Table of Content

15 March 2026, Volume 0 Issue 3

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Theoretical Economics

Research on the Influence of Technology Integration of Digital and Real Industries on Labor Income Share of Enterprises

Xue Long, Ouyang Zhi-gang

2026, 0(3):  3-15. 

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Increasing the share of labor income in enterprises is an important way to optimize the income distribution pattern and achieve modernization with Chinese characteristics. Against this backdrop, it is particularly important to conduct an in-depth investigation into the influencing factors of enterprise labor income share. This paper measures the digital-real industrial technology integration with the patent citation information and conducts an empirical study on the basis of the non-financial A-share listed enterprises in Shanghai and Shenzhen stock exchanges from 2008 to 2022 as samples. The findings reveal that digital-real industrial technology integration can significantly enhance enterprise labor income shares. The mechanism analysis indicates that digital-real industrial technology integration promotes the upgrading of enterprise human capital structure, thereby increasing enterprise labor income share. The heterogeneity analysis demonstrates that, in terms of enterprise characteristics, the positive effect of digital-real industrial technology integration on the labor income share is more pronounced in non-state-owned enterprises and high-tech enterprises. From the perspective of external environments, the enhancing effect is more substantial for enterprises located in regions with higher levels of intellectual property protection and more advanced digital infrastructure development. Based on these conclusions, to further leverage the role of digital-real industrial technology integration in boosting enterprise labor income share, it is imperative to improve digital technology infrastructure, optimize the supply-demand structure of the labor market, and advance digital-real industrial technology integration through tailored policies adapted to the enterprise-specific and region-specific conditions.

Local Government Debt Management System Reform and Entrepreneurial Spirit

Xiang Xue-feng, Niu Geng, Zhou Yang

2026, 0(3):  16-27. 

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Promoting the healthy and sustainable development of local government debt is a crucial strategy for preventing and resolving systemic financial risks. Using the local government debt management system reform initiated in 2015 as a quasi-natural experiment, this paper conducts a study from the entrepreneurial perspective by employing the panel data of prefecture-level cities and a multi-time point difference-in-differences model. The findings reveal that: firstly, the reform has significantly enhanced regional entrepreneurial activity, which is conducive to stimulating entrepreneurship. Secondly, the mechanism test results indicate that the reform can not only alleviate credit constraints in entrepreneurial activities but also improve government-business relationships, thereby promoting regional entrepreneurial activity and fostering entrepreneurship through these two channels. Thirdly, the entrepreneurial promotion effect generated by the reform exhibits heterogeneity in terms of ownership and industry sectors, being more pronounced in private enterprises, the service industry, and high-tech sectors. Fourthly, the reform produces a stronger entrepreneurial promotion effect in cities with higher information disclosure levels, lower fiscal pressure, and superior legal and business credit environments. Based on these findings, local governments could consider leveraging the opportunity of local debt governance to improve government-business relationships and alleviate financing difficulties faced by market entities, thereby fully stimulating market entrepreneurial vitality. However, it is necessary to implement differentiated reform promotion strategies based on actual conditions, such as local fiscal pressure, while accelerating the establishment of public information service platforms and the construction of a social credit system.

Public Economics & Administration

Research on the Fiscal Stress-Alleviating Effect of“Artificial Intelligence +”

Chen Shao-lian, Han Feng-qin

2026, 0(3):  28-42. 

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Promoting the deep integration of artificial intelligence with the economy and society is of great significance for unleashing its fiscal and economic efficiency and alleviating the financial pressure on local governments. Based on the panel data from 280 cities in China from 2010 to 2023, this paper constructs a multi-period difference-in-differences model to empirically examine the impact of the“AI+”initiative on local fiscal pressure and its underlying mechanism. The findings show that the“AI+”initiative, with the national new-generation AI innovation and development pilot zones as its policy vehicle, has significantly alleviated local fiscal pressures. The mechanism analysis shows that the policy boosts entrepreneurial vitality among market entities, thereby increasing tax revenue, and optimizes the allocation of government funds to improve fiscal expenditure efficiency, thus relieving fiscal pressure. The heterogeneity analysis reveals that the alleviating effect is more pronounced in regions with lower fiscal self-sufficiency rates and higher industrial agglomeration. Additionally, the “AI+”initiative helps mitigate regional disparities in initial digital infrastructure and policy support. Therefore, efforts should be made to further advance the“AI+”initiative, unleashing its fiscal and economic effects; promote better integration of an effective market and a proactive government, facilitating the transmission mechanism for alleviating fiscal pressures; and implement a differentiated “AI+”development strategy by region to precisely mitigate local fiscal burdens.

