Transactions on Economics, Business and Management Research
Transactions on Economics, Business and Management Research (TEBMR) aims to publish peer-reviewed proceedings from conferences on the theories and methods in all fields of economics, business and management.
Quantitative Measurement of Investor Sentiment Indicators and Theoretical Research on Stock Market Return Prediction
This paper, from the perspective of behavioral finance, explores the quantitative measurement methods of investor sentiment indicators and their impact on stock market returns. First, define investor sentiment and summarize its mechanism of action, and explore how sentiment factors affect the pricing efficiency of the capital market. In terms of measurement methods, this paper constructs a comprehensive investor sentiment index from the perspectives of direct questionnaires, indirect market data, and text mining, and uses principal component analysis to extract the general factors in the sentiment factors, thereby overcoming the shortcomings brought by a single indicator. An empirical analysis of China's A-share market from 2010 to 2023 shows that there is A significant non-linear relationship between investor sentiment and stock market returns: sentiment is positively correlated with returns in the short term, indicating price deviations caused by sentiment. In the long term, there is a negative correlation, indicating a rational return to the market. Further predictive models showed that VAR models with sentiment variables improved yield predictions by 15% to 20% compared to traditional financial models, especially when market volatility was high. At the same time, the sentiment of different investors has a different effect on the prediction of yields. The sentiment of institutional investors has a better predictive effect on long-term yields, while the sentiment of individual investors has a better explanatory power for short-term market volatility. This paper provides empirical support for enriching and developing behavioral finance theory, and also offers useful references for investors' investment decisions and risk control.
Investor Sentiment; Quantitative measures; Stock market returns; Predictive models; Behavioral Finance.
Copyright (c) 2026 Transactions on Economics, Business and Management Research https://creativecommons.org/licenses/by-nc/4.0
A Comparative Study on Welfare Losses of Specific Duties and Ad Valorem Duties in Monopolistic Markets
Based on the establishment of a monopoly market model, this paper conducts a comparative analysis of the welfare effects of specific tax and AD valorem tax policies. The findings show that in a monopoly market, specific taxes and AD valorem taxes have different effects on market equilibrium, consumer surplus, producer surplus, and total social welfare. By studying monopolistic markets described by linear demand functions and cost functions, we explore the pricing, output and welfare loss of monopolistic enterprises under two tax systems. The results show that the specific tax, which is a fixed unit tax rate, directly increases marginal costs, thus resulting in a small increase in monopoly prices but a significant decrease in output. AD valorem taxes, which are levied proportionally, indirectly affect pricing, and the extent of their welfare loss depends on the rate of tax and the elasticity of demand. In general, AD valorem taxes cause less unnecessary loss than specific taxes because AD valorem taxes have a certain self-regulating function, which to some extent can mitigate the adverse effects of monopoly pricing on social welfare. But when the elasticity of market demand is low or the degree of monopoly is high, the gap in welfare loss between the two will be smaller. In addition, this paper also analyzes issues such as tax revenue, administrative costs, and the possibility of policy implementation, and argues that AD valorem tax has certain advantages in terms of the stability of tax revenue and the effectiveness of anti-monopoly, but there are also problems in terms of collection costs and regulatory difficulty. Therefore, the findings of this study provide some reference value for the government in formulating tax policies in monopolistic industries. It is recommended to choose appropriate tax methods based on the characteristics of different industries, market conditions and policy goals to achieve the greatest social benefits.
Specific taxation; AD valorem tax; Monopoly market; Loss of benefits; Unnecessary loss.
Research on the Facilitating Role of the Digital Economy in Industrial Structure Upgrading -- An Empirical Analysis Based on Panel Data from Anhui Province
The digital economy is playing an increasingly prominent role as a key driver for promoting high-quality economic development and upgrading industrial structure. This study utilizes panel data from 16 prefecture-level cities in Anhui Province from 2011 to 2022 to conduct an empirical analysis. The results demonstrate that rapid progress in the development of the digital economy positively contributes to industrial structure upgrading, facilitating both the advancement and rationalization of the industrial structure. Based on the research findings, the following recommendations are proposed: local governments in Anhui Province should implement policies to support the sustained and healthy development of the digital economy and improve the integration of industry digitization and digital industrialization. By enhancing the application of digital technology in industries and increasing the proportion of digital technology adoption, continuous efforts should be made to strengthen the integration of industry and digital technology, improve the level of industrial informatization and intelligence, thereby facilitating the enhancement of industrial structure.
Digital Economy; Industrial Structure Upgrading; Enabling Effect; Anhui Province.
