Economics and Public Policy ISSN Print: 3104-4387 ISSN Online: 3104-4395 CD ISSN: 3104-4409
A Literature Review on the Green Transformation of Grain Production by farmers
The green transformation of grain production is an essential pathway for alleviating pressures on agricultural resources and environment, ensuring food security, and achieving the dual carbon goals. As the core decision-making entities in grain production, farmers’ green transformation behaviors are influenced by multiple factors and have become a frontier topic in agricultural economics research. This paper systematically reviews the literature on the green transformation of grain production by farmers. It summarizes the driving mechanisms of agricultural green production transformation from the perspectives of technological innovation, institutional synergy, market incentives, and multi-actor interaction. It analyzes the influencing factors of farmers’ green production transformation from the perspectives of individual characteristics, digital participation, industrial organization models, and external environmental factors, and proposes pathways for enhancing agricultural green transformation. The research indicates that farmers’ green transformation is a process co-driven by technological empowerment, policy regulation, market pull, social norms, and organizational leadership. However, existing research still has limitations, including insufficient identification of social interaction mechanisms in transformation behaviors and inadequate assessment of transformation outcomes. This paper provides a literature foundation and directional insights for deepening the theoretical understanding of farmers’ green transformation and optimizing policy design.
Copyright (c) 2026 by author(s) and Erytis Publishing Limited https://creativecommons.org/licenses/by-sa/4.0
A Study on the Collaborative Governance Mechanism for Electricity Aggregators Involving Multiple Stakeholders: A Perspective Based on Stakeholder Theory
As platform-based market entities that integrate distributed resources within the new power system, electricity aggregators have become a key enabler for achieving high-proportion renewable energy grid integration and flexible demand-side regulation. However, issues such as disputes over revenue distribution and high resource exit rates, which have emerged during their rapid development, stem from the heterogeneity of multiple stakeholders’ demands and power asymmetries. Existing research has focused excessively on technical optimisation and market mechanism design, whilst neglecting the governance essence of these entities.Drawing on the salience model within stakeholder theory, this paper identifies and classifies key stakeholders, including the government, grid operators, owners of distributed resources, and electricity consumers; combining this with collaborative governance theory, it analyses the causes of conflicting demands and the consequences of inefficient equilibria;thereby proposing a ‘Four-Dimensional Collaborative Governance Framework’ (comprising decision-making, incentive, risk-sharing and communication mechanisms) to achieve multi-stakeholder coordination through power redistribution, positive incentives and negative constraints, market-based risk diversification, and digital technologies such as blockchain.The empirical section takes Guangdong Province’s ‘Juhebao’ project as a case study. Through pre-post comparisons and horizontal benchmarking, it verifies that the implementation of this framework has yielded multiple Pareto improvements, including a 7.1 percentage point increase in the internal rate of return for resource owners, a 56 per cent rise in aggregators’ revenues, a reduction of 0.039 yuan/kWh in end-user electricity prices, and a decrease of nearly 13 percentage points in the resource exit rate.The study’s conclusions indicate that the four-dimensional framework is highly operational and universally applicable, providing an institutional model for the healthy and sustainable development of electricity aggregators nationwide. It also puts forward seven policy recommendations at the national, provincial and aggregator levels. This paper fills a gap in the theory and practice of multi-stakeholder collaborative governance for electricity aggregators, contributing a ‘Chinese solution’ to the development of a new electricity system.
A Review of Research on Power Battery Closed-Loop Supply Chains from the Perspective of Supply Chain Management Theory
Driven jointly by carbon neutrality strategies and the rapid expansion of the new energy vehicle (NEV) industry, the large-scale retirement of power batteries has rendered resource circulation and environmental pollution problems increasingly urgent, and the power battery closed-loop supply chain (CLSC) has accordingly emerged as a frontier subfield of supply chain management research. Adopting supply chain management theory as the analytical perspective, this paper systematically reviews domestic and international literature published between 2001 and 2025. After clarifying the theoretical foundations—circular economy theory, extended producer responsibility (EPR), transaction cost economics, and contract theory—it synthesizes research progress along six thematic dimensions: recycling channel selection, pricing and contract coordination, echelon (second-life) utilization, government policy intervention, social preference behavior, and second-hand market competition, followed by a critical assessment along the three dimensions of theory, method, and context. The review finds that the theoretical paradigm of this field has shifted from static efficiency orientation toward dynamic resilience, greening, and intelligence orientation, and that a preliminary multidisciplinary, multimethod, and multiobjective research framework has taken shape; however, problems remain prominent, including unrealistic model assumptions, the absence of dynamic evolution characterizations, superficial treatment of sustainability mechanisms, and the disconnection between digital technologies and management science. Accordingly, this paper proposes six operationalizable future research agendas—dynamic multiperiod modeling, behavioral closed-loop supply chains, the integration of digital technology and governance, supply chain resilience, multiobjective optimization under carbon constraints, and cross-chain collaborative governance—to inform subsequent theory building and practical innovation.
