Current Issue

2026 Vol. 41, No. 1

column
  Previous Issue
Display Method:
Intelligent Finance
Artificial Intelligence Hype and Analyst Earnings Forecast
YAO Shujie, HONG Tao, CHEN Xiyi
2026, 41(1): 4-16.
[Abstract](57) [FullText HTML] (31) [PDF 1143KB](9)
Abstract:
Speculative practices such as trend-chasing and narrative-driven hype prevail in capital markets and pose substantial risks to the quality of the information environment. How to identify and govern discrepancies between firms' rhetoric and actual practices in promoting artificial intelligence (AI) activities constitutes a critical issue for the high-quality development of the AI industry. Using textual data from listed firms' annual reports and firm-level data on AI innovation and application from 2007 to 2023, this study constructs a novel measure of corporate AI hype. The results show that AI hype significantly exacerbates analyst forecast bias while failing to generate corresponding substantive innovation or application outcomes. Mechanism analyses indicate that this effect operates by elevating optimism among analysts and investors. Heterogeneity analyses further show that analysts' on-site visits, stronger professional competence, and a well-functioning external information environment help mitigate the misleading effects of AI hype, whereas firms' incentives for market value manipulation intensify these effects. Overall, the findings reveal corporate speculative behavior amid the AI wave and its implications for the capital market information environment, and provide useful insights for promoting the healthy development of AI and improving the standardization and credibility of information disclosure.
Artificial Intelligence and the Development of the Elderly Care Industry
DU Panpan, CHEN Zhao, GAO Chuansheng
2026, 41(1): 17-32.
[Abstract](44) [FullText HTML] (46) [PDF 1232KB](6)
Abstract:
In the context of the in-depth development of China's aging population, artificial intelligence has become an important driving force to address the challenges of aging and boost the development of the elderly care industry. Based on panel data from 30 provinces in China from 2014 to 2023, this study measures the development level of the elderly care industry across various provinces and empirically examines the impact of AI on this development level. The results indicate that the impact of AI on the development level of the elderly care industry is inverted U-shaped. Yet, the current AI development level in most provinces of China lies on the left side of the inflection point, with a prominent technological dividend effect. AI exerts its influence on the development of elderly care industry through the effect of industrial structure servitization and the effect of human capital structure optimization. Both the level of marketization and the degree of opening-up strengthen the inverted U-shaped relationship between AI and the development level of the elderly care industry. Regionally, the impact of AI on the development level of elderly care industry presents an inverted U-shape in the eastern and central regions, while it exerts a positive promoting effect in the western region. In terms of aging intensity, an inverted U-shaped relationship is observed in low-aging areas, whereas a positive promotional effect is manifested in high-aging areas. Further exploration reveals that the impact of AI on the elderly care industry demonstrates differentiated characteristics across different application scenarios. Therefore, while promoting the "incremental empowerment" of AI applications, it is also important to pay attention to improving its adaptability to the development of the elderly care industry, in order to fully unleash the dividends of artificial intelligence technology and drive high-quality development of the elderly care industry.
Management and Corporate Performance
STAR Market Listing, Technological Positioning, and High-Quality Corporate Innovation
GAO Yu, SUN Yannan, ZHAO Xiaoyang
2026, 41(1): 33-49.
[Abstract](79) [FullText HTML] (57) [PDF 1929KB](5)
Abstract:
As a key institutional innovation platform in the reform of the registration-based IPO system, the STAR Market (Science and Technology Innovation Board) is aimed to address the issue of "innovation stagnation" under the traditional IPO framework through the design focused on "hard technology" positioning and enhanced information disclosure. Based on micro-level data of Chinese firms listed on the STAR Market from 2017 to 2022, this paper employs a difference-in-differences model to evaluate the impact of STAR Market listing on firms' high-quality innovation. The findings show that firms do not experience an expected leap in innovation quality immediately after listing, while they reduce high-risk, long-term exploratory R & D and shift toward more easily achievable strategic innovation. Mechanism analysis indicates that the STAR Market's institutional arrangements influence firms' innovation decisions mainly through two channels: post-listing market valuation pressures compelling firms to reallocate R & D resources, and stricter information disclosure requirements altering management's risk-taking willingness. Heterogeneity tests reveal that increased information transparency strengthens knowledge spillovers within industries, which benefits technology-following firms in improving innovation performance, however, for technology-leading firms at the frontier, higher disclosure costs and risks of core technology leakage suppress their high-quality innovation. Dynamic analysis uncovers that these negative effects are concentrated mainly in the early post-listing period and ease as firms gradually adjust their strategies. This study enriches empirical evidence at the micro-level regarding the relationship between information disclosure systems and corporate innovation behavior under the registration-based reform, and provides targeted policy implications for more effectively incentivizing high-quality technological innovation while promoting capital market transparency.
