Research


Refereed Journal Articles
Software
Books
Book Chapters
Case Studies

Refereed Journal Articles

  1. K.W. De Bock, K. Coussement, A. De Caigny, C. Ciobanu, Integrating E-commerce and Social Media Metrics in Prescriptive Multichannel Retail Store Efficiency Analysis: A Case Study in Do-It-Yourself Retailing, Information & Management, (2026, forthcoming) (DOI).
  2. M. Meire, W. Standaert, A. De Caigny, K. Coussement, M. Szerovay, Diversity & Inclusion and Social Media Engagement: An Empirical Study in the Football Context, Journal of Business Ethics (2026, forthcoming).
  3. R. Kumar, M. Talaei-Khoei, A. Kumar, K. Coussement, A. Oztekin, Leveraging Online Reviews to Decode Quality-Induced Customer Dissatisfaction: From Perception to Product Discouragement, Decision Sciences, (2026, forthcoming).
  4. A. Kumar, S. Piramuthu, K. Coussement, D. Delen, Combating Misinformation for Societal Benefits in the Generative AI Age: From Bots to Deepfakes, Information Systems Frontiers, (2026, forthcoming).
  5. M. Meire, S. Hoornaert, A. De Caigny, K. Coussement, A Decision Support Framework for Estimating the Impact of Covariate Shift in Machine Learning Systems, Decision Support Systems, 203 (April), (2026), pp 114632 (DOI).
  6. K. Topuz, I. Abdulrashid, B. Davazdahemami, K. Coussement, D. Delen, Developing an Interpretable Decision Support Framework for Artifact Design in Organ Transplantation, Information Systems Frontiers, 27, (2025), pp 2573-2597 (DOI).
  7. D. Wang, Y. Feng, M.Z. Abedin, Y. Yin, E. Tai Chiu Cheng, K. Coussement, An Adaptive Heterogeneous Ensemble Learning Method for Multi-dimensional Company Performance Decision-Making, Annals of Operations Research, 353 (2025), pp 693-725 (DOI).
  8. E. Weber, K. Coussement, M. Buettgen, P. Harrigan, The Social Media Playbook for CEOs: How to Use Transformational Leadership-oriented Language on Social Media Successfully, Journal of Leadership Studies, 19 (4) (2026) (DOI).
  9. M. Hasan, M.Z. Abedin, P. Hajek, K. Coussement, N. Sultan, B. Lucey, A Blending Ensemble Learning Model for Crude Oil Price Forecasting, Annals of Operations Research, 353, (2025), pp 485-515 (DOI).
  10. S. Beyer Diaz, A. De Caigny, K. Coussement, From Collaborative Filtering to Deep Learning: Advancing Recommender Systems with Longitudinal Data in the Financial Services Industry, European Journal of Operational Research, 323 (2) (2025), pp 609-625 (DOI).
  11. K. Topuz, A. Bajaj, K. Coussement, T.L. Urban, Interpretable Machine Learning and Explainable Artificial Intelligence, Annals of Operations Research, 347 (2025), pp 775-782 (DOI).
  12. C. Sanchez, C. Vairetti, K. Coussement, S. Maldonado, Bounded Individualized Treatment Effect: A Novel Approach for Uplift Modeling, IEEE Access, August (2025), pp 1-17 (DOI).
  13. A. De Caigny, K. Coussement, S. Hoornaert, M. Meire, Life-event Based Marketing Using AI, Journal of Business Research, 193 (April) (2025), pp 115349 (DOI).
  14. A. De Caigny, K. Coussement, M. Meire, S. Hoornaert, Investigating the Impact of Undersampling and Bagging: An Empirical Investigation for Customer Attrition Modeling, Annals of Operations Research, 346, (2025), pp 2401-2421 (DOI).
  15. Y. Trautwein, F. Ziechel, K. Coussement, M. Meire, M. Buettgen, Opening the ‘Black Box’ of HRM Algorithmic Bias – How Hiring Practices Induce Discrimination on Freelancing Platforms, Journal of Business Research, 192 (April) (2025), pp 1-14 (DOI).
  16. A. Nath-Mishra, P. Sengupta, B. Biswas, A. Kumar, K. Coussement, Leveraging Machine Learning and Generative AI for Content Engagement: An Exploration of Drivers for the Success of YouTube Videos, Journal of Business Research, 193 (April), (2025), pp 1-15 (DOI).
  17. S. Simsek, A. Dag, K. Coussement, E.Y. Kibis, A. Asilkalkan, S. Ragothaman, A Decision Support Framework for Misstatement Identification in Financial Reporting: A Hybrid Tree-Augmented Bayesian Belief Approach, Decision Support Systems, 189 (February) (2025), pp 1-18 (DOI).