Research on Optimization of Fresh Cold Chain Based on PCM Passive Temperature Control and Intelligent Algorithms
Against the background of rapid development in the fresh food industry and increasing demand for green and low-carbon logistics, traditional cold chain systems face prominent pain points such as unstable temperature control, high energy consumption, and inefficient scheduling. Taking Muyangsu Cold Chain Co., Ltd. as the research object, this paper proposes a comprehensive optimization scheme integrating PCM passive temperature control, intelligent algorithms, and 5G Internet of Things. By constructing a multi-objective optimization model, introducing improved Sparrow Search Algorithm and Reinforcement Learning-based Whale Optimization Algorithm, and building a combined prediction model, the study systematically optimizes temperature stability, scheduling efficiency, and risk management. The results show that the proposed scheme significantly reduces energy consumption and loss rate while improving logistics efficiency and service reliability. This research provides a replicable technical framework and practical reference for the high-quality development of the fresh cold chain. In addition, this study conducts in-depth investigation and analysis of the company’s current operation status and existing problems. The research systematically constructs a multi-dimensional risk assessment and prevention system for cold chain transportation. The proposed technical solution is verified through simulation and real-scenario testing. The research results offer clear guidance for the practical transformation and upgrading of cold chain enterprises. It also provides valuable insights for promoting standardized and intelligent development in the fresh cold chain industry.
Fresh cold chain; CPM passive temperature control; intelligent algorithm; cold chain optimization.
The Research on the Influence of Chairman’s Hometown Identity on Labor Cost Stickiness of State-owned Enterprises
This paper investigates the impact of the chairman’s hometown identity on labor cost stickiness within Chinese state-owned enterprises (SOEs). Using a sample of Shanghai and Shenzhen A-share listed SOEs from 2007 to 2023, the empirical results show that SOEs with local chairmen exhibit weaker labor cost stickiness. This finding remains robust after a series of robustness checks, including instrumental variable analysis, PSM tests, HDFE models, and alternative measures for the key explanatory variable. Mechanism tests reveal that local chairmen reduce labor cost stickiness primarily through salary reductions rather than layoffs. Moderation effect analyses confirm that local chairmen, by sharing a cultural background with employees and thus gaining their trust and support, can effectively reduce labor cost stickiness. Finally, a series of heterogeneity analyses are conducted from three perspectives: external supervision, market environment, and internal corporate governance. The results indicate that when firms face negative conditions such as weak external supervision, poor market environments, or inferior internal governance, the informal institution of the chairman’s hometown identity becomes effective, significantly reducing labor cost stickiness.
State-Owned Enterprises; Hometown Identity; Cost Stickiness; Salary Adjustment.
Government Procurement Contract Financing Policy and Total Factor Productivity
Government Procurement Contract Financing Policy (referred to as the "government procurement loan" policy) represents a crucial institutional innovation in fiscal and financial synergy aimed at supporting the development of firms. Exploiting the phased implementation of the "government procurement loan" policy across regions as a quasi-natural experiment, this paper uses A-share listed firms from 2015 to 2024 as the research sample and employs a difference-in-differences (DID) approach to examine the impact of the policy on firm total factor productivity (TFP). The findings show that the "government procurement loan" policy significantly promotes firm total factor productivity. Mechanism analysis indicates that the policy mainly operates through three channels: alleviating financing constraints, stimulating corporate innovation, and optimizing labor resource allocation. Further analysis reveals that the effect is more pronounced among firms with lower audit quality, firms in high-tech industries, and private enterprises. From the perspective of total factor productivity, this paper expands the research dimensions of government procurement policy evaluation and uncovers the mechanisms through which the "government procurement loan" policy affects firms’ production efficiency. As an innovative financing policy based on government procurement contracts, the policy effectively activates existing government resources and enhances firm production efficiency while facilitating the targeted allocation of financial capital without increasing fiscal burdens. Therefore, future policy optimization should further exploit the credit-enhancing role of government procurement contracts, improve the closed-loop management mechanism of tripartite accounts, and implement differentiated support according to firm characteristics to better promote firm total factor productivity.
Government Procurement Contract Financing Policy; Total Factor Productivity; Financing Constraints; Corporate Innovation; Labor Resource Allocation.
