Economics & Business Management ISSN Print: 3079-5214 ISSN Online: 3079-5222
Influences of Social Media Live Streaming on Building Stable Customer Loyalty in Global Trade Cooperation
With the digitalisation of global trade, the old ways of communicating that are offline trade fairs, static emails and printed product catalogues are unable to maintain continuous cooperation among buyers and suppliers due to a lack of timely information updates and delayed feedback. Social media live-streaming platforms, including Facebook Live, Instagram Live and TikTok Live, have begun to use live streaming for a long time and are now often employed by cross-border enterprises to keep in touch with consumers. The object of this paper is the construction of trust in real time during live broadcasts, and based on the stimulus-organism-response (SOR) model and relationship marketing theory, it studies how live streaming affects the stable loyalty of customers in global trade cooperation. Based on industry data and typical cases of B2B foreign trade, this paper will examine the three internal mechanisms that promote buyer trust through live interaction, summarize four operational live-streaming customer retention models, identify the main problems of cross-cultural barriers, homogeneous content and disconnected post-live services, and put forward corresponding improvement plans. Based on the above study, timely communication with foreigners can be initiated to build rapport and increase the frequency of such contact; thus, the sense of switching costs for importers will be reduced, motivating them to be more willing to buy and engage in subsequent trade, extending the period of cooperation among these enterprises and their overseas partners for small and medium-sized export enterprises.
Copyright (c) 2026 by author(s) and Erytis Publishing Limited https://creativecommons.org/licenses/by-sa/4.0
Factors Influencing Consumer Trust in Beauty Product Live Streamers and Improvement Pathways: An Analysis Based on the SOR Model
With the rapid development of digital transformation and e-commerce, beauty live commerce has emerged as the core growth engine of China’s beauty retail market. However, the industry’s explosive expansion has been marred by escalating trust issues, including false advertising, exaggerated efficacy claims, and inadequate quality control, which severely hinder its sustainable development. Grounded in the Stimulus-Organism-Response (SOR) theoretical framework, this paper systematically examines how three core characteristics of beauty live streamers—professionalism, authenticity, and interactivity—shape consumer trust. The study identifies four key points underlying the current trust crisis: insufficient professional literacy among streamers, fabricated scenarios and personas, weak supply chain quality control, and severe content homogenization. To address these challenges, this study proposes a four-pronged trust enhancement framework encompassing capacity building, technology empowerment, institutional safeguards, and content innovation. This research provides theoretical insights and practical strategies for regulating the beauty live commerce industry, building streamer IPs, and optimizing brand marketing practices.
Digital Infrastructure Empowering the High-Quality Development of China's Agricultural Exports: Mechanisms and Pathways
In the digital economy era, digital infrastructure has become a key force reshaping international trade. Based on technology diffusion theory, this study explores how digital infrastructure promotes the high-quality development of China's agricultural exports through three core pathways: reducing trade costs, enhancing production efficiency and product value added, and optimizing international market matching. China has made notable progress in digital village construction, smart agriculture, and cross-border e-commerce. However, challenges remain, including the urban-rural digital divide, shortage of interdisciplinary digital talents, and lack of unified digital standards. To fully unleash the enabling effects, efforts should focus on targeted infrastructure investment in rural areas, talent cultivation, building internationally compatible digital standards and traceability systems, and innovating financial support instruments, thereby building new "digital capability"-centered competitive advantages for China's agricultural exports.
A Study on the Impact of Digital Inclusive Finance on County-Level Farmers’ Income in Sichuan Province
Based on county-level panel data from Sichuan Province from 2014 to 2022 (176 districts and counties), this paper employs a fixed-effects model to empirically examine the impact of digital inclusive finance on rural residents' disposable income. The findings reveal that: (1) digital inclusive finance has a significant positive effect on farmers' income, with a 1% increase in the digital inclusive finance index leading to a 0.347% increase in farmers' income; (2) the level of financial development plays a partial mediating role between digital inclusive finance and farmers' income ; (3) all three dimensions of digital inclusive finance—coverage breadth, usage depth, and degree of digitalization—significantly contribute to the growth of farmers' income; (4) the promoting effect of digital inclusive finance is more pronounced in areas with a high urbanization rate.
