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Artificial Intelligence Models and Employee Lifecycle Management: A Systematic Literature Review
12 references·3 citing·53 second hop
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(2005)The Future of Management (2008)Human resource management and performance: still searching for some answers (2011)Analyzing Employee Attrition Using Explainable AI for Strategic HR Decision-Making (2023)The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration (2009)Deep learning with long short-term memory networks for financial market predictions (2017)A Systematic Survey of Driving Fatigue Monitoring (2022)Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020–2022 (2023)Machine learning in business and finance: a literature review and research opportunities (2024)A Meta-Analysis of Antecedents and Correlates of Employee Turnover: Update, Moderator Tests, and Research Implications for the Next Millennium (2000)What really matters in a job? Hedonic measurement using quit data (2001)Machine learning and role of artificial intelligence in optimizing work performance and employee behavior (2021)Predicting and explaining employee turnover intention (2022)Comparison of PubMed, Scopus, Web of Science, and Google Scholar: strengths and weaknesses (2007)The journal coverage of Web of Science and Scopus: a comparative analysis (2015)Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies (2020)Large-scale comparison of bibliographic data sources: Scopus, Web of Science, Dimensions, Crossref, and Microsoft Academic (2021)Fuzzy-set qualitative comparative analysis (fsQCA) in business and management research: A contemporary overview (2022)Guidelines for Bibliometric‐Systematic Literature Reviews: 10 steps to combine analysis, synthesis and theory development (2024)A Dynamic Theory of Organizational Knowledge Creation (1994)Business Model Innovation: Opportunities and Barriers (2009)Business Intelligence and Analytics: From Big Data to Big Impact (2012)Impact of artificial intelligence assimilation on firm performance: The mediating effects of organizational agility and customer agility (2022)Evaluation of data analytics-oriented business intelligence technology effectiveness: an enterprise-level analysis (2023)Applications of generative AI and future organizational performance: The mediating role of explorative and exploitative innovation and the moderating role of ethical dilemmas and environmental dynamism (2024)
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References

  • 2010Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement12,147 cited
  • 2021The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis2,085 cited
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  • 2001A Taxonomy of Business Process Modeling and Information Systems Modeling Techniques328 cited
  • 2020Predicting Employee Attrition Using Machine Learning Techniques280 cited
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  • 2018Employee Turnover Prediction with Machine Learning: A Reliable Approach170 cited
  • 2020Explaining and predicting employees’ attrition: a machine learning approach101 cited
  • 2019Predictive Modelling of Employee Turnover in Indian IT Industry Using Machine Learning Techniques83 cited
  • 2018Early Prediction of Employee Attrition using Data Mining Techniques82 cited
  • 2012I-Competere: Using applied intelligence in search of competency gaps in software project managers48 cited
  • 2022Predicting HR Professionals’ Adoption of HR Analytics: An Extension of UTAUT Model32 cited

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  • 2025Predictive Analytics in Human Resources Management: Evaluating AIHR’s Role in Talent Retention39 cited

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2023
Sustainable Development of Employee Lifecycle Management in the Age of Global Challenges: Evidence from China, Russia, and Indonesia
30 cited
  • 2024Intercultural Communicative Competence in Virtual and Face-to-Face Teamwork: A Quantitative Analysis of Culturally Diverse Teams13 cited