Climate Shocks and Systemic Risks in the Real Economy
As global warming becomes increasingly severe,frequent extreme weather events and the accelerated transition to a low-carbon economy have made climate shocks a significant factor affecting the operation of the real economy and the stability of financial markets.This paper uses data from Chinese A-share listed companies from 2007 to 2024 as the initial research sample to empirically examine the impact of climate shocks on the systemic risk of real enterprises.The study finds that climate shocks significantly increase corporate systemic risk,and this conclusion remains valid after a series of robustness tests.Mechanism analysis indicates that climate shocks amplify systemic risk by exacerbating financial distress,reducing production efficiency,and worsening information asymmetry.Heterogeneity analysis shows that green finance reforms,climate finance innovations,and green fiscal policies effectively mitigate the adverse transmission of climate shocks to corporate systemic risk by alleviating information asymmetry,providing risk hedging tools,and enhancing corporate resilience.Moderation analysis reveals that ESG performance significantly mitigates the positive impact of climate risk on corporate systemic risk.This risk-mitigating effect primarily stems from substantial contributions from the environmental (E) and governance (G) dimensions,while the social (S) dimension plays a negligible role.Further analysis indicates that the upward pressure of climate risk on systemic risk in the real economy is primarily driven by transition risk,with the impact of physical risk being relatively limited.These findings align with the logic that climate shocks ultimately elevate systemic risk by deteriorating corporate operations and financial conditions and exacerbating risk transmission.This conclusion provides theoretical references and practical insights for regulators to improve climate risk prevention and control systems,guide enterprises in proactively managing climate risks,and guard against systemic financial risks.
Climate shocks; Systemic risks in the real economy; Financial distress; ESG; Transition risks.
Research on Cost Control Optimization of Yango Group Real Estate Company
Against the background of increasingly fierce competition and stricter government regulation in the real estate industry, cost control has become critical to the survival and development of real estate enterprises. Taking Yango Real Estate Company as the research object, this paper analyzes its current cost control status, organizational structure, institutional system and cost composition data, and identifies prominent problems such as outdated management concepts, insufficient awareness of full-staff cost control, ineffective control of labor costs, overspending of marketing expenses, poor management of material costs and delayed feedback of dynamic costs. The root causes lie in insufficient authorization of cost control departments, imperfect responsibility–power–benefit system, lack of collaborative culture and inadequate accumulation of cost data. Based on relevant theories of cost control, this paper puts forward targeted optimization strategies, including establishing full-staff and all-round cost control awareness, rationally allocating and controlling labor costs, strengthening marketing and material cost control, and feeding back and adjusting dynamic costs in a timely manner. The conclusions of this study can help Yango Real Estate improve its management level, reduce costs and increase efficiency, and also provide reference for cost control practices of other real estate enterprises.
real estate enterprise; cost control; cost optimization.
Patient Capital and Corporate Human Capital Upgrading: Evidence from Chinese Listed Firms
As economies transition from demographic dividends to human capital-driven growth, patient capital—investment allocations focused on long-term value creation—emerges as a critical driver of corporate competitiveness. Using a panel dataset of Chinese A-share listed firms from 2007 to 2023, this paper investigates the impact of patient capital on firm-level human capital and explores its underlying mechanisms. We find a robust positive effect of patient capital on corporate human capital upgrading. Mechanism analyses reveal that this effect operates through three channels: capital deepening, the expansion of research and development (R&D) investments, and strengthened internal and external monitoring. Furthermore, this positive effect is more pronounced among state-owned enterprises (SOEs), firms located in economically developed eastern regions, and those without CEO duality. Our findings provide micro-level evidence that patient capital can facilitate the transition from demographic to human capital-driven growth, informing policies aimed at optimizing long-term investments and talent structures.
Patient Capital; Corporate Human Capital; R&D Expansion; Corporate Monitoring.
Government Regulation of Scenic Spot Ticket Prices: Evidence from Nanjing
With the rapid development of China’s economy, the number of domestic tourists has been increasing year by year. As a popular tourist destination, Nanjing has experienced sustained growth in visitor arrivals. Tourists’ rising demand for high-quality travel experiences places greater pressure on the service standards of scenic areas. However, issues such as unreasonable ticket prices, inadequate management, and disordered site conditions have become key factors undermining the tourist experience. Although these problems appear to center on ticket pricing, their underlying causes are multifaceted. This paper examines how ticket price regulation can be deepened under government oversight, analyzes the current state of ticket price management in Nanjing’s scenic areas, identifies existing problems, and proposes corresponding policy measures. The goal is to rationalize ticket prices, improve the structure of the tourism economy, and support the sustainable and healthy development of Nanjing’s tourism industry.
Government regulation; Ticket prices; Nanjing.
