Investigating the effect of AI technostress on employee’s working behaviors: a stress response model

Purpose This study aims to adopt the stressor–response–outcome framework and coping theory to examine hospitality employees’ cognitive and emotional coping strategies, and their behavioral decisions in response to artificial intelligence (AI)-induced technostress. Design/methodology/approach We surveyed 386 participants and utilized partial least square- structural equation modelling to analyze the research model. Findings The results reveal that (1) AI technostress creators drive employees to use problem-focused coping (PFC) and emotion-focused coping (EFC) strategies. (2) EFC leads to a negative work outcome (lying flat), while PFC leads to a positive one (involution). (3) Work value congruence affects the relationship between PFC and involution, and the connection between EFC and lying flat. Originality/value This study contributes to the literature by exploring the psychological coping processes, behavioral trigger condition and outcomes experienced by hospitality employees affected by AI technostress. The findings can help hospitality organizations better manage employee stress and behaviors in the context of AI applications, as well as facilitate the collaborative adaptation of AI within hospitality operations.