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A Novel Framework for Decision Support System in Human Resource Management
5 references·1 citing·28 second hop
A Novel Framework for Decision Support System in Human Resource Management (2020)A Novel Framework for Decision Support Sy…Intelligent human resource information system (i-HRIS): a holistic decision support framework for HR excellence. (2018)Intelligent human resource in…Employee Turnover Prediction with Machine Learning: A Reliable Approach (2018)Employee Turnover Prediction …Artificial Intelligence in Human Resources Management: Challenges and a Path Forward (2018)Artificial Intelligence in Hu…A data mining approach to employee turnover prediction (case study: Arak automotive parts manufacturing) (2015)A data mining approach to emp…Intelligent Techniques for Decision Support System in Human Resource Management (2010)Intelligent Techniques for De…HRM Algorithms: Moderating the Relationship between Chaotic Markets and Strategic Renewal (2024)HRM Algorithms: Moderating th…Past, present, and future of decision support technology (2002)Decision Support and Business Intelligence Systems (2006)Fundamentals of Human Resource Management (2010)Classify interval range of crime forecasting for crime prevention decision making (2016)Why Do Swiss HR Departments Dislike Algorithms in Their Recruitment Process? An Empirical Analysis (2024)Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management (2004)Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)5 Turnover and Retention Research: A Glance at the Past, a Closer Review of the Present, and a Venture into the Future (2008)Employees recruitment: A prescriptive analytics approach via machine learning and mathematical programming (2020)A machine learning-based analytical framework for employee turnover prediction (2021)Retention is All You Need (2023)Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry (2006)Prediction of Employee Turnover in Organizations using Machine Learning Algorithms (2016)A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective (2021)From Big Data to Deep Data to Support People Analytics for Employee Attrition Prediction (2021)Responsible artificial intelligence in human resources management: a review of the empirical literature (2023)THE PEOPLE MAKE THE PLACE (1987)Two Types of Bureaucracy: Enabling and Coercive (1996)Algorithm Aversion: People Erroneously Avoid Algorithms after Seeing Them Err (2014)Artificial Intelligence Chatbots are New Recruiters (2019)Human-AI Interaction in Human Resource Management: Understanding Why Employees Resist Algorithmic Evaluation at Workplaces and How to Mitigate Burdens (2021)The Power of Artificial Intelligence in Recruitment: An Analytical Review of Current AI-Based Recruitment Strategies (2023)Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology (1989)The theory of planned behavior (1991)Common method biases in behavioral research: A critical review of the literature and recommended remedies. (2003)Achieving Operational Excellence Through Artificial Intelligence: Driving Forces and Barriers (2021)When technology meets people: the interplay of artificial intelligence and human resource management (2021)A study of Artificial Intelligence impacts on Human Resource Digitalization in Industry 4.0 (2023)
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References

  • 2018Employee Turnover Prediction with Machine Learning: A Reliable Approach170 cited
  • 2018Artificial Intelligence in Human Resources Management: Challenges and a Path Forward160 cited
  • 2018Intelligent human resource information system (i-HRIS): a holistic decision support framework for HR excellence.99 cited
  • 2015A data mining approach to employee turnover prediction (case study: Arak automotive parts manufacturing)56 cited
  • 2010Intelligent Techniques for Decision Support System in Human Resource Management35 cited

Cited by

  • 2024HRM Algorithms: Moderating the Relationship between Chaotic Markets and Strategic Renewal13 cited

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