Hi, welcome to the personal web site of Koen W. De Bock

Koen W. De Bock, Ph.D., is Full Professor of Marketing Analytics and Digital Marketing at triple-accredited Audencia Business School with campuses in France, China and Brazil. He obtained M.Sc. degrees from the University of Antwerp and Ghent University in Belgium, and obtained his Ph.D. from Ghent University in 2010.

Audencia Business School is a triple-accredited (AACSB, EQUIS and AMBA) grande école de commerce, offering under- and postgraduate programs, MBA and DBA degrees. At Audencia, Koen De Bock is in charge of courses related to Digital Marketing and Marketing Analytics in multiple M.Sc. and specialized postgraduate masters programs.

Since November 2011, he served as visiting professor at several leading international business schools, including the University of Stellenbosch Business School (USB; Cape Town, SA) and TIAS School for Business and Society (Utrecht, the Netherlands).

He has published in several international peer-reviewed journals (see publications page) and collaborated on numerous business projects.

Recent Publications by Koen W. De Bock

  • De Bock, K.W., Coussement, K., De Caigny, A., Słowiński, R., Baesens, B., Boute, R.N., Choi, T.-M.. Delen, D., Kraus, M., Lessmann, S., Maldonado, S., Martens, D., Óskarsdóttir, M., Vairetti, C., Verbeke, W., Weber, R., 2023, Explainable AI for Operational Research: A Defining Framework, Methods, Applications, and a Research Agenda, 2023, Forthcoming at European Journal of Operational Research. Link (open access article).
  • Dwivedi, Y.K., Balakrishnan, J., Mishra, A., De Bock, K.W., Al-Busaidi, A., 2024, The Role of Embodiment, Experience, and Self-Image Expression in Creating Continuance Intention in the Metaverse, Forthcoming at Technological Forecasting and Social Change.
  • De Caigny, A., De Bock, K.W., Verboven, S., 2024, Hybrid Black-Box Classification for Customer Churn Prediction with Segmented Interpretability Analysis, Forthcoming at Decision Support Systems.
  • De Bock, K.W., Coussement, K., De Caigny, A., 2024, Editorial to the Special Issue: Explainable AI for Operational Research, Forthcoming at European Journal of Operational Research.
  • Liu, Z., Ping, J., De Bock, K.W., Wang, J., Zhang, L., Niu, X., 2023, Extreme Gradient Boosting Trees with Efficient Bayesian Optimization for Profit-Driven Customer Churn Prediction. Forthcoming at Technological Forecasting and Social ChangeLink.
  • Mena, C.G, Coussement, K., De Bock, K.W., De Caigny, A., and Lessmann, S., 2023, Exploiting Time-Varying RFM Measures for Customer Churn Prediction with Deep Neural Networks. Forthcoming at Annals of Operations Research. Link.
  • Debrulle, J., Steffens, P., De Bock, K.W., De Winne, S. and Maes, J., 2023, Configurations of Business Founder Resources, Strategy, and Environment Determining New Venture Performance. Journal of Small Business Management, pp. 1023-1063. Link.