International Journal of World Economic Research
International Journal of World Economic Research (IJWER) is an international, peer-reviewed journal. The mission of the journal is to provide an academic platform for scholars and practitioners to discuss the issues of economics, business, finance, management across the world. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
Research on the Spring Festival Effect and Market Efficiency of the Shanghai Composite Index
To examine the efficiency of China's stock market, this study employs the Efficient Market Hypothesis as its theoretical framework. Using daily closing price data of the Shanghai Composite Index from January 1.2008 to September 30.2024 we construct a GARCH (1,1)-M model to empirically test the return characteristics of the three days before and after the Spring Festival. The findings reveal a significant pre-Spring Festival effect in the SSE Composite Index, while the post-Spring Festival effect is insignificant. This result indicates that publicly available calendar information can predict short-term returns, challenging the weak-form efficient market hypothesis. It provides empirical evidence that China's stock market has not yet fully achieved weak-form efficiency, offering insights into market pricing efficiency.
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Transport Infrastructure Connectivity and China–DRC Bilateral Trade Performance: An Empirical Analysis
This paper examines the causal relationship between transport infrastructure connectivity and bilateral trade performance between China and the Democratic Republic of Congo (DRC) over the period 2000–2023. Employing a gravity model augmented with infrastructure quality indices, panel data fixed-effects estimations, and vector autoregression (VAR) analysis, we provide robust empirical evidence that improvements in road density, port efficiency, and multimodal connectivity significantly increase bilateral trade flows. Using provincial-level panel data and an instrumental variable (IV) strategy based on historical colonial transport networks as an instrument for contemporary infrastructure quality, our baseline estimates indicate that a 10% increase in infrastructure connectivity raises bilateral trade by 6.8–9.4%, with effects persisting over a 2–3 year horizon. Heterogeneity analysis reveals that the trade-enhancing effects are most pronounced for manufactured goods and mining outputs, consistent with Belt and Road Initiative (BRI) sector-specific investment patterns. Our findings survive a battery of robustness checks including alternative infrastructure measures, synthetic control methods, and spatial error corrections. The results carry important policy implications for infrastructure-led development strategies in Sub-Saharan Africa.
The impact of Vietnamese consumers' sense of environmental responsibility on green purchasing behavior
Amid escalating environmental challenges in Vietnam, understanding the drivers of green consumption has become increasingly important. This study examines the influence of Environmental Responsibility (ER) on Green Purchase Behavior (GPB) through an integrated framework that incorporates both mediating and moderating mechanisms. Specifically, Green Perceived Value (GPV) and Perceived Behavioral Control (PBC) are modeled as mediators, while Cognitive Effort Saving (CES) and External Incentive Policies (EIP) are introduced as moderators. Using survey data from 438 Vietnamese consumers, the proposed model is tested via Structural Equation Modeling (SEM) and multi-group analysis. The findings demonstrate that ER significantly affects GPB both directly and indirectly through GPV and PBC. Moreover, the strength of these relationships increases under conditions of higher CES and stronger EIP. By integrating the Value–Belief–Norm (VBN) theory with the Theory of Planned Behavior (TPB), this study advances the understanding of sustainable consumption behavior in emerging markets. The results also provide practical implications for policymakers and firms to design interventions that lower cognitive barriers and strengthen institutional support for green consumption.