Commercial Banks' ESG Performance and the Governance of Enterprises' Zombie Risk
WANG Lei, CAI Yitong, SHA Yifan
2026, 41(1): 50-67.
[Abstract](52) [FullText HTML] (40) [PDF 1112KB](6)
Abstract:
Using financial tools to address the challenges of zombie enterprise governance is a key measure to promote the orderly withdrawal of backward production capacity and prevent and resolve major economic and financial risks. Based on the loan data disclosed in listed companies' announcements, this paper empirically examines the governance effect of banks' ESG performance on zombie enterprises. The findings show that banks' ESG performance can effectively reduce enterprises' zombie risk, when the level of banks' ESG performance increases by one standard deviation, the probability of enterprises becoming zombie enterprises decreases by 1.21%. Mechanism tests reveal that, different from the traditional "credit blood transfusion", banks' ESG performance not only eases enterprises' credit constraints, but also systematically reduces their zombie risk by strengthening the governance of backward production capacity and improving their investment efficiency and production efficiency, thereby helping zombie enterprises escape from distress and achieve rebirth. Heterogeneity tests indicate that the governance effect of banks' ESG performance is more significant for non-state-owned enterprises, non-heavily polluting enterprises, enterprises with high external financing dependence, and the enterprises with high debt financing costs.
Public Data Openness and Entrepreneurial Vitality of Low-altitude Economy Enterprises
ZHANG Lin, LI Shunyi
2026, 41(1): 68-81.
[Abstract](41) [FullText HTML] (50) [PDF 1213KB](6)
Abstract:
Accelerating the release of entrepreneurial vitality among low-altitude economy enterprises is a crucial approach to developing this sector in a context-specific manner. Drawing on business registration data from 282 Chinese cities from 2011 to 2023, this study leverages a quasi-natural experiment facilitated by government public data platforms. A multi-period difference-in-differences model is constructed to empirically examine the impact and underlying mechanisms of public data openness on entrepreneurial dynamism within the low-altitude economy. The findings reveal that public data openness significantly enhances entrepreneurial dynamism in the low-altitude economy, increasing the average number of new enterprises by 11.1%. This effect operates through strengthening technological integration, optimizing institutional and cultural environments, alleviating financing constraints, and expanding market demand. Heterogeneity analysis indicates that the promotional effect of public data openness is more pronounced in regions with steeper topography and higher internet penetration rates, while it exerts a stronger impact on the entrepreneurial dynamism of the medium-to-large-scale enterprises in the low-altitude economy. These findings enrich empirical evidence on the entrepreneurial effects of public data openness and offer valuable insights for unleashing entrepreneurial vitality in low-altitude economy enterprises and promoting their safe and healthy development.
Economic Theory and Exploration
Mechanisms and Pathways of the Digital Economy to Resolve the Triple Energy Dilemma
ZHANG Xixi, LAI Junming
2026, 41(1): 82-96.
[Abstract](56) [FullText HTML] (43) [PDF 1147KB](6)
Abstract:
In the context of the deep integration of global energy transition and the digital economy, it is crucial to leverage digital innovation to address the trilemma of energy security, equity, and sustainability. Based on the panel data from 276 Chinese cities from 2008 to 2023, this study constructs models of dynamic panel and mediation effect, employing the system GMM method to empirically examine the internal mechanisms through which the digital economy influences the energy trilemma. The findings reveal that: the digital economy has a significant and sustained ameliorating effect on the energy trilemma; its impact exhibits a notable"Matthew effect", with more pronounced benefits in cities with a stronger foundation for energy transition; the pathways of influence display stage-specific characteristics—technology innovation dominates in robust cities, presenting that "technology-industry" dual-driven dynamics emerge in advanced cities, while industrial structure upgrading plays the primary role in potential cities; the digital economy operates through a trinity transmission mechanism of "technology-structure-capital", mediated by technological innovation, industrial restructuring, and capital infusion. This research deepens the understanding of how the digital economy enables energy transition, and provides theoretical and empirical support for formulating differentiated policies and promoting the deep integration of the digital economy with energy systems.
