International Journal of Computer Science & Network Security

국제컴퓨터통신보호논문지학회 (International Journal of Computer Science & Network Security)
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A Bibliometric Analysis Data Visualization in Human Resource Management

  • 투고 : 2023.11.05
  • 발행 : 2023.11.30
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초록

As the old saying goes "a picture is worth a thousand words" data visualization is essential in almost every industry. Companies make Data-driven decisions and gain insights from visual data. However, there is a need to investigate the role of data visualization in human resource management. This review aims to highlight the power of data visualization in the field of human resources. In addition, visualize the latest trends in the research area of human resource and data visualization by conducting a bibliometric analysis. The study adopted a literature review on recent publications from 2017 to 2022 to address research questions.

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참고문헌

  1. Caughlin, D.E. and Bauer, T.N. (2019), "Data Visualizations and Human Resource Management: The State of Science and Practice", Buckley, M.R., Wheeler, A.R., Baur, J.E.and Halbesleben, J.R.B. (Ed.) Research in Personnel and Human Resources Management(Research in Personnel and Human Resources Management, Vol. 37), Emerald Publishing Limited, Bingley, pp. 89-132.
  2. Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact?. Scientometrics, 105(3), 1809-1831.  https://doi.org/10.1007/s11192-015-1645-z
  3. Friendly, M. (2008). A brief history of data visualization. In Handbook of data visualization (pp. 15-56). Springer, Berlin, Heidelberg. 
  4. Khan, S. (2021). Visual Data Analysis and Simulation Prediction for COVID-19 in Saudi Arabia Using SEIR Prediction Model. International Journal of Online & Biomedical Engineering, 17(8). 
  5. Y. Zhang and Y. Luo, "Data mining technology based on the visualization of enterprise human resources information data research," 2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), 2020, pp. 2489-2493, doi: 10.1109/ICMCCE51767.2020.00538. 
  6. Gong, T., Jiang, Y., Saldivia, L. E., & Agard, C. (2021). Using Sankey diagrams to visualize drag and drop action sequences in technology-enhanced items. Behavior Research Methods, 1-16. 
  7. Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact?. Scientometrics, 105(3), 1809-1831.  https://doi.org/10.1007/s11192-015-1645-z
  8. Wang, X., Zhang, J., Yao, K., & Qin, J. (2021). ResumeVis Interactive Visualization of Resumes Based on Multi-Source Data. International Journal of Web Services Research (IJWSR), 18(2), 40-53. http://doi.org.sdl.idm.oclc.org/10.4018/IJWSR.202104010 
  9. Filipov, V., Arleo, A., Federico, P., & Miksch, S. (2019, June). CV3: Visual exploration, assessment, and comparison of CVs. In Computer Graphics Forum (Vol. 38, No. 3, pp. 107-118).  https://doi.org/10.1111/cgf.13675
  10. Alfaifi, Asma Abdulsalam; Khan, Shakir Gayour (2022) "Utilizing Data from Twitter to Explore the UX of "Madrasati" as a Saudi e-Learning Platform Compelled by the Pandemic", Arab Gulf Journal of Scientific Research, Vol. 39 Issue 3, p200-208. https://doi.org/10.51758/AGJSR-03-2021-0025 
  11. Setiawan, I., Suprihanto, S., Nugraha, A. C., & Hutahaean, J. (2020, April). HR analytics: Employee attrition analysis using logistic regression. In IOP Conference Series: Materials Science and Engineering (Vol. 830, No. 3, p. 032001). IOP Publishing. 
  12. Lalic, D., Boskovic, D., Milic, B., Havzi, S., & Spajic, J. (2020, August). Virtual and Augmented Reality as a Digital Support to HR Systems in Production Management. In IFIP International Conference on Advances in Production Management Systems(pp. 469-478). Springer, Cham. 
  13. P. Chertchom, "Employee assessment using data mining techniques: modeling individual capability to improve the competency of companies," 2018 International Conference on Information Technology (InCIT), 2018, pp. 1-5, doi: 10.23919/INCIT.2018.8584861 
