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 …
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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.
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