The Impact of Digital Technology on Agricultural Production Efficiency in Sichuan Province
This study evaluates agricultural production efficiency in 21 cities and prefectures of Sichuan Province and examines its relationship with digital technology. Output-oriented DEA-BCC/CCR models measure static efficiency, and the Malmquist index decomposes productivity change. A composite digital index covers infrastructure, digital-industry development, and digital financial inclusion. Mean comprehensive efficiency rose from 0.848 in 2011 to 0.966 in 2021. Mean total factor productivity for 2014-2021 was 1.0903 and was driven mainly by technical progress. In the controlled Tobit model, digital technology remained positively associated with production efficiency. The results support targeted investment in rural digital infrastructure, agricultural digital services, inclusive finance, and interregional coordination.
Analysis of the Impact of Internet Monopoly on the Network Environment
In recent years, the scale of China's Internet industry has continuously expanded, and cases revolving around Internet monopolies have also been increasing. Internet monopoly has become an issue that must be prioritized today. However, determining the boundaries of monopoly in the Internet industry cannot simply rely on copying the theories of traditional industries. It is necessary to discuss how to maximize the benefits of the Internet industry within benign competition. This paper observes relevant data from leading Internet enterprises in the industry, analyzes the characteristics of Internet monopolies through economic principles, and puts forward suggestions regarding China's attitude and coping policies toward Internet monopolies.
Measuring Enterprise Digital Readiness in Manufacturing: Multi-Dimensional Index Construction, Structural Heterogeneity, and Longitudinal Spatiotemporal Evolution
Accurately quantifying enterprise digital capability is fundamental to evaluating industrial modernization, yet conventional empirical inquiries predominantly rely on single-dimensional proxy variables or unweighted keyword counts, failing to capture the multidimensional integration of digital assets. Moving beyond causal regression paradigms and reductionist metrics, this inquiry develops a comprehensive, objective Digital Readiness Index (DRI) for physical manufacturing enterprises using an information-theoretic Entropy Weight Method (EWM). Grounded in multi-source text-mining disclosures and corporate balance sheets across 41,756 firm-year observations of Chinese A-share listed manufacturing enterprises spanning 2000 to 2025, the evaluation framework integrates eight discrete operational indicators across three dimensions: Technical Depth (AI, Big Data, Cloud Computing, Blockchain, and Digital Applications), Intangible Capital Endowments, and Governance Oversight. Objective entropy weighting demonstrates that specialized frontier technologies, particularly Blockchain (w=37.81%), Artificial Intelligence (w=15.95%), Big Data Analytics (w=15.93%), and Cloud Computing (w=15.66%)—constitute the primary sources of informational divergence across manufacturing firms. Longitudinal trajectory evaluation reveals a sustained upward trajectory in mean digital readiness, accelerating markedly after the 2015 macroeconomic policy inflection point. Non-parametric Gaussian Kernel Density Estimation uncovers a distinct dynamic polarization pattern, characterized by a shifting rightward distribution and an elongating upper tail. Cross-sectional decomposition establishes substantial structural disparities: high-tech sectors such as Computers and Electronics exhibit the highest mean digital readiness (DRI=16.28), whereas chemical and pharmaceutical sectors display persistent digital inertia (DRI≈4.06). Furthermore, non-state-owned enterprises (Non-SOEs) systematically outperform state-owned enterprises (SOEs) across all asset scale tiers. These findings provide an objective measurement tool and benchmark for corporate technology auditing and industrial policy calibration.
