International Journal of Global Economics and Management
International Journal of Global Economics and Management (IJGEM), a peer-reviewed open access journal published in English-language, provides an international platform for the publication and dissemination of original work that contributes to the understanding of the main and related disciplines of global economics and management either empirical or theoretical. The journal covers the whole spectrum of economics, business, management, which includes, engineering and technology management, finance and accounting, economic behavior and organization, investment and management, sustainability management, theoretical and applied business, economics, finance and management sciences, business and economic development, risk management, public policy and administration, and more.
Corporate Environmental Social Responsibility under the Governance of Low-Carbon Economy
The advancement of global climate governance alongside the deep implementation of China's "dual carbon" strategy has elevated the collaborative governance of the ecological environment to a central position within high-quality economic and social development. As ecological and environmental issues receive increasing attention, corporations, as the primary consumers of environmental resources and the principal sources of environmental pollution, bear a significant responsibility for improving and protecting the existing ecological environment. Against the backdrop of developing a low-carbon economy, it is imperative to clarify the environmental social responsibility that enterprises should undertake in environmental protection from multiple dimensions, including fostering low-carbon philosophies, enacting environmental legislation, increasing investment in low-carbon technology R&D, and strengthening government guidance.
Copyright (c) 2026 International Journal of Global Economics and Management https://creativecommons.org/licenses/by-nc/4.0
Research on the Relationship between Debt Financing and Corporate Growth of Logistics Listed Companies
Taking A-share logistics listed companies on the Shanghai and Shenzhen stock markets from 2020 to 2025 as the research object, this study empirically analyzes the impact of debt financing on corporate growth using structural equation modeling (SEM) and mediation effects. The results indicate that debt financing is significantly negatively correlated with corporate growth; Executive incentives have a significant positive causal relationship with corporate growth, while debt financing has a significant negative correlation with executive incentives, and debt financing can indirectly affect corporate growth through the mediating effect of executive incentives. The direct effect of debt financing on corporate growth is -0.277, the mediating effect is -0.041, and the total effect is -0.318.
Joint Replenishment Problems in Inventory and Distribution Systems: A Review of Models, Constraints, and Algorithms
The joint replenishment problem (JRP) examines replenishment cycles, order quantities, and coordinated execution decisions for multiple items that share ordering costs or operational resources. As inventory management becomes increasingly connected with distribution networks, JRP has moved beyond static cost minimization and has been extended to stochastic demand, dynamic demand, resource constraints, joint replenishment and delivery, inventory routing, vendor-managed inventory, and learning-based optimization. This paper provides a narrative review of representative studies on JRP and related integrated inventory-distribution problems. The review is organized around four themes: relaxation of modeling assumptions, incorporation of operational constraints, expansion of decision boundaries, and evolution of algorithmic paradigms. It compares the decision scope of JRP, JRD, IRP, and S&OP-related models, and discusses the applicability of heuristics, metaheuristics, mathematical programming, approximation algorithms, and reinforcement learning. The review suggests that JRP research is shifting from replenishment-cycle selection under a single cost objective toward integrated supply chain decision-making under uncertain demand, limited resources, distribution coordination, and multi-objective performance requirements.
Research on the Secondary Recycling Strategy of Packaging Waste Based on a Tripartite Evolutionary Game Model
Under the background of the "dual carbon" goals and the promotion of green development strategies, China has continuously strengthened the governance of packaging and the construction of packaging waste recycling systems. This paper focuses on the packaging issues in the online sales of gift-attribute commodities. Using evolutionary game theory as an analytical tool, it constructs an evolutionary game model. The results show that the initial recycling willingness of enterprises has the greatest impact on the synergy pace of the system, exhibiting a significant "herding effect"; enterprise recycling decisions are significantly influenced by reuse benefits, as well as R&D and operational costs; the depth of logistics enterprises' participation depends heavily on government special subsidies and social benefits; the sharing of environmental governance responsibility and governance investment both positively drive the behavior of the three parties; and an increase in the recycling benefit coefficient can enhance overall synergy from the market side.