  18. E. Guliyev, J. Sanchez Ramirez, A. De Caigny, K. Coussement, Improving B2B Customer Churn Through Action Rule Mining, Industrial Marketing Management, 125 (February) (2025), pp 1-11 (DOI).
  19. S. Beyer Diaz, K. Coussement, A. De Caigny, Improved Decision-Making Through Life Event Prediction: A Case Study in the Financial Services Industry, Decision Support Systems, 187 (December) (2024), pp 1-17 (DOI).
  20. K. De Bock, K. Coussement, A. De Caigny, Explainable Analytics in Operational Research, European Journal of Operational Research, 317 (2), (2024), pp 243-248 (DOI).
  21. K.W. De Bock, K. Coussement, A. De Caigny, R. Slowinski, B. Baesens, R.N. Boute, T.-M. Choi, D. Delen, M. Kraus, S. Lessmann, S. Maldonado, D. Martens, M. Oskarsdottir, C. Vairetti, W. Verbeke, R. Weber, Explainable AI for Operational Research: A Defining Framework, Methods, Applications, and a Research Agenda, European Journal of Operational Research, 317 (2), (2024), pp 249-272 (DOI).
  22. K. Coussement, M.Z. Abedin, M. Kraus, S. Maldonado, K. Topuz, Explainable A.I. for Enhanced Decision Making, Decision Support Systems, 184 (September) (2024), pp 1-6 (DOI).
  23. G. Mena, K. Coussement, K.W. De Bock, A. De Caigny, S. Lessmann, Exploiting Time-Varying RFM Measures for Customer Churn Prediction with Deep Neural Networks, Annals of Operations Research, 334, (2024), pp 765-787 (DOI).
  24. J. Sanchez Ramirez, K. Coussement, A. De Caigny, D.F. Benoit, E. Guliyev, Incorporating Usage Data for B2B Churn Prediction Modeling, Industrial Marketing Management, 120 (July) (2024), pp 191-205 (DOI).
  25. P.N. Borchert, K. Coussement, J. De Weerdt, A. De Caigny, Industry-Sensitive Language Modeling for Business, European Journal of Operational Research, 315 (2) (2024), pp 691-702 (DOI).
  26. S. Beyer Diaz, K. Coussement, A. De Caigny, L.F. Pérez Armas, S. Creemers, Do the US President’s Tweets Better Predict Oil Prices? An Empirical Examination Using Long Short-Term Memory Networks, International Journal of Production Research, 62 (6) (2024), pp 2158–2175 (DOI).
  27. J. Weismueller, R.L. Gruner, P. Harrigan, K. Coussement, S. Wang, Information Sharing and Political Polarisation on Social Media: The Role of Falsehood and Partisanship, Information Systems Journal, 34 (3) (2024), pp 854-893 (DOI).
  28. F. Zechiel, M. Blaurock, E. Weber, M. Buettgen, K. Coussement, How Tech Companies Advance Sustainability Through Artificial Intelligence: Developing and Evaluating an AI x Sustainability Strategy Framework, Industrial Marketing Management, 119 (May) (2024), pp 75-89 (DOI).
  29. K. Idbenjra, K. Coussement, A. De Caigny, Investigating the Beneficial Impact of Segmentation-based Modelling for Credit Scoring, Decision Support Systems, 179 (April) (2024), pp 1-12 (DOI).
  30. D.F. Benoit, W.K. Tsang, K. Coussement, A. Raes, High-stake Student Drop-out Prediction Using Hidden Markov Models in Fully Asynchronous Subscription-based MOOCs, Technological Forecasting & Social Change, 198 (January) (2024), pp 1-9 (DOI).
  31. S.K. Roy, G. Singh, S. Sadeque, P. Harrigan, K. Coussement, Customer Engagement with Digitalized Interactive Platforms in Retailing, Journal of Business Research, 164, (2023), pp 1-15 (DOI).
  32. P.N. Borchert, K. Coussement, A. De Caigny, J. De Weerdt, Extending Business Failure Prediction Models With Textual Website Content Using Deep Learning, European Journal of Operational Research, 306 (1), (2023) (DOI).
  33. M. Phan, A. De Caigny, K. Coussement, A Decision Support Framework to Incorporate Textual Data for Early Student Dropout Prediction in Higher Education, Decision Support Systems, 168 (May) (2023), pp 1-13 (DOI).
  34. Y. Zhu, T. Tessitore, P. Harrigan, K. Coussement, Graphic Design in Advertising: A Guideline on the Use of Colour-evoked Emotion and Design Complexity in the Construction of Functional versus Experiential Advertisements, Journal of Advertising Research, March (3) (2023), pp 81-103 (DOI).
  35. M. Antioco, K. Coussement, C. Fletcher-Chen, C. Prange, What’s in a Word? Adopting a Linguistic-Style Analysis of Western MNCs’ Global Press Releases, Journal of World Business, 58 (2) (2023), pp 1-16 (DOI).