The Electric Vehicle Competition between German and China: Based on RCA and IIT Analyse New Energy Vehicle Trade
In recent years, under the backdrop of accelerating global energy transition, new energy vehicles have become a new focus of strategic competition among major countries and international trade negotiations. Currently, most research on new energy vehicles focuses on the competition among developed countries' new energy vehicle industries, especially the competition between China and the United States. As a traditional automotive manufacturing power, Germany has conducted relatively less research on the electricization competition of new energy vehicles between China and itself. This paper, from the perspective of international trade, takes new energy vehicle complete vehicles (HS: 870380), lithium-ion batteries (HS: 850760), and motors/electronics control systems (HS: 850131/8503710) as research objects. Using methods such as RCA index (explicit comparative advantage) and IIT index (industry internal trade index), based on data from UN Comtrade and WTO Tariff Database, it studies and analyzes the international division of labor in intra-industry trade between China and Germany and the comparative advantages of each product of the two countries. At the same time, this paper combines China and Germany's tariff measures, the EU's subsidies and localization policies for new energy vehicles, as well as China's dual-subsidy policy, to analyze the impact of these trade policies on bilateral trade. The research finds that China has a significant comparative advantage in new energy vehicle complete vehicles (including pure electric plug-in hybrids), while Germany attempts to protect its domestic industry by means of anti-subsidy, localization requirements, etc., even though it does not have a comparative advantage. Based on this, this paper proposes that China should consolidate its advantages in battery power and vehicle manufacturing to stabilize the market and actively expand the market through subsidies, export tariff policies, etc., in order to maintain its initiative in the new round of energy trade competition.
Research on the Driving Mechanism and Transformation Path of Digital Transformation of Publishing Groups
Driven by the digital economy and national policies, the digital transformation of publishing groups has been continuously advanced. Most existing studies on the digital transformation of publishing groups adopt qualitative case descriptions or static analysis, lacking clear transformation paths and driving mechanisms. Based on the principles of system dynamics, this study constructs a transformation framework consisting of four subsystems: resource base, empowerment support, value output and environmental regulation, to reveal the internal logic and driving mechanism of the digital transformation of publishing groups. With the annual report data of Phoenix Media from 2020 to 2024 for parameter calibration and empirical simulation, this paper realizes the dynamic simulation and quantitative test of the transformation process. The research finds that the benefits of digital transformation show an accelerated growth trend after the initial investment stage. Through sensitivity analysis, it is identified that digital talent reserve is a more influential key leverage than investment in content assets. Accordingly, this paper puts forward resource optimization strategies for the high-quality transformation of publishing groups from the perspectives of dynamically adjusting resource input, strengthening talent echelons and optimizing organizational collaboration.
Study on irrational behavior of retail investors in the post-COVID-19 market boom
Against the backdrop of the COVID-19 pandemic's global economic impact, the subsequent market boom has drawn significant attention, with retail investors demonstrating remarkable activity during this period. Grounded in behavioral finance theory, this study employs literature review, data analysis, case studies, and comparative analysis to investigate irrational decision-making patterns among retail investors during the post-pandemic market rally. The findings reveal that retail investors frequently exhibit herd behavior, chasing "internet-famous stocks" and speculative assets. Social media amplifies overconfidence and "fear of missing out" mentality, leading to short-term price surges and high volatility. These behavioral biases explain price distortions and rapid emotional shifts. The research provides crucial insights for investors to improve decision-making quality and for regulators to promote stable market development.