A Text Analysis Approach for Assessing Annual Report Quality: A Comparative Case Study of Vietnamese and Chinese Companies
This study develops and validates a multidimensional framework for assessing corporate annual report quality through advanced text analysis, with a comparative focus on Vietnam and China, two dynamic yet institutionally distinct emerging markets. Leveraging a corpus of 60 English-language annual reports (2020–2024) from listed companies across seven industries, we extract 13 textual indicators spanning readability, sentiment, thematic focus, and disclosure volume. These indicators are integrated into an Annual Report Quality Index (ARQI) using a Multi-Criteria Decision Making (MCDM) framework that combines the Entropy Weight method for objective indicator weighting and the PROMETHEE method for nonlinear ranking. A two-tier research design enables both cross-industry characterization and a focused intra-industry banking case study, where three systemically important banks from each country are compared. Results reveal significant disparities: Chinese banks demonstrate consistently higher and more stable ARQI scores, reflecting greater institutional maturity under the China Securities Regulatory Commission (CSRC) framework. Vietnamese banks exhibit greater volatility but a clear upward convergence trend, particularly after 2022, suggesting adaptive responses to evolving disclosure regulations such as Circular 22/2019/TT-BTC. Component-level analysis shows that Chinese reports excel in risk transparency, sentiment stability, and thematic integration, while Vietnamese reports demonstrate emerging strengths in sustainability and digital transformation narratives. An internal consistency test confirms strong alignment between ARQI scores and task group assessments (Pearson’s r = 0.927, p < 0.001), validating the index’s reliability. This study contributes a scalable, replicable methodology for assessing narrative disclosure quality and provides empirical evidence on how institutional contexts shape corporate communication in emerging Asian economies. The ARQI framework offers practical utility for investors seeking transparent information, corporate managers aiming to benchmark reporting practices, and regulators striving to enhance market transparency.
Green Technology Innovation, Carbon Emissions, and High-Quality Development of Manufacturing Firms: Mechanisms and Empirical Evidence
High-quality development of enterprises is a critical issue in China’s pursuit of a modern development paradigm. Against this backdrop, green technology innovation plays a vital role in achieving carbon reduction targets and promoting high-quality development. Focusing on the pathways through which green technology innovation drives high-quality development in manufacturing firms, this study constructs an analytical framework of “green technology innovation—carbon emissions—high-quality development” using data from Chinese listed manufacturing companies from 2015 to 2024. Empirical tests are conducted using baseline regression, mediation effect, and threshold models. The results show that green technology innovation significantly promotes high-quality development in manufacturing firms. Carbon emissions play a positive mediating role, accounting for 56.22% of the total effect. Moreover, the impact of green technology innovation on high-quality development exhibits a single-threshold effect, characterized by an insignificant effect in the early stage and a significantly strengthened effect in the later stage. Accordingly, policy recommendations are proposed, including strengthening innovation support and providing differentiated policy provisions.
High-quality development of manufacturing firms
Research on Quality Evaluation of Landscape Resources and Its Spatial Visualization in the Chengdu-Chongqing Yangtze River Tourism Corridor
The Chengdu-Chongqing Yangtze River Tourism Belt is a core area for the construction of the Yangtze National Cultural Park. Scientifically evaluating its landscape quality is of great significance for regional cultural and tourism integration and ecological value conversion. This paper constructs an 8-indicator evaluation system containing two dimensions of visual perception and resource endowment, coupling Analytic Hierarchy Process (AHP) and GIS spatial analysis technology to quantitatively measure and spatially visualize the corridor landscape quality. The results show that: (1) The spatial differentiation of landscape quality is significant, showing a gradient pattern of "High in East, Low in Middle, Stable in West". The high-value area is concentrated in the Fuling to Wushan section of Chongqing, and the low-value area is embedded in the Chongqing main city urban area. (2) Indicator weights show that Openness and Naturalness are the dominant factors, with a combined weight of over 42%, indicating that visual corridor permeability and ecological endowment authenticity are the core of quality evaluation. (3) The high-intensity urbanization process produces a "double shielding" effect on the core high-weight factors, which is the main cause of the "collapse" of landscape quality in the middle section. Based on this, a segmented differentiated control strategy of strict protection in the east section, restoration and improvement in the middle section, and optimization and enhancement in the west section is proposed, so as to provide a scientific basis for the planning of the Yangtze National Cultural Park.
