing immersive, interactive, and generative teaching scenarios, realizes a cognitive shift from "disembodied" knowledge to "embodied" knowledge. However, the deep embedding of technology also triggers ethical risks such as algorithmic bias, information cocoons, and the alienation of subjectivity, posing severe challenges to the value-leading function of ideological and political education. Based on the perspectives of technological phenomenology and Marxist humanism, this paper deeply analyzes the internal mechanism of Generative AI empowering scenario-based teaching in Civics Courses, dialectically examines the dilemma of "technological overreach" it may encounter, and explores practical paths for unifying technological empowerment with the essence of education from three dimensions: the reshaping of subjects through human-machine synergy, the ethical regulation of algorithmic governance, and the return of value rationality. This aims to provide theoretical support and action reference for the high-quality development of university ideological and political courses in the new era.
University Ideological and Political Courses