Bibliographische Detailangaben
| Titel: |
The ABCs of Quiet Quitting: A Bifurcated Framework of Its Passive and Deliberate Types. |
| Autoren: |
Kanwal, Fizza1 (AUTHOR) fizza.kanwal@unt.edu, Putri, Niken1,2 (AUTHOR), Jordan, Samantha L.1 (AUTHOR), Lopez‐Kidwell, Virginie1 (AUTHOR), Sawhney, Gargi3 (AUTHOR), Reger, Rhonda K.1 (AUTHOR), Bijlani, Ashish4 (AUTHOR) |
| Quelle: |
Human Resource Management. Aug2025, p1. 34p. 1 Illustration. |
| Schlagwörter: |
*ORGANIZATIONAL behavior, *HUMAN resources departments, PSYCHOLOGICAL disengagement |
| Abstract: |
ABSTRACT Our multi‐study, mixed‐methods research introduces a novel framework of quiet quitting and distinguishes it from related constructs in the human resources and organizational behavior literature. Studies 1 and 2 employ topic modeling of social and news media data and qualitative content analysis of in‐depth interviews with self‐identified quiet quitters, respectively, to examine how social media users, journalists, and quiet quitters define quiet quitting and describe its antecedents and consequences. Drawing on Kahn's framework of disengagement, we develop a bifurcated framework of quiet quitting comprising passive and deliberate types, each with distinct affective, cognitive, and behavioral dimensions. Study 3 uses a quasi‐Q‐sort methodology to compare passive and deliberate quiet quitting with existing human resources and organizational behavior constructs and reveals that quiet quitting is a novel concept, with its passive and deliberate types being distinct from nomologically related constructs. Our bifurcated framework makes valuable theoretical contributions and offers nuanced practical implications for organizations, establishing a solid foundation for future research to treat quiet quitting as a discrete phenomenon, moving the conversation beyond debating its academic relevance. [ABSTRACT FROM AUTHOR] |
|
Copyright of Human Resource Management is the property of Wiley-Blackwell 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.) |
| Datenbank: |
Business Source Index |