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.
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.
Copyright (c) 2026 International Journal of Global Economics and Management https://creativecommons.org/licenses/by-nc/4.0
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.
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.
A Study on the Optimization of Company K’s Finished Goods Warehouse Layout Based on SLP
With intensifying market competition and rising logistics costs, warehouse layout optimization has become a critical factor for manufacturing enterprises to improve operational efficiency. This paper takes the finished goods warehouse of Company K, a garment manufacturer, as its research subject. Addressing issues such as low operational efficiency, circuitous handling routes, and insufficient equipment utilization, the study proposes a warehouse layout optimization method that integrates System Layout Planning (SLP) with Flexsim simulation. The study first analyzed the operational processes and current status of functional zones in the finished goods warehouse through on-site research, clarifying the interrelationships between logistics and non-logistics factors. Second, the SLP method was employed to quantitatively assess the logistics intensity and non-logistics associations between functional zones, establishing a comprehensive relationship analysis model to generate two optimized layout schemes. Finally, a three-dimensional dynamic model was constructed using the Flexsim simulation platform to compare and validate the original and optimized layouts across four dimensions: handling distance, logistics throughput, equipment utilization, and operation cycle. Simulation results indicate that the optimized Scheme 2 demonstrates significant improvements over the original scheme across key metrics: total handling distance was reduced by 25.2%, outbound volume per unit time increased by 20.3%, forklift utilization decreased by 21.8%, and overall operational efficiency improved by 21.8%. This study not only provides Company K with a practical warehouse optimization solution but also offers a methodological reference for warehouse layout optimization in similar manufacturing enterprises, validating the practical value of combining SLP with discrete-event simulation in the field of facility planning.
Research on Dual-Channel Supply Chain Decisions in Live-Stream E-Commerce under Different Commission Contracts
This paper examines contract choice and pricing decisions in a dual-channel supply chain where a manufacturer sells products through both online direct sales and influencer live-streaming. We develop two Stackelberg game models—a pure commission contract and a commission-plus-service-fee contract—and derive equilibrium solutions via backward induction. We analyze how streamer influence, channel spillover effects, and service fee intensity shape channel pricing, streamer marketing effort, and supply chain profitability. Results show that stronger streamer influence significantly raises channel prices and streamer marketing effort. The commission-plus-service-fee contract outperforms the pure commission contract in motivating streamer effort and lifting channel prices, yet the service fee has an optimal range: an excessively high service fee reduces total supply chain profit. A positive channel spillover effect enhances the profits of all supply chain members and improves system performance. These findings offer theoretical and practical insights for contract design, pricing, and coordinated operations in live-stream e-commerce supply chains.
Exploration of Human–Robot Collaborative Two-Sided Assembly Line Optimization Based on Workload Balancing
In the context of Industry 4.0, collaborative robots, as a key enabler of intelligent manufacturing, are increasingly being introduced into assembly environments, forming a novel human–robot collaborative paradigm with workers. This study focuses on the optimal allocation of human–robot collaborative assembly tasks in two-sided assembly line scenarios. A systematic investigation is conducted on assembly line balancing modeling methods incorporating both physical and cognitive workload evaluation mechanisms. On this basis, a multi-objective optimization model is developed with production cycle time, cost, working time, and workload balance as the primary objectives. Furthermore, the conventional Migrating Birds Optimization (MBO) algorithm is extended to a multi-objective framework and enhanced with adaptive improvement strategies to improve solution effectiveness and distribution. The results provide theoretical support and methodological insights for developing human-centric and efficiency-oriented collaborative production systems.