Chengdu-Chongqing Yangtze River Tourism Belt
Analysis and Improvement of Pricing Models for Bilateral Media Platforms
In the context of increasingly intense competition among digital platforms, the strategic pricing behavior of two-sided media platforms has attracted considerable academic attention. The pricing model for two-sided platforms proposed by Amaldoss et al. provides a theoretical foundation for understanding the interaction among consumer heterogeneity, multi-homing behavior, and advertising strategies. However, a series of idealized assumptions within the model present limitations when applied to real-world scenarios. This paper offers a systematic review and critical analysis of the model, identifying key issues in aspects such as consumer representation, advertiser behavior, platform strategy space, and market structure assumptions. Based on these insights, several extensions are proposed, including the introduction of continuous advertising aversion levels, endogenous attention allocation mechanisms, advertiser heterogeneity and budget constraints, asymmetric platform capabilities, and a dynamic game framework. Through structural modifications and mechanism enhancements, the model’s behavioral realism and practical explanatory power are significantly improved, offering valuable references for the development of platform pricing theory and its practical implementation.
Study on the Coordination Mechanism of Blockchain-Based Cross-Chain Traceability Systems for Food Supply Chains
Addressing the issues of insufficient information sharing and low coordination efficiency in food supply chain cross-chain traceability, this study proposes a coordination mechanism based on blockchain technology. We innovatively construct a Stackelberg game model consisting of a "pork supply chain" (upstream) and a "frozen dumpling supply chain" (downstream). By introducing the concept of the "cost threshold effect," we quantify the critical conditions for investment in blockchain technology and propose, for the first time, a "Blockchain Technology Investment Decision Matrix" to define the technical adaptation boundaries under various cost-preference combinations. Numerical simulations validate the effectiveness of blockchain in reducing inventory costs for the upstream supply chain and expanding the potential market for the downstream supply chain. The findings reveal a significant cost threshold for blockchain application and suggest that enterprises should dynamically adjust investment strategies based on a dual-dimensional "cost-preference" framework—for instance, prioritizing deployment for high-value-added products or sharing costs through consortium chains for SMEs. This research provides a theoretical framework for coordination mechanisms and empirical evidence for government subsidy policies and corporate investment optimization.
GIS-Based Ecological Sensitivity Analysis of Baoji City
Optimized territorial development and intensive land use constitute an important part of ecological civilization construction. Ecological sensitivity analysis provides an important basis for optimizing territorial spatial planning and land-use development, while also contributing to the sustainable development of the regional ecological environment. With the support of GIS technology, this study selected five ecological sensitivity factors, namely elevation, slope, water bodies, NDVI, and land-use type. The Analytic Hierarchy Process (AHP) was employed to determine factor weights, and spatial overlay analysis was used to quantitatively assess ecological sensitivity. The results were classified into four categories: highly sensitive, moderately sensitive, low-sensitive, and non-sensitive areas. On this basis, a comprehensive analysis of each ecological sensitivity zone was conducted, yielding both single-factor and integrated ecological sensitivity assessment results for Baoji City. Finally, corresponding suggestions for zoned protection and development were proposed for the construction of the Guanzhong Plain Urban Agglomeration.
From Scrolling to Travelling: How TikTok's Micro-Gamification and Recommendation Cues Shape Destination Visit Intentions Among Nepalese Users
The rapid proliferation of short-video platforms like TikTok has transformed how individuals discover and select travel destinations, particularly in emerging markets such as Nepal, where tourism is vital for economic growth. This thesis investigates the psychological mechanisms through which TikTok's content influences users' intention to visit destinations. Drawing on the Stimulus–Organism–Response paradigm, the study integrates two rarely combined sets of antecedents: micro-gamification mechanisms (mastery and narratives) and recommendation cues (perceived accuracy and perceived serendipity) for TikTok context. These four stimuli are hypothesized to trigger two parallel psychological states—cognitive flow experience and affective destination attachment—which jointly explain users’ intention to visit a portrayed destination. A survey of 218 active TikTok users was analysed through PLS-SEM. Results show that perceived recommendation serendipity (β = 0.331, p < 0.001) and accuracy (β = 0.319, p < 0.001) are the strongest drivers of destination attachment, while mastery enhances both attachment (β = 0.234, p < 0.01) and flow (β = 0.276, p < 0.01). Narratives exert only marginal influence on flow experience while insignificant for destination attachment. Flow experience (β = 0.416, p < 0.001) and destination attachment (β = 0.312, p < 0.001) significantly predict visit intention, with both partially mediating the stimulus–response chain. Post-hoc multi-group analysis (MGA) indicates no significant gender moderation, suggesting model generalizability across demographics. Control variables like age and income showed negligible influence. The study advances tourism-psychology theory by modeling a complete S-O-R sequence for short-form video platforms and offers evidence-based guidance to destination marketers, content creators, and platform engineers in emerging markets.
