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Understanding the Ecosystem and Addressing the Fundamental Concerns of Commercial MVNO
8 references·0 citing·39 second hop
Understanding the Ecosystem and Addressing the Fundamental Concerns of Commercial MVNO (2020)Understanding the Ecosystem and Addressin…An In-depth Study of Commercial MVNO (2019)An In-depth Study of Commerci…Customer churn prediction by hybrid neural networks (2009)Customer churn prediction by …Churn Prediction Model in Retail Banking Using Fuzzy C-Means Algorithm (2009)Churn Prediction Model in Ret…Spearman Rank Correlation Coefficient (2008)Spearman Rank Correlation Coe…Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques (2006)Churn prediction in subscript…Applying data mining to telecom churn management (2005)Applying data mining to telec…Analysing Customer Churn in Insurance Data – A Case Study (2004)Analysing Customer Churn in I…Customer Satisfaction Cues To Support Market Segmentation and Explain Switching Behavior (2000)Customer Satisfaction Cues To…Book Review: Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control (1977)Subexponential Distributions (2004)User Behavior Modelling Approach for Churn Prediction in Online Games (2012)Just-in-time customer churn prediction in the telecommunication sector (2017)Swarm intelligence goal-oriented approach to data-driven innovation in customer churn management (2021)Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management (2004)Handling class imbalance in customer churn prediction (2008)Profit Maximization Analysis Based on Data Mining and the Exponential Retention Model Assumption with Respect to Customer Churn Problems (2015)What's In A Name? Malay Seals As Onomastic Sources (2018)Churn Prediction for Savings Bank Customers: A Machine Learning Approach (2020)A Logit Model of Brand Choice Calibrated on Scanner Data (1983)Customer Evaluations of Service Complaint Experiences: Implications for Relationship Marketing (1998)Switching barriers and repurchase intentions in services (2000)Customer churn prediction using improved balanced random forests (2008)Building comprehensible customer churn prediction models with advanced rule induction techniques (2010)Customer churn prediction in telecommunications (2011)Customer Switching Behavior in Service Industries: An Exploratory Study (1995)Forecasting with artificial neural networks: (1998)Application of data mining techniques in customer relationship management: A literature review and classification (2008)Churn prediction using comprehensible support vector machine: An analytical CRM application (2014)Customers churn prediction and marketing retention strategies. An application of support vector machines based on the AUC parameter-selection technique in B2B e-commerce industry (2016)Customer churn prediction in telecommunication industry using data certainty (2018)Significance tests and goodness of fit in the analysis of covariance structures. (1980)A Conceptual Model of Service Quality and Its Implications for Future Research (1985)SERVQUAL: A multiple-Item Scale for measuring consumer perceptions of service quality (1988)Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments (2000)Some New Thoughts on Conceptualizing Perceived Service Quality: A Hierarchical Approach (2001)The Roles of Quality, Value, and Satisfaction in Predicting Cruise Passengers’ Behavioral Intentions (2004)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis (1999)Building Data Mining Applications for CRM (1999)A survey of results on mobile phone datasets analysis (2015)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)A practical guide to analytical method validation, including measurement uncertainty and accuracy profiles (2007)The Proof and Measurement of Association between Two Things (1904)A new method for strategic decision-making in higher education (2017)Integrating the DEMATEL with the analytic network process for effective decision-making (2018)Applications for ordering food: The specifics of choice for installation on computers and laptops (2023)
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References

  • 2000Customer Satisfaction Cues To Support Market Segmentation and Explain Switching Behavior629 cited
  • 2005Applying data mining to telecom churn management514 cited
  • 2006Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques432 cited
  • 2009Customer churn prediction by hybrid neural networks321 cited
  • 2008Spearman Rank Correlation Coefficient166 cited
  • 2004Analysing Customer Churn in Insurance Data – A Case Study50 cited
  • 2019An In-depth Study of Commercial MVNO25 cited
  • 2009Churn Prediction Model in Retail Banking Using Fuzzy C-Means Algorithm24 cited

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