The Impact and Mechanism of Green Bonds on Corporate Carbon Emissions—An Empirical Study of Multi-Period DID under the TOE Framework and Taking into Account TWFE Weighted
Green finance is widely regarded as an important policy tool for promoting the low-carbon transformation of enterprises, but its micro-governance effects and intrinsic mechanisms still need systematic testing. Based on data from A-share listed companies in Shanghai and Shenzhen from 2010 to 2023, this paper uses green bond policy as a quasi-natural experiment and employs a difference-in-differences model to identify the impact of green bonds on corporate carbon emissions. The study finds that green bond issuance significantly reduces corporate carbon emissions, a conclusion that holds true after multiple robustness tests. Mechanism testing shows that green bonds reduce corporate carbon emissions by alleviating corporate financing constraints, strengthening green investment incentives, promoting the simultaneous improvement of the quantity and quality of green innovation, and enhancing executives' green awareness. Further heterogeneity analysis based on the TOE framework reveals that the above-mentioned emission reduction effects are more significant in enterprises with higher levels of digital transformation, sufficient reserves of high-tech talent, strong risk-bearing capacity, and better ESG performance, as well as in regions with higher industry competition intensity and higher levels of environmental regulation. This paper reveals the path of green bonds in reducing corporate carbon emissions from a comprehensive perspective of the linkage between financing structure optimization, corporate governance improvement, and green technology innovation, providing new empirical evidence for improving the green finance system and promoting corporate green development.
green bonds; corporate carbon emissions; TOE framework; difference-in-differences model.
National Agricultural Green Development Pioneer Zone and Enterprise Total Factor Productivity: Empirical Evidence from Chinese Agricultural Enterprises
The construction of the National Agricultural Green Development Pioneer Zone represents a crucial strategic direction for promoting green transformation in agriculture and advancing high-quality agricultural development. This paper treats the green agricultural development pilot zone initiative as a quasi-natural experiment, selecting A-share agricultural listed enterprises from 2005 to 2024 as the research sample, and employs the staggered difference-in-differences (DID) method to empirically examine the impact of the green agricultural development pilot zone policy on agricultural enterprise total factor productivity (TFP). The findings reveal that: (1) The green agricultural pilot zone policy effectively enhances agricultural enterprise TFP, and this conclusion remains robust after conducting a series of robustness tests including parallel trends test, placebo test, and PSM-DID test. (2) Heterogeneity analysis demonstrates that the policy effects are more pronounced in asset-light enterprises, enterprises in central regions, and major grain-producing areas. (3) Mechanism analysis indicates that the policy operates through three pathways: increasing government subsidies, enhancing technological innovation, and promoting industrial agglomeration. This study evaluates policy effects from the enterprise micro-level perspective, providing empirical support and policy implications for China's continued advancement of green agricultural development and improvement of the agricultural support policy system.
National Agricultural Green Development Pioneer Zone; Agricultural enterprise total factor productivity; Government subsidies; Technological innovation; Industrial agglomeration.
The Revision of Antitrust Law and Corporate Innovation
As China's economy transitions to a stage of high-quality development, strengthening antitrust measures has become a core task for improving competition policy. However, its impact mechanism and effect on micro-level corporate innovation remain unclear. Using a sample of A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2018 to 2024, and employing the implementation of the newly revised Antitrust Law in 2022 as a quasi-natural experiment, this study systematically examines the impact of antitrust policy on corporate innovation level and innovation quality using a Difference-in-Differences (DID) approach. The findings show that the new Antitrust Law significantly suppresses both the total innovation output and the proportion of exploratory innovation among firms with high market power. This conclusion remains robust after a series of tests, including parallel trend tests, placebo tests, and PSM-DID analysis. Heterogeneity analysis reveals that the aforementioned inhibitory effect is more complex in coastal regions and high-tech industries: the suppression of total innovation is stronger, but the relative suppression of exploratory innovation is weaker. Mechanism analysis indicates that the law compresses firms' innovation resource space through two pathways: exacerbating financing constraints and intensifying market competition. These results are consistent with the theoretical expectation that antitrust law inhibits innovation by strengthening resource constraints and risk-bearing pressure. This study provides micro-level evidence for evaluating the economic consequences of antitrust law revisions and offers important insights for refining competition policy design and stimulating market innovation vitality.
Antitrust Law; Financing Constraints; Market Competition; Corporate Innovation.
Enterprise online sales and extreme changes in stock prices
With the continuous development of the Internet, online sales are increasingly becoming an important sales channel for enterprises, and its impact on the capital market is also increasing. This article uses the online sales data of A-share listed firms between 2015 and 2024 to study the effect of online sales of enterprises on the soar and crash of stock prices. The study found that online sales, on the one hand, suppresses the soar and crash of stock prices by improving the transparency of information, and on the other hand, the abnormal fluctuations of online sales data affect investors' judgement, thus promoting the soar and crash of stock prices. The regression results of sub-samples show that the impact of online sales data on the soar and crash of stock prices is more obvious in enterprises with duality and the rate of separation of company’s shareholding and management. Mechanism analysis shows that online sales affect extreme changes in stock prices by increasing the number of Baidu searches, news and improving the quality of financial information. The above results are consistent with the logic that online sales can not only improve the information environment, but also amplify the irrational investment of investors. This conclusion is of certain significance for listed companies to improve information disclosure, strengthen corporate governance and prevent extreme fluctuations in stock prices.
