Publications

  • Nasini S., Martinez-de-Albeniz V., Dehdarirad T., (2017), Conditionally exponential random models for individual properties and network structures: Method and application, Social Networks, 48(1), pp. 202–212
  • Moysan Y., (2017), Robots et intelligence artificielle investissent la banque privée et la banque de détail, Revue Banque, 803-804(January 2017), pp. 124-128
  • Charry K., Coussement K., Demoulin N., Heuvinck N., (2016), Marketing Research with IBM SPSS Statistics, 978-1-4724-7745-3 , Routledge, London, 264 pages
  • De Kerviler G., Demoulin N., Zidda P., (2016), Adoption of in-store mobile payment: Are perceived risk and convenience the only drivers?, Journal of Retailing and Consumer Services, 31(July), pp. 334-344
  • Demoulin N., Djelassi S., (2016), An Integrated Model of Self-Service Technology (SST) Usage in a Retail Context, International Journal of Retail & Distribution Management, 44(5), pp. 540-559
  • Demoulin N., Coussement K., (2016), L’adoption des outils de text-mining : un choix stratégique des entreprises ayant une forte orientation client , Survey Magazine, (T2), pp. 32
  • Debaere S., Coussement K., Van Neck S., De Ruyck T., (2016), Minority Report in Market Research Online Communities: The future can be seen, member disengagement can be prevented, in: Tim Macer et al.(Eds.) in ASC 2016. Are We There Yet? Where Technological Innovation is Leading Research
  • Moysan Y., (2016), Big Data: des opportunités sur l’ensemble de la chaîne de valeur, Revue Banque, (800), pp. 62-66
  • Moysan Y., Paparoidamis N., (2016), Le beacon au service des réseaux bancaires ?, Revue Banque, 796, pp. 74-77
  • Moysan Y., Paparoidamis N., (2016), Can beacons be a source of inspiration for banks to increase sales and improve customer experience?, Journal of Digital Banking, 1, pp. 1-9
  • Moysan Y., (2015), Des ventes d’assurance finalisées en ligne marginales, Courtage News, pp. 56-57
  • Coussement K., Harrigan P., Benoit D., (2015), Improving Direct Mail Targeting Through Customer Response Modelling, Expert Systems with Applications, 42(22), pp. 8403–8412
  • Coussement K., Vindevogel B., (2015), Global.com: Building Analytical Capabilities in the Mobile Telecom Market, Case Centre, case study 315-096-1, teaching note 315-096-8
  • Coussement K., Benoit D., Antioco M., (2015), A Bayesian Approach for Incorporating Expert Opinions into Decision Support Systems: A Case Study of Online Consumer-Satisfaction Detection, Decision Support Systems, 79, pp. 24-32
  • Coussement K., Boujena O., De Bock K. W., (2015), Data Driven Customer Centricity: CRM Predictive Analytics, in: T. Tsiakis(Eds.), Trends and Innovations in Marketing Information Systems, 9781466684591, IGI Global, Hershey, PA
  • Cabooter E., Weijters B., Geuens M., Iris V., (forthcoming), Effects of scale format statement polarity and numbering on response option interpretation and use, Journal of Business Research
  • Charry K., Coussement K., Demoulin N., Heuvinck N., (2015) Marketing Research with IBM SPSS Statistics, Gower Publishing.
  • Moysan Y., Grynbaum L., (2015), e assurance / m assurance, 978-2-35474-214-0, Les Éditions de L’Argus de l’assurance, Paris
  • Coussement K., Harrigan Paul, (2014) All You Need Is True Love (With Your Customers)! A Customer Relationship Management Fairy Tale, Gower Publishing.Ghent University Press,, Ghent.
  • Coussement K., Van den Bossche F.A.M., De Bock K. W., (2014). Data Accuracy’s Impact on Segmentation Performance: Benchmarking RFM Analysis, Logistic Regression, and Decision Trees, Journal of Business Research, 67 (1) 2751-2758.