Can green credit improve the environmental information disclosure level of industrial enterprises under the background of low-carbon economy —— Empirical analysis based on DID model
Promoting the green and low-carbon development of the economy and society is a key link in achieving high-quality development. Industrial enterprises are the main sources of carbon emissions. As environmental information disclosure is an important influencing factor for enterprise financing, can green credit improve the environmental information disclosure level of industrial enterprises? This article takes the Notice on Conducting the Evaluation of Green Credit Performance of Deposit-Taking Financial Institutions in the Banking Industry issued by the People's Bank of China in 2018 as a quasi-natural experiment. It selects industrial enterprises from 2010 to 2022 as the research objects. By constructing the DID model, this paper investigates the impact and mechanism of green credit policies on the environmental information disclosure level of industrial enterprises. The research finds that: First, the implementation of the green credit policy has enhanced the environmental information disclosure level of industrial enterprises. Secondly, the green credit policy promotes industrial enterprises' environmental information disclosure by easing their financing constraints. The results of heterogeneity analysis show that the improvement of environmental information disclosure level of industrial enterprises by green credit policies is more obvious in non-state-owned enterprises and those with a higher degree of regional marketization.
The Level of Environmental Information Disclosure
Copyright (c) 2026 by author(s) and Erytis Publishing Limited. https://creativecommons.org/licenses/by-sa/4.0
From Questioning Norms to Critiquing Institutions: Cost, Risk, and Emotion in Chinese Youth's Nonmarriage Decisions
Currently, China faces a significant decline in marriage registrations and a growing prominence of nonmarriage. This study analyses 6,095 user answers from Zhihu on two questions regarding nonmarriage. Using high-frequency word analysis, LDA topic modeling, and sentiment analysis, it explores the complex reasons and emotional tendencies behind Chinese young people's choice of nonmarriage. The research finds that young people's explanations for nonmarriage exhibit clear stages and progression, with their nonmarriage logic shifting from questioning marital norms to systematically critiquing institutional factors. The perceived sanctity and inevitability of marriage in personal life are being challenged. As discussions deepen, criticism extends further to systemic issues behind marriage, including social structures, economic pressures, legal frameworks, and patriarchal culture. Meanwhile, the social environment and popular culture continually construct legitimising narratives for nonmarriage, while online emotional polarisation amplifies risk perception and accelerates the social diffusion of nonmarriage preferences.
Research on the Development Strategies of Digital Reading Against the Background of National Reading: A Knowledge Mapping Analysis Based on CiteSpace
The Regulations on the Promotion of National Reading came into force on February 1, 2026, marking China’s national reading has entered a legalized and systematic stage. As a core carrier of modern knowledge dissemination, digital reading is shifting from scale expansion to value cultivation. Based on 281 core journal articles from CNKI (2015–2025), this study uses CiteSpace 6.3.R1 to conduct keyword co-occurrence, clustering, timeline and burst detection analysis. Results show that research focuses on digital reading, national reading and reading promotion, forming four dimensions: policy and public services, infrastructure equalization, technology empowerment and user-centered content innovation. The field has experienced popularization and high-quality development stages, with current frontiers concentrating on artificial intelligence, service systems, in-depth reading and digital divide. Faced with contradictions such as mismatched content supply and demand, superficial technology application and unequal public services, this paper constructs a trinity development strategy of infrastructure reconstruction, in-depth technology empowerment and institutional improvement, providing theoretical support and practical guidance for the high-quality development of digital reading.
