Employee retention remains a persistent challenge in the
hospitality industry due to high labour intensity, emotional labour demands,
and volatile employment conditions. At the same time, hospitality organisations
are increasingly adopting artificial intelligence (AI)–enabled human resource
(HR) systems to improve efficiency and decision-making. While prior research
emphasises the role of HR practices in shaping employee retention, it largely
overlooks how employees’ acceptance of technology conditions the effectiveness
of these practices in AI-enabled organisational contexts. Drawing on the
Technology Acceptance Model (TAM) and insights from established HR and
motivation theories, this study examines the relationships between core HR
practices, perceived usefulness, perceived ease of use, and employees’
intention to stay in AI-enabled hospitality organisations. Using an explanatory
research design, data were collected through a structured questionnaire
administered to employees of four- and five-star hotels in Kolkata, India. A
total of 193 valid responses were analysed using reliability analysis,
correlation analysis, hierarchical regression, and mediation–moderation testing
with the PROCESS macro. The results indicate that compensation and benefits
have a significant direct effect on intention to stay, while training and
development, career development, and performance appraisal do not exhibit
significant direct effects. Importantly, perceived usefulness mediates the
relationship between HR practices and intention to stay, whereas perceived ease
of use moderates the effectiveness of HR practices by shaping employees’
acceptance of AI-enabled HR systems.
The findings extend the Technology Acceptance Model beyond
technology adoption to explain employee retention and offer a socio-technical
perspective on HR effectiveness in AI-enabled hospitality contexts. The study
provides actionable insights for hospitality managers seeking to leverage
AI-enabled HR systems to strengthen employee retention.
Author(s) Details
Mahasweta Ghosh
NSHM, Durgapur, India.
Please see the book here :- https://doi.org/10.9734/bpi/nhstc/v7/7014
No comments:
Post a Comment