Page 13 - Azerbaijan State University of Economics

Prerna Ahuja, Meenu Gupta, Jinesh Jain, Kiran Sood, Luan Vardari: HR Analytics Research
Landscape (2003–2024): A Systematic, Bibliometric, and Content Analysis

Intellectual Structure
Content Analysis includes scientific plotting of the themes with the most frequently
used words by the authors. First, the thematic mapping was done through Biblioshiny
(R Studio) as shown in Figure 5. The matrix divided into four quadrants explains the
Motor themes (essential for the research area), Niche themes (developed studies),
Basic themes (common themes), and Emerging themes (newer themes) [Donthu N,
Kumar S, Mukherjee D, Pandey N, Lim WM. 2021].

Figure 5: Major themes
Source: Author’s findings

The studies developed by researchers focus on employment and HR metrics. The
themes essential for the domain include decision-making, information management,
competitive advantage, HR analytics and Artificial Intelligence. The common themes
researched upon by the scholars are human resource, ethics and productivity. The
emerging themes include forecasting, benchmarking, and algorithms.

Apart from this, the most frequently used words by the authors are also shown in
Figure 6. The most commonly used words by the authors are HR analytics, people
analytics and workforce analytics. The intellectual structure which emerges from these
themes has been utilised further for content analysis.

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