The Operation Mode and Commercialization Journey of New Energy Ride-Hailing Vehicles
This study focuses on the operation mode and commercialization process of new energy ride-hailing vehicles, exploring how they can replace traditional fuel vehicles through technological and business model innovation. It analyzes the reasons why ride-hailing services serve as the optimal entry point for the commercialization of new energy vehicles and summarizes China's successful experiences. Ride-hailing services are regarded as an ideal scenario for the commercialization of new energy vehicles, which can be attributed to their high-frequency operation characteristics, significant cost differences, strict regulatory environment, and large-scale platform-based application model. Through policy guidance, market-driven forces, and technological progress, China has established a replicable development path, achieving a rapid increase in the penetration rate of new energy vehicles in the ride-hailing sector, improvement of infrastructure, maturity of business models, and accelerated promotion of autonomous driving technology, thus constructing a complete industrial ecosystem. The conclusions of this study provide theoretical support and practical references for the global promotion of new energy ride-hailing services, contributing to the sustainable transformation of the global transportation industry. In the future, with policy optimization, infrastructure improvement, reduction of autonomous driving costs, and innovation of profit models, new energy ride-hailing services will develop towards large-scale, high-efficiency, and commercialization.
Digital Infrastructure Construction and Energy Efficiency: A Literature Review
Against the backdrop of the digital economy and China’s dual carbon goals, the impact of digital infrastructure construction on energy efficiency has attracted growing academic attention. This paper systematically reviews the existing literature from three perspectives: conceptual measurement, theoretical mechanisms, and literature assessment. The review reveals that digital infrastructure promotes energy efficiency primarily through technological innovation, industrial structure upgrading, and resource allocation optimization, though rebound effects and other negative consequences cannot be overlooked. The current literature largely supports the positive effect of digital infrastructure on energy efficiency and identifies heterogeneity across regions and city sizes as well as significant spatial spillover effects. However, research on micro-level mechanisms and negative effects remains limited.
Fiscal and Tax Law Countermeasures for Building a Unified National Data Factor Market in China
The construction of a unified national data factor market is a cornerstone strategy for China's economic transformation. As a novel production factor with virtuality, non-rivalry, and high liquidity, data diverges fundamentally from tangible inputs and poses institutional challenges to China's fiscal and legal frameworks. Currently, China's data market suffers from regional segmentation, distorted tax bases, imbalanced revenue distribution, inadequate regulation, and fragmented incentives. This paper identifies core governance dilemmas, analyzes their institutional origins, and proposes a coherent framework encompassing legislative unification, tax redesign, digitalized administration, transfer payment optimization, and targeted incentives.
Measurement and Influencing Factors of Green Logistics Efficiency in the Yangtze River Delta Region
Under the dual-carbon target and regional integration strategy, green logistics has become a core path for high-quality development of the logistics industry. This paper takes the Yangtze River Delta (Shanghai, Jiangsu, Zhejiang) as the research object, and constructs an input-output index system including capital, labor, energy, expected outputs and undesirable outputs (CO₂ emissions). The Super-SBM model with undesirable outputs and the Global Malmquist-Luenberger (GML) index are used to measure static and dynamic green logistics efficiency from 2006 to 2023. Furthermore, a fixed-effects model and fuzzy-set qualitative comparative analysis (fsQCA) are adopted to explore influencing factors. The results show that: 1) The overall green logistics efficiency of the region is on the rise with obvious inter-provincial differences, and Shanghai ranks first; 2) Technological progress is the main driving force for efficiency growth; 3) Economic development, logistics scale and environmental governance positively affect efficiency, while energy intensity has a negative impact. Finally, targeted strategies are proposed from the perspectives of resource allocation, energy structure and policy coordination.
