2018/10/10 by Sushil S. Nifadkar, Sushil Nifadkar, Wen Wu +1 · 63 citations
Business, Management and Accounting · Psychology · Social Sciences · #Applied psychology #Computer science #Information retrieval #Information seeking #Information sharing #Job Satisfaction and Organizational Behavior #Knowledge Management and Sharing #Knowledge management #Psychology #Social psychology #Structural equation modeling #Test (biology) #Work (physics) #Work-Family Balance Challenges #World Wide Web
paper · doi:10.1111/peps.12305
published in Personnel Psychology 72(2), 241-269 (Wiley)
openalex publication_date 2018/10/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/02
Abstract Although significant scholarly attention has been devoted to understanding subordinates’ information seeking from supervisors, researchers have not paid adequate attention to information sharing by supervisors. Moreover, research on supervisors’ information sharing behavior has focused almost exclusively on work‐related information sharing, disregarding supervisors’ sharing of information not related to work (e.g., that related to family). Drawing on self‐disclosure theory, we argue that supervisors share both work‐related and nonwork information with their subordinates and propose that these two forms of information sharing are conceptually distinct. Furthermore, to unravel the role of supervisors’ nonwork information sharing, we develop an interactive model to test how it may be associated with important employee outcomes. We conducted pilot studies using five samples and, through a sixth study, tested the hypothesized model using a four‐wave data collection design. This study makes three major contributions to research and theory. First, it integrates information sharing and information seeking literatures. Second, it underlines the importance of supervisors’ nonwork information sharing in organizations by testing its direct and interactive effects. Third, it contributes to theory by presenting trust as a mechanism that links information disclosure in dyads. Results obtained using structural equation modeling generally supported the proposed model.