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

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. Big Data Analysis and Small Data AnalysisPurpose: This study based on the two-Factor Theory, this study aims to explore determinants affecting job satisfaction of former and current employees within the restaurant industry by using two analytical. Methods: (1) Big data analysis through the collection of a large amount of corporate data from Job Planet, a Korean job portal site (2) Survey data analysis through the collection of questionnaires with relatively small data. The above results derived from two different methodologies are compared and analyzed to see if their implications are compatible to one another. Conclusions: This study utilized both survey and review data analyses to explore factors affecting job satisfaction among former and current employees in the restaurant industry based on the two-Factor Theory. The results of such analytical methods were compared to detect any differences between them. Implications: The results of analyzing survey and review data were similar in many aspects with minor differences. This suggests that either survey method or big data analysis can be meaningfully used in different contexts. For example, in situations where it is challenging to collect data from a specific group of audience who have low access to Internet, researchers may choose to use survey methods to collect information directly from the participants. Limitations: This study only used ratings on reviews that belong to quantitative information. However, job portal sites provide not only ratings on job satisfaction but also text reviews which are qualitative. We suggest future studies to understand job satisfaction of employees using qualitative reviews and various other information as well.