Cross-Regional Co-construction and Reconstruction Path of Guangdong's Sports, Culture, and Tourism Industry Ecosystem under the Regional Coordinated Development Strategy
Under the macro background of deeply advancing the regional coordinated development strategy and accelerating the construction of a new development paradigm, exploring the cross-border integration of industries and inter-regional collaborative governance has gradually become the theoretical direction for optimizing the macroeconomic spatial layout and cultivating new growth poles for the regional economy. As a representative province with strong economic vitality and significant gradient characteristics in regional development, Guangdong Province, in the process of promoting the integrated development of sports, culture, and tourism industries, objectively faces the theoretical demand of evolving from the relatively isolated operation of single industrial elements to a cross-regional composite industrial ecosystem. Moving beyond traditional empirical models and quantitative measurements, this paper adopts a theoretical speculative perspective of qualitative research, combining regional coordinated development theory, industrial ecology theory, and spatial political economy theory, to systematically explore the cross-regional co-construction and reconstruction paths of Guangdong's sports, culture, and tourism industry ecosystem under the regional coordinated development strategy. The research posits that Guangdong's steady construction of this ecosystem is a practical reflection of resolving regional development imbalances and responding to the macro spatial pattern optimization strategy. Its theoretical connotation is mainly reflected in the systematic coupling of cross-border heterogeneous elements and the cross-spatial reconstruction of value networks. Addressing the phased realistic dilemmas currently faced by Guangdong in advancing this initiative—such as administrative friction in cross-regional governance mechanisms, data and infrastructure shortcomings in factor mobility, and the need to enhance internal industrial division and collaborative innovation capacity—this paper explores a composite dynamic mechanism superimposed by the external drive of institutional innovation, the endogenous momentum of digital technology empowerment, and the objective traction of evolving market demands. Based on this, the study proposes reconstruction paths with certain academic exploratory value and practical reference significance, spanning from reshaping the cross-regional collaborative governance system to alleviate administrative division restrictions, advancing the interconnection of regional infrastructure to promote factor flow, deepening internal industrial division and collaboration to explore differentiated development, and shaping a comprehensive regional brand IP matrix to enhance cultural soft power. This aims to provide theoretical reference for Guangdong Province in advancing cross-border industrial synergy and constructing a regional industrial ecosystem.
Analysis of the Production Planning Process for Midea Air Conditioning Products Based on Flexible Manufacturing
As intelligent manufacturing and flexible production become increasingly important in the manufacturing industry, the design of scientific, efficient and flexible production plans has become essential for improving operational efficiency and customer responsiveness. Taking Midea's air conditioning products as the research object, this paper examines the formulation process, hierarchical structure, supporting information systems and adjustment mechanisms of production planning. Based on flexible manufacturing theory, it analyzes planning strategies for a product system characterized by multiple varieties, multiple models and seasonal demand fluctuations. The analysis shows that Midea's production planning process has formed a relatively complete closed loop composed of demand forecasting, master production scheduling, medium and short term scheduling, execution monitoring and feedback adjustment. Information systems such as ERP, MES and APS provide an important technical basis for flexible planning. However, problems remain in demand forecasting accuracy, cross departmental coordination, supplier response and the timeliness of plan adjustment. This paper proposes optimization measures involving intelligent forecasting, system integration, supplier collaboration and rapid on-site response. The findings provide practical implications for production planning in large scale home appliance manufacturing enterprises.
Analysis of AI-Empowered "New Liberal Arts + OBE" Teaching in Auditing Courses
In light of the requirements of The Times for new liberal arts to serve national strategies and social development, undergraduate courses in auditing have long faced "four difficult problems": the difficulty in effectively crossing the knowledge barriers of related disciplines, the difficulty in deeply integrating ideological and political education with professional courses, the difficulty in truly constructing practical teaching case scenarios, and the difficulty in implementing output-oriented education (OBE) throughout the entire process. It has severely restricted the effectiveness and advancement of the "new liberal arts +OBE" teaching. This paper explores the deep reform and reconstruction of modern AI-enabled auditing course teaching and constructs the "one two three four" "new liberal arts +OBE" teaching model of auditing course. In terms of teaching concepts, achieve "new liberal arts +OBE" leading the way; In terms of teaching methods, achieve empowerment through the "two-wheel drive" of teachers, students and large AI models; In terms of teaching content, achieve the integration of disciplinary connections and the convergence of ideological and political education in courses and practical cases in new liberal arts teaching; In terms of teaching methods, achieve "four-way integration" throughout the OBE process. Make full use of large AI models, implement individualized teaching and closed-loop continuous improvement of OBE, enhance the quality of teaching output of the auditing course, ensure that the course teaching ADAPTS to the evolution of the new liberal arts era, and cultivate top-notch talents in modern economic management.
