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Integrating the Voice of Customers through Call Center Emails into a Decision Support System for Churn Prediction

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Cited by:

  1. Antioco, Michael & Coussement, Kristof, 2018. "Misreading of consumer dissatisfaction in online product reviews: Writing style as a cause for bias," International Journal of Information Management, Elsevier, vol. 38(1), pages 301-310.
  2. M. Ballings & D. Van Den Poel & E. Verhagen, 2013. "Evaluating the Added Value of Pictorial Data for Customer Churn Prediction," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/869, Ghent University, Faculty of Economics and Business Administration.
  3. Aysun Kapucugil İkiz & Güzin Özdağoğlu, 2015. "Text Mining as a Supporting Process for VoC Clarification," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 3(1), pages 25-40, June.
  4. Park, Sangwon & Kim, Dae-Young, 2017. "Assessing language discrepancies between travelers and online travel recommendation systems: Application of the Jaccard distance score to web data mining," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 381-388.
  5. Kwon, Heeyeul & Kim, Jieun & Park, Yongtae, 2017. "Applying LSA text mining technique in envisioning social impacts of emerging technologies: The case of drone technology," Technovation, Elsevier, vol. 60, pages 15-28.
  6. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2017. "A multidisciplinary perspective of big data in management research," International Journal of Production Economics, Elsevier, vol. 191(C), pages 97-112.
  7. Lessmann, Stefan & Coussement, Kristof & De Bock, Koen W. & Haupt, Johannes, 2018. "Targeting customers for profit: An ensemble learning framework to support marketing decision making," IRTG 1792 Discussion Papers 2018-012, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  8. Alasdair Reid, 2023. "Closing the Affordable Housing Gap: Identifying the Barriers Hindering the Sustainable Design and Construction of Affordable Homes," Sustainability, MDPI, vol. 15(11), pages 1-27, May.
  9. Roland T. Rust & Ming-Hui Huang, 2014. "The Service Revolution and the Transformation of Marketing Science," Marketing Science, INFORMS, vol. 33(2), pages 206-221, March.
  10. Arno de Caigny & Kristof Coussement & Koen W. de Bock & Stefan Lessmann, 2019. "Incorporating textual information in customer churn prediction models based on a convolutional neural network," Post-Print hal-02275958, HAL.
  11. Coussement, Kristof & Van den Bossche, Filip A.M. & De Bock, Koen W., 2014. "Data accuracy's impact on segmentation performance: Benchmarking RFM analysis, logistic regression, and decision trees," Journal of Business Research, Elsevier, vol. 67(1), pages 2751-2758.
  12. Chen, Zhen-Yu & Fan, Zhi-Ping & Sun, Minghe, 2012. "A hierarchical multiple kernel support vector machine for customer churn prediction using longitudinal behavioral data," European Journal of Operational Research, Elsevier, vol. 223(2), pages 461-472.
  13. Mirjana Pejić Bach & Živko Krstić & Sanja Seljan & Lejla Turulja, 2019. "Text Mining for Big Data Analysis in Financial Sector: A Literature Review," Sustainability, MDPI, vol. 11(5), pages 1-27, February.
  14. Iva Salov & Aleksandra Krajnovic & Ante Panjkota, 2017. "Relation between Data Mining and Business Fields in the Four Dimensional CRM Model," MIC 2017: Managing the Global Economy; Proceedings of the Joint International Conference, Monastier di Treviso, Italy, 24–27 May 2017,, University of Primorska Press.
  15. Sheng, Jie & Amankwah-Amoah, Joseph & Wang, Xiaojun, 2019. "Technology in the 21st century: New challenges and opportunities," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 321-335.
  16. K. W. De Bock & D. Van Den Poel, 2011. "An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/717, Ghent University, Faculty of Economics and Business Administration.
  17. Li, Yixin & Hou, Bingzhang & Wu, Yue & Zhao, Donglai & Xie, Aoran & Zou, Peng, 2021. "Giant fight: Customer churn prediction in traditional broadcast industry," Journal of Business Research, Elsevier, vol. 131(C), pages 630-639.
  18. Zhiyong Zhou & Jianhui Huang & Yao Lu & Hongcai Ma & Wenwen Li & Jianhong Chen, 2022. "A New Text-Mining–Bayesian Network Approach for Identifying Chemical Safety Risk Factors," Mathematics, MDPI, vol. 10(24), pages 1-25, December.
  19. De Caigny, Arno & Coussement, Kristof & De Bock, Koen W. & Lessmann, Stefan, 2020. "Incorporating textual information in customer churn prediction models based on a convolutional neural network," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1563-1578.
  20. Johannes Habel & Sascha Alavi & Nicolas Heinitz, 2023. "A theory of predictive sales analytics adoption," AMS Review, Springer;Academy of Marketing Science, vol. 13(1), pages 34-54, June.
  21. Capponi, Giovanna & Corrocher, Nicoletta & Zirulia, Lorenzo, 2021. "Personalized pricing for customer retention: Theory and evidence from mobile communication," Telecommunications Policy, Elsevier, vol. 45(1).
  22. Nathalie Demoulin & Kristof Coussement, 2018. "Acceptance of text-mining systems: The signaling role of information quality," Post-Print hal-02111772, HAL.
  23. Fawad Ahmed & Yuan Jian Qin & Luis Martínez, 2019. "Sustainable Change Management through Employee Readiness: Decision Support System Adoption in Technology-Intensive British E-Businesses," Sustainability, MDPI, vol. 11(11), pages 1-28, May.
  24. D. Thorleuchter & D. Van Den Poel & A. Prinzie, 2011. "Analyzing existing customers’ websites to improve the customer acquisition process as well as the profitability prediction in B-to-B marketing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/733, Ghent University, Faculty of Economics and Business Administration.
  25. Md. Abdul Moktadir & Ashish Dwivedi & Akib Rahman & Charbel Jose Chiappetta Jabbour & Sanjoy Kumar Paul & Razia Sultana & Jitender Madaan, 2020. "An investigation of key performance indicators for operational excellence towards sustainability in the leather products industry," Business Strategy and the Environment, Wiley Blackwell, vol. 29(8), pages 3331-3351, December.
  26. Arno de Caigny & Kristof Coussement & Koen de Bock, 2020. "Leveraging fine-grained transaction data for customer life event predictions," Post-Print hal-02507998, HAL.
  27. D. Thorleuchter & D. Van Den Poel & A. Prinzie & -, 2010. "A compared R&D-based and patent-based cross impact analysis for identifying relationships between technologies," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 10/632, Ghent University, Faculty of Economics and Business Administration.
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