Name
Abstract | ||
|---|---|---|
This paper reports the results obtained from use of project complexity parameters in modeling effort estimates. It highlights
the attention that complexity has recently received in the project management area. After considering that traditional knowledge
has consistently proved to be prone to failure when put into practice on actual projects, the paper endorses the belief that
there is a need for more open-minded and novel approaches to project management. With a view to providing some insight into
the opportunities that integrate complexity concepts into model building offers, we extend the work previously undertaken
on the complexity dimension in project management. We do so analyzing the results obtained with classical linear models and
artificial neural networks when complexity is considered as another managerial parameter. For that purpose, we have used the
International Software Benchmarking Standards Group data set. The results obtained proved the benefits of integrating the
complexity of the projects at hand into the models. They also addressed the need of a complex system, such as artificial neural
networks, to capture the fine nuances of the complex systems to be modeled, the projects. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/s10479-010-0776-0 | Annals OR |
Keywords | DocType | Volume |
artificial neural network,complex system,linear model,traditional knowledge,data mining,project management,model building | Journal | 186 |
Issue | ISSN | Citations |
1 | 1572-9338 | 3 |
PageRank | References | Authors |
0.39 | 17 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manuel Castejón-Limas | 1 | 5 | 7.26 |
| Joaquín Ordieres-Meré | 2 | 102 | 14.39 |
| Ana González-Marcos | 3 | 25 | 7.76 |
| Víctor González-Castro | 4 | 90 | 10.70 |