Can the“Internet + Government Services”Policy Promote the Optimization of the Tax Ecology?

Wang Hong-zi, Liu Rong

2026, 0(3):  43-57. 

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Promoting the digital transformation of government services is not only crucial for accelerating the construction of digital government and enhancing administrative efficiency, but also serves as a significant underpinning for advancing the modernization of China's governance system and capacity. Taking the data from China's A-share listed companies in Shanghai and Shenzhen stock markets as samples and leveraging the“Internet+Government Services”policy to establish a quasi-natural experiment, this study investigates the impact of this policy on the corporate tax ecosystem and its mechanism. The findings show that the“Internet+Government Services”policy can significantly enhance corporate tax compliance, thereby optimizing the tax ecosystem. This effect is more pronounced among state-owned enterprises, retail sector firms, as well as companies with a higher degree of digital transformation and a lower degree of financing constraints. The mechanism analysis indicates that the policy optimizes the tax ecosystem through three pathways: reducing cost burdens, reshaping government-business relationships, and strengthening the order of tax collection and administration. Further research reveals that this policy can also stimulate market vitality, cultivate sustainable tax sources, and achieve the expansion and stabilization of the tax base, leading to a more profound optimization of the tax ecosystem. Based on these findings, the government should deepen the application of digital technologies to systematically reduce institutional transaction costs within the tax ecosystem, construct digital interaction mechanisms to profoundly reshape government-business trust relationships, and implement precise, collaborative governance to continuously improve the order of tax collection and administration.

Modern Finance

Can Supply Chain Shareholding Improve the Efficiency of Enterprise Capital Allocation?

Bai Zong-hang, Hu Hai-feng

2026, 0(3):  58-70. 

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The key to promoting enterprises to achieve high-quality development and stimulating the vitality of economic development is to improve the efficiency of capital allocation. In the context of global industrial chain reconstruction and the intensifying competition between major powers, it is of paramount importance for enterprises to enhance the overall supply chain synergy and cooperation and to restructure the stable and secure supply chain relationships. Based on this, using the data from listed companies and their upstream and downstream supply chains from 2008 to 2022, this paper examines the impact of supply chain shareholding on corporate capital allocation efficiency and its underlying mechanisms. The findings indicate that supply chain shareholding helps enhance corporate capital allocation efficiency, with broadening financing channels and improving the corporate information environment serving as two potential mechanisms. The heterogeneity analysis reveals that the promoting effect of supply chain shareholding on corporate capital allocation efficiency is more pronounced in enterprises with weaker supply chain stability and lower“chain leader”status, as well as in those operating during industry economic downturns. The analysis of economic consequences demonstrates that supply chain shareholding can improve the efficiency of capital allocation in enterprises, thereby reducing the risk of bankruptcy. Therefore, it is recommended that government departments further improve the supporting policy system related to supply chain shareholding, formulate special support policies and adopt incentive measures, actively guide and promote the construction of supply chain cooperation relationships and equity linkage mechanisms among enterprises, so as to fully play the important role of supply chain shareholding in optimizing resource allocation and improving capital operation efficiency.

Study on the Stock Price Response of Interest Rate Changes from the Perspective of Investor Sentiment Decomposition

Liu Peng-yu, Jin Chun-yu

2026, 0(3):  71-85. 

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In recent years, influenced by factors such as the shift in monetary policies of major economies and frequent favorable policies in the stock market, China's stock prices have experienced intensified volatility. Investor sentiment in the stock market is highly sensitive to policy changes, and policy interest rates are in a downward cycle. In this context, studying the impact of interest rate changes on stock prices from the perspective of investor sentiment decomposition has important practical significance. This paper uses the Regional Vector Autoregressive (RVAR) model to decompose investor sentiment, and adopts the Regional Dependent Local Projection (RLP) model to examine the transmission effect of interest rate changes on stock prices in China under different channels of investor sentiment. The findings show that when investor sentiment is low, interest rate changes cause multi-level stock price movements in the same direction and opposite direction through blind and directional investor sentiment channels, respectively. When investor sentiment is high, interest rate changes cause multi-level stock prices to experience first in the same direction and then in the opposite direction through blind investor sentiment channels, and first in the opposite direction and then in the same direction through directional investor sentiment channels. Meanwhile, in the zone of high investor sentiment, the self reinforcing characteristics of investor sentiment in China's stock market are mainly manifested in blind investor sentiment rather than directional investor sentiment. Therefore, in order to ensure the stability of stock prices after interest rate adjustments, China should fully leverage the investment leading role of smart investors over ordinary investors, and guide and manage the emotions and capital flows of ordinary investors in the stock market through a small number of smart investors after interest rate changes.

