Study on the application of data visualization technology in human resource management and employee turnover prediction

[1] Guest, D. E. (2017). Human resource management and employee well‐being: towards a new analytic framework. Human Resource Management Journal, 27(1), 22-38. Search in Google Scholar

[2] A, A. K., Josune Sáenz b, & B, N. A. (2017). Knowledge-based human resource management practices, intellectual capital and innovation. Journal of Business Research, 81, 11-20. Search in Google Scholar

[3] Karen, Becker, Michelle, & Smidt. (2016). A risk perspective on human resource management: a review and directions for future research. Human Resource Management Review. Search in Google Scholar

[4] Al Ariss, A., & Sidani, Y. (2016). Comparative international human resource management: future research directions. Human Resource Management Review, 352-358. Search in Google Scholar

[5] Madariaga, R., Oller, R., & Martori, J. C. (2018). Discrete choice and survival models in employee turnover analysis. Employee Relations, 40(2), 381-395. Search in Google Scholar

[6] Javed, S., & Azhar, A. (2017). Forecasting employee turnover for human resource based on time series analysis. International Journal Of Economics Research, 14(16), 445-456. Search in Google Scholar

[7] Poornappriya, T. S., & Gopinath, R. (2021). Employee attrition in human resource using machine learning techniques. Webology (ISSN: 1735-188X), 18(6). Search in Google Scholar

[8] Ponnuru, S., Merugumala, G., Padigala, S., Vanga, R., & Kantapalli, B. (2020). Employee attrition prediction using logistic regression. Int. J. Res. Appl. Sci. Eng. Technol, 8(5), 2871-2875. Search in Google Scholar

[9] Ozolina-Ozola, I. (2016). An exploratory study of the role of human resource management in models of employee turnover. International Journal of Learning and Change, 8(3-4), 231-244. Search in Google Scholar

[10] Voegtlin, C., & Greenwood, M. (2016). Corporate social responsibility and human resource management: a systematic review and conceptual analysis. Human Resource Management Review, 26(3), 181-197. Search in Google Scholar

[11] Sandra, Rothenberg, Clyde, Eiríkur, Hull, & Zhi, et al. (2016). The impact of human resource management on corporate social performance strengths and concerns. Business & Society. Search in Google Scholar

[12] Lee, H. W., Pak, J., Kim, S., & Li, L. Z. (2016). Effects of human resource management systems on employee proactivity and group innovation. Journal of Management, 014920631668002. Search in Google Scholar

[13] Kehoe, R. R., & Collins, C. J. (2017). Human resource management and unit performance in knowledge-intensive work. Journal of Applied Psychology, 102(8). Search in Google Scholar

[14] Tung, & Rosalie, L. (2016). New perspectives on human resource management in a global context. Journal of World Business, 51(1), 142-152. Search in Google Scholar

[15] Gao, X., Wen, J., & Zhang, C. (2019). An improved random forest algorithm for predicting employee turnover. Mathematical Problems in Engineering, 2019. Search in Google Scholar

[16] Mohammed, A. M., Lai, Y., Daskalaki, M., & Saridakis, G. (2016). Employee turnover as a cost factor of organisations. Biotechniques, 60(5), 515-522. Search in Google Scholar

[17] Wild Ali, A. B. (2021). Prediction of employee turn over using random forest classifier with intensive optimized pca algorithm. Wireless Personal Communications, 119(4), 3365-3382. Search in Google Scholar

[18] Sumathi, K., Balakrishnan, D., Naveen, V., Hariharan, P., & Rahul Iniyan, M. (2021). Talent Flow Employee Analysis Based Turnover Prediction on Survival Analysis. Annals of the Romanian Society for Cell Biology, 3844-3857. Search in Google Scholar

[19] Zhu, X., Seaver, W., Sawhney, R., Ji, S., Holt, B., Sanil, G. B., & Upreti, G. (2017). Employee turnover forecasting for human resource management based on time series analysis. Journal of Applied Statistics, 44(8), 1421-1440. Search in Google Scholar

[20] Li, Q., Lourie, B., Nekrasov, A., & Shevlin, T. (2022). Employee turnover and firm performance: Large-sample archival evidence. Management Science, 68(8), 5667-5683. Search in Google Scholar

[21] Torabipour, S. M. R., Taghvaei, R., & Hamidi, K. (2022). Employee Separation Management (ESM) Model For Iranian Public Organizations. Quarterly Journal of Public Organizations Management, 10(2), 155-174. Search in Google Scholar