  36. M. Meire, K. Coussement, A. De Caigny, S. Hoornaert, 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 (October) (2022), pp 292-307 (DOI).
  37. K. Coussement, K.W. De Bock, S. Geuens, A Decision-analytic Framework for Interpretable Recommendation Systems with Multiple Input Data Sources: A Case Study for a European E-tailer, Annals of Operations Research, 315 (2022), pp 671-694 (DOI).
  38. L. Becker, K. Coussement, M. Buettgen, E. Weber, Leadership in Innovation Communities: The Impact of Transformational Leadership Language on Member Participation, Journal of Product Innovation Management, 39 (3) (2022), pp 371-393 (DOI).
  39. J. Weismueller, P. Harrigan, K. Coussement, T. Tessitore, What Makes People Share Political Content on Social Media? The Role of Emotion, Authority and Ideology, Computers in Human Behavior, 129 (April) (2022) (DOI).
  40. A. De Caigny, K. Coussement, W. Verbeke, K. Idbenjra, M. Phan, Uplift Modeling and its Implications for B2B Customer Churn Prediction: A Segmentation-based Modeling Approach, Industrial Marketing Management, 99 (November) (2021), pp 28-39 (DOI).
  41. K. Coussement, D.F. Benoit, Interpretable Data Science for Decision Making (Editorial), Decision Support Systems, 150, (2021), pp 1-6 (DOI).
  42. S. Lessmann, J. Haupt, K. Coussement, K.W. De Bock, Targeting Customers for Profit: An Ensemble Learning Framework to Support Marketing Decision-making, Information Sciences, 557 (May) (2021), pp 286-301 (DOI).
  43. P. Sulikowski, T. Zdziebko, K. Coussement, K. Dyczkowski, K. Kluza, K. Sachpazidu-Wójcicka, Gaze and Event Tracking for Evaluation of Recommendation Driven Purchase, Sensors, 21 (4) (2021), pp 1-21 (DOI).
  44. P. Harrigan, T. Daly, K. Coussement, J. Lee, G. Soutar, U. Evers, Identifying Influencers on Social Media, International Journal of Information Management, 56 (2021), pp 1-11 (DOI).
  45. A. De Caigny, K. Coussement, K.W. De Bock, S. Lessmann, Incorporating Textual Information in Customer Churn Prediction Models Based on a Convolutional Neural Network, International Journal of Forecasting, 36 (4) (2020), pp 1563-1578 (DOI).
  46. K. Coussement, M. Phan, A. De Caigny, D.F. Benoit, A. Raes, Predicting Student Dropout in Subscription-Based Online Learning Environments: The Beneficial Impact of the Logit Leaf Model, Decision Support Systems, 135 (2020), pp 1-11 (DOI, LLM R package).
  47. K.W. De Bock, K. Coussement, S. Lessmann, Cost-sensitive Business Failure Prediction When Misclassification Costs Are Uncertain: A Heterogeneous Ensemble Selection Approach, European Journal of Operational Research, 285 (2020), pp 612-630 (DOI, CMES R package).
  48. P. Harrigan, K. Coussement, C. Lancelot Miltgen, C. Ranaweera, The Future of Technology in Marketing; Utopia or Dystopia? (Editorial), Journal of Marketing Management, 36 (3-4) (2020), pp 211-215 (DOI).
  49. A. De Caigny, K. Coussement, K.W. De Bock, Leveraging Fine-Grained Transaction Data for Customer Life Event Predictions, Decision Support Systems, 130 (2020), pp 1-12 (DOI).
  50. D.A. Olaya, W. Verbeke, K. Coussement, A Survey and Benchmarking Study of Multi-treatment Uplift Modeling, Data Mining and Knowledge Discovery, 34 (2020), pp 273-308.(DOI).
  51. N. Demoulin, K. Coussement, Acceptance of Text-Mining Systems: The Signaling Role of Information Quality, Information and Management, 57 (1) (2020), pp 1-11 (DOI).
  52. S. Debaere, F. Devriendt, J. Brunneder, W. Verbeke, T. De Ruyck, K. Coussement, Reducing Inferior Member Community Participation Using Uplift Modeling: Evidence From A Field Experiment, Decision Support Systems, 123 (August) (2019), pp 1-12 (DOI).
  53. P.H. Kim, R. Kotha, S. Fourné, K. Coussement, Taking Leaps of Faith: Evaluation Criteria and Resource Commitments for Early-stage Inventions, Research Policy, 48 (6) (2019), pp 1429-1444 (DOI).
  54. S. Debaere, K. Coussement, T. De Ruyck, Multi-label Classification of Member Participation in Online Innovation Communities, European Journal of Operational Research, 270 (2) (2018), pp 761-774 (DOI).