Business Administration

How Artificial Intelligence Emotional Support Reshapes Employee Interpersonal Relationships: From a Self-Concept Perspective

Chen Jia-ying, Xue Jia-xin, Li Yu-hui

2026, 0(3):  86-96. 

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With the continuous development of emotional functions in artificial intelligence, the phenomenon of employees seeking emotional support from artificial intelligence is increasing, which will have a profound impact on interpersonal behavior in the workplace. However, compared to the widespread focus on work behavior and outcomes, researches on how artificial intelligence affects employee interpersonal relationships, especially from the perspective of artificial intelligence emotional support, is very limited. Based on the self-concept theory, this study analyzes the data from 440 employees using a three-point questionnaire survey method to explore how artificial intelligence emotional support affects employee relationship reshaping. The research results show that artificial intelligence emotional support can promote employee relationship reflection, thereby facilitating relationship reshaping. The extraversion enhances the positive effect of artificial intelligence emotional support on relationship reflection, while also strengthening the mediating role of relationship reflection between artificial intelligence emotional support and relationship reshaping. Based on the above conclusion, enterprises should pay attention to the potential impact of artificial intelligence emotional functions on the workplace, and effectively plan the application layout of artificial intelligence emotional support based on individual differences of employees, so as to leverage the positive role of artificial intelligence in interpersonal relationships in the workplace.

FinTech Development and SMEs' Performance: New Evidences from National Tax Survey Data

Wei Shan-shan, You Jia-xing, Liu Ying

2026, 0(3):  97-111. 

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FinTech has reshaped the entire financial ecosystem and economic operational system, leaving small and medium-sized enterprises (SMEs) unable to remain unaffected as risks and opportunities coexist. This paper conducts an empirical study by using unique large sample data of SMEs to examine in detail whether and how financial technology affects their performance. The findings show that for SMEs, the risks brought by the development of financial technology outweigh the opportunities, and have a significant negative impact on their performance. This impact mainly comes from the contraction of credit supply, intensified industry competition, and stricter financial regulation. The heterogeneity test results show that the impact of financial technology on the performance of SMEs is closely related to the stage of financial technology development and the level of traditional financial development. The exploratory test results indicate that the impact of financial technology development on the performance of SMEs is more manifested as a significant decrease in operating profit margins and a significant increase in management expenses. At the same time, facing the enormous challenges brought by the development of financial technology, from the dual perspectives of enterprise and policy, it systematically reveals the response logic and external support path of SMEs in the context of financial technology development. Based on the above conclusion, the government should improve the top-level design for the development of SMEs and implement related policies and regulations. Financial institutions should rely on financial technology transformation and innovate product services to broaden their financing channels for enterprises. SMEs should leverage financial technology to accelerate transformation and upgrading, and achieve high-quality development.

Industry & Trade

High-Standard International Economic and Trade Rules in the Digital Domain and Digital Trade

Ma Meng-juan, Yu Zi-ling, Ma Li-li

2026, 0(3):  112-126. 

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Accelerating the alignment with high-standard international economic and trade rules in the digital domain is of great significance for releasing the growth potential of digital trade. By making use of Trade Agreements Provisions on Electronic-Commerce and Data from 2000 to 2022 and the United Nations Conference on Trade and Development Statistical Database, this study examines the impact of international high standard economic and trade rules in the digital field on digital trade from the perspective of post border clauses in free trade agreements. The findings show that international high standard economic and trade rules in the digital field have a significant promoting effect on digital trade. Among them, the promoting effect of inclusive rule docking is more prominent, while the restrictive rule docking presents restraining effects. Its mechanism of action mainly includes the support effect of the digital industry and the reconstruction effect of the digital network. The heterogeneity analysis reveals that the promotion effect of digital service clauses is the strongest, followed by digital intellectual property and digital investment clauses, while the role of competition policy clauses is relatively weaker. The expansion analysis reveals that there are differences in the impact of different institutional integration paths on digital trade. The promotion effect of China, the United States, or the joint accession of China and the United States to the Comprehensive and Progressive Agreement for Trans Pacific Partnership is particularly evident, while the accession or rule integration of some developing countries may have inhibitory effects on digital trade. In addition, international high standard economic and trade rules in the non digital field indirectly promote the development of digital trade through innovative factor activation effects, business environment optimization effects, and human capital adaptation effects. Therefore, countries should prioritize promoting the implementation of inclusive rules and avoid blindly exporting systems. At the same time, they should strengthen the support capacity of the digital industry and the access rules of hierarchical classification, thus forming a gradient based regional rule adaptation path.

