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Analyzing Determinants of Job Satisfaction Based on Two-Factor Theory

Author

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  • Byunghyun Lee

    (Department of Big Data Analytics, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02453, Korea)

  • Changjae Lee

    (Department of Business Administration, Graduate School, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02453, Korea)

  • Ilyoung Choi

    (Department of Big Data Analytics, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02453, Korea)

  • Jaekyeong Kim

    (Department of Big Data Analytics, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02453, Korea
    School of Management, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02453, Korea)

Abstract

For one company to have a competitive advantage and sustainability over others, its human resource management is of the utmost importance to secure competent employees. As job satisfaction plays a critical role in securing excellent manpower and enhancing corporate performance, it is essential to identify factors that would affect employees’ job satisfaction. Recently, writing reviews with integrity on job portal sites by former and current employees has become prevalent as such websites have guaranteed the reviewers’ anonymity. For this reason, we collected a vast amount of review data over nine industries, such as IT web communication, from one of the representative job portal sites in South Korea, Job Planet, and investigated factors that affect one’s job satisfaction based on the two-factor theory. As a result, it was found that (1) both motivation and hygiene factors had a substantial effect on job satisfaction over all industries; (2) the moderating effect between former and current employees was different for each industry; and (3) there was no moderating effect on job satisfaction between motivation and hygiene factors.

Suggested Citation

  • Byunghyun Lee & Changjae Lee & Ilyoung Choi & Jaekyeong Kim, 2022. "Analyzing Determinants of Job Satisfaction Based on Two-Factor Theory," Sustainability, MDPI, vol. 14(19), pages 1-19, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12557-:d:931989
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    References listed on IDEAS

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    Cited by:

    1. Dr. Muhammad Bilal Ahmad & Ayesha Badar & Dr. Muhammad Ramzan, 2023. "Investigating the Factors Affecting Employee Job Satisfaction through Job Autonomy in the Growing Concept of Hybrid Working Model in the IT Industry," Journal of Policy Research (JPR), Research Foundation for Humanity (RFH), vol. 9(2), pages 591-601.
    2. Changjae Lee & Byunghyun Lee & Ilyoung Choi & Jaekyeong Kim, 2023. "Exploring Determinants of Job Satisfaction: A Comparison Between Survey and Review Data," SAGE Open, , vol. 13(4), pages 21582440231, December.
    3. Phi-Hung Nguyen, 2023. "A Fully Completed Spherical Fuzzy Data-Driven Model for Analyzing Employee Satisfaction in Logistics Service Industry," Mathematics, MDPI, vol. 11(10), pages 1-34, May.

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