Data-driven recruitment and HR analytics: A Review of strategic applications in talent acquisition

Authors

  • Chetna Raikwar Dr. Hari Singh Gour Vishwavidyalaya, India
  • Suneet Walia Dept. Of Business Management

Keywords:

Data-driven recruitment, Human resource management, HR analytics, Algorithmic fairness, Workforce diversity, Resource-Based View

Abstract

This study presents a systematic review of data-driven recruitment (DDR) literature published between 2015 and 2025. Based on 26 peer-reviewed studies, the review uses the PRISMA framework to analyze methodological patterns, thematic trends, and theoretical contributions. The results show a shift from early efficiency-focused research to more recent concerns about algorithmic fairness, diversity, and governance. By situating DDR within the Resource-Based View, Human Capital Theory, organizational justice perspectives, and socio-technical systems theory, the review highlights how recruitment analytics influence both organizational performance and ethical considerations. Key research gaps include the limited number of studies in emerging economies, methodological diversity, and inadequate accountability mechanisms. The paper provides theoretical, managerial, and policy implications, proposing a more integrated framework for balancing efficiency with fairness in recruitment analytics and advancing the HRM literature.

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Published

2026-04-16

How to Cite

Raikwar, C., & Walia, S. (2026). Data-driven recruitment and HR analytics: A Review of strategic applications in talent acquisition. International Journal of Economic Perspectives, 20(4), 387–405. Retrieved from https://www.ijeponline.org/index.php/journal/article/view/1281

Issue

Vol. 20 No. 4 (2026)

Section

Peer Review Articles
Copyright & Licensing

Copyright (c) 2026 Chetna Raikwar

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