What makes people stay? A focus on retention and job embeddedness as an alternative approach to the staff turnover problem in hospitality.

Abstract

This study takes a novel approach to the turnover problem by applying the job embeddedness (JE) construct to the hospitality industry and focusing on the factors that contribute to retention rather than turnover. A better understanding of the factors that contribute to employee embeddedness and retention of experienced employees is critical to business success. The job embeddedness construct considers the role of organisational (on-the-job) and community (off-the-job) dimensions, and these are considered in the context of hospitality employment. The study investigates the relative importance of organisational and community links, fit, and sacrifice domains, and explores the effect of these dimensions on intention to leave (ITL) the organisation. A mixed methods approach was adopted for the study, with in-depth interviews used in Study 1 to identify key themes for employee retention; and then these themes were used to inform development of the survey instrument in Study 2 for data collection. In conclusion, this study provides a novel perspective on job embeddedness and its relationship to intention to leave in the hospitality context. Confirmatory factor analysis provides qualified support for the job embeddedness model; however, after controlling for traditional attachment measures in this sample, JE did not identify any unique variance in intention to leave. The recognition of the influence of non-work-related factors on intention to leave using the job embeddedness community dimension may help organisations to better understand the factors that contribute to retention; and this in turn allows organisations to implement effective strategies such as customising work tasks and schedule flexibilities to increase employees’ job satisfaction and organisational commitment. In turn, this may increase employee retention and lead to improved retention of experienced and high value employees.

Date of Award	16 Jun 2018
Original language	English
Supervisor	R D Gordon (Supervisor) & Michael Raybould (Supervisor)