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Purpose This study examines the relative effects of human capital (HC), social capital (SC) and psychological capital (PC) on hotel employees’ job performance. Design/methodology/approach A sample of 417 employees from seven five-star hotels in China was recruited for the study. Both exploratory and confirmatory factor analyses were used to confirm the quality of measurement structures. Stepwise regression was used to examine the relative effects of the three capitals on hotel employees’ job performance. Findings PC was found to be the strongest predictor of self-reported job performance (SJP) among the three capitals under investigation. Education and work experience in the HC domain affected SJP, whereas SC dimensions did not. However, only education and work experience in the HC domain were found to affect supervisor-rated job performance (RJP). Practical implications Given the impact of PC on hotel employee’s SJP, human resource managers should attend to this capital in staff recruitment, retention and training and development. Originality/value This study provides a holistic comparative lens to examine the relative contribution of the three capitals on hotel employees’ job performance. This will help to further clarify the roles played by each of the capitals in hotel service work, thus advancing the development of the theories underlying each of the three capitals.

Background Triglyceride glucose-body mass index (TyG-BMI) has been recommended as an alternative indicator of insulin resistance. However, the association between TyG-BMI and pre-diabetes remains to be elucidated. Methods More than 100,000 subjects with normal glucose at baseline received follow-up. The main outcome event of concern was pre-diabetes defined according to the diagnostic criteria recommended by the American Diabetes Association (ADA) in 2018 and the World Health Organization (WHO) in 1999. A Cox proportional hazard regression model was used to evaluate the role of TyG-BMI in identifying people at high risk of pre-diabetes. Results At a mean observation period of 3.1 years, the incidence of pre-diabetes in the cohort was 3.70 and 12.31% according to the WHO and ADA diagnostic criteria for pre-diabetes, respectively. The multivariate Cox regression analysis demonstrated that TyG-BMI was independently positively correlated with pre-diabetes, and there was a special population dependence phenomenon. Among them, non-obese people, women and people under 50 years old had a significantly higher risk of TyG-BMI-related pre-diabetes (P-interaction< 0.05). Conclusions These findings suggest that a higher TyG-BMI significantly increases an individual’s risk of pre-diabetes, and this risk is significantly higher in women, non-obese individuals, and individuals younger than 50 years of age.