Human–AI Collaboration and Employee Service Innovation in Tourism Services: The Mediating Role of AI-Enabled Knowledge Integration and the Moderating Role of Organisational Support

Abstract

Artificial intelligence (AI) is increasingly embedded in tourism service work, yet the presence or use of AI does not by itself explain how employees convert machine-generated information into innovative service responses. This study develops and tests a conditional-process model in which Human–AI Collaboration (HAIC) is associated with Employee Service Innovation Behaviour (SIB) through AI-enabled Knowledge Integration (AIKI), while Organisational Support for Human–AI Collaboration (AISUP) conditions the HAIC–AIKI relationship. Drawing on dynamic capabilities theory and sociotechnical systems theory, the study conceptualises employee–AI collaboration as an enacted work process and AI-enabled knowledge integration as a micro-level transformation mechanism through which AI information is evaluated, combined with professional and customer knowledge, and translated into service action. The empirical analysis uses 450 complete employee records containing 19 focal indicators measured on five-point Likert scales. The four-factor measurement model showed very good fit, χ²(146) = 166.07, p = 0.122, CFI = 0.997, TLI = 0.996, RMSEA = 0.017, and SRMR = 0.025. HAIC was positively associated with AIKI (B = 0.558, p < 0.001), AIKI was positively associated with SIB (B = 0.422, p <0 .001), and HAIC remained positively associated with SIB (B = 0.320, p < 0.001). The HAIC × AISUP interaction was positive and statistically significant (B = 0.122, SE = 0.060, p = 0.044). A 5,000-resample bootstrap indicated a positive indirect association through AIKI (B = 0.236, 95% CI [0.184, 0.288]) and a significant index of moderated mediation (B = 0.051, 95% CI 0[0.008, 0.097]). Conditional indirect effects were 0.201 at low AISUP and 0.270 at high AISUP. The findings position AI-enabled knowledge integration as the central conversion mechanism linking employee–AI collaboration with service innovation and show that organisational support changes the strength of this conversion process. Given the cross-sectional, single-source design, the results are interpreted as associational rather than causal.