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The trickle-down effect of leader mindfulness on employee creative deviance behavior: A moderated mediation model.

  • Published In: Social Behavior & Personality: an international journal, 2023, v. 51, n. 9. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Chen, Jiaxian; Peng, Wei; Han, Lijuan 3 of 3

Abstract

Applying social learning theory and the trickle-down effect, in this study we built a cross-level research model to explore how high-level leader mindfulness stimulates employee creative deviance behavior via the mediating effect of middle-level leader mindfulness. Using data obtained from 345 employees and 81 of their leaders in manufacturing research and development enterprises in China, our results showed that high-level leader mindfulness had a significantly positive effect on middle-level leader mindfulness. Middle-level leader mindfulness, in turn, positively affected employee creative deviance behavior and mediated the relationship between high-level leader mindfulness and employee creative deviance behavior. Further, leader–member exchange positively moderated the relationship between high-level leader mindfulness and middle-level leader mindfulness, and also moderated the indirect effect of high-level leader mindfulness on employee creative deviance through middle-level leader mindfulness. The study findings will help organizations to understand how leader mindfulness affects employees' creative deviance behavior and also provide practical enlightenment for enterprise innovation management. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Social Behavior & Personality: an international journal. 2023/09, Vol. 51, Issue 9, p1
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2023
  • ISSN:0301-2212
  • DOI:10.2224/sbp.12574
  • Accession Number:171847022
  • Copyright Statement:Copyright of Social Behavior & Personality: an international journal is the property of Scientific Journal Publishers Limited and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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