MMF-EDRM: A Multi-Modal Fusion and Dual-Risk Modeling Framework for Renewable Energy Project Financing and ECM/DCM Pricing
Renewable energy infrastructure investment faces substantial uncertainty arising from heterogeneous data sources, including environmental variability, policy interventions, and financial market fluctuations. Traditional valuation methods, such as discounted cash flow (DCF) and conventional multi-factor models, are limited in their ability to integrate unstructured information and to jointly capture risk–return dynamics in financing decisions. To address these challenges, this paper proposes MMF-EDRM (Multi-Modal Fusion and Dual-Risk Energy financing model), a unified framework for renewable energy project financing valuation and ECM/DCM pricing. The model integrates multi-modal deep learning with multi-factor statistical modeling to establish a risk–return–pricing linkage for infrastructure assets. Specifically, satellite imagery, meteorological time series, policy documents, and structured financial indicators are encoded through modality-specific networks and fused via a cross-modal attention mechanism. A heteroscedastic dual-head architecture is then employed to jointly estimate expected returns and conditional risk uncertainty. These outputs are further incorporated into an extended multi-factor pricing formulation to derive equity valuation (ECM) and credit spread estimation (DCM). The framework is optimized using a multi-task learning objective that aligns prediction and pricing consistency. Empirical results on the constructed multi-modal renewable energy dataset show that MMF-EDRM reduces RMSE for return prediction by 17.6% compared with CNN-LSTM baselines, while achieving 14.0% improvement in equity pricing error and 12.7% reduction in credit spread prediction error. In addition, the model attains a lower NLL of 0.742, indicating superior risk calibration under volatile policy conditions. These results confirm the effectiveness of the proposed framework.
Digital Marketing Research Report on Haba (Ningbo) International Trading Co., Ltd.
This study focuses on Haba (Ningbo) International Trading Co., Ltd., a cross-border e-commerce subsidiary of a Dutch group. It analyzes the company’s digital marketing macro and micro environment, STP strategy, and 4Ps marketing mix. The findings show the company has a sound marketing system and clear positioning but faces weak digital tech application, insufficient localization, over-reliance on parent brand, and imperfect after-sales service. Finally, targeted optimization strategies are proposed to boost its global competitiveness.
Research on the Revitalization of Local Resources and the Integration of Agriculture, Culture, and Tourism: A Case Study Based on the Tea Industry - Tourism Integration Project in the Area of Source of Yaojiang River Region in Siming Mountain
Using the Source of Yaojiang River Tea-Tourism Integration Project in Siming Mountain as a case study, this paper explores effective approaches for revitalizing local resources and integrating agriculture, culture, and tourism. It analyzes challenges encountered during project implementation and proposes corresponding strategies. Through case analysis, the study provides a detailed examination of the region's practices in resource revitalization and integrated development. Findings indicate that resource revitalization can be achieved by enhancing tea industry quality, leveraging cultural assets, and utilizing natural landscapes; whereas integrated development manifests as a multifaceted convergence of the tea industry with tourism and cultural elements. The study aims to offer theoretical insights and practical guidance for the sustainable development of the Source of Yaojiang River region in Siming Mountain and similar rural areas.
Integration of agriculture, culture, and tourism
The Influence Mechanism and Heterogeneity Analysis of Internal Control Quality on Corporate Accounting Information Transparency
Addressing the practical issues of accounting information distortion and insufficient transparency in capital markets that constrain pricing efficiency, this study elucidates the mechanism and heterogeneous characteristics of internal control quality on corporate accounting information transparency. Using A-share listed companies from 2018 to 2023 as samples, we examined the causal relationship through a fixed-effects model, identified the transmission path using a mediation effect model, and conducted heterogeneity analysis via grouped regression. The results demonstrate that high-quality internal controls significantly enhance corporate accounting information transparency—a conclusion validated by endogeneity and robustness tests. The core transmission path involves curbing earnings management, reducing agency costs, and improving information disclosure quality, with the mediation effect of earnings management suppression being the strongest. This positive effect is particularly pronounced in non-state-owned enterprises, regions with high marketization levels, and small-to-medium-sized enterprises. The study provides empirical evidence for companies to optimize their internal control systems and for regulators to refine information disclosure regulations.