Online sales; stock prices soar and crash; information asymmetry; abnormal fluctuation of sales data.
Research on Copyright Issues of Artificial Intelligence-Generated Works
With the advancement of artificial intelligence technology, artificial intelligence-generated works have been widely integrated into all aspects of social life. How to protect their copyright is an inevitable issue in contemporary legal practice. On the premise of meeting the requirements of originality, intellectual achievement attribute and tangible reproduction, artificial intelligence-generated works can constitute works in the sense of copyright law and have the rationality of being protected by copyright law. Taking the principle of closest connection and the principle of encouraging creation as the core, the copyright should be mainly attributed to the user. At the same time, a multi-dimensional mechanism including contract agreement, technical measures and liability sharing should be adopted to balance the interests among developers, investors and users, exert the maximum institutional efficiency, and enable it to continue to shoulder the mission of encouraging creation and prospering culture. Artificial intelligence-generated works; Copyright law; Work attribute; Right attribution.
Artificial intelligence-generated works; Copyright law; Work attribute; Right attribution.
Platform Ecosystem Embeddedness and Enterprise Total Factor Productivity: An Empirical Analysis of A-Share Listed Companies from 2007 to 2020
In the digital economy era, the platform ecosystem, as a new paradigm of innovation in business ecosystems, has driven the transformation of industrial organization forms from traditional linear division of labor to networked collaboration, creating conditions for the improvement of enterprises' total factor productivity (TFP). Based on the data of A-share listed companies from 2007 to 2020, this paper studies the impact and mechanism of platform ecosystem embeddedness on enterprises' TFP. The results show that platform ecosystem embeddedness has a significant positive impact on enterprises' TFP, and this conclusion remains robust after robustness tests such as replacing samples, changing variables, propensity score matching (PSM) and instrumental variable method. This positive effect is more significant in state-owned enterprises, enterprises without CEO duality and enterprises in the eastern region. Mechanism analysis indicates that platform ecosystem embeddedness promotes the improvement of enterprises' TFP through three paths: enhancing enterprise resilience, promoting industrial chain integration and alleviating resource mismatch. This paper clarifies the internal logic of platform ecosystem embeddedness affecting enterprises' TFP, enriches the research in related fields, and provides empirical reference and practical guidance for enterprise operation and the government's formulation of digital economy policies.
Platform Ecosystem Embeddedness; Enterprise Total Factor Productivity; Enterprise Resilience; Industrial Chain Integration; Resource Misallocation.
Arbitrage Opportunity Identification Model Based on Stochastic Modelling of Implied Volatility Surfaces
The paper considers insufficient fit accuracies, fragmented modelling and identification, and high misjudgement rate with fixed thresholds in implied volatility surface modelling and arbitrage opportunity identification. It proposes an in-depth algorithm based on stochastic coefficient Vol Transformer-adaptive arbitrage threshold (SC-VT-AT), which integrates the stochastically coefficient mechanism of Vol Transformer. The algorithm employs stoically coefficients to describe the technically dynamic features of implied volatility surface, and uses Vol Transformed to efficiently extract the two-dimensional features of the currency size and time to expiration. In parallel, it develops an adaptive threshold module to dynamically update the arbitrage decision criteria based on real-time market volatility factors and simultaneously perform surface modelling & arbitrage opportunities identification. The results on daily CSI 300 ETF options from 2019 to 2023 show the RMSE, MAE, and QLIKE losses of the proposed algorithm are smaller than the ones of traditional comparison methods such as SABR, ordinary Vol Transformer, and GAN. arbitrage identification accuracy reaches 86.7%, data processing time per trading day is 0.87 seconds, annualized return of the simulated arbitrage scheme is 12.3%, and maximum drawdown is only 4.1%. The proposed algorithm can efficiently improve the accuracy of surface modelling with minimizing misjudgement and missing judgment of arbitrage offers in real-times and trading practicality. It can also provide an efficient integrated decision tool to quantitatively track the options markets.
Options; Implied Volatility Surface; Stochastic Modelling; Vol Transformer; Adaptive Threshold; Arbitrage Identification.
Green Credit Policies Enhance Firms’ Innovation Performance
Green credit regulation embeds environmental criteria into bank lending decisions and may therefore influence firms’ financing conditions and innovation behavior. Based on Chinese A-share listed firms from 2008 to 2023, this study treats the 2012 Green Credit Guidelines as an external policy shock and evaluates their effect on corporate innovation performance. By integrating environmental risks into credit decisions, it improves resource allocation and incentivizes technological innovation. The effect works through three channels: strengthening green orientation, easing financing constraints, and promoting technological upgrading. The innovation effect is stronger in non-competitive industries, eastern and central regions, and state-owned enterprises, suggesting moderation by industry competition, regional finance, and ownership type. Green credit thus serves not only environmental governance but also firm-level technological progress. The findings provide firm-level evidence on how credit-based environmental regulation affects innovation decisions and offer implications for improving the design of green finance policies.
