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- W4382045925 abstract "Does female employee whose job embeddedness is high proactively perform voice behavior which is potentially risky? This paper proposes an intelligent fuzzy neural network algorithm, which uses the memory characteristics of the neural network to automatically select the control strategy of each control stage. Make quick and accurate adjustments. Based on the questionnaire survey of 336 subordinate-supervisor dyads, this research explores the relationship between female employee's job embeddedness, work-family conflict and voice behavior, the mediating effect of work-family conflict and the moderating effect of supervisor support. The results indicate that female employee's job embeddedness has a positive effect on self-job-concerned voice and self-job-unconcerned voice while it negatively affects work-family conflict which mediates the relationship between female employee's job embeddedness and the two kinds of voice, supervisor support moderates the relationship between female employee's job embeddedness and work-family conflict as well as self-job-concerned voice. This research provides enterprises with guiding significance for preventing work-family conflict and encouraging voice behavior of female employees." @default.
- W4382045925 created "2023-06-27" @default.
- W4382045925 creator A5028694633 @default.
- W4382045925 date "2022-12-09" @default.
- W4382045925 modified "2023-09-27" @default.
- W4382045925 title "Analysis of Coupling Factors of Work Embeddedness Based on Intelligent Fuzzy Neural Network Algorithm" @default.
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- W4382045925 doi "https://doi.org/10.1145/3598438.3598463" @default.
- W4382045925 hasPublicationYear "2022" @default.
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