Intelligence-driven and psychological adaptation: the double-edged sword effect of AI awareness on intrapreneurial behavior among hotel employees

Purpose This study aims to examine how artificial intelligence (AI) awareness exerts a double-edged sword effect on intrapreneurial behavior through two parallel mechanisms: job insecurity (a resource–loss pathway) and organizational identification (an identity–enhancement pathway), moderated by mindfulness. Design/methodology/approach This study collected data via a two-wave survey of 434 employees in the Chinese hotel industry. Data analysis was conducted using AMOS 24.0, SPSS 26.0 and Hayes’ PROCESS macros. Findings Results indicate that AI awareness triggers two different psychological processes. It both heightens job insecurity (thereby suppressing intrapreneurial behavior) and strengthens organizational identification (thereby fostering such behavior). Furthermore, employee mindfulness moderates these relationships, buffering the negative path and amplifying the positive one. Originality/value By jointly applying conservation of resources and social identity theories, the study reveals how resource threats and identity enhancement influence employees’ responses to AI. The findings offer practical insights for fostering innovation in human–AI collaborative environments.

Authors

Institutions

Publication Details

Journal
Journal of Hospitality and Tourism Technology
Published
2026-04-11
DOI
https://doi.org/10.1108/jhtt-03-2025-0254
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Intelligence-driven and psychological adaptation: the double-edged sword effect of AI awareness on intrapreneurial behavior among hotel employees

Jianxin Zhou, furu wang, Jing Huang, Xi Li
Journal of Hospitality and Tourism Technology
AI in Service Interactions
article

Intelligence-driven and psychological adaptation: the double-edged sword effect of AI awareness on intrapreneurial behavior among hotel employees

Jianxin Zhou, furu wang, Jing Huang, Xi Li
article en

Abstract

Purpose This study aims to examine how artificial intelligence (AI) awareness exerts a double-edged sword effect on intrapreneurial behavior through two parallel mechanisms: job insecurity (a resource–loss pathway) and organizational identification (an identity–enhancement pathway), moderated by mindfulness. Design/methodology/approach This study collected data via a two-wave survey of 434 employees in the Chinese hotel industry. Data analysis was conducted using AMOS 24.0, SPSS 26.0 and Hayes’ PROCESS macros. Findings Results indicate that AI awareness triggers two different psychological processes. It both heightens job insecurity (thereby suppressing intrapreneurial behavior) and strengthens organizational identification (thereby fostering such behavior). Furthermore, employee mindfulness moderates these relationships, buffering the negative path and amplifying the positive one. Originality/value By jointly applying conservation of resources and social identity theories, the study reveals how resource threats and identity enhancement influence employees’ responses to AI. The findings offer practical insights for fostering innovation in human–AI collaborative environments.

Journal of Hospitality and Tourism Technology
National Taiwan University of Science and Technology (TW), Shenzhen University (CN), Longyan University (CN), University Town of Shenzhen (CN), City University of Macau (MO)
Decent work and economic growth
Openalex Percentile: Top 5%
AI in Service Interactions
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.