Page 20 - Azerbaijan State University of Economics

THE JOURNAL OF ECONOMIC SCIENCES: THEORY AND PRACTICE, V.82, # 2, 2025, pp. 4-31

Researchers consistently highlight both the positive impact of HR analytics on
organisational outcomes and the challenges surrounding its adoption. To overcome such
challenges, organisations should implement transparent AI-driven tools for screening
the applications of candidates and ensure the fairness of such practices through regular
audits. Large firms with high-volume hiring can benefit from predictive models,
whereas smaller organisations may use streamlined integrated platforms depending on
their needs and resources. In performance management, data-informed dashboards
should be integrated to deliver real-time feedback, enabling targeted intervention and
timely performance insights for employees. Moreover, workforce planning can be
improved using HR analytics in scenario modelling and forecasting, with big enterprises
opting for comprehensive software and smaller firms adopting customised modular
tools. Additionally, considering the job requirement, organisations should adopt
analytics in benchmarking of incentives and developing skill development strategies.
Scholars have also raised concerns about the increased probability of potential misuse
of personal information. Therefore, organisations must adopt strong data governance
frameworks, establish ethics committees, and maintain transparency in data usage.

The bibliometric analysis conducted in this context has yielded significant findings. It
revealed a substantial growth in publications in this field over the period from 2003 to
2023, with European countries contributing the most to research in this area. Moreover,
the thematic analysis undertaken in this arena suggests that HR analytics is evolving from
traditional HR practices to AI-driven, strategic decision-making tools. However, issues
like ethics, predictive capabilities, and benchmarking need further investigation and
refinement for widespread adoption.

While the field of HR Analytics has witnessed significant advancements, there remain
ample opportunities for the research community to address existing gaps. First, there
is an urgent need to investigate the impact of the widespread use of advanced AI and
machine learning techniques in HR analytics, with a focus on enhancing predictive
capabilities and personalising HR interventions.

Moreover, future research studies may consider factors such as work-life balance, employee
stress levels, and job satisfaction to explore the use of HR analytics to improve employee
experience, well-being, and engagement. Third, scholars can also conduct longitudinal
studies to examine the long-term impact of HR analytics on organisational performance,
employee outcomes, and overall business success. Fourth, the impact of HR Analytics
across different organisational contexts, industries, and cultural settings may also be
empirically investigated to comprehend its generalizability and adaptability.

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