Theoretical Mechanisms and Coping Strategies of Generative AI's Impact on Employment Structural Polarization
The rapid integration of generative artificial intelligence is deeply reshaping the labor market, but existing theories of employment polarization are facing challenges in their explanatory power. This paper, based on classic task models and skills-biased technological progress theory, introduces the variable of "cognitive automation" to analyze the essential characteristics of generative AI that distinguish it from previous technological changes and its impact mechanism on employment polarization. The study finds that generative AI drives employment polarization through a three-pronged, progressive mechanism: the accelerated substitution of routine cognitive tasks constitutes a direct impact; the structural expansion of skill premiums leads to labor market restructuring; and the technological gap in occupational transitions creates a solidification effect. These three mechanisms jointly drive employment polarization from the traditional "expansion at both ends and collapse in the middle" to a new form of "cognitive layer collapse." The response strategy should target each mechanism with intervention, with the core being to narrow the adaptive gap between technology diffusion and human capital accumulation.
Systematic Reform of AI-empowered Master of International Business Education
Against the backdrop of global economic digital transformation, Master of International Business (MIB) education urgently requires systematic reform. Taking the 2023-2024 cultivation programs of 20 MIB institutions nationwide as samples, this paper uses Python jieba word segmentation and word frequency analysis to extract seven core competency objectives. On this basis, it proposes a knowledge system restructuring scheme integrating artificial intelligence technology and a "Broad-Specialized-Integrated" curriculum system, and designs an AI-driven virtual simulation practice platform and structured case library. The study shows that current MIB cultivation programs are clearly insufficient in coverage of keywords such as data analytics and AI application. The reform plan proposed in this paper can systematically improve students' technology-driven decision-making capabilities while preserving traditional international business advantages. The research provides an actionable curriculum design framework and implementation pathway for MIB educational reform.
Analysis on the Competitiveness of Traditional Chinese Medicine Industry in Anhui Province
The origins of traditional Chinese medicine (TCM) can be traced back to ancient times, boasting a profound historical heritage spanning thousands of years. In Anhui Province in particular, the development of TCM reflects a long-standing tradition and remarkable influence. In recent years, alongside the rapid growth of China’s economy, TCM—as one of the treasures of China’s traditional culture—has attracted rising attention, and market demand for TCM and its related products has increased markedly. This paper collects relevant data on the traditional Chinese medicine industry in Anhui Province, adopts the SWOT-PEST analysis method to analyze the current status of the province’s TCM industry, and then employs Porter’s Diamond Model as the theoretical framework to identify factors affecting the competitiveness of Anhui’s TCM industry. Finally, it puts forward several suggestions for the future development of the TCM industry in Anhui Province.
Cross-Domain Applications of AI in Management Decision-Making: Tourism vs. Healthcare
Artificial intelligence (AI) has increasingly become a core instrument in management decision-making across diverse institutional domains. This study examines the cross-domain applications of AI in tourism and healthcare to demonstrate that AI primarily reshapes management logic rather than serving as a sector-specific technology. Drawing on verifiable datasets and established policy frameworks, the analysis focuses on how AI supports forecasting, resource optimization, risk management, strategic planning, and governance functions in both domains. The findings show that tourism management systems use AI to predict visitor demand, optimize capacity utilization, and enhance crisis response, while healthcare management systems apply AI to support risk stratification, resource allocation, and system-level planning. Despite differences in data environments, regulatory structures, and operational risks, the functional roles of AI remain structurally similar. AI-enabled decision-making improves decision quality, efficiency, transparency, and institutional coordination in both sectors. By comparing tourism, healthcare, and urban governance contexts, this study demonstrates the transferability of AI-supported management functions across complex systems. The results highlight that AI operates as a management science tool that augments human judgment, strengthens governance frameworks, and enables data-driven decision processes. Healthcare is treated as one application case rather than the core focus of AI research, reinforcing the author's positioning as an AI management scholar. Overall, the study contributes to management science by clarifying how AI reshapes organizational decision-making logic across domains and by providing a cross-sectoral framework for understanding AI's role in contemporary governance systems.
Tax Incentives and Urban Green Innovation: Evidence from the "Replacing Business Tax with Value-Added Tax (VAT)" Reform
Tax reduction is an important measure to stimulate urban green innovation vitality. Taking the structural tax reduction policy of replacing business tax with VAT (the "VAT reform") as an example, this paper constructs a staggered difference-in-differences (DID) model based on panel data of 287 prefecture-level cities in China from 2009 to 2021 to evaluate the impact of the VAT reform on urban green innovation. The study finds that the implementation of the VAT reform significantly promotes the level of urban green innovation. Mechanism analysis shows that the tax reduction forces local governments to proactively adjust their expenditure structure, increasing spending on science and technology to broaden the tax base, thereby enhancing urban green innovation vitality. This paper provides empirical evidence for further leveraging the incentive role of tax incentives in green innovation.
