Proceedings of the 1st International Conference on Business, Economics, Management Science (BEMS 2019)

Review and Prospect of the Combination of Human Resource Management and Big Data in Enterprises

Authors
Wei Tang, Xiaoyu Liu
Corresponding Author
Wei Tang
Available Online May 2019.
DOI
https://doi.org/10.2991/bems-19.2019.54How to use a DOI?
Keywords
big data, human resources management, prediction and optimization, work experience data.
Abstract
The rapid development of big data has successfully served all walks of life. In the aspect of human resources management, capacity data, potential data and so on are complex and complex. They are only based on artificial assumptions and have large errors. With the support of big data analysis, we can not only plan the recruitment of talents to avoid the mismatch between the position and the supply of talents, but also make reasonable forecast and arrangement for the needs of departments and employees. In addition, we can optimize and improve the job evaluation and reward system according to the data of employees and departments. At the same time, this paper also puts forward the prospects of big data in the direction of human resources, including using previous experience data to plan the career of new recruits, or using previous work experience data to predict the potential of new recruits.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
1st International Conference on Business, Economics, Management Science (BEMS 2019)
Part of series
Advances in Economics, Business and Management Research
Publication Date
May 2019
ISBN
978-94-6252-720-1
ISSN
2352-5428
DOI
https://doi.org/10.2991/bems-19.2019.54How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Wei Tang
AU  - Xiaoyu Liu
PY  - 2019/05
DA  - 2019/05
TI  - Review and Prospect of the Combination of Human Resource Management and Big Data in Enterprises
BT  - 1st International Conference on Business, Economics, Management Science (BEMS 2019)
PB  - Atlantis Press
SN  - 2352-5428
UR  - https://doi.org/10.2991/bems-19.2019.54
DO  - https://doi.org/10.2991/bems-19.2019.54
ID  - Tang2019/05
ER  -