  14. M. Ameer, S. P. Rahul and S. Manne, "Human Resource Analytics using Power Bi Visualization Tool," 2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS), 2020, pp. 1184-1189, doi: 10.1109/ICICCS48265.2020.9120897. 
  15. M. AlAjmi, S. Khan (2015) PART OF AJAX AND OPENAJAX IN CUTTING EDGE RICH APPLICATION ADVANCEMENT FOR E-LEARNING, INTED2015 Proceedings, pp. 4058-4063. 
  16. Ozcan, S., Sakar, C. O., & Suloglu, M. (2020). Human resources mining for examination of R&D progress and requirements. IEEE Transactions on Engineering Management. 
  17. Mohapatra, M., & Sahu, P. (2017). Optimizing the recruitment funnel in an ITES company: An analytics approach. Procedia computer science, 122, 706-714.  https://doi.org/10.1016/j.procs.2017.11.427
  18. Mohammed, D., & Quddus, A. (2019). HR analytics: a modern tool in HR for predictive decision making. Journal of Management, 6(3). 
  19. Setiawan, I., Suprihanto, S., Nugraha, A. C., & Hutahaean, J. (2020, April). HR analytics: Employee attrition analysis using logistic regression. In IOP Conference Series: Materials Science and Engineering (Vol. 830, No. 3, p. 032001). IOP Publishing. 
  20. Nikolaidis, P.; Ismail, M.; Shuib, L.; Khan, S.; Dhiman, G. Predicting Student Attrition in Higher Education through the Determinants of Learning Progress: A Structural Equation Modelling Approach. Sustainability 2022, 14, 13584. https://doi.org/10.3390/su142013584 
  21. Zhao, Y., Hryniewicki, M. K., Cheng, F., Fu, B., & Zhu, X. (2018, September). Employee turnover prediction with machine learning: A reliable approach. In Proceedings of SAI intelligent systems conference (pp. 737-758). Springer, Cham. 
  22. Raguvir, S., & Babu, S. (2020). Enhance employee productivity using Talent analytics and Visualization. 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), 2020 International Conference On, 1-5. https://doiorg.sdl.idm.oclc.org/10.1109/ICDABI51230.2020.9325682 
  23. S. Khan, "Data Visualization to Explore the Countries Dataset for Pattern Creation", Int. J. Onl. Eng., vol. 17, no. 13, pp. pp. 4-19, Dec. 2021.  https://doi.org/10.3991/ijoe.v17i13.20167
  24. Sato, Y., Kobayashi, N., & Shirasaka, S. (2019, July). A Proposal of HR System's Visualization Based on Harvard Model, Life Cycle, and Organization Strategy and Management Type. In 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI) (pp. 740-745). IEEE 
  25. Murthy, M. V. S., Kinange, U., & Shaikh, A. (2017). Influence of HR Analytics Representation on Awareness, Technology and Decision Making: A Study of Medium and Large Organizations. Reviews of literatur 
  26. Lalic, D., Boskovic, D., Milic, B., Havzi, S., & Spajic, J. (2020, August). Virtual and Augmented Reality as a Digital Support to HR Systems in Production Management. In IFIP International Conference on Advances in Production Management Systems(pp. 469-478). Springer, Cham. 
  27. Khan, Shakir. "Artificial Intelligence Virtual Assistants (Chatbots) are Innovative Investigators." International Journal of Computer Science and Network Security 20.2 (2020): 93-98.  https://doi.org/10.22937/IJCSNS.2020.20.02.13
  28. S. Khan (2017) AN INTER-OPERABILITY AND OPEN SOURCE PROBLEM FOR INTEGRATED LIBRARY SYSTEM (KOHA) AND DIGITAL LIBRARY (DSPACE) AS SINGLE SYSTEM, EDULEARN17 Proceedings, pp. 7041-7047. https://dx.doi.org/10.21125/edulearn.2017.2650 
  29. Shakir Khan (2018) "Modern Internet of Things as a Challenge for Higher Education", IJCSNS International Journal of Computer Science and Network Security, Vol. 18 No. 12, pp. 34-41. 
  30. S. Khan and S. Alqahtani, "Big Data Application and its Impact on Education", Int. J. Emerg. Technol. Learn., vol. 15, no. 17, pp. 36-46, Sep. 2020. http://dx.doi.org/10.3991/ijet.v15i17.14459 
  31. Sinar, E. F. (2018). Data Visualization: Get Visual to Drive HR's Impact and Influence. Society for Human Resource Management (SHRM)-Society for Industrial- Organizational Psychology (SIOP) Science of HR White Paper Series