大数据
数据科学
独创性
计算机科学
分析
商业分析
功能(生物学)
数据分析
人才管理
知识管理
数字化转型
人力资源
商业模式
业务
数据挖掘
万维网
管理
营销
业务分析
经济
生物
法学
进化生物学
政治学
创造力
作者
Arnold Saputra,Gunawan Wang,Zuopeng Zhang,Abhishek Behl
出处
期刊:The Tqm Journal
[Emerald Publishing Limited]
日期:2021-09-20
卷期号:34 (1): 178-198
被引量:35
标识
DOI:10.1108/tqm-03-2021-0089
摘要
Purpose The era of work 4.0 demands organizations to expedite their digital transformation to sustain their competitive advantage in the market. This paper aims to help the human resource (HR) department digitize and automate their analytical processes based on a big-data-analytics framework. Design/methodology/approach The methodology applied in this paper is based on a case study and experimental analysis. The research was conducted in a specific industry and focused on solving talent analysis problems. Findings This research conducts digital talent analysis using data mining tools with big data. The talent analysis based on the proposed framework for developing and transforming the HR department is readily implementable. The results obtained from this talent analysis using the big-data-analytics framework offer many opportunities in growing and advancing a company's talents that are not yet realized. Practical implications Big data allows HR to perform analysis and predictions, making more intelligent and accurate decisions. The application of big data analytics in an HR department has a significant impact on talent management. Originality/value This research contributes to the literature by proposing a formal big-data-analytics framework for HR and demonstrating its applicability with real-world case analysis. The findings help organizations develop a talent analytics function to solve future leaders' business challenges.
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