Spatiotemporal Dynamics and Obstacle Factor Diagnosis of Social-Ecological System Resilience in Qilian Mountain National Park
Scientifically assessing social-ecological system resilience (SESR) in national parks in alpine-arid regions is crucial for to balancing ecological conservation with sustainable development. As a vital ecological security barrier and a sensitive zone for human-nature coupling in western China, the Qilian Mountain National Park (QMNP) necessitates a systematic research of its SESR trends and driver factors. Based on the social-ecological system (SES) framework, this study constructed a multi-criteria indicator system encompassing social, economic, and ecological dimensions. Employing the CRITIC method, three-dimensional Kernel Density Estimation, and the Obstacle Degree Model, we analyzed the temporal evolution, spatial differentiation, and key obstacle factors of SESR in QMNP from 2010 to 2024. The results show that: (1) The comprehensive social-ecological system resilience index (SESRI) of QMNP steadily increased from 0.3645 to 0.4308 from 2010 to 2024, exhibiting a consistent upward trajectory. (2) The spatial pattern evolved from an initially low-level homogeneity to a pronounced "high-west, low-east" differentiation, featuring a high-resilience cluster in the northwest driven and a resilience-lagging zone in the southeast con-strained."(3) Population density, per capita GDP, and net primary productivity (NPP) persisted as the core obstacle factors inhibiting the enhancement of SESR. This study provides a scientific basis and decision-making reference for hierarchical adaptive management and the optimization of sustainable development pathways for national parks in alpine and arid regions.
A Review of Intelligent Optimization Algorithms for Oilfield Development
To identify the most suitable oilfield development strategy for maximizing energy supply or economic returns, optimization of oilfield development remains one of the most critical challenges in closed-loop reservoir management. In recent decades, with the advancement of artificial intelligence technologies, intelligent optimization algorithms have been increasingly applied to improve the efficiency and accuracy of optimization outcomes in oilfield development. This paper provides a comprehensive review of intelligent optimization algorithms applied to oilfield development optimization problems. It covers several key topics within this domain, ranging from the fundamental components of such problems—decision variables, objective functions, and constraints—to various algorithmic approaches developed from different perspectives and for different types of optimization problems.
International Tax Planning Case Study: A Analysis of Alibaba
Driven by economic globalization and digitalization, the cross-border e-commerce industry has developed rapidly. As an industry benchmark, Alibaba's international tax planning practices hold significant research value. This paper takes Alibaba as the subject to analyze the implementation paths, core elements, existing challenges, and legal basis of its tax planning. The research finds that Alibaba achieves tax optimization and improved cash flow by establishing subsidiaries in low-tax jurisdictions, building multi-tiered equity structures, employing transfer pricing and cost-sharing strategies, and fully leveraging tax incentives. Its approach is centered on legal compliance, business-tax synergy, and data informatization, while also facing challenges such as disagreements over tax residency determination. Relevant experiences can serve as a reference for cross-border e-commerce enterprises undertaking international tax planning.
Research on the Global PNG Trade Community Analysis and The Current Situation of Our Country's PNG Imports
Against the backdrop of global energy green and low-carbon transition and the "Dual Carbon" target, PNG, as a low-carbon clean energy source, has become increasingly prominent in the global energy consumption market. Research on the global PNG trade network contributes to an in-depth understanding of the current PNG trade pattern, clarifies China’s position in the global PNG system, and provides strategic support for China’s PNG supply security and energy security. This study employs social network analysis to classify countries involved in the global PNG trade into different communities. It investigates the agglomeration degree of supply and receiving stations within the same community and the formation mechanism of communities, and analyzes the community characteristics where China is located. The current situation of China’s PNG import trade is examined from two dimensions: trade dependence index and import channels. The results demonstrate that: Firstly, community analysis reveals that geographical proximity constitutes the dominant factor influencing the global PNG trade. China acts as a leader in the Asia-Pacific community and holds a leading position in imports. Nevertheless, potential risks including geopolitical tensions, price volatility, and transportation security warrant vigilance. Secondly, the analysis of PMI and import channels indicates that China’s PNG imports maintain a steady growth trend, and the structure of import channels is gradually moving toward diversification. Accordingly, policy recommendations are proposed to stabilize China’s PNG supply and enhance the security capacity of national energy supply by adhering to the dual principles of expanding supply sources and controlling demand.
Public Participation-Based Environmental Regulation and Urban Green Innovation: Evidence from Chinese City-Level Panel Data
This study examines whether public participation-based environmental regulation promotes urban green innovation in China. Using a city-level panel of 2,488 observations for 2013–2021, the paper estimates two-way fixed-effects and dynamic specifications in which green innovation is measured by ln (green patent grants + 1) and the core explanatory variable is the one- to three-year lagged average of the logged public-participation indicator. The preferred dynamic model yields a positive and statistically significant coefficient of 0.1083, suggesting that stronger public participation is associated with higher green patent output after controlling for city effects, year effects, and innovation persistence. Mechanism tests indicate that the environmental-governance channel is better supported than the government-response channel. The positive association is also stronger in cities with higher openness and larger environmental expenditure shares. Overall, the evidence suggests that public participation can complement formal environmental governance by strengthening monitoring and improving the credibility of green upgrading, although the identification remains observational rather than quasi-experimental.