  55. A. De Caigny, K. Coussement, K.W. De Bock, A New Hybrid Classification Algorithm for Customer Churn Prediction Based on Logistic Regression and Decision Trees, European Journal of Operational Research, 269 (2) (2018), pp 760-772 (DOI, LLM R package).
  56. M. Antioco, K. Coussement, Misreading of Consumer Dissatisfaction in Online Product Reviews: Writing Style as a Cause for Bias, International Journal of Information Management, 38 (2018), pp 301-310 (DOI).
  57. S. Geuens, K. Coussement, K.W. De Bock, A Framework for Configuring Collaborative Filtering-based Recommendations Derived from Purchase Data, European Journal of Operational Research, 265 (1) (2018), pp 208-218 (DOI).
  58. A. Bequé, K. Coussement, R. Gayler, S. Lessmann, Approaches for Credit Scorecard Calibration: An Empirical Analysis, Knowledge-based Systems, 134 (October) (2017), pp 213-227 (DOI).
  59. K. Coussement, S. Debaere, T. De Ruyck, Inferior Member Participation Identification in Innovation Communities: The Signaling Role of Linguistic Style Use, Journal of Product Innovation Management,  35 (5) (2017), pp 565-579 (DOI).
  60. K. Coussement, S. Lessmann, G. Verstraeten, A Comparative Analysis of Data Preparation Algorithms for Customer Churn Prediction: A Case Study in the Telecommunication Industry, Decision Support Systems, 95 (March) (2017), pp 27-36 (DOI).
  61. K. Coussement, D.F. Benoit, M. Antioco, A Bayesian Approach for Incorporating Expert Opinions into Decision Support Systems: A Case Study of Online Consumer-Satisfaction Detection, Decision Support Systems, 79 (November) (2015), pp 24-32 (DOI).
  62. K. Coussement, P. Harrigan, D.F. Benoit, Improving Direct Mail Targeting Through Customer Response Modelling, Expert Systems with Applications, 42 (22) (2015), pp 8403–8412 (DOI).
  63. K. Coussement, Improving Customer Retention Management through Cost-sensitive Learning, European Journal of Marketing, 48 3/4 (2014), pp 477-495 (DOI).
  64. K. Coussement, F.A.M. Van den Bossche, K.W. De Bock, Data Accuracy’s Impact on Segmentation Performance: Benchmarking RFM Analysis, Logistic Regression, and Decision Trees, Journal of Business Research, 67 (1) (2014), pp 2751-2758 (DOI).
  65. K. Coussement, K.W. De Bock, Customer Churn Prediction in the Online Gambling Industry: The Beneficial Effect of Ensemble Learning, Journal of Business Research, 66 (9) (2013), pp 1629-1636 (DOI).
  66. K. Coussement, W. Buckinx, A Probability-Mapping Algorithm for Calibrating the Posterior Probabilities: A Direct Marketing Application, European Journal of Operational Research, 214 (2011), pp 732-738 (DOI).
  67. K.W. De Bock, K. Coussement and D. Van den Poel, Ensemble Classification Based on Generalized Additive Models, Computational Statistics & Data Analysis, 54 (6) (2010), pp 1535-1546 (DOI, GAMens R package).
  68. K. Coussement, D.F. Benoit and D. Van den Poel, Improved Marketing Decision Making in a Customer Churn Prediction Context Using Generalized Additive Models, Expert Systems with Applications, 37 (2010), pp 2132-2143 (DOI).
  69. K. Coussement, D. Van den Poel, Improving Customer Attrition Prediction by Integrating Emotions from Client/Company Interaction Emails and Evaluating Multiple Classifiers, Expert Systems with Applications, 36 (3) (2009), pp 6127-6134 (DOI).
  70. K. Coussement, D. Van den Poel, Integrating the Voice of Customers through Call Center Emails into a Decision Support System for Churn Prediction, Information and Management, 45 (3) (2008), pp 164-174 (DOI).
  71. K. Coussement, D. Van den Poel, Improving Customer Complaint Management by Automatic Email Classification Using Linguistic Style Features as Predictors, Decision Support Systems, 44 (4) (2008), pp 370-382 (DOI).
  72. K. Coussement, D. Van den Poel, Churn Prediction in Subscription Services: An Application of Support Vector Machines while Comparing Two Parameter-selection Techniques, Expert systems with applications, 34 (1) (2008), pp 313-327 (DOI).