Design of Cross-Platform Cryptocurrency Futures-Spot Arbitrage Strategies and Risk Optimization Analysis
This paper focuses on the cross-platform arbitrage of cryptocurrency, clarifies its definition, principle, and application scenarios, sorts out relevant theories and market mechanisms, designs two standardized arbitrage strategies of forward and reverse arbitrage, analyzes potential risks, formulates a complete practical operation process, and conducts income calculation and cost analysis. The research adjusted the traditional arbitrage theory according to the characteristics of the cryptocurrency market, designed an arbitrage mechanism combining basis and capital rate, realized efficient hedging through the static dual-account mode, formulated a perfect practical operation process and risk control rules, and verified the effectiveness and feasibility of the strategy through historical review, which can provide practitioners with a quantitative trading scheme with low risk and stable returns.
The Transformation of Trade Intermediaries: A Case Study of Garment Fabric Trading Companies
In the global trade landscape characterized by the rise of trade protectionism and the accelerated digital transformation, clothing fabric trade intermediaries are confronted with multiple survival crises, including profit compression, supply - chain instability, and information asymmetry. Existing research on the transformation of fabric traders is relatively scarce. This paper takes clothing fabric trading enterprises as the research object, outlines the four - stage evolutionary characteristics of the domestic fabric industry since 2000, analyzes the four core development dilemmas of traditional intermediaries, and quantitatively disassembles the driving weights of industry transformation from three dimensions: market, industry, and policy - technology. Based on this, four differentiated transformation paths are proposed: comprehensive supply - chain service providers, cross - border e - commerce multi - channel operators, full - chain industrial and trading integrated enterprises, and fabric brand operators. The applicable entities, profit - making logics, and implementation thresholds of each model are compared, and four typical enterprises are selected for case studies to quantitatively verify the improvement effects of different transformation models on revenue structure, profit margin, and operational efficiency. The research finds that the shortage of funds, the gap in professional talents, and the difficulties in digital technology adaptation are the main obstacles to enterprise transformation. Corresponding countermeasures such as diversified financing, joint talent cultivation between schools and enterprises, and technology collaboration among industry, academia, and research are proposed. The research predicts that the industry will evolve towards green and low - carbon development and the intelligent application of AI and the Internet of Things, providing theoretical basis and practical references for the digital and service - oriented upgrading of fabric trade intermediaries at home and abroad.
Navigating Business Breakthroughs: Traditional Bookstores in the Digital Era
This study aims to explore the survival challenges faced by traditional brick-and-mortar bookstores in the digital age. Through literature review and case analysis, this study identifies the limitations of existing research, and then constructs a transformation theoretical framework based on industry collaboration and digital integration, and looks forward to the future path of bookstore function reconfiguration. In the context of the digital age, the physical bookstore industry is experiencing a double predicament of scale contraction and increasing operational pressure. The industry transformation lacks a universal paradigm and requires adaptive adjustments based on its own resource endowments. The study further clarifies that the core value of physical bookstores lies in content curation and cultural scene creation, which provides theoretical guidance for seizing opportunities in related industry policies and promoting digital transformation.
The FDI Attraction Effect of Green Supply Chain Certification: Evidence from RCEP Countries
Against the backdrop of a sluggish global economic recovery, escalating geopolitical volatility, and increasingly urgent climate governance, the flow of Foreign Direct Investment (FDI) by Multinational Enterprises (MNEs) is undergoing profound structural reshaping. With the global green trade barriers, represented by the European Union's Carbon Border Adjustment Mechanism (CBAM), officially entering the definitive implementation and verification phase in 2026, the environmental compliance capacity of host countries has transitioned from a mere cost burden to a core novel determinant of capital flows. Grounded in the macro context of the Regional Comprehensive Economic Partnership (RCEP), this paper deeply integrates the institution-based view, the "Porter Hypothesis", and institutional decoupling theory to systematically analyze the underlying logic and micro-mechanisms of how Green Supply Chain (GSC) certification influences MNEs' FDI location choices. Based on panel data from 15 member countries spanning 2010 to 2022 and constructing a two-way fixed effects model, the empirical results reveal that GSC certification, represented by ISO 14001, significantly promotes FDI inflows. This finding not only confirms that environmental compliance has transformed from a "transaction cost" into an "institutional asset" with strategic premium, but also highlights the critical signaling role of voluntary environmental standards in reducing information asymmetry in cross-border transactions and evading "greenwashing" regulatory risks. This study expands the connotation of location advantages in the classic Ownership-Location-Internalization (OLI) paradigm. It not only provides scientific location coordinates for MNEs to navigate penetrative carbon verification and optimize Asia-Pacific supply chain layouts, but also offers forward-looking empirical evidence and strategic insights for developing RCEP members to abandon formalistic investment attraction strategies and formulate substantive macro-green economic transition policies.