Low-Carbon Development Dilemmas and Differentiated Pathways for Non-Core Cities in China's Chengdu–Chongqing Economic Zone: A Case Study of Nanchong
China's dual-carbon strategy calls for all cities to formulate carbon peaking action plans, yet the academic literature overwhelmingly focuses on megacities and core economic centers, leaving the low-carbon transition challenges facing non-core, underdeveloped cities underexplored. This paper addresses this gap by examining Nanchong, a populous yet economically peripheral prefecture-level city in the Chengdu–Chongqing Economic Zone (CCEZ), as an in-depth case study. Drawing on Gerschenkron's latecomer advantage theory and the comparative advantage framework, and using publicly available statistical data, government policy documents, and secondary literature, we construct a systematic comparison between Nanchong and the CCEZ's twin core cities (Chengdu and Chongqing) across six analytical dimensions: economic structure, carbon emission profile, energy endowment, industrial innovation capacity, green finance accessibility, and human capital. Our analysis reveals that non-core cities face a distinctive "low-carbon development trilemma" — the simultaneous pressure to industrialize, urbanize, and decarbonize — which core cities have largely resolved sequentially. However, we identify four differentiated low-carbon pathways available to Nanchong that leverage its latecomer status: (1) leapfrogging through new-energy commercial vehicle manufacturing; (2) exploiting natural gas resource endowments for a transitional "grey-to-blue-to-green" hydrogen strategy; (3) green upgrading of the traditional silk industry chain through eco-certification and cultural branding; and (4) utilizing near-zero-carbon industrial park pilots as institutional innovation platforms. We argue that non-core cities need not replicate the carbon-intensive industrialization trajectory of core cities but can pursue "curve-bending" strategies that compress the time between economic take-off and emission peaking. The findings carry implications for similar non-core cities across China's western urban agglomerations and for developing-country cities more broadly.
From the Overture to the Voice of the Universe: A Brief Introduction to the History of Western Symphonic Music
As one of the most iconic genres in Western art music, symphonic music has evolved through pivotal historical periods including the Baroque, Classical, Romantic, and Modernist eras. This study chronologically traces its development from the embryonic form of Italian opera overtures, through the foundational and maturation phases of the Viennese Classical School, to the emotional expansion and diverse evolution of national music schools during the Romantic period, culminating in the stylistic fragmentation of the 20th century. The analysis focuses on the creative characteristics and formal innovations of representative composers across historical stages, revealing how symphonic music has continuously assimilated new aesthetic concepts and techniques while preserving fundamental structural principles, ultimately evolving into a "sound universe" that embodies humanity's spiritual aspirations.
The Current Status and Insights of China's RTA Environmental Provisions
This paper systematically reviews the development status of environmental clauses in global and Chinese regional trade agreements (RTAs). At the global level, RTA environmental provisions have shown an evolutionary trend from decentralized distribution to the establishment of independent environmental chapters, and from principled provisions to legally binding provisions. China has signed 23 free trade agreements, covering various forms of environmental provisions, but there are still few agreements with special environmental chapters, and the enforcement of laws needs to be improved. Based on the current situation, this paper puts forward three enlightenments: first, take the initiative to lead and participate in the negotiation and upgrading of high-standard RTA environmental clauses; second, actively benchmark international rules and optimize the institutional environment of the domestic service industry; The third is to strategically deepen and expand the RTA network, giving priority to promoting "South-South cooperation" and rule docking with developing countries.