Green Credit Policy, Corporate Innovation, Green Finance, Credit Resource Allocation, High-quality Development.
The Dynamic Impact of Macroeconomic Uncertainty on Corporate Accounting Policy Choices
Against the backdrop of an increasingly complex macroeconomic environment, macroeconomic uncertainty has become an important external factor shaping corporate decision-making. Using a sample of Chinese A-share listed firms, this paper examines the impact of macroeconomic uncertainty on corporate accounting policy choices and their dynamic features. The results show that macroeconomic uncertainty significantly affects corporate accounting policy choices and, on average, strengthens firms’ strategic financial reporting behavior. Further analysis indicates that this effect is not limited to the current period, but persists in the short run and gradually weakens over time. In addition, the effect of macroeconomic uncertainty on corporate accounting policy choices is more pronounced among firms facing stronger financing constraints. This study extends the literature on the determinants of corporate accounting policy choices from the perspective of changes in the macroeconomic environment, and highlights the intertemporal response of firms’ financial reporting behavior to external uncertainty shocks. The findings provide new empirical evidence for understanding corporate financial reporting decisions under macroeconomic uncertainty and offer useful implications for regulators, investors, and corporate managers.
Macroeconomic uncertainty, accounting policy choices, dynamic effects, strategic financial reporting.
The Impact of Global Central Bank Digital Currency Policies on Cross-Border Capital Flows
As central bank digital currencies (CBDCs) move from conceptual exploration toward institutionalized pilots and cross-border applications, their implications for the international financial system extend well beyond payment innovation itself and increasingly reshape the institutional conditions of cross-border capital flows. From the perspective of policy design, this paper systematically examines the mechanisms through which global CBDC policies affect cross-border capital flows and the heterogeneous consequences they generate across countries. The paper identifies four core policy dimensions of CBDCs, namely cross-border access, interoperability, holding limits and remuneration, and regulatory embedding, and on this basis develops an analytical framework for understanding their effects on capital mobility. It argues that CBDC policies influence the scale, structure, and volatility of cross-border capital flows mainly through four channels: lower transaction costs, stronger asset substitution, bank disintermediation, and programmable regulation. Specifically, CBDCs may, on the one hand, reduce frictions in cross-border payment and settlement, improve the efficiency of international capital allocation, and expand the scale of capital movements. On the other hand, they may also intensify capital flow volatility, currency substitution, and financial fragility by reinforcing safe-asset preferences, weakening the buffering role of the banking system, and lowering the cost of capital withdrawal. The analysis further shows that the international effects of CBDC policies are highly asymmetric across countries. For major currency economies, CBDCs are more likely to strengthen international currency attractiveness and capital concentration effects, whereas for emerging market and developing economies, their cross-border expansion is more likely to generate digital currency substitution, capital outflow pressures, and financial instability risks. On this basis, the paper argues that future CBDC policy should seek a more appropriate institutional balance among payment efficiency, financial stability, monetary sovereignty, and international coordination, while embedding necessary safeguards into the design stage in order to mitigate destabilizing effects on cross-border capital flows.
Central Bank Digital Currency, Cross-Border Capital Flows, Policy Design, Financial Stability.
Comparative Effectiveness of Carbon Pricing, Industrial Subsidies, and Innovation Support in Green New Deal Strategies: A Systematic Literature Review
The accelerating climate emergency has prompted governments worldwide to adopt comprehensive Green New Deal strategies that combine multiple policy instruments to deliver deep decarbonization while sustaining economic growth. This study conducts a systematic literature review, structured around the PRISMA 2020 protocol, of three core policy instruments central to Green New Deal frameworks: carbon pricing, industrial subsidies including feed in tariffs, and public innovation support. Drawing on 147 quantitative studies published between 1990 and 2025 and indexed in Web of Science, Scopus, and EconLit, we standardize effect sizes using semi elasticity coefficients, abatement cost in dollars per ton of carbon dioxide, and patent based innovation indicators. Results show that carbon pricing achieves the lowest unit abatement cost in the short to medium term, with semi elasticities clustered between 0.003 and 0.008 per dollar per ton increase and minimal macroeconomic disruption. Industrial subsidies and feed in tariffs accelerate technology deployment and trigger learning by doing cost reductions of roughly 20 percent per doubling of cumulative capacity, although early stage abatement costs frequently exceed 100 dollars per ton. Public innovation support increases high quality clean technology patents by 10 to 20 percent but exhibits long temporal lags. The three instruments are complementary rather than substitutable, and an optimally sequenced combination dominates any single instrument approach. The review provides a quantitative evidence base to support the design of effective Green New Deal policy packages.
