Impact of career development, job insecurity, and tech awareness on the quiet quitting of hospitality employees in Indonesia

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Employee performance is one of the main drivers for company development. However, there is an emergence of quiet quitting behavior, which many Generation Z workers experience. This behavior is detrimental to the company because it affects employee performance. The objective of this study is to analyze the influence of perceptions of career development opportunities, job insecurity, and awareness of intelligent technology on quiet quitting and its correlation with work performance, especially in Generation Z in Jakarta, Indonesia. This paper adopts an explanatory research design to elucidate the causal relationships between these variables using quantitative methods. Stratified random sampling was used to ensure representative data. Questionnaires were distributed to 289 hotel employees in Jakarta, capturing diverse perspectives across various job roles and departments. The data were analyzed using SmartPLS. The results showed a significant negative relationship between perceived career development opportunities and quiet quitting behavior. A positive and significant relationship exists between job insecurity and quiet quitting behavior. The study identifies a positive correlation between awareness of smart technology and quiet quitting behavior. Additionally, the paper reveals a significant negative relationship between quiet quitting behavior and employee performance. Perceived career development opportunities significantly reduce quiet quitting behavior, while job insecurity and awareness of smart technology increase it. Quiet quitting behavior, in turn, significantly negatively impacts employee performance. Organizations can develop targeted strategies to reduce this behavior by understanding the factors influencing quiet quitting.

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    • Figure 1. Conceptual framework
    • Table 1. Profile of research respondents
    • Table 2. Measurement model
    • Table 3. Fornell-Larcker’s criterion
    • Table 4. Path analysis
    • Conceptualization
      Nurul Sukma Lestari, Veithzal Rivai Zainal, Syafrizal Chan
    • Data curation
      Nurul Sukma Lestari, Lenny Christina Nawangsari
    • Formal Analysis
      Nurul Sukma Lestari, Veithzal Rivai Zainal, Syafrizal Chan, Lenny Christina Nawangsari
    • Investigation
      Nurul Sukma Lestari, Lenny Christina Nawangsari
    • Software
      Nurul Sukma Lestari, Syafrizal Chan
    • Writing – original draft
      Nurul Sukma Lestari
    • Writing – review & editing
      Nurul Sukma Lestari
    • Project administration
      Veithzal Rivai Zainal
    • Supervision
      Veithzal Rivai Zainal, Syafrizal Chan, Lenny Christina Nawangsari
    • Validation
      Veithzal Rivai Zainal, Syafrizal Chan, Lenny Christina Nawangsari
    • Methodology
      Syafrizal Chan, Lenny Christina Nawangsari
    • Resources
      Lenny Christina Nawangsari