From Market Efficiency to Firm Valuation: The Role of Digital Finance
With the penetration of the digital technology into the financial sector becoming increasingly pervasive, most of the scholarly work has centered on the way this change alters financial service supply models, but have not considered its serious impact on the capital markets and the value of listed companies. With the help of the PKU-DFIIC, A-share listed companies financial report, and exchange trading data, this paper investigates the relationship among these three factors, i.e., the development of digital finance, the efficiency of the market and the valuation of companies. Built upon the consensus and gaps within the current literature it takes apart what digital finance really does in practice regarding information transfer, capital movement and resource distribution and outlines the whole road of how enhanced market efficiency is transmitted to company value. Research has found that digital finance can mitigate information barriers, optimize the overall trading environment, and alleviate the problem of firm value mismatch by improving financing conditions and governance mechanisms. Firms of different sizes and property rights have varying abilities to capture the benefits from digital finance. By analyzing the limitations of the industry reality, this paper provides actionable insights for optimizing the construction of the capital market and managing firm value.
The Quality of Teacher-Student Interaction and University Students’ Self-Efficacy
As a core variable influencing university students’ learning engagement, academic achievement and mental health, the development of self-efficacy is closely linked to the quality of teacher-student interaction in the classroom. Drawing on social cognitive theory, this paper systematically analyses the connotations and dimensions of the quality of teacher-student interaction, and explores four core pathways through which it influences university students’ self-efficacy: verbal persuasion, vicarious experience, direct experience of success, and emotional arousal. Building on this, the paper further distinguishes the differential effects of four interaction types—supportive, challenging, egalitarian, and feedback-oriented interactions—on self-efficacy, and proposes teaching strategies to enhance the quality of interaction in order to strengthen students’ self-efficacy. Research indicates that high-quality teacher-student interaction not only directly enhances students’ self-efficacy but also produces lasting effects through mechanisms such as establishing a safe psychological learning environment, providing precise demonstrations of learning strategies, and promoting positive shifts in students’ attributional styles. This paper provides a theoretical basis for promoting students’ psychological development through the optimisation of teacher-student interaction in higher education practice.
Accounting System Convergence and Enterprise Cross-border Investment Efficiency in Countries Along the Belt and Road
Against the background of the in-depth advancement of the "Belt and Road" (B&R) Initiative, cross-border direct investment (CBFI) has become a core driver of economic cooperation among countries along the route. However, significant differences in accounting systems among these countries have exacerbated cross-border information asymmetry, thereby restricting the improvement of investment efficiency. Taking panel data of 48 countries along the B&R from 2015 to 2023 as the research sample, this study measures the convergence degree of national accounting standards with International Financial Reporting Standards (IFRS) using the adoption degree and clause similarity scoring method. It empirically tests the impact of accounting system convergence on enterprise CBFI efficiency through panel regression, and explores the mediating role of information asymmetry, as well as the moderating effects of cultural differences, legal environment, and national governance level. The results show that: (1) The IFRS convergence level of countries along the B&R has obvious regional differences, generally at a medium to low level; (2) Accounting system convergence can significantly alleviate cross-border information asymmetry, thereby positively improving enterprise CBFI efficiency; (3) Cultural differences have a negative moderating effect on the positive impact of accounting convergence on investment efficiency, while a sound legal environment and high national governance level can positively strengthen this effect. Based on the research conclusions, this study puts forward targeted policy suggestions for promoting regional accounting coordination along the B&R and improving the efficiency of enterprise cross-border investment, which provides theoretical and practical references for the sustainable development of B&R cross-border investment and the integration of global accounting systems.
