人际交往
心理学
透视图(图形)
中心性
社会心理学
人际关系
多级模型
考试(生物学)
计算机科学
生物
组合数学
古生物学
数学
机器学习
人工智能
作者
Naina Gupta,Violet T. Ho,Jeffrey M. Pollack,Lei Lai
摘要
Summary While it is generally known that interpersonal trust facilitates individual functioning, few studies have examined the role of specific features of the interpersonal trust network — individual, dyadic, third‐party, and network‐level features — on individual performance. We adopt a multilevel perspective of interpersonal trust to examine how individuals' performance is not only predicted by their individual‐level centrality in the interpersonal trust network but also moderated, at the network level, by the overall centralized nature of that network. Further, we examine whether mutual trust relationships at the dyadic level, as well as shared trust ties to common third parties, can predict individuals' performance. We test our hypotheses with 206 members in 15 professional networking groups and find that interpersonal trust operates at multiple levels to predict members' performance in terms of generating income from business referrals. These findings provide theoretical and practical implications on how interpersonal trust relationships operate and can be managed for performance gains. Copyright © 2016 John Wiley & Sons, Ltd.
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