Copyright (c) 2026 by author(s) and Erytis Publishing Limited. https://creativecommons.org/licenses/by/4.0/
The Impact of Supply Chain Concentration on Operational Efficiency: An Intermediary Analysis Based on Inventory Management
This study uses non-financial A-share listed companies in China from 2020 to 2024 as its research sample. Based on resource dependence theory and operations management theory, and utilizing micro-level firm data from the Guotai-An CSMAR database, the study empirically examines the impact of supply chain concentration on firm operational efficiency and its underlying mechanisms. Furthermore, it explores the heterogeneous effects of ownership structure, regional characteristics, and industry type on this relationship. The findings reveal that supply chain concentration and firm operational efficiency exhibit a U-shaped relationship: moderate supply chain concentration enhances operational efficiency, whereas excessive concentration inhibits such improvements due to increased supply chain risks. Inventory management (measured by inventory turnover rate) plays a partial mediating role between supply chain concentration and operational efficiency; specifically, supply chain concentration influences operational efficiency by affecting a firm’s inventory turnover efficiency. Heterogeneity analysis indicates that these effects are more pronounced in non-state-owned enterprises. From the perspective of optimizing supply chain layout and enhancing inventory management capabilities, this paper provides empirical evidence and practical recommendations for enterprises to cultivate new-quality productive forces and improve operational efficiency through supply chain management.
A Study on The Impact of Cross-Border Data Flow Restrictions on The Efficiency of China's Digital Services Trade Exports
This study first reviews the cross-border data flow restriction policies of various countries and the export situation of China's digital service trade. Using panel data from 2014 to 2023, a stochastic frontier digital gravity model is constructed to measure the export efficiency of China's digital service trade. The results show that the export efficiency of China's digital service trade remains at a relatively low level with slow growth. To explore the impact of cross-border data flow restrictions on China's digital service trade export efficiency, a trade inefficiency model is constructed for regression analysis, yielding the following conclusions: Increased levels of cross-border data flow restrictions significantly inhibit China's digital service trade export efficiency. The improvement in internet development levels of destination countries can mitigate the negative impact of their cross-border data flow restriction policies on China's digital service trade export efficiency; however, the expansion of institutional distance between the two sides exacerbates this negative effect. Specifically, policies in infrastructure connectivity, electronic transactions, payment systems, and intellectual property rights all exhibit significant inhibitory effects, with intellectual property royalties and the personal, cultural, and entertainment services sectors being more sensitive to cross-border data flow restriction policies.
Artificial Intelligence and Supply Chain Disruption Risks of Chinese Outward-Oriented Enterprises
Against the backdrop of increasing uncertainty in the global economic and trade environment, exploring the role of artificial intelligence in reshaping the supply chain resilience of overseas enterprises and mitigating disruption risks is of great significance. Drawing on information asymmetry theory, supply chain dynamic capabilities theory, and co-evolutionary theory, this study systematically investigates the impact of AI on supply chain disruption risks of Chinese overseas enterprises using a sample of Chinese listed overseas enterprises from 2012 to 2023, employing text mining and ordinary least squares methods. The results show that AI significantly reduces supply chain disruption risks for Chinese overseas enterprises. This finding remains robust after a series of robustness checks, including instrumental variable method and Heckman two-stage estimation. The conclusions of this study help Chinese overseas enterprises develop more precise risk warning and response strategies, offering managerial insights for leveraging AI to prevent supply chain risks and ensure stable international operations.
Research on Book Topic Planning Based on Online Review Mining
In the context of digital reading and the growing importance of online reviews for publishing decisions, traditional topic planning faces challenges such as information overload and delayed feedback. This study analyzes over 59,000 valid reviews from Dangdang.com’s TOP15 best-selling literary books (April 2025). Using a “text mining + multi-dimensional comparison” approach and an optimized DTC framework with a topic mapping layer, we identify 17 core features of literary books via TF-IDF and K-means. Findings show that keywords like “classic,” “moving,” and “healing” significantly influence topic decisions and can be directly translated into content, author, and format strategies. The study validates the DTC model’s applicability in publishing and provides data-driven support for topic planning.