A Review of Research on Intergenerational Education Mobility: Influencing Factors, Heterogeneity, and Prospects
Intergenerational educational mobility is a critical indicator for gauging the equality of educational opportunity and the level of social mobility, and is of great significance for advancing social equity and realizing common prosperity. The academic circle has produced extensive research on intergenerational educational mobility. Still, there is a shortage of papers that provide a relatively systematic review of dimensions such as influencing factors, heterogeneity, and research prospects. Accordingly, this paper presents a comprehensive overview of studies relevant to intergenerational educational mobility. Apart from explicating core concepts related to intergenerational educational mobility, it mainly introduces the latest research advances in two key areas: the factors influencing intergenerational educational mobility and its heterogeneity, and further discusses existing limitations as well as future development directions.
Research Review on the Scheduling Optimization of Production and Energy Systems under Uncertain Environments
The uncertainties in actual production and energy systems pose severe challenges to the stable, efficient, and low-carbon operation of the systems. Centering around the core of "uncertainty handling," this paper systematically reviews the mainstream modeling and solution methods for dealing with uncertainties in the current scheduling optimization field. At the measurement level, uncertainties can be characterized from two dimensions: parameter fluctuations and event perturbations, and there are essential differences in the impact mechanisms of the two on the scheduling scheme. From the perspective of uncertainty modeling, the theoretical foundations and applicable scenarios of methods such as fuzzy programming, stochastic programming, robust optimization, and distributionally robust optimization are reviewed; from the perspective of solution strategies, the evolution of methods from exact algorithms to heuristic, meta-heuristic, and then to intelligent decision-making methods based on learning and simulation is analyzed. At the effect level, uncertainties will significantly weaken the economic benefits and environmental performance of the scheduling scheme, but there are significant scenario heterogeneities in the degree of their impact. Research shows that distributionally robust optimization has attracted much attention due to its good balance between conservatism and economy, and the hybrid-driven method that combines simulation and learning is becoming an important trend to improve the adaptability of the scheduling system. Future research needs to further focus on the decision-making requirements in complex scenarios such as the coupling of multiple uncertainties, multi-agent games, and real-time dynamic responses.
Research on the Impact of Internal Control Deficiencies on the Cost of Enterprise Debt Financing
In recent years, the instability of the international economic situation and the turbulence of China's domestic and international environment have caused a downturn in the domestic financial market, making enterprises face the dilemma of "difficult financing" and "expensive financing". Therefore, based on the information asymmetry theory, principal-agent theory and signal transmission theory, this paper analyzes the impact of internal control defects on corporate debt financing costs with the sample of Shanghai and Shenzhen A-share listed companies from 2020 to 2024. The empirical study found that the reduction of internal control defects can effectively reduce the financing cost of enterprises. At the same time, from the perspective of audit quality and the nature of property rights, this paper analyzes their regulatory role in the relationship between internal control defects and corporate debt financing costs. The study found that, compared with enterprises with higher audit quality, the impact of internal control defects on corporate debt financing costs is more significant in enterprises with lower audit quality. And compared with state-owned enterprises, the impact of internal control defects on the cost of corporate debt financing is more significant in non-state-owned enterprises. This study helps enterprises realize the important role of the identification of internal control defects in the process of enterprise financing, and also enriches the theoretical research in related fields.
“Reading” China’s Economic Development Through Energy Indexes
This paper systematically analyzes the logic between China’s energy transition and economic development by constructing a quantitative analytical framework. The study introduces three core indexes—the Energy Consumption Growth Index, which measures gross domestic product (GDP) reliance on total energy scale; the Renewable Energy Contribution Index, which evaluates structural and qualitative improvements; and the Green Electricity Economic Contribution Index, which estimate the conversion of green efficiency into economic value—to dynamically assess the energy consumption characteristics of economic growth and the progress of green transition from a " volume–structure–efficiency" tripartite perspective. The research shows that China’s energy system has entered a positive synergy phase in which renewable energy dominates incremental growth and green power drives high-quality economic development.
