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Date Available
5-1-2028
Year of Publication
2026
Document Type
Doctoral Dissertation
Degree Name
Doctor of Business Administration (DBA)
College
Business and Economics
Department/School/Program
Accountancy
Faculty
Hong Xie
Faculty
Brian Bratten
Faculty
Monika Causholli
Abstract
This study examines whether technological peer pressure (TPP) distorts the informativeness of corporate AI investment disclosure, defined as how faithfully disclosed AI investment reflects underlying AI investment. Using textual analysis based on word-embedding machine learning and data on AI-skilled employees, I measure disclosure distortion as the difference between a firm’s decile rank in retrospective AI investment disclosure and its decile rank in actual AI investment among peer firms. I find that TPP is positively associated with overstatement of underlying AI investment. This effect is stronger when managers have incentives to benefit from favorable investor perceptions, avoid appearing technologically behind, or signal AI competitiveness, but weaker when proprietary cost concerns dominate. Using AI innovation breakthroughs as a quasi-natural experiment, I provide causal evidence linking TPP to overstatement. This distortion is associated with capital market mispricing: highly overstating firms appear temporarily overvalued, while a hedge portfolio that shorts these firms and longs low distortion firms earns significant abnormal returns over the subsequent one- to two-year horizon. Overstating firms also attract more capital without delivering superior operating or AI innovation performance relative to peers whose disclosures align with underlying AI investment. Overall, the evidence raises regulatory concerns about truthful AI-related disclosure and efficient capital allocation.
Digital Object Identifier (DOI)
https://doi.org/10.13023/etd.2026.146
Archival?
Archival
Recommended Citation
Ju, Zeyang Jackie, "Does technological peer pressure distort the informativeness of corporate AI investment disclosure?" (2026). Theses and Dissertations--Accountancy. 26.
https://uknowledge.uky.edu/accountancy_etds/26