Exploration of New Foreign Trade Opportunities in the Reshaping of Global Supply Chain
Global industrial chains are shifting toward nearshoring, digitalization, decarbonization, and enhanced resilience, driven by geopolitical, technological, environmental, and pandemic-related factors. This is both a pressure and a new opportunity for China's foreign trade. On the basis of analyzing the main directions of global industrial chain reconstruction, this article focuses on discussing the foreign trade opportunities it holds, including localized supply chain supporting industries, digital supply chain technology and services, low-carbon and environmentally friendly product and service exports, specialized vertical markets, and cross-border service industries. At the same time, based on the actual situation of China's foreign trade enterprises, the author also provides specific and feasible strategic ideas from the perspectives of market positioning, supply chain coordination, digital transformation, brand marketing, risk compliance, etc., aiming to help enterprises find new opportunities and build new competitiveness in the changing situation, and contribute to the high-quality and sustainable development of China's foreign trade.
Exploration and Future Trends of Empowering ESG Development with Artificial Intelligence
With the global emphasis on ESG, the concept of "Environment (E) - Society (S) - Corporate Governance (G)" has also entered people's vision and been widely used, mainly to describe a company's specific practices in environmental protection, social responsibility, corporate governance, and other aspects. In recent years, artificial intelligence (AI) has shown strong performance in data analysis, deep learning, and automated analysis, bringing new possibilities and development directions to ESG. This article explores the application of AI in promoting ESG from the perspective of environmental management, social management, and enterprise management. It also discusses the main obstacles that need to be addressed, such as data availability, technical complexity, and supervision boundaries. Based on this, it proposes future development trends such as cross application of technology, standardization construction, and management mode transformation. It can be foreseen that AI technology empowering ESG will promote enterprises to achieve a value restructuring process from passive responsibility to active pursuit of sustainability, but there must be corresponding governance systems to ensure the responsible and inclusive use of these technologies.
Future Development Prospects of Green Bond Assessment
Against the macro-background of China's efforts to promote a green and low-carbon economic and social transformation and implement the dual carbon goals, green finance has emerged as a core pathway to support low-carbon development. This paper reviews the current state of research on green bonds, analyzes the challenges in their value assessment work, and integrates domestic and international research findings with market practices. It explores optimized pathways for green bond valuation and provides an outlook on future development trends. The aim is to refine the theoretical framework for green bond assessment and promote the healthy and sustainable growth of China's green finance market.
Service Quality and Client Satisfaction in Beijing Public Hospitals: An Application of the Donabedian Model
This study examined the service quality and client satisfaction of public hospitals in Beijing using the Donabedian Structure–Process–Outcome (SPO) Model as the guiding framework and the SERVQUAL dimensions as operational indicators. A quantitative descriptive–correlational design was employed, with patients from selected public hospitals serving as respondents. Results revealed that structural aspects of service quality were rated high, reflecting the success of hospital modernization and technological investments. However, process dimensions such as responsiveness and empathy scored only moderate, indicating challenges in interpersonal communication, waiting time management, and patient-centered care. Outcome measures showed moderate to high satisfaction, especially in communication and trust, but highlighted weaknesses in coordination and shared decision-making. Overall, findings confirm that while Beijing’s public hospitals have achieved strong structural modernization, process optimization remains incomplete. The study concludes that aligning structure, process, and outcome dimensions is essential to achieve sustainable service excellence and improve patient-centered outcomes.
Research on the Impact of Blockchain-Based Credible Return Information Mechanism on the Anti-Fraud Effect of Government Subsidies
Governments issuing consumer subsidies often falls prey to clever frauds that mostly work due to information imbalance left after you buy and get your hands on a thing. Bad guys do “phantom returns”, when they buy something subsidized and then claim the government’s money as a return, but don’t really send it back using fake shipping, so stores get their subsidy for nothing and can still sell the real stuff. This paper examines in detail the effect that if we were to adopt an actual working credible return information system, on such systemic scam of Government subsidy. Using the characteristics that cannot be changed, were scattered around, and could transparently see things by means of distributed ledger technology, we integrated e-commerce platforms, 3PLs, government auditors all under one roof into a cryptographic consortium network. In this article I make comparison from the recent pilots which has been researched and proved by using the data of the introduction on intelligent contract –automatic verification will greatly increase detection, prevention, and punishment of fraud. When there were less of the financial leaks there would be a lesser amount of time to do an audit, instead of after something has been found it is now during: In the end, it gives out very important theoretical framework and useful policy suggestions for government agencies wanting to make public financial stimulation projects both more economic efficient and administratively sound by using modern crypto technology in strategic ways.