RT journal article
T1 Generative artificial intelligence as a catalyst for employee happiness and sustainable performance in green hotel management
A1 Robina Ramírez, Rafael
A1 Ravina Ripoll, Rafael
A1 Leal-Solis, Ana
A1 Medina-Merodio, José Amelio
A2 Organización de Empresas
K1 Green hotels
K1 Happiness
K1 Sustainability
K1 Generative artificial intelligence
K1 Technology
AB Purpose – This study aims to empirically examine the impact of generative artificial intelligence (GAI) onemployee happiness within green hotel environments in Spain. By analyzing 221 eco-hotels, it explores howGAI influences the awareness of key sustainability indicators, environmental performance, processmanagement, and sustainability – and how these, in turn, affect employee happiness. Employee happiness isdirectly related to occupational well-being and job satisfaction, fostering greater motivation, lower turnover andimproved service quality. The study explores how advanced technologies foster sustainable, competitive andhuman-centered workplaces in hospitality, addressing gaps in happiness management research.Design/methodology/approach – This study uses a mixed-method approach combining focus group insightsand PLS-SEM analysis of 221 Spanish Ecostars-certified green hotels, examining how generative AI impactsemployee happiness, environmental performance, management processes and sustainability, providing a novelframework for Industry 5.0 competitiveness.Findings – The study confirms that generative AI positively influences employee happiness in green hotels byenhancing process efficiency, sustainability and environmental awareness. GAI improves managementprocesses (61.6% variance),supports sustainable practices and enablesfulfilling work. Environmentally drivenperformance significantly increases happiness, validating GAI and sustainability as key predictors for acompetitive, responsible tourism sector.Originality/value – This first EU study links generative AI to employee happiness in Spain’s green hospitalitysector, validating a PLS-SEM model thatshows GAI fosters pro-environmental behavior, operational efficiencyand well-being, challenging the view of AI as purely job automation.
PB Emerald
SN 1758-6658
YR 2025
FD 2025-12-02
LK http://hdl.handle.net/10498/38268
UL http://hdl.handle.net/10498/38268
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 09-nov-2026