Can Enterprise Intelligent Transformation Resolve the “Productivity Paradox?” Evidence from Chinese Listed Companies

Intelligent transformation is one of the primary strategies driving industrial upgrading, enhancing quality, and increasing efficiency in China. This study quantifies the extent of intelligent transformation among Chinese listed companies from 2009 to 2023, employing text processing techniques and a...

Full description

Saved in:
Bibliographic Details
Published inJournal of advanced computational intelligence and intelligent informatics Vol. 29; no. 4; pp. 894 - 909
Main Authors Yang, Jingyi, Zhang, Xiuwu, Deng, Yarui
Format Journal Article
LanguageEnglish
Published Tokyo Fuji Technology Press Co. Ltd 20.07.2025
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Intelligent transformation is one of the primary strategies driving industrial upgrading, enhancing quality, and increasing efficiency in China. This study quantifies the extent of intelligent transformation among Chinese listed companies from 2009 to 2023, employing text processing techniques and analyzing annual reports. It subsequently investigates the comprehensive impact of intelligent transformation on these enterprises’ total factor productivity (TFP) and clarifies the dynamic mechanism enterprise environmental, social, and governance (ESG) performance plays in this process. The findings reveal that: (1) the introduction of intelligent capital leads to improved factor market competition, thereby reducing the dispersion of nominal TFP among firms and ultimately driving TFP growth; (2) intelligent transformation significantly enhances firms’ TFP, a conclusion that remains valid after considering endogeneity issues and conducting a series of robustness checks, thereby disproving the “productivity paradox;” (3) in terms of impact mechanisms, it promotes the improvement of TFP by enhancing corporate ESG performance; however, (4) the enabling effect of intelligent transformation on TFP varies significantly across firms based on the nature of their ownership, factor intensity, and geographical location.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1343-0130
1883-8014
DOI:10.20965/jaciii.2025.p0894