Gender’s Moderating Effect on Perceived Organizational Politics and Withdrawal Dimensions Among Construction Professionals.
Saved in:
| Title: | Gender’s Moderating Effect on Perceived Organizational Politics and Withdrawal Dimensions Among Construction Professionals. |
|---|---|
| Authors: | Dhanasekar, Yuvaraj1, K. S., Anandh1 anandh.ks@gmail.com |
| Source: | Construction Economics & Building. Jul2025, Vol. 25 Issue 2, p69-88. 20p. |
| Subjects: | Gender, Office politics, Construction industry personnel, Withdrawal (Psychology), Social exchange, Psychological disengagement, Labor turnover |
| Abstract: | The current study, supported by equity theory of motivation, explores how gender moderates perceived organizational politics effects on psychological and physical organizational withdrawal behaviors of professionals within the construction sector, a field characterized by a challenging work environment and high employee turnover. Quantitative data were collected from 318 construction professionals and analyzed using partial least squares structural equation modeling (PLS-SEM). The findings reveal that perceived organizational politics significantly and positively impacts both psychological and physical withdrawal behaviors among construction professionals. Further, gender moderates this relationship, with female professionals showing a greater tendency to disengage compared to their male counterparts. This research contributes to the construction management literature by highlighting the gender effects of organizational politics on employee withdrawal, a previously underexplored area. The study underscores the critical need for organizations to address political dynamics in the workplace to foster a fair and supportive environment, ultimately enhancing employee well-being and organizational performance. [ABSTRACT FROM AUTHOR] |
| Copyright of Construction Economics & Building is the property of University of Technology, Sydney 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.) | |
| Database: | Engineering Source |
Be the first to leave a comment!