Dimensions of social network position as predictors of employee performance.

Description:

Research of social networks has revealed that certain components of network position can have an impact on organizational effectiveness, yet relatively little research has been conducted on network position and individual performance. This study sought to determine if a relationship exists between an employee's social network position and an individual's job performance. The participant organization was a network of individuals within an Information Technology (IT) department at a major defense company. A social network analysis (SNA) was conducted to determine the employee's network position, measured by centrality and constraint. Centrality refers to the extent to which an individual is connected to others. Constraint refers to how constrained or inhibited an individual is within the network. Performance was measured by annual appraisal ratings provided by the employee's supervisor. Hierarchical regression analysis was performed to determine relationships between the dependent variable (performance) and independent variables of centrality and constraint. Secondary variables also studied in relation to the model included education level, service years (tenure), job grade, and age. The overall model revealed 17% of variance explained. The primary predictors of network position, centrality and constraint, were not statistically significant predictors of performance ratings. Three variables, job grade, tenure and age, were found to be statistically significant predictors of employee performance. Further research is suggested to provide additional insight into the predictive value of these variables.

Creator(s): Burton, Paul
Creation Date: August 2007
Partner(s):
UNT Libraries
Collection(s):
UNT Theses and Dissertations
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Total Uses: 739
Past 30 days: 20
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Publisher Info:
Publisher Name: University of North Texas
Place of Publication: Denton, Texas
Date(s):
  • Creation: August 2007
  • Digitized: July 13, 2007
Description:

Research of social networks has revealed that certain components of network position can have an impact on organizational effectiveness, yet relatively little research has been conducted on network position and individual performance. This study sought to determine if a relationship exists between an employee's social network position and an individual's job performance. The participant organization was a network of individuals within an Information Technology (IT) department at a major defense company. A social network analysis (SNA) was conducted to determine the employee's network position, measured by centrality and constraint. Centrality refers to the extent to which an individual is connected to others. Constraint refers to how constrained or inhibited an individual is within the network. Performance was measured by annual appraisal ratings provided by the employee's supervisor. Hierarchical regression analysis was performed to determine relationships between the dependent variable (performance) and independent variables of centrality and constraint. Secondary variables also studied in relation to the model included education level, service years (tenure), job grade, and age. The overall model revealed 17% of variance explained. The primary predictors of network position, centrality and constraint, were not statistically significant predictors of performance ratings. Three variables, job grade, tenure and age, were found to be statistically significant predictors of employee performance. Further research is suggested to provide additional insight into the predictive value of these variables.

Degree:
Level: Doctoral
Language(s):
Subject(s):
Keyword(s): Social network analysis | network position | job performance | relationship | employee
Contributor(s):
Partner:
UNT Libraries
Collection:
UNT Theses and Dissertations
Identifier:
  • OCLC: 191848353 |
  • ARK: ark:/67531/metadc3994
Resource Type: Thesis or Dissertation
Format: Text
Rights:
Access: Public
License: Copyright
Holder: Burton, Paul
Statement: Copyright is held by the author, unless otherwise noted. All rights reserved.