Regaining drifting mobile communication customers: Predicting the odds of success of winback efforts with competing risks regression
暂无分享,去创建一个
[1] Kurt Ulm,et al. Applying competing risks regression models: an overview , 2013, Lifetime data analysis.
[2] V. Coviello,et al. Cumulative Incidence Estimation in the Presence of Competing Risks , 2004 .
[3] Melinda Mills,et al. Introducing Survival and Event History Analysis , 2011 .
[4] M. Eisend,et al. Buyers’ perceived switching costs and switching: a meta-analytic assessment of their antecedents , 2014 .
[5] Gábor Benedek,et al. The Importance of Social Embeddedness: Churn Models at Mobile Providers , 2014, Decis. Sci..
[6] Michael Lewis. Incorporating Strategic Consumer Behavior into Customer Valuation , 2005 .
[7] Prabin Kumar Panigrahi,et al. A Neural Network based Approach for Predicting Customer Churn in Cellular Network Services , 2011, ArXiv.
[8] Customer relationship reactivation in the telecommunications sector , 2013 .
[9] Reza Tavakkoli-Moghaddam,et al. Customer churn prediction using a hybrid method and censored data , 2013 .
[10] A. Keramati,et al. Churn analysis for an Iranian mobile operator , 2011 .
[11] Katherine N. Lemon,et al. The WOW factor: Creating value through win-back offers to reacquire lost customers , 2007 .
[12] O. Aalen,et al. Survival and Event History Analysis: A Process Point of View , 2008 .
[13] Chih-Ping Wei,et al. Turning telecommunications call details to churn prediction: a data mining approach , 2002, Expert Syst. Appl..
[14] Luo Bin,et al. Customer Churn Prediction Based on the Decision Tree in Personal Handyphone System Service , 2007, 2007 International Conference on Service Systems and Service Management.
[15] Myengja Yang. Churn Management and Policy: Measuring the Effectiveness of Fixed-Mobile Bundling on Mobile Subscriber Retention , 2013 .
[16] Ruth N. Bolton,et al. A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction , 1994 .
[17] C. Ranganathan,et al. Two-level model of customer retention in the US mobile telecommunications service market , 2008 .
[18] M. Haenlein. Social interactions in customer churn decisions: The impact of relationship directionality☆ , 2013 .
[19] Ali Tamaddoni Jahromi,et al. Managing B2B customer churn, retention and profitability , 2014 .
[20] J. Dignam,et al. The Use and Interpretation of Competing Risks Regression Models , 2012, Clinical Cancer Research.
[21] Hyunbo Cho,et al. Mining churning behaviors and developing retention strategies based on a partial least squares (PLS) model , 2011, Decis. Support Syst..
[22] Christian Homburg,et al. Einflussgrößen des Kundenrückgewinnungserfolgs: Theoretische Betrachtung und empirische Befunde , 2003 .
[23] Reasons for Switching Service Providers , 2012 .
[24] B. Stauss,et al. Preisunzufriedenheit als Determinante der Kundenabwanderung bei Commodity-Dienstleistungen , 2011 .
[25] StataCorp. Stata survival analysis and epidemiological tables reference manual , 2011 .
[26] Bart Baesens,et al. Building comprehensible customer churn prediction models with advanced rule induction techniques , 2011, Expert Syst. Appl..
[27] G. Özer,et al. The analysis of antecedents of customer loyalty in the Turkish mobile telecommunication market , 2005 .
[28] R. H. Evans,et al. An Application of Equity Theory to Buyer-Seller Exchange Situations , 1978 .
[29] R. Abbott. Logistic regression in survival analysis. , 1985, American journal of epidemiology.
[30] Euiho Suh,et al. An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industry , 2004, Expert Syst. Appl..
[31] Christian Homburg,et al. Einflussgrößen des Kundenrückgewinnungserfolgs , 2004 .
[32] Kun Chang Lee,et al. Bayesian Network Approach to Predict Mobile Churn Motivations: Emphasis on General Bayesian Network, Markov Blanket, and What-If Simulation , 2010, FGIT.
[33] D. Cox. Regression Models and Life-Tables , 1972 .
[34] Christian Homburg,et al. How to get lost customers back? , 2007 .
[35] E. Blery,et al. Service quality and customer retention in mobile telephony , 2009 .
[36] Bin Li,et al. Automated Cellular Modeling and Prediction on a Large Scale , 2000, Artificial Intelligence Review.
[37] Chi-Hyuck Jun,et al. Improved churn prediction in telecommunication industry by analyzing a large network , 2014, Expert Syst. Appl..
[38] Kristof Coussement,et al. Improving customer attrition prediction by integrating emotions from client/company interaction emails and evaluating multiple classifiers , 2009, Expert Syst. Appl..