Cross-border direct investment efficiency
Mechanisms and Effects of Artificial Intelligence on New Quality Productive Forces in New Energy Vehicle Firms: Evidence from the Yangtze River Delta
Artificial intelligence is increasingly recognized as an important driver of firms’ new quality productive forces. Based on panel data of new energy vehicle firms in the Yangtze River Delta from 2001 to 2023, this paper constructs firm-level indicators of artificial intelligence and new quality productive forces, and examines the impact of artificial intelligence on the new quality productive forces of new energy vehicle firms and its underlying mechanisms. The results show that artificial intelligence significantly promotes the growth of new quality productive forces in new energy vehicle firms, and this conclusion remains robust after addressing endogeneity concerns and conducting robustness checks. In addition, R&D expenditure does not constitute a significant mediating channel, although its negative path coefficient suggests a possible short-term adjustment effect. This indicates that the expansion of R&D funds does not necessarily translate immediately into improvements in firms’ new quality productive forces. Heterogeneity tests show that the promoting effect of artificial intelligence is more pronounced in Jiangsu and Zhejiang and among small-sized enterprises. Mechanism tests provide empirical evidence that artificial intelligence affects firms’ new quality productive forces through the optimization of R&D personnel structure and the improvement of innovation output.
Green Reverse Logistics for Closed-Loop Supply Chains of NEV Power Batteries: A Case Study of BYD
Grounded in green logistics and reverse logistics theories, and incorporating the framework of closed-loop supply chain (CLSC) theory, this study systematically examines the current state of green reverse logistics management within China’s power battery recycling system for new energy vehicles. Taking BYD Auto as a case study, it provides an in-depth analysis of critical challenges related to recycling network efficiency, hazardous material logistics safety, and the collaborative functioning of the CLSC. The findings reveal that a fragmented recycling network layout, pronounced safety risks in logistics operations, and the limited processing capacity of single-brand closed-loop systems severely constrain both recycling efficiency and environmental performance. In response, this paper proposes a set of optimization strategies: the construction of a three-tier collection network comprising “community collection points, centralized recycling centers, and regional treatment bases”; the promotion of low-carbon practices in packaging, transportation, and warehousing; and the establishment of cross-brand battery recycling alliances. The study aims to enhance the operational efficiency and safety of green reverse logistics, facilitate the resource-based circular utilization of power batteries, and provide both theoretical support and practical guidance for developing a highly efficient, environmentally sound, and sustainable closed-loop recycling system for the NEV industry.
Practical Pathways and Challenges of Energy Law and Social Equity
Energy is a fundamental condition for modern economic activity, technological progress, and social life. Its development affects not only productivity and industrial transformation but also the distribution of opportunities, risks, and welfare among different regions and social groups. In the process of energy production, distribution, and consumption, problems such as energy poverty, unequal access to clean energy, uneven participation in decision-making, and unequal exposure to environmental burdens remain prominent. These problems make social equity an essential objective of energy law and energy governance. Based on energy justice theory and social equity theory, this paper analyzes the relationship between legal frameworks, energy management, and social equity. It discusses international and domestic energy governance frameworks, examines practical pathways for reducing energy poverty, improving public participation, and allocating environmental responsibility, and identifies challenges related to regional applicability, market coordination, policy implementation, and regulatory effectiveness. The study argues that a fairer energy system requires more precise subsidy policies, stronger infrastructure support for disadvantaged regions, better coordination between market mechanisms and public-interest objectives, and more transparent and participatory regulatory arrangements. The paper provides theoretical support and practical suggestions for promoting social equity in energy transition and for building a more inclusive, low-carbon, and sustainable energy governance system.
Research on the Integrated Development Pathways of Cross-border E-commerce and Characteristic Industrial Belts Based on an Ecosystem Model
Against the backdrop of the escalating China-US trade war and the accelerated restructuring of global supply chains, the integrated development of cross-border e-commerce and characteristic industrial belts has become an important pathway to respond to external shocks and promote high-quality regional economic development. This study integrates business ecosystem theory and the Analytic Network Process (ANP) to construct a cross-border e-commerce ecosystem model comprising diverse populations, internal factors and external environment. Through Grounded theory and expert interviews, key internal factors and external environment influencing the integration of cross-border e-commerce and characteristic industrial belts have been identified. The ANP model quantifies the impact weights of each factor, revealing that credit risk management and platform services are the most critical driving factors. This study proposes policy recommendations including strengthening credit risk management and compliance capabilities, upgrading platform services and digital supply chains, promoting brand transformation of industrial belts, and deepening industry-education integration to cultivate composite talents. These findings provide theoretical references and decision-making support for regions with high foreign trade dependence to cope with trade frictions and achieve industrial belt transformation and upgrading.