Research on the Impact of Green Finance on Ecological Environment Governance
To investigate the impact of green finance on ecological environment governance, this study measures the development level of green finance in 30 Chinese provinces from 2008 to 2020. Based on existing research and theoretical analysis, an empirical test was conducted to explore the effect of green finance development on the emission of "three wastes" pollutants. The results indicate that the adoption of green finance can effectively reduce regional "three wastes" pollutant emissions, holding significant positive implications for environmental pollution control. Through transmission mechanism analysis, it is found that industrial structure upgrading effectively promotes regional environment governance, with green finance playing a pivotal role in this process. Furthermore, regional heterogeneity analysis reveals that compared to central provinces, the eastern and western provinces exhibit a more prominent performance in environmental governance through green finance. Based on these conclusions, policy recommendations are proposed, including improving the level of environmental information disclosure by financial institutions, perfecting the green finance policy system, strengthening green finance incentive mechanisms, and enhancing government supervision and management to promote pollution reduction and ecological quality improvement.
Research on Operational Efficiency Improvement of Auto Parts Manufacturing Enterprises from the Perspective of Lean Management
Aiming at the common problems of chaotic production processes, excessive work-in-process inventory, and low equipment utilization in small and medium-sized auto parts manufacturing enterprises in China, this paper adopts the core lean management theory of industrial engineering, takes an auto chassis parts manufacturing enterprise in Sichuan Province as the research object, and applies lean tools including value stream mapping, 5S management, standardized operation, and quick die change to conduct systematic process optimization. The results show that after 6 months of lean management implementation, the production cycle of the enterprise's core product is shortened by 32.7%, work-in-process inventory is reduced by 41.2%, overall equipment effectiveness is increased by 28.5%, and the first pass yield of products reaches 98.6%. This paper verifies the significant positive effect of lean management on the operational efficiency of manufacturing enterprises, and provides a replicable lean implementation path for similar small and medium-sized manufacturing enterprises.
Research on Strategies for Enhancing Manufacturers' Resilience Under Competition from E-Commerce Private Brands in the Smart Home Industry
Against the backdrop of platform-based transformation in the smart home industry, growing competition from e-commerce private brands and frequent supply chain disruptions have put manufacturers in a dilemma between channel dependence, market competition, quality improvement, and resilience building. To fill the research gap that separates quality competition and supply chain resilience, this paper establishes a two-echelon supply chain game model with a budget constraint, integrating quality investment and resilience investment. Using backward induction, we derive the subgame perfect Nash equilibrium and conduct comparative static analysis. The results reveal a stable proportional relationship between resilience and quality investments, which shrinks under resource constraints, thus restraining quality input. Platform private brand pricing positively motivates manufacturers’ quality investment. Supply chain disruption risks affect platform pricing depending on resilience efficiency, while tight budgets push platforms to lower prices. Resource constraints reduce manufacturers’ profits. This study constructs a quality-resilience coordinated decision framework, reflects realistic resource limits, and deepens the understanding of platforms’ dual identity. It provides managerial insights for manufacturers’ resource allocation and strategic adjustment, and supports platforms in maintaining ecosystem health.
Research on the Driving Effect of Corporate Digital Transformation on Green Technological Innovation
Under the "dual carbon" goals and digital economy integration, green innovation drives manufacturing's high-quality development and environmental protection, while digital transformation helps firms break green innovation bottlenecks. Using text analysis to measure digital transformation, this paper takes A-share manufacturing listed companies (Shanghai & Shenzhen, 2019–2024) as samples. With a year fixed-effects model, it tests digital transformation's impact, mechanisms, and heterogeneity on green innovation.Results show digital transformation significantly raises corporate green innovation. This holds after robustness tests including PSM, instrumental variable method, core variable replacement, observation period extension, multi-fixed-effects control, and sample scope adjustment.Mechanism tests reveal three paths: resource effect (easing financing constraints), governance effect (weakening agency conflicts), and multiplier effect (enhancing growth capacity), providing financial guarantee, governance support, and endogenous motivation.Heterogeneity analysis shows the positive effect is stronger in non-high-tech enterprises and heavily polluting industries. Further, digital transformation significantly drives both green invention patents and green utility model patents.This study expands research on digital transformation's economic consequences and green innovation's drivers, offering empirical evidence and practical references for manufacturing's digital-green synergy and for differentiated industrial policies.
