1,217
Views
13
CrossRef citations to date
0
Altmetric
Articles

Trust in the supervisor and the development of employees’ social capital during organizational entry: a conservation of resources approach

&
Pages 2503-2523 | Published online: 12 Oct 2016
 

Abstract

This article aims to understand how trust in the supervisor contributes to the development of employees’ social capital using Conservation of Resources theory as a theoretical framework and networking ability as an indicator of social capital development. We hypothesize that the relationship between newcomers’ trust in the supervisor and networking ability will be mediated by feedback seeking from the supervisor and moderated by emotional exhaustion. Based on a three-wave time-lagged study of newcomers (N = 224), we found trust in the supervisor to be indirectly and positively related to networking ability through the mediating influence of feedback seeking from the supervisor. In addition, feedback seeking interacted with emotional exhaustion in predicting networking ability such that it was more positively related to it at high levels of emotional exhaustion. The indirect relationship of trust to networking ability as mediated by feedback seeking was also stronger at high levels of emotional exhaustion. We discuss this study’s implications for our understanding of supervisors’ role and newcomers’ experience during entry, as well as for social capital research.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 352.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.