Data Factor Marketization and Key Core Technological Breakthroughs in Advanced Manufacturing Enterprises: A Transaction Cost Perspective
GUO Qiaozhe, GENG Chengxuan, YAO Nengzhi
2026, 41(1): 97-113.
[Abstract](48) [FullText HTML] (43) [PDF 1245KB](7)
Abstract:
Data factor marketization is a crucial link in unlocking the value of data as a factor of production. By facilitating the efficient, low-cost circulation of data, it is of significant importance for firms seeking breakthroughs in key and core technologies. Drawing on transaction cost theory, this study uses a sample of A-share listed firms in China's advanced manufacturing sector from 2012 to 2022 and exploits the establishment of data trading platforms as a quasi-natural experiment to examine the effect of data factor marketization on firms' key core technological breakthroughs. The results show that data factor marketization significantly promotes such technological breakthroughs, and this finding remains robust across a series of robustness checks. Mechanism analyses indicate that easing financing constraints and reducing both institutional transaction costs and market transaction costs constitute the key channels through which data factor marketization fosters breakthroughs in key and core technologies. Heterogeneity analyses further reveal that the positive effect varies significantly across firm characteristics, industry and regional environments, and platform characteristics. This study enriches the literature on how data factor marketization shapes firms' technological breakthroughs, extends the analytical perspectives of transaction cost economics and innovation management, and provides policy-relevant implications for advancing China's innovation-driven development and the building of a strong scientific and technological nation.
Fiscal and Public Administration
The Impact of Fiscal Digital Transformation on Hidden Debt Risks of Local Government
CHEN Nanxu, YANG Jiayao, LI Yi
2026, 41(1): 114-129.
[Abstract](58) [FullText HTML] (54) [PDF 1239KB](6)
Abstract:
Effectively controlling the hidden debt risks of local government serves as a critical defense against regional financial risks escalating into systemic financial crises. The ongoing fiscal digital transformation may offer modern solutions for managing hidden debt risks through penetrative supervision and intelligent early warning systems. Therefore, based on deconstructing the theoretical link between these two concepts, this study examines the impact of fiscal digital transformation on the hidden debt risks of local government using the data from China's prefecture-level cities from 2016 to 2023. The study finds that fiscal digital transformation can mitigate hidden debt risks by enhancing debt expenditure efficiency and improving fiscal revenue quality. The governance effect on the risks is more pronounced in regions with smaller economies, favorable institutional environments, and relatively lagging digital innovation and business environments. These findings offer valuable insights for accelerating digital fiscal development, mitigating the hidden debt risks of local government, and alleviating fiscal revenue-expenditure pressures.
The Impact of Government Service Informatization on Firms' Labor Income Share
JIANG Pengcheng, QIN Shuai, CHEN Jinzhi
2026, 41(1): 130-144.
[Abstract](75) [FullText HTML] (57) [PDF 1257KB](6)
Abstract:
The deep integration of information technology and government services has reshaped governance models and become a key driver of economic transformation and development. Using the policy of "National Pilot Cities for Information Benefiting the People" as a quasi-natural experiment, this study employs a difference-in-differences (DID) framework to examine the effect of government service informatization on firms' labor income share. The results show that government service informatization significantly increases firms' labor income share. This effect is stronger for firms with a lower share of fixed assets, higher leverage, those in the secondary sector, firms operating in regions with greater market segmentation, firms in administratively monopolized industries, and firms located in regions with more advanced digital infrastructure. Mechanism tests indicate that government service informatization raises the labor income share by easing financing constraints and increasing labor hiring. Further analysis suggests that government service informatization reduces intra-firm income inequality and curbs excessive pay disparities. These findings provide theoretical support and policy implications for promoting governance transformation, improving the income distribution pattern, and advancing common prosperity in a solid and sustained manner.

Editorial Office of Journal of Guangdong University of Finance and Economics

Address：21 Luntou Road, Guangzhou    China Pos：510320    Tel：020-84096712、84096029

Supported by: Beijing Renhe Information Technology Co. Ltd