AI-Driven Media Agenda Setting and Public Policy Response: Cases from Chinese Grassroots Governance
Generative artificial intelligence is reorganising media agenda setting, which is, in turn, shaping public policy response in China. This paper examines how existing response mechanisms adapt as public issues are increasingly shaped by algorithmic recommendation, short-video circulation, and AI-assisted communication. Using official documents, policy materials and examples from grassroots governance, it argues that AI has the potential to facilitate early issue detection, aggregate widely dispersed public concerns, and thus make response processes more data-sensitive. However, it is capable of splintering information, raising emotional content, directing attention to topics the platform traffic logic prefers, rather than public importance. The author contends that the fundamental constraints to the state of the policy response currently are not technical, but structural, with weak precision, incoherent interdepartmental cooperation, and inadequate follow-up and longer-term correction as the main limitations. What is, then, important is not just the use of AI, but how it is integrated into institutional practice. A more effective response relies on a framework linking monitoring, differentiated handling, coordination, and accountability.
Platform Economy, Data Asset Valuation, and Risk Governance: A Framework for Analysis and Response
The platform economy has positioned data as a critical production factor, yet data asset valuation faces systemic risks that remain inadequately governed. This paper develops an integrated framework addressing three questions: What distinctive risks characterize platform-based data valuation? How do these risks originate? How can an effective governance framework respond? The coupling of platform characteristics—network effects, multi-sided markets, data-driven operations—with data asset features—non-rivalry, value uncertainty, property ambiguity—generates a distinctive risk spectrum across the valuation process. These risks stem from interacting technological, economic, and institutional factors that reinforce one another. Drawing on collaborative governance theory, we propose a multi-actor framework engaging government, platforms, users, and third parties in differentiated but coordinated roles. Game-theoretic analysis reveals that incentive-compatible mechanisms are essential for aligning private interests with public goals. The framework integrates risk diagnosis with governance response, offering theoretical contributions and practical implications for stakeholders navigating data-driven value creation.
Research on the Formation Mechanism of New Quality Productivity from the Perspective of Context: a Longitudinal Case Study Based on XAG Company
Promoting the development of emerging technologies by contexts has become an important part of China's industrial policy. Research on the formation mechanism of new quality productivity is of great significance for the application of emerging technologies. Based on the pioneering innovation of XAG company in agricultural plant protection UAV, the exploratory case study was carried out, and the formation mechanism of new productivity with the logic of "Contexts discovery of emerging technologies - Adaptation of emerging technologies to contexts - Iteration of major functions of emerging technologies - Iteration of secondary functions of emerging technologies - Ecological development of emerging technologies" was summarized. The research finds that the promotion and application of emerging technologies depend on finding appropriate contexts for them, and emerging technologies have competitive advantages in these contexts; The prerequisite for the application of emerging technologies in the scene is that its main functions can meet the needs of the scene and are constantly upgraded, and then its secondary functions are upgraded, and finally the ecological application of emerging technologies is realized. The research provides a theoretical basis and practical reference for the research and development of emerging technologies for the scene.
Spatio-temporal Patterns and Driving Mechanisms of Coupling Coordination Between Urban Resilience and Low-Carbon Development in the Yellow River Basin
Against the dual backdrop of intensifying global climate change and the deepening of Sustainable Development Goals, the synergistic advancement of low-carbon transition and resilience building has emerged as a critical pathway for the international community to address complex environmental risks. This study constructs a comprehensive evaluation indicator system for urban resilience and low-carbon development in the Yellow River Basin. By employing the entropy-weighted TOPSIS model and the coupling coordination degree model, it quantifies the synergy level between urban resilience and low-carbon development in the Yellow River Basin from 2006 to 2021 and reveals its spatio-temporal evolution characteristics. Furthermore, Geographic Detector is utilized to identify key driving factors, and finally, the Spatial Durbin Model is applied to explore their spatial effects. The results indicate that from 2006 to 2021, the overall urban resilience level in the Yellow River Basin exhibited a fluctuating upward trend, displaying a spatial gradient pattern where the lower reaches surpass the middle reaches, which in turn exceed the upper reaches. Low-carbon development demonstrated phased acceleration, although the energy transition lagged, with a spatial pattern characterized as "high in the east and low in the central and western regions." The coupling coordination degree between the two increased from 0.29 to 0.45, with regional disparities widening; the lower reaches experienced the fastest improvement and formed high-value agglomeration areas, the middle reaches showed accelerated catch-up growth, while progress in the upper reaches remained sluggish. The effect of the "Low-Carbon City" pilot policy initially declined and subsequently increased, exhibiting siphonic spillovers. Gross Domestic Product and fiscal expenditure emerged as the most dominant driving factors, with the synergy between economy and resources constituting a key impetus. The spatial spillover effects of various factors differ significantly across the upper, middle, and lower reaches as well as among agglomeration types, and the interaction effects of paired factors are substantially stronger than those of single factors. Therefore, systematic synergistic governance represents a crucial pathway for enhancing the level of coupling coordination between urban resilience and low-carbon development in the Yellow River Basin.
