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Predicting Customer Value Using Clumpiness: From RFM to RFMC

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  1. Orhan Bahadır Doğan & V. Kumar & Avishek Lahiri, 2024. "Platform-level consequences of performance-based commission for service providers: Evidence from ridesharing," Journal of the Academy of Marketing Science, Springer, vol. 52(4), pages 1240-1261, July.
  2. Rodrigo Rivera-Castro & Polina Pilyugina & Evgeny Burnaev, 2020. "Topological Data Analysis for Portfolio Management of Cryptocurrencies," Papers 2009.03362, arXiv.org.
  3. Noorizadeh, Abdollah & Kuosmanen, Timo & Peltokorpi, Antti, 2021. "Effective purchasing reallocation to suppliers: insights from productivity dynamics and real options theory," International Journal of Production Economics, Elsevier, vol. 233(C).
  4. Lu, Huidi & van der Lans, Ralf & Helsen, Kristiaan & Gauri, Dinesh K., 2023. "DEPART: Decomposing prices using atheoretical regression trees," International Journal of Research in Marketing, Elsevier, vol. 40(4), pages 781-800.
  5. Annika Baumann & Johannes Haupt & Fabian Gebert & Stefan Lessmann, 2019. "The Price of Privacy," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(4), pages 413-431, August.
  6. Chou, Ping & Chuang, Howard Hao-Chun & Chou, Yen-Chun & Liang, Ting-Peng, 2022. "Predictive analytics for customer repurchase: Interdisciplinary integration of buy till you die modeling and machine learning," European Journal of Operational Research, Elsevier, vol. 296(2), pages 635-651.
  7. Park, Chang Hee, 2017. "Online Purchase Paths and Conversion Dynamics across Multiple Websites," Journal of Retailing, Elsevier, vol. 93(3), pages 253-265.
  8. Shu-Hui Chao & Mu-Kuan Chen & Hsin-Hung Wu, 2021. "An LRFM Model to Analyze Outpatient Loyalty From a Medical Center in Taiwan," SAGE Open, , vol. 11(3), pages 21582440211, July.
  9. Shu-Hui Chao & Mu-Kuan Chen & Hsin-Hung Wu, 2021. "An Empirical Study of Hospital’s Outpatient Loyalty From a Medical Center in Taiwan," SAGE Open, , vol. 11(2), pages 21582440211, April.
  10. Patrick Bachmann & Markus Meierer & Jeffrey Näf, 2021. "The Role of Time-Varying Contextual Factors in Latent Attrition Models for Customer Base Analysis," Marketing Science, INFORMS, vol. 40(4), pages 783-809, July.
  11. Farnoosh Khodakarami & J. Andrew Petersen & Rajkumar Venkatesan, 2024. "Customer behavior across competitive loyalty programs," Journal of the Academy of Marketing Science, Springer, vol. 52(3), pages 892-913, May.
  12. Chen, Yanhong & Liu, Luning & Zheng, Dequan & Li, Bin, 2023. "Estimating travellers’ value when purchasing auxiliary services in the airline industry based on the RFM model," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
  13. Valendin, Jan & Reutterer, Thomas & Platzer, Michael & Kalcher, Klaudius, 2022. "Customer base analysis with recurrent neural networks," International Journal of Research in Marketing, Elsevier, vol. 39(4), pages 988-1018.
  14. Nobuhiko Terui & Shohei Hasegawa & Greg M. Allenby, 2015. "A Threshold Model for Discontinuous Preference Change and Satiation," TMARG Discussion Papers 122, Graduate School of Economics and Management, Tohoku University.
  15. Ryosuke Igari & Takahiro Hoshino, 2018. "A Bayesian Gamma Frailty Model Using the Sum of Independent Random Variables: Application of the Estimation of an Interpurchase Timing Model," Keio-IES Discussion Paper Series 2018-021, Institute for Economics Studies, Keio University.
  16. Rocío G. Martínez & Ramon A. Carrasco & Cristina Sanchez-Figueroa & Diana Gavilan, 2021. "An RFM Model Customizable to Product Catalogues and Marketing Criteria Using Fuzzy Linguistic Models: Case Study of a Retail Business," Mathematics, MDPI, vol. 9(16), pages 1-31, August.
  17. Jeff Shockley & Jason R. W. Merrick & Xiaojin Liu & Jeffery S. Smith, 2023. "How much do customer ordering practices drive medical supplies distribution (in)efficiency for primary care markets?," Production and Operations Management, Production and Operations Management Society, vol. 32(12), pages 3908-3930, December.
  18. Liu, Feng & Zhao, Shaoqiong & Li, Yang, 2017. "How many, how often, and how new? A multivariate profiling of mobile app users," Journal of Retailing and Consumer Services, Elsevier, vol. 38(C), pages 71-80.
  19. Carlos Fernández-Loría & Maxime C. Cohen & Anindya Ghose, 2023. "Evolution of Referrals over Customers’ Life Cycle: Evidence from a Ride-Sharing Platform," Information Systems Research, INFORMS, vol. 34(2), pages 698-720, June.
  20. Petra P. Šimović & Claire Y. T. Chen & Edward W. Sun, 2023. "Classifying the Variety of Customers’ Online Engagement for Churn Prediction with a Mixed-Penalty Logistic Regression," Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 451-485, January.
  21. Mina Ameri & Elisabeth Honka & Ying Xie, 2024. "Watching intensity and media franchise engagement," Quantitative Marketing and Economics (QME), Springer, vol. 22(3), pages 291-356, September.
  22. Zhang, Shoutong Thomas, 2016. "Firm valuation from customer equity: When does it work and when does it fail?," International Journal of Research in Marketing, Elsevier, vol. 33(4), pages 966-970.
  23. Michael Platzer & Thomas Reutterer, 2016. "Ticking Away the Moments: Timing Regularity Helps to Better Predict Customer Activity," Marketing Science, INFORMS, vol. 35(5), pages 779-799, September.
  24. Gary Mena & Kristof Coussement & Koen W. Bock & Arno Caigny & Stefan Lessmann, 2024. "Exploiting time-varying RFM measures for customer churn prediction with deep neural networks," Annals of Operations Research, Springer, vol. 339(1), pages 765-787, August.
  25. Hyeokkoo Eric Kwon & Sanjeev Dewan & Wonseok Oh & Taekyung Kim, 2023. "Self-Regulation and External Influence: The Relative Efficacy of Mobile Apps and Offline Channels for Personal Weight Management," Information Systems Research, INFORMS, vol. 34(1), pages 50-66, March.
  26. Reutterer, Thomas & Platzer, Michael & Schröder, Nadine, 2021. "Leveraging purchase regularity for predicting customer behavior the easy way," International Journal of Research in Marketing, Elsevier, vol. 38(1), pages 194-215.
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