This research aims to use meta-analytical structural equation modeling to look into how hospitality employees use technology at work. It further investigates if the relationship between the constructs of the technology acceptance model (TAM) is moderated by job level (supervisory versus non-supervisory) and different cultures (eastern versus western).
In total, 140 relationships from 30 empirical studies (N = 6,728) were used in this study’s data analysis in accordance with the preferred reporting items for systematic reviews and meta-analysis.
The findings demonstrated that perceived usefulness had a greater influence on “user attitudes” and “acceptance intention” than perceived ease of use. This study also identified that the effect sizes of relationships among TAM constructs appeared to be greater for supervisory employees or in eastern cultures than for those in non-supervisory roles or western cultures.
The findings provide valuable information for practitioners to increase the adoption of employee technology. Practitioners need to focus on the identification of hospitality employee attitudes, social norms and perceived ease of use. Moreover, hospitality practitioners should be cautious when promoting the adoption of new technologies to employees, as those at different levels may respond differently.
This is the very first empirical investigation to meta-analyze the predictive power of the TAM in the context of hospitality staff technology adoption at the workplace. The findings also demonstrated differences in the predictive power of TAM constructs according to job level and cultural differences.
This work was jointly supported by the National Natural Science Foundation of China (71661006, 72041026) and the Hainan Provincial Natural Science Foundation of China.(2019CXTD402).
Guo, Q., Zhu, D., Lin, M.-T.(B)., Li, F.(S)., Kim, P.B., Du, D. and Shu, Y. (2022), "Hospitality employees’ technology adoption at the workplace: evidence from a meta-analysis", International Journal of Contemporary Hospitality Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJCHM-06-2022-0701
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