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Software

  1. A. De Caigny, K. Coussement, K.W. De Bock, LLM: Applies the Logit Leaf Model Classifier for Binary Classification, R Package & Reference Manual version 1.1.0 (2020) (LLM R package).
  2. K.W. De Bock, K. Coussement, S. Lessmann, CSMES: Cost-sensitive Multi-criteria Ensemble Selection for Uncertain Cost Conditions, R Package & Reference Manual version 1.0.0 (2020) (CSMES R package).
  3. K.W. De Bock, K. Coussement, D. Van den Poel, GAMens: Applies GAMbag, GAMrsm and GAMens Ensemble Classifiers for Binary Classification, R Package & Reference Manual version 1.2.1 (2018) (GAMens R package).
  4. A. De Caigny, K. Coussement, K.W. De Bock, LLM: Applies the Logit Leaf Model Classifier for Binary Classification, R Package & Reference Manual version 1.0 (2018) (LLM R package).
  5. K.W. De Bock, K. Coussement, D. Van den Poel, GAMens: Applies GAMbag, GAMrsm and GAMens Ensemble Classifiers for Binary Classification, R Package & Reference Manual version 1.2 (2016).
  6. K.W. De Bock, K. Coussement, D. Van den Poel, GAMens: Applies GAMbag, GAMrsm and GAMens Ensemble Classifiers for Binary Classification, R Package & Reference Manual version 1.1 (2010).

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Books

  1. K. Charry, K. Coussement, N. Demoulin, N. Heuvinck, Marketing Research with IBM SPSS Statistics (First Edition), Routledge – Taylor & Francis, Oxford (United Kingdom) (2016) (DOI, Google Books, Amazon).
  2. K. Coussement, P. Harrigan, All You Need Is True Love (With Your Customers)! A Customer Relationship Management Fairy Tale, University Press, Ghent (Belgium) (2014).
  3. K. Coussement, K.W. De Bock, Scott A. Neslin (Eds.), Advanced Database Marketing: Innovative Methodologies & Applications of Managing Customer Relationships, Gower Publishing, London (United Kingdom) (2013) (DOI, Google Books, Amazon) (translated in simplified Chinese. –, The China Enterprise Management Publishing House, Beijing (China) (2014)).
  4. K. Coussement, N. Demoulin, K. Charry, Marketing Research with SAS Enterprise Guide (First Edition), Gower Publishing, London (United Kingdom) (2011) (view DOI, Google Books, Amazon).
  5. K. Coussement, Issues in Customer Intelligence: Data and Method Creativity to Improve Marketing Decision Making, Doctoral Dissertation submitted to the Faculty of Economics & Business Administration, Ghent University Press (Belgium) (2008).