  • Coussement K., (2014). Improving Customer Retention Management through Cost-sensitive Learning, European Journal of Marketing, 48 (3/4) 477 – 495.
  • Moysan Y., (2014), Les objets connectés dans le secteur bancaire: révolution ou simple évolution?, Revue Banque, 776
  • Coussement K., De Bock K. W., (2013). Customer Churn Prediction in the Online Gambling Industry: The Beneficial Effect of Ensemble Learning, Journal of Business Research, 66 (9) 1629-1636.
  • Coussement K., De Bock K. W., Neslin S.A., (2013) Advanced Database Marketing: Innovative Methodologies & Applications of Managing Customer Relationships , Gower Publishing.Ghent University Press,Gower,, Ghent., London.
  • Coussement K., De Bock K. W., (2013), Ensemble Learning in Database Marketing , in: Advanced Database Marketing: Innovative Methodologies & Applications of Managing Customer Relationships .
  • Coussement K., De Bock K. W., (2013), Textual Customer Data Handling for Quantitative Marketing Analysis, in: Advanced Database Marketing: Innovative Methodologies & Applications of Managing Customer Relationships.
  • De Bock K. W., Van den Poel D., (2012). Reconciling Performance and Interpretability in Customer Churn Prediction using Ensemble Learning based on Generalized Additive Models, Expert Systems with Applications, 39 (8) 6816-6826.
  • Moysan Y., Maymo V., (2012), Stratégie bancaire de développement durable: Levier humain et nouvelles technologies : deux facteurs de succès , Revue Banque, 754
  • Moysan Y., (2011), Banques américaines et réseaux sociaux: une relation privilégiée avec la communauté, Banque & Stratégie
  • De Bock K. W., Van den Poel D., (2011). An empirical evaluation of rotation-based ensemble classifiers forcustomer churn prediction, Expert Systems with Applications, 38 (10) 12293-12301.
  • Coussement K., Buckinx W., (2011). A probability-mapping algorithm for calibrating the posterior probabilities: A direct marketing application, European Journal of Operational Research, 214 (3) 732-738.
  • Coussement K., Demoulin N., Charry K., (2011) Marketing Research with SAS Enterprise Guide , Gower Publishing.Ghent University Press,Gower,Gower,, Ghent., London., Farnham.
  • Coussement K., Benoit D.F., Van den Poel D., (2010). Improved Marketing Decision Making in a Customer Churn Prediction Context Using Generalized Additive Models, Expert Systems with Applications, 37 (3) 2132-2143.
  • De Bock K. W., Coussement K., Van den Poel D., (2010). Ensemble Classification Based on Generalized Additive Models, Computational Statistics & Data Analysis, 54 (6) 1535-1546.
  • De Bock K. W., Van den Poel D., (2010). Predicting website audience demographics for web advertising targeting using multi-website clickstream data, Fundamenta Informaticae, 98 (1) 49-67.
  • De Bock K. W., Van den Poel D., (2010), Ensembles of probability estimation trees for customer churn prediction, in: Trends in Applied Intelligent Systems.
  • De Bock K. W., Van den Poel D., (2010), Trends in Applied Intelligent Systems, in: 23rd International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems Springer-Verlag Berlin Heidelberg, pp.57-66.
  • Coussement K., Van den Poel D., (2009). Improving Customer Attrition Prediction by Integrating Emotions from Client/Company Interaction Emails and Evaluating Multiple Classifiers, Expert Systems with Applications, 37 (3) 2132-2143.
  • Coussement K., Van den Poel D., (2008). Improving Customer Complaint Management by Automatic Email Classification Using Linguistic Style Features as Predictors, Decision Support Systems, 44 (4) 370-382.
  • Coussement K., Van den Poel D., (2008). Integrating the voice of customers through call center emails into a decision support system for churn prediction, Information & Management, 45 (3) 164-174.
  • Coussement K., Van den Poel D., (2008). Churn prediction in subscription services: an application of support vector machines while comparing two parameter-selection techniques, Expert Systems with Applications, 34 (1) 313-327.