Research on the Impact of ESG Performance on Corporate Value in Listed Companies
Against the backdrop of the deepening global sustainability concept, ESG (Environmental, Social, and Governance) has transcended the boundaries of traditional corporate social responsibility, evolving into a core analytical tool for assessing a company's long-term value creation capacity and sustainable development efficacy. To explore the impact of listed companies' ESG performance on corporate value, this study adopts a risk premium perspective, utilizing data from China's A-share market between June 2019 and December 2024, along with the ESG evaluation system of the China Securities Index Co., Ltd. and the CSMAR database. It conducts an in-depth analysis of the risk premium characteristics of listed companies' ESG performance. By employing empirical methods such as univariate portfolio analysis and panel regression models, while controlling for industry and time fixed effects, the study verifies the existence of ESG risk premiums in China's A-share market. The empirical results reveal that companies with superior ESG performance exhibit lower stock return premiums. Further analysis indicates that this risk premium primarily stems from the reduced environmental, policy, and reputational risks associated with high ESG performers, leading to correspondingly lower risk compensation demanded by investors.
The Impact of State-owned Capital Participation on Stock Returns of Listed Family Firms
Against the background of China's mixed-ownership reform, reverse mixed reform featuring state-owned capital participation in private family firms has gradually become a critical path to optimize corporate governance and boost market performance. This paper takes China's A-share listed family firms from 2018 to 2022 as the research sample, and empirically examines the impact of state-owned capital participation on stock returns of listed family firms through descriptive statistics, correlation analysis, baseline regression and robustness test. The results show that state-owned capital participation significantly improves the stock returns of family firms, verifying the governance supervision effect and resource support effect of state-owned shareholders. After replacing the core variable measurement method and adopting the fixed effect model for robustness test, the conclusion remains stable. This study enriches the research on the economic consequences of reverse mixed reform and provides empirical evidence for family firms to optimize equity structure and enhance market value.
Research on the Impact of China's Digital Inclusive Finance Development on Residents' Consumption Structure
With the continuous deepening of digital economy construction, the importance of digital inclusive finance in economic development has become increasingly prominent. Consumption is the endogenous driving force for building a new development pattern, and expanding domestic demand is the strategic basis for realizing the "dual circulation." To achieve high-quality development of China's economy, we must pay attention to the upgrading of residents' consumption structure while promoting the improvement of their consumption level. Based on panel data from 31 provinces, autonomous regions, and municipalities in mainland China from 2011 to 2021, this paper constructs a two-way fixed effect model and an intermediary effect model for empirical research. The results show that the development of digital inclusive finance in China can promote the upgrading of residents' consumption structure. This promotion effect has a heterogeneous impact on urban and rural residents, being more pronounced in urban areas. Furthermore, digital inclusive finance promotes the upgrading of residents' consumption structure through both direct and indirect channels. Directly, it has revolutionized payment methods, facilitating consumer payments. Indirectly, it has increased residents' net property income. These findings provide empirical evidence and policy references for leveraging digital inclusive finance to expand domestic demand and achieve high-quality economic development.
Financial Deepening, Credit Behavior and Credit Efficiency: Evidence from Urban Commercial Banks in China
In recent years, China's banking sector has experienced significant financial deepening and structural transformation. Urban commercial banks, as an important component of the financial system, play a crucial role in allocating financial resources and supporting regional economic development. This paper examines the relationship between financial deepening, bank credit behavior, and credit efficiency using data from urban commercial banks in China. The study analyzes how financial deepening influences credit allocation and improves credit efficiency through changes in banks’ lending behavior. The results suggest that financial deepening significantly enhances credit efficiency by improving information transparency, strengthening competition, and optimizing credit allocation. Meanwhile, credit behavior acts as an important transmission mechanism through which financial deepening affects credit efficiency. The findings provide policy implications for improving financial reforms and strengthening the role of urban commercial banks in economic development.
