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

Author:

Lee Changjae1,Lee Byunghyun1ORCID,Choi Ilyoung1,Kim Jaekyeong1

Affiliation:

1. Kyung Hee University, Dongdaemun-gu, Seoul, Korea

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.

Publisher

SAGE Publications

Subject

General Social Sciences,General Arts and Humanities

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3