Author
Listed:
- Zhu, Di
- Qiu, Xiaodong
- Zhu, Chenzhi
Abstract
In the era of digital intelligence, while artificial intelligence injects new momentum into corporate development, its efficacy in enhancing brand management performance remains an open empirical question. Grounded in the Technology Affordance Actualization Theory, which posits that AI possesses the potential to drive brand value enhancement, yet the achievement of expected outcomes depends on the implementation practices employed by enterprises. This theory emphasizes the interaction between technology's objective and subjective attributes, offering an appropriate research perspective to address this research question. Consequently, we construct a research framework structured as “AI Affordance–Consumer Value Perception–Brand Value.” Employing machine learning techniques to develop an AI affordance lexicon, this research analyzes the annual reports of Chinese listed companies to construct corporate-level measures of AI autonomy and interactivity affordance. It thereby examines the impact and mechanistic pathways through which AI affordance influences corporate brand value. The findings reveal: (1) AI affordance exerts a statistically significant positive effect on brand value, with empirical robustness confirmed through the Heckman two-stage model and propensity score matching analyses. (2) Threshold analysis indicates a dual-threshold effect of AI affordances on corporate brand value. (3) Mediation analysis reveals that consumers' perceptions of functional, economic, and emotional value partially mediate the link between AI affordances and brand value. (4) Heterogeneity analysis, based on data from listed Chinese brand firms, indicates that AI affordances' brand value enhancement effect is more pronounced among firms in highly competitive markets, regions with elevated local government data openness, China's time-honored brand, and politically affiliated entities. This research extends the applicability of technological affordances actualization theory in the AI era, providing actionable insights for leveraging AI to amplify brand value.
Suggested Citation
Zhu, Di & Qiu, Xiaodong & Zhu, Chenzhi, 2026.
"Artificial intelligence affordances, consumer value perceptions, and corporate brand value,"
Technology in Society, Elsevier, vol. 87(C).
Handle:
RePEc:eee:teinso:v:87:y:2026:i:c:s0160791x26001570
DOI: 10.1016/j.techsoc.2026.103368
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:teinso:v:87:y:2026:i:c:s0160791x26001570. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/technology-in-society .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.