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Kristof Coussement
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- affiliation: University of Lille, IESEG School of Management, France
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2020 – today
- 2024
- [j38]C. Gary Mena, Kristof Coussement, Koen W. De Bock, Arno De Caigny, Stefan Lessmann
:
Exploiting time-varying RFM measures for customer churn prediction with deep neural networks. Ann. Oper. Res. 339(1-2): 765-787 (2024) - [j37]Khaoula Idbenjra, Kristof Coussement, Arno De Caigny:
Investigating the beneficial impact of segmentation-based modelling for credit scoring. Decis. Support Syst. 179: 114170 (2024) - [j36]Kristof Coussement, Mohammad Zoynul Abedin
Explainable AI for enhanced decision-making. Decis. Support Syst. 184: 114276 (2024) - [j35]Stephanie Beyer Díaz
Improved decision-making through life event prediction: A case study in the financial services industry. Decis. Support Syst. 187: 114342 (2024) - [j34]Philipp Borchert
Industry-sensitive language modeling for business. Eur. J. Oper. Res. 315(2): 691-702 (2024) - [j33]Koen W. De Bock, Kristof Coussement, Arno De Caigny:
Explainable Analytics for Operational Research. Eur. J. Oper. Res. 317(2): 243-248 (2024) - [j32]Koen W. De Bock
Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda. Eur. J. Oper. Res. 317(2): 249-272 (2024) - [j31]Stephanie Beyer Díaz
Do the US president's tweets better predict oil prices? An empirical examination using long short-term memory networks. Int. J. Prod. Res. 62(6): 2158-2175 (2024) - [j30]Jason Weismueller
Information sharing and political polarisation on social media: The role of falsehood and partisanship. Inf. Syst. J. 34(3): 854-893 (2024) - [c3]Mathias Kraus, Nico Hambauer, Kristina Müller, Pavlina Kröckel, Nalika Ulapane, Arno De Caigny, Koen W. De Bock, Kristof Coussement:
Coupling Neural Networks Between Clusters for Better Personalized Care. HICSS 2024: 3627-3636 - 2023
- [j29]Minh Phan, Arno De Caigny, Kristof Coussement:
A decision support framework to incorporate textual data for early student dropout prediction in higher education. Decis. Support Syst. 168: 113940 (2023) - [j28]Philipp Borchert
Extending business failure prediction models with textual website content using deep learning. Eur. J. Oper. Res. 306(1): 348-357 (2023) - [c2]Philipp Borchert
CORE: A Few-Shot Company Relation Classification Dataset for Robust Domain Adaptation. EMNLP 2023: 11792-11806 - [i2]Philipp Borchert, Jochen De Weerdt, Kristof Coussement, Arno De Caigny, Marie-Francine Moens:
CORE: A Few-Shot Company Relation Classification Dataset for Robust Domain Adaptation. CoRR abs/2310.12024 (2023) - 2022
- [j27]Kristof Coussement
A decision-analytic framework for interpretable recommendation systems with multiple input data sources: a case study for a European e-tailer. Ann. Oper. Res. 315(2): 671-694 (2022) - [j26]Jason Weismueller
What makes people share political content on social media? The role of emotion, authority and ideology. Comput. Hum. Behav. 129: 107150 (2022) - 2021
- [j25]Kristof Coussement
Interpretable data science for decision making. Decis. Support Syst. 150: 113664 (2021) - [j24]Paul Harrigan
Identifying influencers on social media. Int. J. Inf. Manag. 56: 102246 (2021) - [j23]Stefan Lessmann
Targeting customers for profit: An ensemble learning framework to support marketing decision-making. Inf. Sci. 557: 286-301 (2021) - [j22]Piotr Sulikowski
Gaze and Event Tracking for Evaluation of Recommendation-Driven Purchase. Sensors 21(4): 1381 (2021) - 2020
- [j21]Diego Olaya
A survey and benchmarking study of multitreatment uplift modeling. Data Min. Knowl. Discov. 34(2): 273-308 (2020) - [j20]Arno De Caigny
Leveraging fine-grained transaction data for customer life event predictions. Decis. Support Syst. 130: 113232 (2020) - [j19]Kristof Coussement
Predicting student dropout in subscription-based online learning environments: The beneficial impact of the logit leaf model. Decis. Support Syst. 135: 113325 (2020) - [j18]Koen W. De Bock, Kristof Coussement
Cost-sensitive business failure prediction when misclassification costs are uncertain: A heterogeneous ensemble selection approach. Eur. J. Oper. Res. 285(2): 612-630 (2020) - [j17]Nathalie T. M. Demoulin, Kristof Coussement
Acceptance of text-mining systems: The signaling role of information quality. Inf. Manag. 57(1) (2020)
2010 – 2019
- 2019
- [j16]Steven Debaere, Floris Devriendt, Johanna Brunneder, Wouter Verbeke
Reducing inferior member community participation using uplift modeling: Evidence from a field experiment. Decis. Support Syst. 123 (2019) - [i1]C. Gary Mena, Arno De Caigny, Kristof Coussement, Koen W. De Bock, Stefan Lessmann:
Churn Prediction with Sequential Data and Deep Neural Networks. A Comparative Analysis. CoRR abs/1909.11114 (2019) - 2018
- [j15]Stijn Geuens
A framework for configuring collaborative filtering-based recommendations derived from purchase data. Eur. J. Oper. Res. 265(1): 208-218 (2018) - [j14]Arno De Caigny
A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees. Eur. J. Oper. Res. 269(2): 760-772 (2018) - [j13]Steven Debaere
Multi-label classification of member participation in online innovation communities. Eur. J. Oper. Res. 270(2): 761-774 (2018) - [j12]Michael Antioco
Misreading of consumer dissatisfaction in online product reviews: Writing style as a cause for bias. Int. J. Inf. Manag. 38(1): 301-310 (2018) - 2017
- [j11]Kristof Coussement
A comparative analysis of data preparation algorithms for customer churn prediction: A case study in the telecommunication industry. Decis. Support Syst. 95: 27-36 (2017) - [j10]Artem Bequé, Kristof Coussement
Approaches for credit scorecard calibration: An empirical analysis. Knowl. Based Syst. 134: 213-227 (2017) - 2015
- [j9]Kristof Coussement
A Bayesian approach for incorporating expert opinions into decision support systems: A case study of online consumer-satisfaction detection. Decis. Support Syst. 79: 24-32 (2015) - [j8]Kristof Coussement
Improving direct mail targeting through customer response modeling. Expert Syst. Appl. 42(22): 8403-8412 (2015) - [c1]Annika Baumann, Stefan Lessmann, Kristof Coussement, Koen W. De Bock:
Maximize What Matters: Predicting Customer Churn With Decision-Centric Ensemble Selection. ECIS 2015 - 2011
- [j7]Kristof Coussement
A probability-mapping algorithm for calibrating the posterior probabilities: A direct marketing application. Eur. J. Oper. Res. 214(3): 732-738 (2011) - 2010
- [j6]Koen W. De Bock
Ensemble classification based on generalized additive models. Comput. Stat. Data Anal. 54(6): 1535-1546 (2010) - [j5]Kristof Coussement
Improved marketing decision making in a customer churn prediction context using generalized additive models. Expert Syst. Appl. 37(3): 2132-2143 (2010)
2000 – 2009
- 2009
- [j4]Kristof Coussement
Improving customer attrition prediction by integrating emotions from client/company interaction emails and evaluating multiple classifiers. Expert Syst. Appl. 36(3): 6127-6134 (2009) - 2008
- [j3]Kristof Coussement
Improving customer complaint management by automatic email classification using linguistic style features as predictors. Decis. Support Syst. 44(4): 870-882 (2008) - [j2]Kristof Coussement
Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques. Expert Syst. Appl. 34(1): 313-327 (2008) - [j1]Kristof Coussement
Integrating the voice of customers through call center emails into a decision support system for churn prediction. Inf. Manag. 45(3): 164-174 (2008)
Coauthor Index
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