Exploring Determinants of Job Satisfaction: A Comparison Between Survey and Review Data

Changjae Lee, Byunghyun Lee, Ilyoung Choi and Jaekyeong Kim

SAGE Open, 2023, vol. 13, issue 4, 21582440231216528

Abstract: Compared to other sectors, the restaurant industry has a high reliance on human resources through active interactions with customers. Therefore, it is important to identify job satisfaction among employees and satisfy their needs at work in order to provide high customer service. Until now, surveys have been the traditional method for measuring employees’ job satisfaction. Recently, numerous studies have analyzed employee job satisfaction based on extensive data collected directly from job portal websites. Therefore, it is necessary to verify whether the results of job satisfaction among employees derived from such methods have similar implications. This study compared the results of job satisfaction analysis using (1) 11,446 big data provided by former & current employees of the restaurant industry from a job portal website based on the two-factor theory and (2) A survey was conducted among 400 former & current employees. We found that only in big data, advancement opportunities & possibilities, and the compensation system significantly and positively (+) affected job satisfaction. In addition, current employees are more satisfied with advancement opportunities & possibilities than former employees only in big data. Thus, the big data and survey data analysis results differ. This can be attributed to the functionality and benefits of job portals. Therefore, it is necessary to consider the portal site’s functions, beneficial features, and online environment characteristics before using big data in the field of human resources.

Keywords: job satisfaction; two-factor theory; survey data; review data; job portal website (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:13:y:2023:i:4:p:21582440231216528

DOI: 10.1177/21582440231216528

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