An Empirical Study on the Applicability of the CAPM Model in the Shanghai A-Share Market
The Capital Asset Pricing Model (CAPM) is widely used to explore the efficiency of China's stock market, and the theory of securities market efficiency also serves as the foundation for studying whether CAPM is applicable to China's stock market. This paper selects the weekly returns of the top 18 enterprises by market capitalization in the Shanghai A-share market from January 2020 to December 2022 as the research object, conducts an empirical analysis on the applicability of CAPM in the Shanghai A-share market, and performs the Fama-Macbeth test on the empirical results. It is concluded that CAPM has limited applicability in China's stock market.
The Impact of Investor Heterogeneous Beliefs on Stock Returns in China ‘s A-Share Market
Traditional asset pricing theory, grounded in strict assumptions of homogeneous investor beliefs and market efficiency, struggles to adequately explain the widespread irrational price fluctuations observed in China’s stock market. With the development of behavioral finance, heterogeneous beliefs—a key variable capturing differences in investor opinions—offer a new perspective for understanding market inefficiency. This analytical perspective aligns more closely with the structure of China's stock market, which is predominantly composed of retail investors. Using A-share market data from January 2007 to August 2025, this study selects adjusted turnover rate and idiosyncratic volatility as proxies for heterogeneous beliefs. Through portfolio analysis, Fama-MacBeth cross-sectional regression, and time-series regression, we systematically examine the impact of investors' heterogeneous beliefs on stock returns.The findings reveal that: (1) Heterogeneous beliefs significantly and negatively predict future stock returns, supporting Miller's (1977) theory of overvaluation under short-sale constraints; (2) This effect is stronger during bear markets and weaker in bull markets; (3) Over time, with improvements in market institutions, the pricing effect of heterogeneous beliefs shows a declining trend; (4) The impact of heterogeneous beliefs varies across market segments—most pronounced in the Main Board, followed by the ChiNext Board, and insignificant in the STAR Market. This research extends asset pricing theory from a behavioral finance perspective, examining its applicability within the practical context and investor structure of China's stock market. Based on the empirical findings, policy recommendations are proposed for regulatory bodies, and the study offers insights for investors to better understand cognitive biases and improve investment decision-making.
A Comprehensive Review of Research on Carbon Tax and Carbon Emissions Trading Policies in Shipping Industry
Carbon tax and carbon emissions trading are currently the two principal policy instruments for achieving carbon emission reduction. Since January 1, 2024, the shipping industry has been formally incorporated into the European Union Emissions Trading System (EU ETS). This paper integrates the development mechanisms and current status of various policies, and provides a systematic review in combination with the existing literature, with the aim of offering a reference for the future development of shipping carbon emissions system.
The Impact of Private Placement on Stock Returns
This paper explores the impact mechanism of private placement on stock returns in China's A-share market, and analyzes the differences of stock return performance under different market environments, private placement scales and issuance purposes with empirical data. The study finds that the announcement of private placement has a short-term excess return effect on stock prices, and the stock return performance is significantly affected by market trends; large-scale and small-scale private placement have more obvious positive returns than medium-scale ones, and the private placement for asset restructuring has a more significant promotion effect on corporate performance and stock returns than project financing. In addition, the discount rate of issuance and the type of subscribers also have different degrees of impact on post-issuance stock returns. This paper puts forward relevant investment suggestions for investors and regulatory suggestions for the capital market, which provides a reference for understanding the market performance of private placement in China.
IShowSpeed's China Tour: Analysis of Social Media Influencer Marketing Strategies and Effects in Cross-Cultural Communication
In the era of global digitalization, social-media influencer marketing has become a central tool in cross-cultural communication. However, existing research often focuses on strategy effectiveness within a single cultural context, leaving cross-cultural scenarios underexplored. This paper takes the 2025 China tour of IShowSpeed as a case study to systematically examine influencer marketing strategies and effects in cross-cultural communication. The study finds that the tour used four major strategies — content localization, sustaining an authentic persona, showcasing real scenarios, and cross-platform dissemination — and that these strategies produced mixed (both positive and negative) outcomes in a cross-cultural setting. Based on the analysis, the paper offers practical implications for tourism destinations seeking to leverage influencer marketing more effectively.