Green New Deal, carbon pricing, feed in tariff, innovation policy, policy mix, climate policy, systematic review.
Does Disclosure of Environmental Investment Amounts Affect Debt Financing Costs? Evidence from China's Electric and Heat Power Production and Supply Industry
This study examines whether environmental investment disclosure affects corporate debt financing costs. Using manually collected data from 79 A-share listed firms, we find no significant association in OLS regression with robust standard errors. Firm size, leverage, and profitability dominate financing costs. Drawing on information asymmetry and signaling theories, we interpret these findings within China's policy-driven disclosure regime, where disclosure may be viewed as regulatory compliance rather than voluntary commitment, weakening its financial impact.
Environmental investment disclosure; debt financing costs; electric and heat power industry; information asymmetry; signaling theory; policy-driven disclosure; China
Hong Kong as an ESG Financial Hub: Mechanisms through Which International ESG Capital Supports China’s Green Transition
This paper examines the role of Hong Kong in the allocation of ESG capital. The article constructs mechanism framework of "institutional compatibility, market infrastructure, asset pricing and information identification", and analyzes how financial centers can reduce institutional and market frictions in cross-border green investment. Taking the example of Goldwind Technology issuing green bond in Hong Kong in 2015 as a case study, the research finds that Hong Kong promotes the entry of international ESG capital into China's green projects through its regulatory system align with international standards, mature bond market and green certification mechanism. Research shows that Hong Kong plays a significant connecting role in ESG capital and China's green transformation.
Hong Kong; green bond; ESG; China’s green transition.
"Do digital reputation systems correct for market failures in information asymmetry, or do they create new inefficiencies through algorithmic discrimination?"
Digital reputation systems, such as seller feedback scores and user ratings, have become ubiquitous mechanisms for building trust in online markets. While scholarly discourse often frames these systems as remedies for the “lemons problem”, a classic market failure rooted in information asymmetry. This dissertation investigates whether digital reputation systems (e.g., seller feedback scores) correct market failures in information asymmetry or create new inefficiencies through algorithmic discrimination. Framing information asymmetry as a classic market failure (Akerlof's "lemons problem") in markets like e-commerce and freelance labor, it draws on Belle Flamme and Peitz to argue these systems can be effective, first-best solutions. However, the central argument reveals a paradox: by reviewing empirical work by Liu and Sefers and theoretical models by Rhodes and Zhou, the study demonstrates how algorithmic design inadvertently generates new inefficiencies—namely, statistical discrimination and herding. The dissertation concludes that these outcomes are co-produced by the same logic: reputation systems are powerful tools but not a panacea, demanding platform governance that balances trust-building with social equity.
Digital reputation systems, information asymmetry, lemons problem, algorithmic discrimination, statistical discrimination, herding, platform governance, market failure, two-sided markets.
The Linked Exchange Rate System and FinTech Development: Synergistic Evolution of Hong Kong's International Financial Centre Status
As a leading global international financial centre, Hong Kong's financial system is anchored by the Linked Exchange Rate System (LERS) established in 1983. Characterized by 100% US dollar reserve backing and the Convertibility Zone of 7.75 to 7.85 Hong Kong dollars per US dollar, this system has provided monetary and financial stability for Hong Kong for over four decades. Concurrently, in response to the global digital economy wave, Hong Kong has accelerated its FinTech development in recent years—from the "FinTech 2025" strategy to the newly announced "FinTech 2030" blueprint—aiming to build next-generation data and payment infrastructure and promote financial tokenization. This paper examines the synergistic relationship between the traditional institutional cornerstone of LERS and the emerging developmental impetus of FinTech innovation. The study finds that the exchange rate stability and free capital movement provided by LERS create an ideal experimental environment for FinTech development; conversely, FinTech innovations such as central bank digital currencies (CBDC) and tokenized deposits hold the potential to optimize the operational efficiency of LERS and enhance its resilience in addressing future challenges. The synergistic evolution of these two pillars jointly consolidates and elevates Hong Kong's status as an international financial centre.
Linked Exchange Rate System; FinTech; Hong Kong International Financial Centre; Central Bank Digital Currency; Tokenization.
Evolution of Global Soybean Trade Flows and Share Reconfiguration Amid Tariff Policy Fluctuations
In response to the United States' proposed “reciprocal tariff” policy scheduled for implementation in 2025, this study aims to quantitatively assess its far-reaching impact on the global soybean trade landscape. Based on monthly high-frequency data from 2000 to 2025, an integrated assessment framework combining an extended gravity model with demand price elasticity is constructed to estimate long-term structural parameters and short-term market responses. Simulation results reveal that tariff barriers trigger significant trade diversion effects, causing U.S. soybean exports to China to plummet by approximately 25% and market share to shrink. Meanwhile, Argentina leverages its low-cost advantage to surge exports by over threefold, emerging as the primary beneficiary of market restructuring, while Brazil maintains its dominant position. This study innovatively integrates long-term and short-term factors, revealing the underlying logic by which unilateral tariff policies reshape the international agricultural competitive landscape through supply chain substitution mechanisms.
