Name
Abstract | ||
|---|---|---|
For decades, organizational researchers have employed standard statistical methods to uncover relationships among variables and constructs. However, in complex organization systems, the prevalence of non-linearity and outliers is to be expected. Under such circumstances, the use of standard statistical methods becomes unreliable and, correspondingly, results in degraded predictions of the relationships within the organizational systems. We describe the use of neural network analyses to model team effectiveness so as to provide more accurate predictions for managers. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.ejor.2005.12.051 | European Journal of Operational Research |
Keywords | Field | DocType |
Organization theory,Neural networks,Group,Outliers | Team effectiveness,Organizational network analysis,Mathematical optimization,Outlier,Systems modeling,Artificial intelligence,Network analysis,Organizational theory,Artificial neural network,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
181 | 2 | 0377-2217 |
Citations | PageRank | References |
5 | 0.79 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| John Grznar | 1 | 8 | 1.76 |
| Sameer Prasad | 2 | 27 | 3.98 |
| Jasmine Tata | 3 | 13 | 1.99 |