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TSUNAMI - an explainable PPM approach for customer churn prediction in evolving retail data environments
16 references·0 citing·54 second hopsampled
TSUNAMI - an explainable PPM approach for customer churn prediction in evolving retail data environments (2023)TSUNAMI - an explainable PPM approach for…Exploiting time-varying RFM measures for customer churn prediction with deep neural networks (2023)Exploiting time-varying RFM m…Customer churning analysis using machine learning algorithms (2023)Customer churning analysis us…An explainable decision support system for predictive process analytics (2023)An explainable decision suppo…Towards Explainable Machine Learning for Bank Churn Prediction Using Data Balancing and Ensemble-Based Methods (2022)Towards Explainable Machine L…Predictive Process Monitoring (2022)Predictive Process MonitoringA survey on machine learning methods for churn prediction (2022)A survey on machine learning …The impact of the COVID-19 crisis on consumer purchasing motivation and behavior (2021)The impact of the COVID-19 cr…A Survey on Churn Analysis in Various Business Domains (2020)A Survey on Churn Analysis in…A novel scheme for employee churn problem using multi-attribute decision making approach and machine learning (2020)A novel scheme for employee c…Outcome-Oriented Predictive Process Monitoring (2019)Outcome-Oriented Predictive P…Handling Concept Drift in Predictive Process Monitoring (2017)Handling Concept Drift in Pre…Hierarchical Change-Detection Tests (2016)Hierarchical Change-Detection…Modeling partial customer churn: On the value of first product-category purchase sequences (2012)Modeling partial customer chu…Modelling and predicting customer churn from an insurance company (2011)Modelling and predicting cust…Customer attrition analysis for financial services using proportional hazard models (2003)Customer attrition analysis f…A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction (1998)A Dynamic Model of the Durati…Determinants of Long-Term Orientation in Buyer-Seller Relationships (1994)Customer Switching Behavior in Service Industries: An Exploratory Study (1995)The Behavioral Consequences of Service Quality (1996)Customer base analysis: partial defection of behaviourally loyal clients in a non-contractual FMCG retail setting (2004)Churn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniques (2006)Building comprehensible customer churn prediction models with advanced rule induction techniques (2010)Zero defections: quality comes to services. (1990)From Marketing Mix to Relationship Marketing: Towards a Paradigm Shift in Marketing (1994)Predicting customer churn from valuable B2B customers in the logistics industry: a case study (2014)User segmentation for retention management in online social games (2017)Machine Learning to Develop Credit Card Customer Churn Prediction (2022)Prospect Theory: An Analysis of Decision under Risk (1979)A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions (1980)Prospect theory: An analysis of decision under risk (1988)Investments in Consumer Relationships: A Cross-Country and Cross-Industry Exploration (2001)Satisfaction, Repurchase Intent, and Repurchase Behavior: Investigating the Moderating Effect of Customer Characteristics (2001)Customer Engagement Behavior: Theoretical Foundations and Research Directions (2010)CONTINUOUS INSPECTION SCHEMES (1954)Monitoring Structural Change (1996)Change-point detection in time-series data by relative density-ratio estimation (2013)Detecting gradual changes from data stream using MDL-change statistics (2016)Combining univariate approaches for ensemble change detection in multivariate data (2018)An Experimental Evaluation of Process Concept Drift Detection (2023)Procedures for Performing Systematic Reviews (2004)Process Mining (2016)Fundamentals of Business Process Management (2018)Survey and Cross-benchmark Comparison of Remaining Time Prediction Methods in Business Process Monitoring (2019)A systematic literature review on state-of-the-art deep learning methods for process prediction (2021)The biggest business process management problems to solve before we die (2023)On the Profitability of Long-Life Customers in a Noncontractual Setting: An Empirical Investigation and Implications for Marketing (2000)The Loyalty Effect (2001)Ensemble Methods in Customer Churn Prediction: A Comparative Analysis of the State-of-the-Art (2023)Machine learning based customer churn prediction in home appliance rental business (2023)Customer Churn Prediction: A Systematic Review of Recent Advances, Trends, and Challenges in Machine Learning and Deep Learning (2025)Evaluating Structural Equation Models with Unobservable Variables and Measurement Error (1981)The theory of planned behavior (1991)Principles and Practice of Structural Equation Modeling (2012)The Impact of Consumer Purchase Behavior Changes on the Business Model Design of Consumer Services Companies Over the Course of COVID-19 (2022)E-commerce channel management on the manufacturers’ side: ongoing debates and future research pathways (2023)Understanding consumer behavior during and after a Pandemic: Implications for customer lifetime value prediction models (2024)The Antecedents and Consequences of Customer Satisfaction for Firms (1993)An adaptive learning approach for customer churn prediction in the telecommunication industry using evolutionary computation and Naïve Bayes (2023)A data-driven approach with explainable artificial intelligence for customer churn prediction in the telecommunications industry (2025)The ProM Framework: A New Era in Process Mining Tool Support (2005)Time prediction based on process mining (2010)Predictive Business Process Monitoring with LSTM Neural Networks (2017)Foundations of Process Event Data (2022)A review of AI and machine learning contribution in business process management (process enhancement and process improvement approaches) (2024)Predictive process monitoring: concepts, challenges, and future research directions (2024)A comparison of machine learning techniques for customer churn prediction (2015)A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector (2019)Customer churn prediction in telecom using machine learning in big data platform (2019)Customer Churn Prediction using Machine Learning Models (2024)Improving Churn Detection in the Banking Sector: A Machine Learning Approach with Probability Calibration Techniques (2024)
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References

  • 1998A Dynamic Model of the Duration of the Customer's Relationship with a Continuous Service Provider: The Role of Satisfaction1,948 cited
  • 2003Customer attrition analysis for financial services using proportional hazard models430 cited
  • 2019Outcome-Oriented Predictive Process Monitoring352 cited
  • 2021The impact of the COVID-19 crisis on consumer purchasing motivation and behavior142 cited
  • 2022Predictive Process Monitoring129 cited
  • 2020A Survey on Churn Analysis in Various Business Domains109 cited
  • 2016Hierarchical Change-Detection Tests102 cited
  • 2023Customer churning analysis using machine learning algorithms95 cited
  • 2012Modeling partial customer churn: On the value of first product-category purchase sequences95 cited
  • 2022A survey on machine learning methods for churn prediction76 cited
  • 2020A novel scheme for employee churn problem using multi-attribute decision making approach and machine learning64 cited
  • 2023Exploiting time-varying RFM measures for customer churn prediction with deep neural networks58 cited
  • 2011Modelling and predicting customer churn from an insurance company56 cited
  • 2022Towards Explainable Machine Learning for Bank Churn Prediction Using Data Balancing and Ensemble-Based Methods53 cited

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  • 2023An explainable decision support system for predictive process analytics53 cited
  • 2017Handling Concept Drift in Predictive Process Monitoring50 cited
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