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| Author: | Zhang, G. P. (et al.) |
| Title: | Predicting information technology project escalation: a neural network approach |
| Journal: | European Journal of Operational Research
2003 : APR, VOL. 146:1, p. 115-129 |
| Index terms: | Information technology Neural networks Project management Logistics |
| Language: | eng |
| Abstract: | The authors compare neural network and logistic regression models in building an effective early warning system to predict project escalation. Variable selection approaches are employed to identify the most important predictor variables from those derived from the project management literature and four behavioral theories. Resuls show that neural networks are able to predict considerably better than the traditional statistical approach - logistic regression. Project management factors are found to be more critical than behavioral factors in accounting for the success of an IT project. |
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