Arno DE CAIGNY

Arno DE CAIGNY
Associate Professor
Ph.D., Sales and Marketing, Marketing - University of Lille
Track: Marketing
LEM Member
Education
  • 2019 : Ph.D., Sales and Marketing, Marketing, University of Lille, France
  • 2015 : Master, Economics and Mathematics Sciences, Marketing, Ghent University, Belgium
  • 2014 : Master, Business Administration, Finance, Ghent University, Belgium
  • 2013 : Bachelor, Business Administration, Business, Ghent University, Belgium
Professional Experiences
Professional Experience :
  • 2015 - 2016, Business Analyst, Deloitte Touche Thomatsu, Brussels, Belgium
Published Papers in Refereed Journals
  • Idbenjra K., Coussement K., De Caigny A., (2024). Investigating the Beneficial Impact of Segmentation-based Modelling for Credit Scoring, Decision Support Systems, 179 (April) 1-12.
  • De Bock K. W., Coussement K., De Caigny A., Slowinski R., Baesens B., Boute R., Choi T.-M., Delen D., Kraus M., Lessmann S., Maldonado S., Martens D., Oskarsdottir M., Vairetti C., Verbeke W., Weber R., (2023). Explainable AI for Operational Research: A Defining Framework, Methods, Applications, and a Research Agenda, European Journal of Operational Research, forthcoming (2023) 1-20.
  • Meire M., Coussement K., De Caigny A., Hoornaert S., (2022). Does it pay off to communicate like your online community? Evaluating the effect of content and linguistic style similarity on B2B brand engagement, Industrial Marketing Management, 106 (2022) 292-307.
Show all
  • De Caigny A., De Bock K. W., (2021). Spline-Rule Ensemble Classifiers with Structured Sparsity Regularization for Interpretable Customer Churn Modeling, Decision Support Systems, 150 (113523) 1-14.
  • De Caigny A., Coussement K., Verbeke W., Idbenjra K., Phan M., (2021). Uplift Modeling And Its Implications For B2B Customer Churn Prediction: A Segmentation-Based Modeling Approach, Industrial Marketing Management, 99 (2021) 28-39.
  • Coussement K., Phan M., De Caigny A., Benoit D. F., Raes A., (2020). Predicting Student Dropout In Subscription-based Online Learning Environments: The Beneficial Impact Of The Logit Leaf Model, Decision Support Systems, 135 (August) 1-11.
  • De Caigny A., Coussement K., De Bock K. W., (2020). Leveraging Fine-Grained Transaction Data for Customer Life Event Predictions, Decision Support Systems, 130 (March) 1-12.
  • De Caigny A., (2019). Innovation in customer scoring for the financial services industry, 4OR: A Quarterly Journal of Operations Research, 18 (1) 381–382.
  • De Caigny A., Coussement K., De Bock K., Lessmann S., (2019). Incorporating Textual Information in Customer Churn Prediction Models Based on a Convolutional Neural Network, International Journal of Forecasting, 36 (4) 1563-1578.
  • De Caigny A., Coussement K., 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) 760-772.
Research fields
  • Marketing Analytics
  • Economics
  • Quantitative Methods