Generative artificial intelligence as a catalyst for employee happiness and sustainable performance in green hotel management

Abstract
Purpose – This study aims to empirically examine the impact of generative artificial intelligence (GAI) on
employee happiness within green hotel environments in Spain. By analyzing 221 eco-hotels, it explores how
GAI influences the awareness of key sustainability indicators, environmental performance, process
management, and sustainability – and how these, in turn, affect employee happiness. Employee happiness is
directly related to occupational well-being and job satisfaction, fostering greater motivation, lower turnover and
improved service quality. The study explores how advanced technologies foster sustainable, competitive and
human-centered workplaces in hospitality, addressing gaps in happiness management research.
Design/methodology/approach – This study uses a mixed-method approach combining focus group insights
and PLS-SEM analysis of 221 Spanish Ecostars-certified green hotels, examining how generative AI impacts
employee happiness, environmental performance, management processes and sustainability, providing a novel
framework for Industry 5.0 competitiveness.
Findings – The study confirms that generative AI positively influences employee happiness in green hotels by
enhancing process efficiency, sustainability and environmental awareness. GAI improves management
processes (61.6% variance),supports sustainable practices and enablesfulfilling work. Environmentally driven
performance significantly increases happiness, validating GAI and sustainability as key predictors for a
competitive, responsible tourism sector.
Originality/value – This first EU study links generative AI to employee happiness in Spain’s green hospitality
sector, validating a PLS-SEM model thatshows GAI fosters pro-environmental behavior, operational efficiency
and well-being, challenging the view of AI as purely job automation.