The Impact of AI Technology Application on Vietnamese Employees' Innovative Behavior
The rapid advancement of artificial intelligence (AI) technology is profoundly reshaping organizational operations and employee work contexts. Based on the Job Demands-Resources (JD-R) Model, this study investigates the dual-path mechanism through which AI technology application influences employee innovative behavior. Using questionnaire data collected from 478 Vietnamese employees, we employed SPSS 22.0 and AMOS 29.0 to conduct reliability and validity tests and structural equation modeling analyses. The results reveal that: (1) job insecurity negatively affects employee innovative behavior, while perceived opportunities positively affect employee innovative behavior; (2) job insecurity partially mediates the relationship between AI technology application and employee innovative behavior; (3) perceived opportunities fully mediate the relationship between AI technology application and employee innovative behavior; and (4) AI knowledge negatively moderates the relationship between AI technology application and job insecurity, while positively moderating the relationship between AI technology application and perceived opportunities. This study extends the understanding of AI's dual effects on employee behavior and provides practical implications for organizational management in the AI era.
The Impact of Artificial Intelligence on Executive Compensation in Listed Companies
As artificial intelligence is elevated to a national strategic level and deeply integrated into the real economy, its core role in driving industrial upgrading and economic growth has become increasingly prominent. Executives, as key decision-makers in corporate strategy, have compensation levels that not only relate to agency costs and incentive effectiveness but also influence the fairness and efficiency of internal income distribution within enterprises against the backdrop of technological change. Based on data from A-share listed companies from 2007 to 2023, this study employs textual analysis to construct a firm-level indicator of AI application and systematically examines the impact of AI on executive compensation. The findings are as follows: First, AI significantly increases the compensation levels of executives in listed companies. This conclusion remains robust after addressing endogeneity concerns through methods such as instrumental variable approaches and conducting a series of robustness tests. Second, mechanism tests reveal that AI indirectly promotes the growth of executive compensation through three pathways: alleviating financing constraints, enhancing enterprise total factor productivity, and increasing the level of executive human capital. Third, the level of corporate governance plays a negative moderating role between AI and executive compensation, suggesting that sound internal governance mechanisms can effectively curb the potential expansion of managerial power and the capture of excess returns by executives during technological change.
Vegetation Greening in Response to Ecological Restoration Programs in Shaanxi Province, China
Vegetation constitutes the structural backbone of terrestrial ecosystems, regulating carbon exchange, water cycling, and energy flux at regional scales. The Normalized Difference Vegetation Index (NDVI), derived from satellite remote sensing, provides a robust proxy for vegetation vitality and has been extensively adopted in long-term ecological monitoring. This study examines the spatio-temporal dynamics of vegetation coverage across Shaanxi Province, northwestern China, over the period 2000–2019, using MODIS MOD13C1 NDVI data. Growing-season (May–October) composites were generated via the Maximum Value Compositing (MVC) method, and pixel-wise temporal trends were quantified through ordinary least-squares regression. Results indicate: (1) spatially, vegetation coverage follows a pronounced south-to-north declining gradient, with high-coverage zones (NDVI > 0.6) concentrated along the southern Qinling foothills and northern Daba Mountains, representing approximately 32.85% of the provincial area; (2) temporally, provincial mean NDVI increased from 0.4488 in 2000 to 0.5405 in 2019, an overall gain of ~20.4%; (3) 98.07% of pixels exhibited positive trends, concentrated in central-southern Shaanbei where afforestation programs were intensively implemented, while declining trends (~1.93%) were confined to the Guanzhong urban agglomeration, attributable to cropland conversion and urban expansion. These findings offer a quantitative baseline for regional ecological assessment and policy evaluation in Shaanxi Province.