A Study of the Impact of Cross-Border Data Flow Restrictions on the GVC Division of Labor Status of Producer Services

Yuan Hong-lin, Liu Dong-xue

2026, 0(3):  127-139. 

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With the deepening development of the digital economy on a global scale, cross-border data flow has a significant impact on the global value chain division of labor in the productive service industry. Based on the Digital Trade Restrictions Index database of the European Centre for International Political Economy (ECIPE), this study quantifies the cross-border data flow restrictions of five major production service industries in 42 economies from 2014 to 2018, and further conducts an empirical analysis on their specific impact on the global value chain division of labor position of the production service industry. The findings show that cross-border data flow restrictions significantly inhibit the advancement of the global value chain division of labor in the productive service industry. The heterogeneity analysis shows that the global value chain division of labor position of wholesale and retail (including motor vehicle repair), transportation and warehousing, leasing, and other business service industries is significantly more suppressed than that of postal and telecommunications industries and financial insurance industries; compared to developed economies, the position of productive services in the global value chain division of labor in developing economies is more inhibited, while economies with higher economic freedom can effectively cope with the negative impact of cross-border data flow restrictions. The mechanism analysis shows that cross-border data flow restrictions reduce the global value chain division of labor position of productive service industries through three paths: inhibiting research and development innovation, causing imbalances in human capital structure, and increasing trade costs. Therefore, the government should further improve the data flow governance framework that balances security and efficiency, and strengthen factor support by incentivizing technological innovation, optimizing human capital structure, and reducing trade costs. At the same time, it should promote the integration of international data standards and enhance policy flexibility and economic freedom, thereby promoting the high-quality development of productive service industries under cross-border data regulation.

Modern Accounting

Can Green Transformation of Parent Company Improve the Performance of Foreign Subsidiaries: Evidences from the Establishment of Green Factory

Pang Su-qin, Li Zhao-hua

2026, 0(3):  140-152. 

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Green transformation provides new opportunities for Chinese enterprises to break through green investment barriers and improve the performance of their overseas subsidiaries. Using the panel data of Chinese manufacturing enterprises and their overseas subsidiaries from 2008 to 2022, this study examines the impact of parent company's green transformation on the performance of overseas subsidiaries through a quasi-natural experiment based on the creation of green factories. The findings show that the green transformation of parent companies can help improve the performance of overseas subsidiaries. The impact mechanism test reveals that the green transformation of the parent company can increase the probability of the parent company entering the host country(region) in a sole proprietorship mode and release green signals, thus the green transformation of the parent company can improve the performance of overseas subsidiaries. The moderation effect analysis reveals that the institutional distance between the home country and the host country(region) may weaken the effect of the parent company's green transformation on the performance improvement of overseas subsidiaries. The heterogeneity analysis reveals that the improvement effect of green transformation of parent companies on the performance of overseas subsidiaries is more significant in parent companies belonging to polluting industries. Compared to R&D overseas subsidiaries, the parent company's green transformation has a stronger effect on improving the performance of production and commercial overseas subsidiaries. To this end, the government should continue to promote and support the creation of green factories, lead foreign direct investment with greenness, and assist Chinese enterprises in high-quality “going global”.

Artificial Intelligence and the Quality of Enterprise Carbon Information Disclosure

Du Jian, Huang Song

2026, 0(3):  153-164. 

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Artificial intelligence is an important driving force for enterprises to change their knowledge production methods and decision-making paradigms. The application of artificial intelligence by enterprises will affect their information generation and disclosure. Taking Chinese A-share listed companies from 2008 to 2023 as samples, this study examines the impact of applying artificial intelligence on the quality of corporate carbon information disclosure. The results show that the application of artificial intelligence by enterprises has significantly improved the quality of carbon information disclosure. The analysis of the mechanism of action reveals that the application of artificial intelligence in enterprises can improve their information environment, ESG performance, and enhance the quality of internal control. Therefore, the application of artificial intelligence in enterprises can improve the quality of carbon information disclosure. The heterogeneity analysis reveals that in regions with strong environmental regulations, industries with high competition, and industries with high environmental sensitivity, the application of artificial intelligence by enterprises has a greater effect on improving the quality of carbon information disclosure. Therefore, enterprises need to accelerate the application of artificial intelligence, improve the quality of data collection, and actively fulfill ESG. The regulatory authorities should use artificial intelligence technology to accelerate the improvement of the carbon information disclosure system.