Financial Forecasting Using Time Series Models: Evidence from iFlytek
A financial analysis of iFlytek, a bellwether in China's artificial intelligence industry, reveals that while the company's assets have been consistently expanding, its profitability has been on a continuous decline in recent years. Therefore, this paper attempts to apply time series models to forecast the company's net profit for the period 2025–2027, aiming to provide decision-making insights for both investors and management.
Research on the Reform of Economics Curriculum Teaching under the Background of Artificial Intelligence
With the rapid advancement of Artificial Intelligence (AI) technology and the continuous restructuring of the digital economy, the traditional economics teaching system can hardly meet the requirements of talent cultivation and disciplinary development in the new era, confronting prominent issues including the disconnection between theory and practice, rigid teaching models, and backward application of AI technology. Based on modern educational theories such as personalized learning and industry-education integration, and considering the abstract, empirical, and applied characteristics of economics courses, this paper systematically examines the advantages and transformative opportunities of AI in economics teaching. It thoroughly elaborates on the inherent logic and practical necessity of economics teaching reform in the context of AI, constructs a systematic reform path of "goal reconstruction—system optimization—model innovation—practice enhancement—evaluation reform," and puts forward supporting measures from four dimensions: technology, faculty, resources, and students. Guided by the construction of new liberal arts, this research enriches the theoretical system of economics teaching reform, provides operable practical references for the intelligent transformation of university economics courses, facilitates the in-depth integration of economics teaching and AI technology, cultivates compound economic talents with data thinking, practical capabilities, and innovative literacy, and highlights the disciplinary value and contemporary mission of economics in "applying knowledge to practical use."
Economics Curriculum Curriculum Teaching
Research on Typology Identification for Low-Carbon Development of Rural Settlements Based on the “Morphology-Size-Function” Framework: A case study of Longxi County
Exploring the spatial configuration of rural settlements for low-carbon development is of great significance for addressing global climate change and promoting sustainable urban-rural transitions. It also constitutes a critical component in achieving China’s “Dual Carbon” goals. Existing studies predominantly focus on the singular dimensions of morphology, size, or function, which limits their capacity to address the complex demands of systemic decarbonization in rural areas. Taking Longxi County, a typical loess hilly-gully region on the Loess Plateau, as a case study, this research constructs a three-dimensional analytical framework integrating “Morphology, Size, and Function”. By employing spatial analysis, K-means clustering, this paper examines the evolution of rural settlements from 2000 to 2020. The results indicated a trend of agglomerative restructuring in settlement morphology, evolving from scattered points to clustered patches. Settlement sizes were characterized by polarization towards large villages and decline of small ones, while functions transitioned from production-dominated to diversified. Both total carbon emissions and emission intensity increased significantly, forming "high-carbon corridors" along transportation arteries and "high-carbon poles" in valley areas. M₂-S₁-F₄ and M₃-S₁-F₄ types demonstrated relatively superior low-carbon performance, whereas M₂-S₁-F₂ and large-scale settlements exhibited higher emissions.
Research on Multi-Actors' Interaction and Value Co-Creation Driven by Corporate Venture Capital from the Perspective of Symbiosis Theory
Corporate venture capital is a window for incumbents to acquire new technologies, and it is also a key force to promote the growth of new ventures, the birth of unicorns and industrial innovation. Combined with the research status and development trend of CVC at home and abroad, the symbiotic unit, symbiotic relationship and symbiotic environment of symbiosis theory are embedded into the practice of corporate venture capital, aiming to build a multi-actors interaction mode driven by corporate venture capital. On this basis, the CVC driven multi-actors value co-creation integration system is built from the perspective of value creation, and the path selection of multi-actors value co-creation is proposed from the macro-level to create the "sensor + adapter" between the enterprise and the environment, the meso level to build the "channel" for the exchange of resources between enterprises, and the micro-level to improve the cognitive ability and creativity of individuals/teams. All these are to improve the ecological construction of equity investment market and promote the harmonious development of large and medium-sized enterprises.
