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Arno De Caigny
Arno De Caigny
Professor of Business Analytics, IESEG School of Management
在 ieseg.fr 的电子邮件经过验证
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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
5382018
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
1412020
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
1332020
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
382019
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
362021
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
322021
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
272023
Leveraging fine-grained transaction data for customer life event predictions
A De Caigny, K Coussement, KW De Bock
Decision Support Systems 130, 113232, 2020
262020
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
202023
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
122023
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
112023
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
92022
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
42024
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
12024
Investigating the beneficial impact of segmentation-based modelling for credit scoring
K Idbenjra, K Coussement, A De Caigny
Decision Support Systems 179, 114170, 2024
12024
Coupling Neural Networks Between Clusters for Better Personalized Care
M Kraus, N Hambauer, K Müller, P Kröckel, N Ulapane, A De Caigny, ...
12024
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
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