Publicação
NOS & Nova SBE project-based learning - predicting the volume of customers to flag forcall center’s specialized team
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | |
| dc.contributor.advisor | Lavado, Susana | |
| dc.contributor.advisor | Pereira, Gustavo | |
| dc.contributor.author | Miranda, Joao | |
| dc.date.accessioned | 2026-03-31T12:00:20Z | |
| dc.date.available | 2026-03-31T12:00:20Z | |
| dc.date.issued | 2025-01-29 | |
| dc.date.submitted | 2025-01-29 | |
| dc.description.abstract | This thesis extends the outcomes of the year-long Project-Based Learning initiative with NOS, a prominent telecommunications company in Portugal, focusing on optimizing the number of clients that should be flagged for specialized call center teams, to increase clients’ satisfaction. Two contributions improve model performance by addressing outlier management and applying ensemble techniques, each resulting in substantial improvements from initial solution. The remaining two focus on model explainability, including a deeper dive into the model’s outcomes and a study on how individuals interpret its explanations. Together, these studies complement the work done in PBL by improving both model performance and interpretability. | eng |
| dc.identifier.tid | 204133726 | |
| dc.identifier.uri | http://hdl.handle.net/10362/201942 | |
| dc.language.iso | eng | |
| dc.relation | UID/ECO/00124/2013 | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Call centers | |
| dc.subject | Time series forecasting | |
| dc.subject | Prediction modling | |
| dc.subject | Outliers | |
| dc.subject | Ensemble learning | |
| dc.subject | Explainability | |
| dc.title | NOS & Nova SBE project-based learning - predicting the volume of customers to flag forcall center’s specialized team | eng |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a Master’s degree in Business Analytics from the Nova School of Business and Economics |