Institutional Innovation and Diffusion Patterns of Inclusive AI at County Level: Evidence from Private Economy-Dominated Regions
The integration of artificial intelligence (AI) and inclusive growth drives transitional economies to narrow regional gaps and pursue common prosperity. China’s private economy-dominated areas are characterized by industrial clusters, market-based operations and severe urban-rural imbalances, creating a unique context for inclusive AI diffusion at the county level. Taking Wenzhou, a private economic hub in Zhejiang’s Common Prosperity Demonstration Zone, as the research sample, this paper adopts field surveys and empirical data to construct a four-dimensional theoretical framework: institutional supply, market adoption, inclusive diffusion and common prosperity empowerment. It systematically explores institutional barriers, innovative mechanisms and spatial diffusion modes of grassroots inclusive AI. The results identify four core constraints on AI popularization: uneven technological resource distribution, cross-regional data isolation, insufficient digital literacy of rural laborers, and high transformation costs for private SMEs. Targeted institutional innovations including tiered financial subsidies, industrial chain coordination, inclusive public computing power and multi-stakeholder co-governance can eliminate the “urban technological highland versus county technological lowland” gap. This study summarizes three localized diffusion patterns: leader-driven chain diffusion, platform-enabled cluster diffusion and scenario-oriented gradient diffusion. Mechanism tests verify that inclusive AI realizes common prosperity through three core paths: industrial efficiency growth, equalized public services and labor skill upgrading. This research expands the theoretical meaning of AI diffusion under institutional limits, provides localized institutional schemes for county-level digital inclusion, and offers practical references for emerging economies to coordinate technological progress and inclusive growth.
The Impact of RCEP Entry into Force on China's Regional International Trade Flows and Industrial Division of Labor
The Regional Comprehensive Economic Partnership (RCEP) took effect on January 1, 2022 and has operated for four years. Based on 2021–2024 official trade data from China's National Bureau of Statistics and 2025 customs statistics, this paper evaluates RCEP's impacts on China's trade volume and regional industrial division. Results show: (1) China's total trade with other RCEP members reached USD 1.385 trillion in 2025, accounting for 30.4% of China's overall foreign trade, up 4.8% from 2021; RCEP has been China's largest regional trade partner for four consecutive years. (2) China's exports to ASEAN economies including Vietnam, Singapore and Indonesia rose sharply, while trade deficits with Japan, South Korea and Australia narrowed continuously. (3) China exports mechanical, textile and high-tech intermediate goods to the bloc and imports integrated circuits and mineral resources, forming distinct regional value chain labor division. This paper concludes with targeted suggestions for regional cooperation, trade structure optimization and industrial upgrading.
Improving Response Efficiency in Extreme Scenarios: Optimizing Emergency Response and Rapid Repair Mechanisms for Natural Gas Leakage in Chengdu
With the acceleration of urbanization and the continuous expansion of gas pipeline networks in Chengdu, natural gas leakage accidents caused by extreme weather, complex terrain, third-party construction damage, and other extreme scenarios occur frequently, posing severe threats to urban public safety, residents’ lives and property, and the ecological environment. The current emergency response and rapid repair mechanisms for natural gas leakage in Chengdu still suffer from insufficient targeted contingency plans, poor emergency coordination, inadequate adaptability of technical equipment, and uneven professional capabilities of repair teams, which can hardly fully meet emergency response demands under extreme scenarios. Based on the characteristics of Chengdu’s gas pipeline network distribution, types of extreme scenarios, and current emergency response status, this paper analyzes typical cases and existing shortcomings, and puts forward targeted optimization suggestions from five dimensions: optimization of the contingency plan system, improvement of the coordination mechanism, upgrading of technical equipment, strengthening of team building, and improvement of the support system. The aim is to enhance the efficiency of emergency response and rapid repair of natural gas leakage in Chengdu under extreme scenarios, build a solid line of defense for urban gas safety, and provide theoretical support and practical references for Chengdu’s construction of a safe and resilient city.
