Exploring the job embeddedness construct as a predictor of intention to leave in hospitality workers

Laurina Yam, Michael Raybould

Research output: Contribution to conferenceAbstractResearchpeer-review

Abstract

It has frequently been claimed that the hospitality industry is plagued by high employee turnover rates. However, there is evidence to suggest that a significant proportion of hospitality staff remain with employers for many years (Taylor & Finley, 2010; Yam and Raybould, 2018). Research into employee tenure in the hospitality industry has focused on the causes of turnover, but there has been little research into the factors that contribute to retention, even though these factors may have more valuable lessons for the design of human resource strategies. This study investigates the factors that contribute to employment stability and retention and provides the first examination and comparison of the job embeddedness construct (Mitchel et al., 2001) with traditional attachment measures, and intent to leave, in a hospitality environment. A survey instrument comprising several well validated, scales was used to collect data from 360 employees in four and five-star hotels in Australia. Confirmatory Factor Analysis supports a twofactor structure for each of the dimensions of the job embeddedness scale. This is consistent with findings by Zhang et al. (2012) and provides more support for a rethink of the original three-factor structure proposed by Mitchel et al. (2001). Multiple regression analysis using only the two dimensions of job embeddedness as independent variables shows that job embeddedness within the organisation was a significant predictor of intention to leave an employer, but the community dimension was not. More importantly, in a combined model that included traditional predictors of turnover, job satisfaction, organisational commitment and perceived organisational support were all significant predictors of intention to leave an employer but neither of the job embeddedness dimensions was significant when controlling for the other predictors.
Original languageEnglish
Pages36
Number of pages1
Publication statusPublished - Apr 2019
EventThe 3rd International Conference on Tourism and Business 2019 - Mahidol University, Bangkok, Thailand
Duration: 27 Aug 201929 Aug 2019
Conference number: 3rd
https://muic.mahidol.ac.th/tourism2019/

Conference

ConferenceThe 3rd International Conference on Tourism and Business 2019
Abbreviated titleICTB
CountryThailand
CityBangkok
Period27/08/1929/08/19
Internet address

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