The Impact of the financial crisis on the value of A-share enterprises in China
Enterprise value creation is heavily influenced by the macroeconomic environment. As an extreme manifestation of environmental uncertainty, the financial crisis can be transmitted to the real economy through trade channels and financial channels, affecting firms' production, operation and strategic decision-making. Taking the 2008 financial crisis as a quasi-natural experiment, this paper selects A-share main board listed companies from 2004 to 2023 as samples and uses the difference-in-differences (DID) model for empirical research. Robustness checks are conducted through counterfactual analysis and replacing firm value variables. This paper further investigates whether the impacts differ among firms with different ownership types.The results show that the outbreak of the financial crisis significantly inhibits enterprise value creation. Financial constraints serve as one channel through which the financial crisis affects firm value, exerting a partial mediating effect. The inhibitory effect of the financial crisis on value creation is stronger in non-state-owned enterprises, and the mediating effect of financial constraints is also more significant.
Research on the Driving Mechanism and Performance Improvement of Industrial Chain Integration of Fuping Persimmon
Industrial chain integration is the core path to enhance the competitiveness of agricultural characteristic industries and boost the revitalization of rural industries. Taking Fuping persimmon industry as the research object, based on the Resource-Based View, Dynamic Capability Theory and Institutional Theory, this paper constructs a theoretical model of "External Environment-Enterprise Resources-Enterprise Capabilities-Integration Performance", and introduces value co-creation as a moderating variable. Through a questionnaire survey, 365 valid samples from various subjects in the persimmon industrial chain were collected, and AMOS 24 software was used for structural equation model fitting and hypothesis testing to explore the driving mechanism and effect path of Fuping persimmon industrial chain integration. The results show that the external environment has a significant positive impact on enterprise resources, enterprise capabilities and industrial chain integration performance; enterprise resources and enterprise capabilities have a positive effect on integration performance respectively, and both play a chain mediating role between the external environment and integration performance; value co-creation positively moderates the relationship between the external environment and industrial chain integration performance. The study also finds that Fuping persimmon industrial chain faces problems such as the lack of a collaborative mechanism, insufficient resource transformation capacity and lagging product innovation. Accordingly, targeted optimization countermeasures are put forward to provide practical reference for the integration and upgrading of agricultural characteristic industrial chains.
Opportunities and Challenges of GIS in the Era of Artificial Intelligence
In the era of artificial intelligence, the deep integration of Geographic Information Systems (GIS) and autonomous vehicles is driving a paradigm shift in spatial decision-making from human experience to algorithmic autonomy. Through interdisciplinary analysis, this paper reveals three key opportunities and structural challenges for GIS-enabled autonomous driving. Technologically, the intelligent evolution of high-precision maps provides vehicles with centimeter-level spatial awareness, while multi-source perception fusion significantly enhances positioning robustness in complex scenarios. Vehicle-road coordination mechanisms have restructured traffic resource allocation models. However, technological progress faces fundamental contradictions: dynamic updates of high-precision maps are constrained by 40% positioning failure in satellite-obscured areas and the exorbitant cost of LiDAR, sparking data ownership disputes; multi-source heterogeneous data fusion encounters 20cm-level coordinate system conversion errors and semantic gaps in traffic signage; fragmented standards and institutional vacuums lead to algorithmic spatial discrimination and national security risks. The study demonstrates that GIS opportunities essentially involve transferring spatial decision-making authority to algorithms, while challenges stem from structural imbalances between technological efficacy and social governance. Future efforts should establish a tripartite governance framework integrating "federated learning updates, algorithm audits, and national security desensitization" to achieve synergistic evolution between technological innovation and spatial justice.
A Study on Financial Risk Identification and Evaluation of Bank A in Vietnam
The sound operation of commercial banks is crucial for maintaining the stability of the financial system, particularly in emerging economies. With the deepening of financial reforms and increasing market competition in Vietnam, commercial banks are facing more complex financial risks. Taking Bank A in Vietnam as the research object, this study focuses on the identification and evaluation of financial risks. A comprehensive financial risk assessment model combining the Analytic Hierarchy Process (AHP) and the Entropy Weight Method (EWM) is constructed. Based on key financial indicators, a multi-level evaluation system covering capital adequacy, asset quality, profitability, and liquidity is established. The integration of AHP and EWM effectively reduces subjectivity in indicator weighting and improves the reliability of evaluation results. Empirical analysis using recent financial data of Bank A demonstrates that the proposed model can effectively assess the bank’s financial risk level and provide useful references for financial risk management in Vietnamese commercial banks.