Digital Trade and Governance of Global Value Chain Resilience
Global value chains are shifting from efficiency-first to security and resilience priority, with digital trade becoming a key force in reshaping governance logic. Based on multiple frontier studies, this research systematically examines the intrinsic relationships among digital technology, digital trade rules, artificial intelligence, and GVC resilience. The findings indicate that digital trade enhances resilience through three mechanisms: risk diversification and supply-demand matching optimization, institutional opening-up and rule network embeddedness, and digital competitiveness improvement and structural constraint mitigation. Key drivers include digital trade rule network status, industrial digitalization, AI application, and new-quality productive forces. Meanwhile, multiple external shocks weaken resilience through rising trade costs, asset-specificity traps, and network modularity lock-in, and the enabling effect exhibits a “Matthew effect.” This research proposes governance pathways including constructing a “China Template” for digital trade rules, advancing institutional opening-up, and strengthening digital infrastructure.
Research on Employment Problems of China's Gig Economy Under Algorithm Guidance
Against the backdrop of algorithm-driven labor market transformation, China's gig economy grapples with structural tensions between employment innovation and labor rights protection. The research centers on "employment in China's gig economy under algorithmic guidance". Contradictions stem from the mismatch between algorithmic control and existing labor governance. The traditional system faces hurdles like liability-identification failures.A multi-faceted approach of "technical ethics reconstruction+institutional innovation+social collaboration" is proposed: clarify legal boundaries, promote algorithm transparency, strengthen supervision and collective bargaining, and boost employment security. Future research should focus on public-driven algorithm governance and cross-platform rights protection for a balance between gig economy growth and rights safeguarding, offering a Chinese model for digital-age labor governance and policy insights.
“Killer Acquisitions” by Platform Firms: A Research Review and Future Prospects
In recent years, large-scale acquisitions of startups by platform firms have drawn significant attention from global antitrust authorities and academia, making “killer acquisitions” one of the most debated topics in competition policy. This paper systematically reviews the literature on killer acquisitions by platform firms, presenting the current state of research and academic controversies across four dimensions: conceptual definition, driving factors, competitive effects, and antitrust regulation. The findings reveal that while a basic consensus has emerged on the definition of killer acquisitions—where incumbent firms acquire innovative startups to eliminate potential competitive threats—there remains a risk of conceptual overextension when applying this notion to the digital platform context. Regarding driving factors, eliminating potential competitive threats is the core explanatory variable, yet ecosystem building, talent acquisition, and data hoarding are also significant and multifaceted motives. Empirical evidence on competitive effects is highly divergent: international studies tend to confirm the anticompetitive harm of killer acquisitions, whereas empirical research based on China’s BAT companies (Baidu, Alibaba, Tencent) finds no consistent “killer” motive, highlighting notable contextual differences between Western and Chinese platform markets. Antitrust regulation faces three major challenges—ineffective merger notification thresholds, difficulty in identifying potential competition, and a heavy burden of proof. Various jurisdictions are exploring regulatory reforms by introducing transaction-value thresholds, ex post review mechanisms, and shifts in the burden of proof. Based on these insights, this paper identifies four promising directions for future research: modeling the dynamic competitive effects of killer acquisitions, comparative institutional analysis of platform merger patterns between China and the West, strategic combinations of regulatory tools and welfare trade-offs, and the evolving forms of killer acquisitions in the AI era alongside corresponding policy responses.
Advantages, Disadvantages, and Development of Technology Licensing
With the increasing importance of technological innovation in economic development, technology licensing has become a key mechanism for promoting technology diffusion and knowledge transfer, and an essential tool for firms to gain competitive advantages and achieve technology commercialization. This paper analyzes the advantages, disadvantages, and future development trends of technology licensing. The study finds that technology licensing can enhance innovation returns, reduce R&D costs, promote technology diffusion and industrial upgrading, and improve resource allocation efficiency and market competition, thereby contributing to overall social welfare. However, it may also generate several negative effects, including the erosion of licensors’ competitive advantages, risks of technology spillovers and knowledge leakage, weakened incentives for independent innovation among licensees, and increased market concentration and transaction costs. Furthermore, with the development of the digital economy and global innovation networks, technology licensing is evolving toward greater openness, platformization, digitalization, and internationalization. It is expected to play an increasingly important role in open innovation, green transformation, and global technological cooperation. Overall, balancing technology diffusion and innovation incentives remains a central issue in the design and development of technology licensing systems.