The level of data element utilization in the integration of the digital and real economies drives AI technological innovation
Using a sample of Chinese A-share listed companies in core digital economy industries from 2015 to 2024, this study examines how data element utilization drives AI technological innovation. Employing a panel fixed‑effects regression model, we find that the level of data factor utilization has a significant positive impact on AI patent output. This effect is more pronounced in firms with low total factor productivity (TFP), exhibiting a "contrarian" catch‑up characteristic. The conclusions remain robust after substituting different TFP measurement methods. This study reveals the unique mechanism through which data elements enable late‑entrant firms to catch up technologically, providing empirical evidence for deepening data element market reforms.
Integration of the digital and real economies
An Analysis of the Current State and Future Trends in Climate Finance Research
Climate finance constitutes a pivotal driver of global climate governance. Drawing upon bibliometric methodology, this study presents a comprehensive review of climate finance research spanning the period from 2015 to 2024. The analysis reveals a notable asymmetry in existing research perspectives, characterized by a "mitigation-dominant" imbalance, with insufficient scholarly attention devoted to adaptation financing and issues of distributive justice in fund allocation. Core research themes predominantly concentrate on the impact of climate policies on climate finance efficacy, as well as the catalytic role of climate finance in fostering energy economy transitions and low-carbon technological advancement. However, extant scholarship primarily emphasizes aggregate assessment, while lacking dynamic analyses of capital flow tracking and the allocation of transnational responsibilities. Future research endeavors should transcend prevailing climate policy frameworks, expand the scope of climate financing subjects and objects, strengthen information disclosure mechanisms among multiple financing entities, and enhance investigations into the economic consequences of climate finance.
Data Factor Sharing and Digital Inclusive Finance: From the Perspective of Open Government Data
Against the backdrop of building a high-standard data factor market in China, digital inclusive finance has become a core engine for advancing inclusive economic growth, yet it faces a critical bottleneck in the transformation from "breadth coverage" to "in-depth services" rooted in long-standing information asymmetry and insufficient demand-side participation. This paper takes the opening of urban public data platforms in China as the analytical entry point, constructs a systematic theoretical framework to examine the impact of open government data (OGD) on the development of digital inclusive finance, and deconstructs its underlying transmission mechanisms. The theoretical analysis demonstrates that OGD, as a fundamental institutional innovation in the data factor market, can significantly promote the high-quality development of digital inclusive finance through two parallel core paths: reducing information error in the financial market and enabling financial technology innovation. Further theoretical exploration reveals the heterogeneous characteristics of OGD’s inclusive effect: its promoting role is more prominent in regions with sound market ecology, lower level of bank digital transformation, and higher degree of financial agglomeration. This paper breaks through the dominant supply-side research paradigm in digital inclusive finance, expands the theoretical research on the economic value of public data in the financial sector, and provides targeted policy references for building a data-driven inclusive financial system in China.
Internationalization and Competitive Dynamics of Electric Vehicles in Southeast Asia
Against the backdrop of global automotive electrification, Southeast Asia (ASEAN) has emerged as a core growth market for electric vehicles (EVs). This paper conducts a management-oriented systematic review to explore the internationalization strategies and competitive dynamics of EV firms in ASEAN. Grounded in the OLI paradigm, institutional theory and the Uppsala model, it synthesizes key internationalization approaches including regional integration, localization and strategic partnerships, and analyzes competitive interactions between global and local players driven by cost advantages, technological disruption, policy instruments and value chain restructuring. The review identifies critical research gaps including insufficient cross-national comparative research, limited long-term performance analysis, and inadequate attention to digitalization and institutional entrepreneurship. It further proposes a future research agenda to advance international business theories and managerial practices.