An empirical analysis of China's Shenzhen Composite Index based on ARIMA-GARCH model
Since the uncertainty of the stock market will affect the returns of investors, and the China Shenzhen Composite Index can basically reflect the fluctuations of the Chinese stock market, it has certain research significance to take the Shenzhen Composite index as the research object. In this paper, the stock composite price index of Shenzhen Composite Index from April 30, 1991 to May 31, 2023 (considering holidays) is selected as the sample, and the ARIMA (2,1,2) model is fitted after first-order difference for this unstable time series. Aiming at the ARCH effect in the residual series of the model, the GARCH (1,1) model is fitted, and the mean value forecast and volatility forecast of the price index of Shenzhen Composite Index from June to the end of October 2023 are carried out according to the fitted model. The final results show that the fitted model has strong short-term prediction ability, but weak long-term prediction ability. However, in general, the prediction results of ARIMA-GARCH model still have great reference value for Chinese investors.
Research on Cross-Regional Carbon Trading Cooperation between Sichuan and Chongqing
As one of the major coal-fired power generation regions, Sichuan and Chongqing rank among the top in the western region in terms of carbon emissions and have great emission reduction potential. Therefore, controlling the total carbon emissions of the two places is an important measure to achieve the goals of carbon peaking and carbon neutrality, and also an effective means to realize the green development of the Chengdu-Chongqing Twin City Economic Circle. However, drawbacks such as insufficient vitality of the carbon markets in Sichuan and Chongqing and enterprises participating only for compliance purposes have become increasingly prominent. To fulfill the dual carbon tasks, stimulate the vitality of the carbon markets in Sichuan and Chongqing, further reduce the energy intensity of the two regions and boost export trade, a cross-regional carbon trading market can be constructed in Sichuan and Chongqing relying on the Chengdu-Chongqing Twin City Economic Circle, the fourth pole of China's economic growth. By formulating cross-regional carbon trading management policies, building a cross-regional carbon trading platform, cultivating professional talents, introducing green carbon reduction technologies and other measures, the circulation of carbon resources between Sichuan and Chongqing can be promoted to realize coordinated emission reduction, joint construction and shared benefits of the two places.
The Embrace of Digitalization by the Tourism Industry: Opportunities, Challenges and Future Directions of Transformation
Against the backdrop of rapid development of information technology, digital transformation has profoundly changed the development model of the tourism industry, bringing new opportunities while posing many challenges. From theoretical and practical perspectives, this paper analyzes the role of technologies such as big data and artificial intelligence in resource integration, service optimization and business model innovation. The research shows that digital transformation can accurately grasp tourists' needs, optimize resource allocation, improve service experience and operational efficiency, and help ecological protection and cultural inheritance, promoting the sustainable development of the tourism industry. However, problems such as data security, digital divide and technological dependence have become increasingly prominent. Based on this, this paper puts forward countermeasures from the perspectives of improving laws and regulations, strengthening infrastructure construction and cultivating interdisciplinary talents, so as to provide reference for the high-quality development of the tourism industry.
Research on the Volatility Spillover Effects among Carbon Market, Energy Market, and Stock Market
With the advancement of China’s "dual carbon" goals and the operation of the national carbon market, the linkages among the carbon market, energy market, and stock market have become increasingly close. Based on the TVP-VAR-DY model, this paper investigates the characteristics and asymmetry of volatility spillovers among these three markets from both static and dynamic perspectives. The findings reveal significant and time-varying volatility spillover effects among the three markets, with asymmetry observed in both static and dynamic contexts. Major external events significantly enhance cross-market volatility spillovers and amplify this asymmetry. This study provides theoretical and empirical support for understanding volatility spillovers among the carbon, energy, and stock markets, offering insights for investor asset allocation and financial regulation.