The Evolution and Effectiveness of China's Regional Coordinated Development Policies: A Comparative Study Based on "Yangtze River Delta Integration", "Northeast Revitalization", and "Guangdong-Hong Kong-Macao Greater Bay Area"
In the process of high-quality economic development in China, regional coordinated development policies play a pivotal role. Due to differences in resource endowments, geographical environments, and historical development foundations, China's regional economic development shows a significant imbalance, which makes the research on regional coordinated development policies of great practical significance. This paper deeply analyzes the evolution process and implementation effectiveness of the three major regional coordinated development policies of "Yangtze River Delta integration", "Northeast Revitalization" and "Guangdong-Hong Kong-Macao Greater Bay Area" by comprehensively using the literature research method, case analysis method, and comparative research method. The study finds that the "Yangtze River Delta integration" policy has achieved remarkable results in promoting high-quality integrated development of the regional economy; although the "Northeast Revitalization" policy has undergone several rounds of adjustments, it still faces challenges in industrial structure optimization and institutional mechanism reform; the "Guangdong-Hong Kong-Macao Greater Bay Area" policy has made positive progress in promoting regional innovation and coordinated development, but there are obstacles in terms of rule connection. Through comparative analysis, this paper puts forward targeted suggestions for improving China's regional coordinated development policies, so as to help build a new pattern of coordinated regional development.
Guangdong - Hong Kong - Macao Greater Bay Area
Team Mindfulness in Management Research: A CiteSpace-Based Bibliometric Analysis
This research explores the use of mindfulness in team management to enhance collaboration, leadership, and performance. Using bibliometric tools (Web of Science, CiteSpace, VOSviewer), the study analyzes literature trends and finds that mindfulness improves team cooperation, reduces stress, and strengthens decision-making. The study concludes that mindfulness effectively enhances team outcomes and suggests future research across diverse cultural and organizational settings.
Copyright (c) 2026 by author(s) and Erytis Publishing Limited. https://creativecommons.org/licenses/by-sa/4.0
Research on the Export Competitiveness and Potential of Chinese Cosmetics in the Indonesian Market
This paper provides a systematic assessment of the competitiveness and growth prospects of Chinese cosmetics in Indonesia. Indonesia’s large population, youthful demographics, and rising incomes create substantial opportunities for Chinese beauty firms. By examining market conditions, product capability, brand influence, and channel development, the study finds Chinese firms hold advantages in supply-chain responsiveness and digital marketing, yet lag in brand equity and cultural localization. The paper proposes targeted measures across three pillars—product innovation, digital branding, and supply-chain optimization—stressing deeper localization, distinctive brand positioning, and cost-structure improvements. The findings offer theoretical insights and practical recommendations for Chinese cosmetics enterprises expanding into Indonesia.
Research on Structural Characteristics and Optimization of Policy Mix for Pollution Reduction and Carbon Abatement in Chengdu-Chongqing Twin-City Economic Circle
Against the background of the carbon peaking and carbon neutrality goals as well as ecological civilization construction, the collaborative governance of pollution reduction and carbon abatement has become an important direction for regional green and low-carbon transition. Taking the Chengdu-Chongqing Twin-City Economic Circle as the research object, this paper constructs a three-dimensional analytical framework of policy objective–policy instrument–policy intensity based on relevant policy texts from 2000 to 2025, and analyzes the evolution process and structural characteristics of the regional policy mix for pollution reduction and carbon abatement. The study finds that policy supply has generally gone through three stages: the initial stage of traditional pollution governance, the expansion stage of green low-carbon development, and the intensified stage of coordinated pollution reduction and carbon abatement. Policy objectives have gradually expanded from single pollution control to compound goals covering carbon emission reduction, energy transition, industrial transformation, ecological protection and regional coordination. Mandatory policy instruments dominate, while market-oriented and guidance-based instruments have been gradually strengthened; nevertheless, voluntary instruments and social participation mechanisms remain insufficient. Policy intensity keeps increasing, whereas joint governance, standard alignment, data sharing and collaborative evaluation mechanisms between Sichuan and Chongqing still need to be improved. On this basis, it is necessary to strengthen overall objective coordination, optimize the structure of policy instruments, enhance regional collaboration and improve the dynamic evaluation mechanism, so as to promote the policy mix to shift from quantitative expansion to structural optimization.
Chengdu-Chongqing Twin-City Economic Circle
Pollution Reduction and Carbon Abatement