Digital Transformation and Enterprise Management Efficiency: Challenges, Paths, and Practical Implications
In the context of the rapidly evolving digital economy, digital transformation has emerged as a critical strategic priority for enterprises seeking to enhance management efficiency and sustain competitive advantage. Despite the growing recognition of its importance, many enterprises continue to struggle with effectively integrating digital technologies into their management systems, resulting in significant gaps between technological investment and actual management outcomes. This paper examines the relationship between digital transformation and enterprise management efficiency from the perspective of business administration. By employing literature analysis and theoretical discussion, this study systematically investigates how digital transformation influences key management dimensions, including information transmission, resource allocation, decision-making quality, and organizational flexibility. Furthermore, the paper identifies five major challenges that enterprises encounter during digital transformation, namely, the lack of a clear digital strategy, insufficient digital talents and capabilities, organizational resistance and cultural barriers, weak data governance and information security, and the imbalance between technology investment and management return. On this basis, a set of practical paths is proposed to guide enterprises in improving management efficiency through digital transformation, encompassing strategic planning, talent development, organizational optimization, data governance enhancement, and performance evaluation mechanism construction. The findings suggest that digital transformation, when effectively aligned with management innovation, can substantially improve enterprise management efficiency and support sustainable organizational development. This study contributes to the existing literature by offering an integrated framework that connects digital transformation practices with concrete management improvement strategies, providing practical implications for both enterprise managers and economic management researchers.
The Impact of Climate Policy Uncertainty on Product Prices in Futures Markets
As climate issues become more frequent, the government's macro-climate policy regulation plays an increasingly important role in financial markets. Based on this, this article starts from four types of futures products in the futures market: food, agricultural products, energy, and chemicals, and explores the potential effects caused by climate policy uncertainty at the level of climate transition risks. The research results show that climate policy changes in the current period are significantly positively correlated with the price index of grain, agricultural products, and energy futures products, and are significantly negatively correlated with the price index of chemical futures products. These results are still robust after lag one period and adding control variables. Climate policy uncertainty has a great impact on futures product prices.
Machine Learning Methods for Bank Term Deposit Subscription Prediction
To address the problem of customer purchase behavior prediction in bank term-deposit services, this paper develops a machine-learning-based prediction framework using the bank marketing dataset. First, the raw data are processed through missing-value inspection, categorical variable encoding, relevant feature selection, imbalance handling, and data standardization. Then, three models, namely Random Forest, Logistic Regression, and LightGBM, are constructed to analyze customer attributes, marketing-related attributes, and economic background attributes. Experimental results show that, among the three models, LightGBM achieves the best overall performance, with an accuracy of 91.95% and a test F1-score of 60.22%, outperforming both Random Forest and Logistic Regression. Further analysis indicates that features such as call duration and campaign frequency have strong influence on customer subscription decisions. The results demonstrate that machine learning methods can effectively improve the accuracy of identifying potential term-deposit customers, and provide useful data support for precision marketing and resource optimization in banking services.
Patient Capital and the Governance of Inefficient Investment and Overcapacity: A Factor Allocation Perspective
Inefficient investment and persistent overcapacity remain central concerns in modern economies, particularly in contexts where capital markets and corporate governance structures are imperfect. This paper examines the role of patient capital in mitigating these problems from the perspective of factor allocation. Rather than treating inefficient investment as a purely behavioral or agency-driven phenomenon, the analysis situates it within a broader framework of resource misallocation within firms. Patient capital, characterized by long investment horizons and tolerance for delayed returns, is argued to influence firms not only by alleviating financing constraints but also by reshaping internal allocation mechanisms and governance structures. Building on existing empirical and theoretical insights, the paper develops a mediation framework in which factor allocation efficiency serves as the transmission channel linking patient capital to investment outcomes. The analysis suggests that patient capital reduces both overinvestment and underinvestment by stabilizing expectations and altering the criteria through which resources are deployed. The findings contribute to the literature by integrating capital structure, governance, and allocation efficiency into a unified analytical perspective.
