Workplace Ties that Matter: The Impact of Advice and Friendship Networks on Employee Identification, Well-Being, and Turnover Intention

While workplace networks shape employees’ perceptions, attitudes, and behaviors, prior research has primarily emphasized organizational and leadership-related factors. This study adopts an egocentric network perspective to explore how employees’ workplace network characteristics—such as network size, relationship closeness, multiplex ties, and employee-organization relationship (EOR) norms—are associated with their organizational identification, well-being, and intentions to leave, within both advice and friendship networks. The findings reveal the nuanced patterns in these associations across the two network types. A larger friendship network corresponds with higher organizational identification and well-being, whereas the size of an advice network does not show a significant relationship with employee outcomes. Relationship closeness within advice networks is linked to greater organizational identification and well-being, while closeness within friendship networks does not show a significant association. EOR norms within both advice and friendship networks are positively related to employee outcomes. Additionally, the higher proportion of friends in advice networks corresponds with greater well-being and lower turnover intentions, while having supervisors as friends is associated with lower well-being. This research contributes to employee and organizational communication literature by highlighting the relevance of personal network dynamics in understanding employee attitudes and behaviors.

Authors

Institutions

Publication Details

Journal
Management Communication Quarterly
Published
2025-10-08
DOI
https://doi.org/10.1177/08933189251388106
Primary Topic
Job Satisfaction and Organizational Behavior
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Workplace Ties that Matter: The Impact of Advice and Friendship Networks on Employee Identification, Well-Being, and Turnover Intention

Hae Jung Kim, Cen April Yue, Alvin Zhou, Yan Qu
Management Communication Quarterly
Job Satisfaction and Organizational Behavior
article

Workplace Ties that Matter: The Impact of Advice and Friendship Networks on Employee Identification, Well-Being, and Turnover Intention

Hae Jung Kim, Cen April Yue, Alvin Zhou, Yan Qu
article en

Abstract

While workplace networks shape employees’ perceptions, attitudes, and behaviors, prior research has primarily emphasized organizational and leadership-related factors. This study adopts an egocentric network perspective to explore how employees’ workplace network characteristics—such as network size, relationship closeness, multiplex ties, and employee-organization relationship (EOR) norms—are associated with their organizational identification, well-being, and intentions to leave, within both advice and friendship networks. The findings reveal the nuanced patterns in these associations across the two network types. A larger friendship network corresponds with higher organizational identification and well-being, whereas the size of an advice network does not show a significant relationship with employee outcomes. Relationship closeness within advice networks is linked to greater organizational identification and well-being, while closeness within friendship networks does not show a significant association. EOR norms within both advice and friendship networks are positively related to employee outcomes. Additionally, the higher proportion of friends in advice networks corresponds with greater well-being and lower turnover intentions, while having supervisors as friends is associated with lower well-being. This research contributes to employee and organizational communication literature by highlighting the relevance of personal network dynamics in understanding employee attitudes and behaviors.

Management Communication QuarterlyVol. 40(2)
University of Minnesota (US), University of Minnesota System (US), University of Maryland, College Park (US), University of Tennessee at Knoxville (US)
Openalex Percentile: Top 67%
Job Satisfaction and Organizational Behavior
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.