Controlling Shareholder's Share Pledging and the Corporate Artificial Intelligence Washing: Evidence From China

ABSTRACT Controlling shareholder share pledging exposes the controlling shareholder to the risk of losing corporate control in the event of a stock price decline. This paper aims to examine whether controlling shareholder share pledging drives corporate AI washing, and to identify the mechanisms through which this effect operates. This study indicates that controlling shareholder share pledging exerts a significant and robust exacerbating effect on corporate AI washing. The mechanism through which this effect operates lies in heightened earnings aggressiveness and aggravated information opacity. Besides, agency problems significantly strengthen this positive relationship, as controlling shareholders with greater agency discretion face fewer internal constraints on opportunistic AI disclosures. Analyst coverage, however, attenuates this exacerbating effect, consistent with the view that external monitoring by information intermediaries disciplines controlling shareholders' opportunistic behavior and mitigates the informational consequences of share pledging. From the perspective of controlling shareholders' financing behavior, this paper examines the driving effect of share pledging on corporate AI washing through heightened earnings aggressiveness and aggravated information opacity, thereby introducing this emerging opportunistic practice into the literature on the real effects of share pledging. Meanwhile, agency problems reinforce this effect from the internal governance perspective, while analyst coverage attenuates it from the external monitoring perspective, providing practical insights for regulators and investors to curb AI washing through the integration of internal and external governance mechanisms.

Authors

Institutions

Publication Details

Journal
Australian Economic Papers
Published
2026-10-28
DOI
https://doi.org/10.1111/1467-8454.70043
Primary Topic
Auditing, Earnings Management, Governance
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Controlling Shareholder's Share Pledging and the Corporate Artificial Intelligence Washing: Evidence From China

Hao Ding, Huangying Gu, Chunlin Liu
2 links
Australian Economic Papers
Auditing, Earnings Management, Governance
article

Controlling Shareholder's Share Pledging and the Corporate Artificial Intelligence Washing: Evidence From China

Hao Ding, Huangying Gu, Chunlin Liu
article en

Abstract

ABSTRACT Controlling shareholder share pledging exposes the controlling shareholder to the risk of losing corporate control in the event of a stock price decline. This paper aims to examine whether controlling shareholder share pledging drives corporate AI washing, and to identify the mechanisms through which this effect operates. This study indicates that controlling shareholder share pledging exerts a significant and robust exacerbating effect on corporate AI washing. The mechanism through which this effect operates lies in heightened earnings aggressiveness and aggravated information opacity. Besides, agency problems significantly strengthen this positive relationship, as controlling shareholders with greater agency discretion face fewer internal constraints on opportunistic AI disclosures. Analyst coverage, however, attenuates this exacerbating effect, consistent with the view that external monitoring by information intermediaries disciplines controlling shareholders' opportunistic behavior and mitigates the informational consequences of share pledging. From the perspective of controlling shareholders' financing behavior, this paper examines the driving effect of share pledging on corporate AI washing through heightened earnings aggressiveness and aggravated information opacity, thereby introducing this emerging opportunistic practice into the literature on the real effects of share pledging. Meanwhile, agency problems reinforce this effect from the internal governance perspective, while analyst coverage attenuates it from the external monitoring perspective, providing practical insights for regulators and investors to curb AI washing through the integration of internal and external governance mechanisms.

Australian Economic Papers
Nanjing University of Science and Technology (CN), Nanjing University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 4%
Auditing, Earnings Management, Governance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon