Koen W. De Bock is Full Professor of Marketing at triple-accredited Audencia Business School (Nantes, France). He obtained master degrees at the University of Antwerp (M.Sc. in Applied Economics) and Ghent University (M.Sc. in Marketing Analysis) in Belgium, and obtained his Ph.D. from Ghent University, Belgium, in 2010. Audencia Business School is a fully-accredited grande école de commerce, offering under- and postgraduate programs accredited by the French government.
At Audencia, Koen De Bock is in charge of courses related to Digital Marketing and Marketing Analytics in multiple MSc programs. Since November 2011, he is a visiting professor at the University of Stellenbosch Business School (USB; Cape Town, SA).
He has published in international peer-reviewed journals (see publications page) and collaborated on numerous business projects.
Recent publications by Koen De Bock
- De Bock, K.W., Lessmann, S. And Coussement, K., 2020, Cost-Sensitive Business Failure Prediction When Misclassification Costs Are Uncertain: a Heterogeneous Ensemble Selection Approach. European Journal of Operational Research, 285 (2), pp. 612-630 (link).
- De Caigny, A., Coussement, K. and De Bock, K.W., 2020, Leveraging Fine-Grained Transaction Data for Customer Life Event Prediction. Decision Support Systems, 130 (March 2020) (link).
- Lessmann, S., Haupt, J., Coussement, K., and De Bock, K.W., 2019 (forthcoming), Targeting customers for profit: An ensemble learning framework to support marketing decision making. Information Sciences (link).
- De Caigny, A., Coussement, K. and De Bock, K.W. Lessmann, S., 2019 (forthcoming), Incorporating Textual Information in Customer Churn Prediction Models Based on a Convolutional Neural Network. International Journal of Forecasting (link).
- De Caigny, A., Coussement, K. and De Bock, K.W., 2018, A New Hybrid Classification Algorithm for Customer Churn Prediction Based on Logistic Regression and Decision Trees. European Journal of Operational Research, 269 (2), pp. 760-772 (link).
- De Bock, K.W., Coussement, K. and Cielen, D., 2018, An Overview of Multiple Classifier Systems Based on Generalized Additive Models. In: Alfaro Cortes, E., Gamez Martinez, M, and Garcia Rubio, N. (Eds.), 2018, Ensemble Classification Methods with Applications in R. Wiley & Sons, New York, USA (link).
- Flores, L. and De Bock, K.W., 2018, L’analyse des données appliquée à la publicité. In: Allary, J. et Balusseau, V. (Eds.), 2018, La publicité à l’heure de la data – Adtech et programmatique expliquées par les experts, Dunod, Paris, France (link).