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Who’s Next: Evaluating Attrition with Machine Learning Algorithms and Survival Analysis
4 references·2 citing·27 second hop
Who’s Next: Evaluating Attrition with Machine Learning Algorithms and Survival Analysis (2018)Who’s Next: Evaluating Attrition with Mac…Prediction of Employee Turnover in Organizations using Machine Learning Algorithms (2016)Prediction of Employee Turnov…An Analytics Approach for Proactively Combating Voluntary Attrition of Employees (2012)An Analytics Approach for Pro…Employee churn prediction (2010)Employee churn predictionEmployee turnover: a novel prediction solution with effective feature selection (2009)Employee turnover: a novel pr…Uplift modeling VS conventional predictive model: A reliable machine learning model to solve employee turnover (2021)Uplift modeling VS convention…An Explicative and Predictive Study of Employee Attrition Using Tree-based Models (2019)An Explicative and Predictive…Voluntary turnover and job performance: Curvilinearity and the moderating influences of salary growth and promotions. (1997)A Meta-Analysis of Antecedents and Correlates of Employee Turnover: Update, Moderator Tests, and Research Implications for the Next Millennium (2000)Targeted employee retention: Performance‐based and job‐related differences in reported reasons for staying (2009)Identifying Employees for Re-skilling Using an Analytics-Based Approach (2015)On the Profitability of Long-Life Customers in a Noncontractual Setting: An Empirical Investigation and Implications for Marketing (2000)A Customer Lifetime Value Framework for Customer Selection and Resource Allocation Strategy (2004)Modeling Customer Lifetime Value (2006)Employees recruitment: A prescriptive analytics approach via machine learning and mathematical programming (2020)A review of machine learning applications in human resource management (2021)A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective (2021)Organizational commitment, job satisfaction, and turnover among psychiatric technicians. (1974)JOB SATISFACTION, ORGANIZATIONAL COMMITMENT, TURNOVER INTENTION, AND TURNOVER: PATH ANALYSES BASED ON META‐ANALYTIC FINDINGS (1993)PERCEIVED ORGANIZATIONAL SUPPORT AND LEADER-MEMBER EXCHANGE: A SOCIAL EXCHANGE PERSPECTIVE. (1997)Domain-Driven Data Mining in Human Resource Management: A Review (2011)Employee turnover prediction and retention policies design: a case study (2017)Mirror, Mirror on the Wall, Who Is Leaving of Them All: Predictions for Employee Turnover with Gated Recurrent Neural Networks (2019)Employee Turnover: A Meta-Analysis and Review with Implications for Research (1986)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Born to burnout: A meta-analytic path model of personality, job burnout, and work outcomes (2010)RFRSF: Employee Turnover Prediction Based on Random Forests and Survival Analysis (2020)Algorithms as work designers: How algorithmic management influences the design of jobs (2021)One hundred years of employee turnover theory and research. (2017)Redefine statistical significance (2017)From Predictive to Prescriptive Analytics (2019)A meta-analytic review of the relationship between absence and turnover. (1992)The economics of skills obsolescence: A review (2004)Causes and Effects of Employee Downsizing: A Review and Synthesis (2009)
this work references cited by second hop

References

  • 2016Prediction of Employee Turnover in Organizations using Machine Learning Algorithms243 cited
  • 2010Employee churn prediction188 cited
  • 2012An Analytics Approach for Proactively Combating Voluntary Attrition of Employees27 cited
  • 2009Employee turnover: a novel prediction solution with effective feature selection25 cited

Cited by

  • 2021Uplift modeling VS conventional predictive model: A reliable machine learning model to solve employee turnover14 cited
  • 2019An Explicative and Predictive Study of Employee Attrition Using Tree-based Models14 cited

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