[39] Doreén Pick,et al. Rückgewinnungs-Pricing im Telekommunikationssektor , 2009 .
[40] Frank G. Sieben. Rückgewinnung verlorener Kunden , 2002 .
[41] Marcin Owczarczuk,et al. Churn models for prepaid customers in the cellular telecommunication industry using large data marts , 2010, Expert Syst. Appl..
[42] Yong Seog Kim,et al. Measuring the Success of Retention Management Models Built on Churn Probability, Retention Probability, and Expected Yearly Revenues , 2012, AMCIS.
[43] Koen W. De Bock,et al. An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction , 2011, Expert Syst. Appl..
[44] Dirk Van den Poel,et al. Predicting customer retention and profitability by using random forests and regression forests techniques , 2005, Expert Syst. Appl..
[45] Robert Gray,et al. A Proportional Hazards Model for the Subdistribution of a Competing Risk , 1999 .
[46] Abbas Raza Ali,et al. Customer Churn Prediction, Segmentation and Fraud Detection in Telecommunication Industry , 2014 .
[47] David C. Yen,et al. Applying data mining to telecom churn management , 2006, Expert Syst. Appl..
[48] Anders Gustafsson,et al. Understanding Frequent Switching Patterns A Crucial Element in Managing Customer Relationships , 2007 .
[49] Shuang Yang,et al. Comparative performance of logistic regression and survival analysis for detecting spatial predictors of land-use change , 2013, Int. J. Geogr. Inf. Sci..
[50] Jung-Kuei Hsieh,et al. Post-adoption switching behavior for online service substitutes: A perspective of the push-pull-mooring framework , 2012, Comput. Hum. Behav..
[51] J. Hair. Multivariate data analysis , 1972 .
[52] H. Bansal,et al. “Migrating” to new service providers: Toward a unifying framework of consumers’ switching behaviors , 2005 .
[53] Anders Gustafsson,et al. Understanding Frequent Switching Patterns , 2007 .
[54] Bruce G. S. Hardie,et al. A Joint Model of Usage and Churn in Contractual Settings , 2013, Mark. Sci..
[55] Yossi Richter,et al. Predicting Customer Churn in Mobile Networks through Analysis of Social Groups , 2010, SDM.
[56] B. Libai,et al. Social Effects on Customer Retention , 2011 .
[57] Zhenzhong Ma,et al. Service quality and customer switching behavior in China's mobile phone service sector , 2013 .
[58] Ofcom. International communications market report 2015 , 2015 .
[59] Özden Gür Ali,et al. Dynamic churn prediction framework with more effective use of rare event data: The case of private banking , 2014, Expert Syst. Appl..
[60] Bart Baesens,et al. New insights into churn prediction in the telecommunication sector: A profit driven data mining approach , 2012, Eur. J. Oper. Res..
[61] Christophe Croux,et al. Bagging and Boosting Classification Trees to Predict Churn , 2006 .
[62] Ali Mustafa Qamar,et al. Telecommunication subscribers' churn prediction model using machine learning , 2013, Eighth International Conference on Digital Information Management (ICDIM 2013).
[63] Dirk Van den Poel,et al. Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting , 2005, Eur. J. Oper. Res..
[64] Abbas Keramati,et al. Improved churn prediction in telecommunication industry using data mining techniques , 2014, Appl. Soft Comput..
[65] John D. Johnson,et al. Churn management optimization with controllable marketing variables and associated management costs , 2013, Expert Syst. Appl..
[66] Bart Larivière,et al. A Meta-Analysis of Relationships Linking Service Failure Attributions to Customer Outcomes , 2014 .
[67] Yi-Fei Chuang,et al. Pull-and-suck effects in Taiwan mobile phone subscribers switching intentions , 2011 .
[68] D. Kleinbaum,et al. Survival Analysis: A Self-Learning Text. , 1996 .
[69] Jill Griffin,et al. Customer Winback: How to recapture lost customers and keep them loyal (Как вернуть потерянных клиентов и сделать их лояльными) , 2001 .
[70] D. Fudenberg,et al. Customer Poaching and Brand Switching , 2000 .
[71] Bernd Stauss,et al. Regaining Service Customers , 1999 .
[72] Eric Johnson,et al. Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry , 2000, IEEE Trans. Neural Networks Learn. Syst..
[73] Robert C. Blattberg,et al. Recapturing Lost Customers , 2004 .
[74] Jae-Hyeon Ahn,et al. Customer churn analysis: Churn determinants and mediation effects of partial defection in the Korean mobile telecommunications service industry , 2006 .
[75] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[76] C. Ranganathan,et al. Switching behavior of mobile users: do users' relational investments and demographics matter? , 2006, Eur. J. Inf. Syst..