Building a Resilient Organization Through Informal Networks: Examining the Role of Individual, Structural, and Attitudinal Factors in Advice-Seeking Tie Formation

Modern organizations operate not only through formal structures but also through informal networks, which play a critical role in fostering a resilient organization. This study focused on informal advice networks within organizations as a key mechanism for strengthening contextual resilience, one of...

Full description

Saved in:
Bibliographic Details
Main Authors: Xiaoyan Jin, Daegyu Yang, Wanlan Sun, Lian Xu
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Systems
Subjects:
Online Access:https://www.mdpi.com/2079-8954/13/4/245
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Modern organizations operate not only through formal structures but also through informal networks, which play a critical role in fostering a resilient organization. This study focused on informal advice networks within organizations as a key mechanism for strengthening contextual resilience, one of the core components of organizational resilience. By analyzing the activation of informal advice networks, this study conceptualized advice-seeking networks as a critical informal system that enhances contextual resilience and examined the individual, structural, and attitudinal factors influencing their formation. Specifically, we hypothesized that employees with higher levels of Machiavellianism are more likely to engage in advice-seeking behaviors, whereas the relationship between Machiavellianism and advice-seeking behaviors is moderated by betweenness centrality and organizational commitment, such that the positive effect of Machiavellianism on advice-seeking is weaker when betweenness centrality or organizational commitment is high. To empirically test these hypotheses, we conducted a network survey of employees at the headquarters of a life insurance company in Seoul, South Korea, and analyzed the data using an Exponential Random Graph Model (ERGM). The findings provide empirical support for all hypotheses. Based on these results, we discussed the theoretical contributions and practical implications of the study, along with its limitations.
ISSN:2079-8954