Gravity Model; Trade Diversion; Price Elasticity.
Preface: 8th International Conference on Global Economy and Business Management (GEBM 2026)
The 2026 8th International Conference on Global Economy and Business Management (GEBM 2026) for the researchers and experts was successfully held in New Delhi, India during May 30-31, 2026. This conference provides a forum for accessing to the most up-to-date and authoritative knowledge, sharing the best practice in the fields of global economy, world trade, financial investment, real estate, economic policy, e-commerce, and business management. The GEBM 2026 program covered invited, oral, and poster presentations from scientists working in similar areas to establish platforms for collaborative research projects in these fields. This conference brought together many participants to exchange and share their experiences, present research results, explore collaborations and to spark new ideas, with the aim of developing new projects in these fields. The organizing committee appreciates the enormous work of the both the editorial board and reviewers in the preparation of this volume. Many thanks also to all authors for their flexibility and meeting deadlines. With warmest regards, GEBM Conference Organizing Committees New Delhi, India
Globalization and The Acceleration of Wealth Digital Platforms, Artificial Intelligence, and Collaborative Entrepreneurship
The current world economy has experienced colossal levels of fluctuations in regards to how wealth is being created which is absent in this section of the globe at any given moment, and this is leading to a paradigm shift of monetary to financial wellbeing. The article unfolds the speed with which the 21 st century is accelerating wealth creation as globalization and digital platforms, artificial intelligence and swarm innovation start to take over. As the article demonstrates, we discovered that in diverse situations (companies, industries or nations) we clarify the process through secondary and cases studies that during the crash of these technical development track economic new paradigms boom as a result of the rapid wealth accumulation. Such findings of research have suggested that individuals and companies can now earn enormous sums of money within a shorter period compared to the previous system of business and at increased penetration rate comes novel forms of economic disparity and risk. The research is also able to project some insight on the manner in which the digital revolution and global connectivity are alleviating the entrepreneurial regions, and income distribution.
Globalization, Digital Platforms, Artificial Intelligence, Collaborative Entrepreneurship, Wealth Acceleration, Digital Economy.
Copyright (c) 2025 Transactions on Economics, Business and Management Research https://creativecommons.org/licenses/by-nc/4.0
The Influence of A Financial Professional Background on Family Pension Insurance Decisions
Based on data from the China Household Finance Survey (CHFS) spanning 2015 to 2019, this study empirically examines the impact of a household member’s financial professional background on the family’s decision to purchase commercial endowment insurance. A key innovation of this research lies in its use of multi-period micro-survey data to investigate how individual occupational backgrounds influence retirement-related decision-making,while employing a two-way fixed effects model to mitigate endogeneity issues. The empirical findings indicate that the presence of a financial professional within a household significantly increases the likelihood of the family obtaining commercial endowment insurance. This conclusion remains robust after undergoing a series of robustness tests and model specification checks. Furthermore, this study focuses on analyzing the heterogeneous characteristics of the impact exerted by financial professional backgrounds on retirement decisions, which, to some extent, expands the existing literature in the field of health economics. Results from the heterogeneity analysis reveal that the positive effect of having a financial professional is more pronounced in urban households, high-income households, and households where the head of the household has a higher level of education. This research provides a new perspective for understanding household decision-making regarding endowment insurance and offers empirical evidence to support the improvement of China’s multi-level elderly care security system.
CHFS, Financial Professional Background, Pension Insurance.
The Influence of Environmental Regulation on Industrial Structure Upgrading in Beibu Gulf Urban Agglomeration
This study examines the impact of environmental regulations on industrial structure upgrading in urban clusters through an economic theory framework. Using panel data from 10 prefecture-level cities in the Beibu Gulf Urban Cluster (2010-2021), we measure industrial upgrading through three dimensions: comprehensive structural transformation, industrial sophistication, and rationalization. Through a fixed-effects model, empirical analysis demonstrates that environmental regulations drive comprehensive industrial upgrading while partially hindering rationalization. The findings suggest establishing a multi-tiered regulatory system to strengthen coordinated pollution control across the cluster, ensuring holistic industrial rationalization. Policy recommendations include improving environmental infrastructure to reduce corporate pollution costs, and removing barriers to comprehensive industrial upgrading.
industrial structure upgrading; environmental regulation; Beibu Gulf city cluster.