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Book Chapters

  1. K.W. De Bock, K. Coussement, D. Cielen, An Overview of Multiple Classifier Systems Based on Generalized Additive Models, in E.A. Cortés, M.G. Martinez, N.G. Rubio (eds) , Ensemble Classification Methods with Applications in R,  Wiley, (2018).
  2. K.W. De Bock, K. Coussement, Special Session: Big Data Analytics for Marketing (Contributed Session by the IÉSEG Center for Marketing Analytics (ICMA)), in Rossi P. (eds) Marketing at the Confluence between Entertainment and Analytics. Developments in Marketing Science: Proceedings of the Academy of Marketing Science, Springer, Paris (France) (2017).
  3. S. Debaere, K. Coussement, S. Van Neck, T. De Ruyck, Minority Report in Market Research Online Communities: The Future Can Be Seen, Member Disengagement Can Be Prevented, in Tim Macer et al.(Eds.), Association for Survey Computing (ASC) 2016:. Are We There Yet? Where Technological Innovation is Leading Research, ASC, Winchester (United Kingdom) (2016).
  4. N. Demoulin, K. Coussement, The Adoption of Text Mining Tools: A Strategic Choice for Companies with a Strong Focus on Client Focus (in French), In Survey Magazine (T2), Paris (France) (2016).
  5. O. Boujena, K. Coussement, K.W. De Bock, Data Driven Customer Centricity: CRM Predictive Analytics, in T. Tsiakis (Ed.), Trends and Innovations in Marketing Information Systems, IGI Global Publishing, Pennsylvania (USA) (2015).
  6. K. Coussement, K.W. De Bock, Textual Customer Data Handling for Quantitative Marketing Analysis, in K. Coussement, K.W. De Bock and Scott A. Neslin (Eds.), Advanced Database Marketing: Innovative Methodologies & Applications of Managing Customer Relationships, Gower Publishing, London (United Kingdom) (2013).
  7. K.W. De Bock, K. Coussement, Ensemble Learning in Database Marketing, in K. Coussement, K.W. De Bock and Scott A. Neslin (Eds.), Advanced Database Marketing: Innovative Methodologies & Applications of Managing Customer Relationships, Gower Publishing, London (United Kingdom) (2013).

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Case Studies

  1. K. Coussement, B. Vindevogel, Global.com: Building Analytical Capabilities in the Mobile Telecom Market, The Case Centre, teaching note 315-096-8 (2015), p 12.
  2. K. Coussement, B. Vindevogel, Global.com: Building Analytical Capabilities in the Mobile Telecom Market, The Case Centre, case study 315-096-1 (2015), p 7.
  3. K. Coussement, L. Zarantonello, Oh You Never Gonna Quit It: Chocolate! A Marketing Research Case Study. Part 2: Hypothesis Testing, Regression Analysis & Moderation/Mediation Analysis, The Case Centre, teaching note 513-081-1 (2013), p 19.
  4. K. Coussement, L. Zarantonello, Oh You Never Gonna Quit It: Chocolate! A Marketing Research Case Study. Part 2: Hypothesis Testing, Regression Analysis & Moderation/Mediation Analysis, The Case Centre, case study 513-081-1 (2013), p 16.
  5. K. Coussement, L. Zarantonello, Oh You Never Gonna Quit It: Chocolate! A Marketing Research Case Study. Part 1: Descriptive Statistics & Factor Analysis, The Case Centre, teaching note 513-080-8 (2013), p 22.
  6. K. Coussement, L. Zarantonello, Oh You Never Gonna Quit It: Chocolate! A Marketing Research Case Study. Part 1: Descriptive Statistics & Factor Analysis, The Case Centre, case study 513-080-1 (2013), p 14.
  7. K. Coussement, P. Harrigan, The Princess and Her Quest for True Love! A CRM Fable: Part (C): One-to-one Marketing & Co-creation, European Case Clearing House (ECCH), teaching note 513-032-8 (2013), p 15.
  8. K. Coussement, P. Harrigan, The Princess and Her Quest for True Love! A CRM Fable: Part (C): One-to-one Marketing & Co-creation, European Case Clearing House (ECCH), case study 513-032-1 (2013) p 22.
  9. K. Coussement, P. Harrigan, The Princess and Her Quest for True Love! A CRM Fable: Part (B): Segmentation & Direct Marketing, European Case Clearing House (ECCH), teaching note 513-031-8 (2013), p 13.
  10. K. Coussement, P. Harrigan, The Princess and Her Quest for True Love! A CRM Fable: Part (B): Segmentation & Direct Marketing, European Case Clearing House (ECCH), case study 513-031-1 (2013) p 25.
  11. K. Coussement, P. Harrigan, The Princess and Her Quest for True Love! A CRM Fable: Part (A): Mass Marketing & Segmentation, European Case Clearing House (ECCH), teaching note 513-030-8 (2013), p 12.
  12. K. Coussement, P. Harrigan, The Princess and Her Quest for True Love! A CRM Fable: Part (A): Mass Marketing & Segmentation, European Case Clearing House (ECCH), case study 513-030-1 (2013) p 25.

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