A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees A De Caigny, K Coussement, KW De Bock European Journal of Operational Research 269 (2), 760-772, 2018 | 538 | 2018 |
Predicting student dropout in subscription-based online learning environments: The beneficial impact of the logit leaf model K Coussement, M Phan, A De Caigny, DF Benoit, A Raes Decision Support Systems 135, 113325, 2020 | 141 | 2020 |
Incorporating textual information in customer churn prediction models based on a convolutional neural network A De Caigny, K Coussement, KW De Bock, S Lessmann International Journal of Forecasting 36 (4), 1563-1578, 2020 | 133 | 2020 |
Churn prediction with sequential data and deep neural networks. a comparative analysis CG Mena, A De Caigny, K Coussement, KW De Bock, S Lessmann arXiv preprint arXiv:1909.11114, 2019 | 38 | 2019 |
Uplift modeling and its implications for B2B customer churn prediction: A segmentation-based modeling approach A De Caigny, K Coussement, W Verbeke, K Idbenjra, M Phan Industrial Marketing Management 99, 28-39, 2021 | 36 | 2021 |
Spline-rule ensemble classifiers with structured sparsity regularization for interpretable customer churn modeling KW De Bock, A De Caigny Decision Support Systems 150, 113523, 2021 | 32 | 2021 |
Extending business failure prediction models with textual website content using deep learning P Borchert, K Coussement, A De Caigny, J De Weerdt European Journal of Operational Research 306 (1), 348-357, 2023 | 27 | 2023 |
Leveraging fine-grained transaction data for customer life event predictions A De Caigny, K Coussement, KW De Bock Decision Support Systems 130, 113232, 2020 | 26 | 2020 |
Explainable AI for operational research: A defining framework, methods, applications, and a research agenda KW De Bock, K Coussement, A De Caigny, R Slowiński, B Baesens, ... European Journal of Operational Research, 2023 | 20 | 2023 |
Exploiting time-varying RFM measures for customer churn prediction with deep neural networks G Mena, K Coussement, KW De Bock, A De Caigny, S Lessmann Annals of Operations Research, 1-23, 2023 | 12 | 2023 |
A decision support framework to incorporate textual data for early student dropout prediction in higher education M Phan, A De Caigny, K Coussement Decision Support Systems 168, 113940, 2023 | 11 | 2023 |
Does it pay off to communicate like your online community? Evaluating the effect of content and linguistic style similarity on B2B brand engagement M Meire, K Coussement, A De Caigny, S Hoornaert Industrial Marketing Management 106, 292-307, 2022 | 9 | 2022 |
Do the US president's tweets better predict oil prices? An empirical examination using long short-term memory networks S Beyer Díaz, K Coussement, A De Caigny, LF Pérez, S Creemers International Journal of Production Research 62 (6), 2158-2175, 2024 | 4 | 2024 |
Industry-sensitive language modeling for business P Borchert, K Coussement, J De Weerdt, A De Caigny European Journal of Operational Research 315 (2), 691-702, 2024 | 1 | 2024 |
Investigating the beneficial impact of segmentation-based modelling for credit scoring K Idbenjra, K Coussement, A De Caigny Decision Support Systems 179, 114170, 2024 | 1 | 2024 |
Coupling Neural Networks Between Clusters for Better Personalized Care M Kraus, N Hambauer, K Müller, P Kröckel, N Ulapane, A De Caigny, ... | 1 | 2024 |
Incorporating usage data for B2B churn prediction modeling JS Ramirez, K Coussement, A De Caigny, DF Benoit, E Guliyev Industrial Marketing Management 120, 191-205, 2024 | | 2024 |
Explainable analytics for operational research K De Bock, K Coussement, A De Caigny HAL Post-Print, 2024 | | 2024 |
Hybrid black-box classification for customer churn prediction with segmented interpretability analysis A De Caigny, KW De Bock, S Verboven Decision Support Systems 181, 114217, 2024 | | 2024 |
Unraveling Key Information in Textual Earnings Disclosures P Borchert, J De Weerdt, K Coussement, A De Caigny Available at SSRN 4816174, 2024 | | 2024 |