Analysis of Land Use Change in Sichuan Province from 2000 to 2020
Against the background of accelerated urbanization and increasing demand for ecological protection, land use change has significant impacts on regional ecological security and sustainable development. Based on land use data of Sichuan Province for the years 2000, 2010, and 2020, this study systematically analyzes the characteristics of land use change from the perspectives of temporal variation, type conversion, and spatial patterns by integrating the land use transition matrix and the standard deviational ellipse method. The results show that from 2000 to 2020, the land use structure in Sichuan Province underwent significant adjustments, with forest and built-up land continuously increasing, while cropland and grassland showed a declining trend. Land use conversion was mainly characterized by mutual transformations among cropland, grassland, and forest, accompanied by the conversion of cropland to built-up land, presenting an overall pattern of “cropland shifting toward ecological land and built-up land.” The spatial distribution pattern was strongly constrained by topographic conditions, forming a basic pattern of “plateau forest-grassland, basin agriculture, and urban agglomeration,” with the overall structure remaining relatively stable over the 20-year period. The spatial distribution directions of different land use types were generally stable, and the migration of the centers of gravity was limited. Among them, cropland exhibited relatively significant changes, while built-up land showed a continuous expansion trend. The findings of this study can provide a scientific reference for optimizing regional land use allocation and ecological protection.
Exploring the Path of Platform Vehicle Source Display and Consumer Trust Building under the Evolution of Used Car Trading Rules in the United States
This article reviews the historical evolution of regulations related to used car sales in the United States, analyzes how these regulations affect the presentation of vehicle information on online used car platforms, and discusses how platforms can establish and improve consumer trust within this legal framework. The author believes that with the continuous improvement of the legal system and business practices of the federal and state governments in the United States, it is an important external driving force to promote the reform of platform information disclosure and standardization. Consumer trust maintenance is a comprehensive and systematic process that includes information quality, platform guarantee measures, credit evaluation system, and social supervision. The article aims to provide a theoretical perspective for understanding the normative development of the US used car online market and to provide some reference for the healthy and benign development of China's used car online market through the study of the correlation between rule changes, innovative presentation methods, and the formation of trust relationships.
Research on Operational Risk Management of Commercial Banks Amid the Development of Financial Technology
The deepening of digital transformation and the deep integration of financial technology and commercial bank management have not only optimized business processes and improved service quality and efficiency, but also presented new characteristics of increased concealment and diversified causes of operational risks. Traditional operational risk management frameworks are facing adaptability challenges. Based on the regulatory rules of the National Administration of Financial Regulation (NAFR), authoritative industry statistical data, and the practical application of financial technology in state-owned large banks, this article systematically analyzes the dual impact of financial technology on bank operational risk, sorts out the existing weaknesses and underlying causes of risk management, and proposes adaptive optimization solutions. Practice has shown that although financial technology effectively reduces traditional risks related to manual operations, it also gives rise to new risks such as data security and algorithm model bias. In addition, the insufficient supply of interdisciplinary talents and the lagging iteration of internal control systems continue to constrain the effectiveness of risk control. This study can provide practical references for commercial banks to improve their operational risk management system and strengthen their risk prevention and control capabilities through the use of financial technology, and help banks achieve stable operations in digital transformation.
Construction of Cross-cultural management Strategies for Corporate Social Responsibility in Global Operations
The deepening of economic globalization has made corporate social responsibility a key support for multinational enterprises to foster international competitiveness. The intensification of management conflicts caused by cultural differences has become the core obstacle to the effective implementation of corporate social responsibility. Based on Hofstede's cultural dimension theory and combined with practical cases of Chinese enterprises' overseas operations and research data from the World Business Council for Sustainable Development, this article analyzes the mechanism of cultural differences on corporate social responsibility practice. From five dimensions of cultural adaptation optimization, cross-cultural communication upgrading, professional talent cultivation, dynamic integration of standards, and performance evaluation improvement, a cross-cultural management framework for corporate social responsibility in a globalized business scenario is established. Field research and data verification confirm that power distance and collectivism/individualism exert the most prominent impact on the implementation quality of CSR. The flexible balance between localization adaptation and globalization standards can promote a 35.2% increase in the success rate of corporate social responsibility projects. This study provides viable approaches for multinationals to address cross-cultural corporate social responsibility management difficulties and achieve long-term operation.