KEY FACTORS THAT INFLUENCE THE SUCCESSFUL IMPLEMENTATION OF HR ANALYTICS IN ORGANIZATIONS: A SYSTEMATIC REVIEW
Abstract
Purpose- In today's rapidly evolving business landscape, organizations are increasingly recognizing the significance of leveraging HR analytics to drive data-driven decision-making and enhance HR outcomes. However, the successful implementation of HR analytics hinges upon a careful consideration of various factors. This paper aims to explore and analyze the key factors that influence the successful implementation of HR analytics, drawing on a comprehensive literature review and expert insights.
Methodology- A systematic literature review is conducted to examine the previous published articles in the HR analytics domain. The Emerald database revealed 37 articles that passed the inclusion criteria and quality assessment.
Findings- The study identifies several critical factors that play a pivotal role in the successful implementation of HR analytics. Leadership support and organizational culture emerge as paramount drivers, as they foster a data-driven decision-making culture, emphasizing the value of evidence-based HR practices.
Conclusion- These factors facilitate the integration of analytics into HR processes and ensure the commitment necessary to overcome implementation challenges.
Keywords
HR analytics leadership support data quality data integration technology infrastructure ethical considerations.
References
- Aman-Ullah, A., Aziz, A., Ibrahim, H., Mehmood, W., & Aman-Ullah, A. (2023). The role of compensation in shaping employee’s behaviour: a mediation study through job satisfaction during the Covid-19 pandemic. Revista de Gestão, 30(2), 221-236.
- Babac, M. B. (2022). Emotion analysis of user reactions to online news. Information discovery and delivery, 51(2), 179-193.
- Calza, F., Pagliuca, M., Risitano, M., & Sorrentino, A. (2020). Testing moderating effects on the relationships among on-board cruise environment, satisfaction, perceived value and behavioral intentions. International Journal of Contemporary Hospitality Management, 32(2), 934-952.
- D’Orazio, M., Bernardini, G., & Di Giuseppe, E. (2023). Predict the priority of end-users’ maintenance requests and the required technical staff through LSTM and Bi-LSTM recurrent neural networks. Facilities, 41(15/16), 38-51.
- Eze, E., Gleasure, R., & Heavin, C. (2022). Worlds apart: a socio-material exploration of mHealth in rural areas of developing countries. Information Technology & People, 35(8), 99-141.
- Falletta, S. V., & Combs, W. L. (2020). The HR analytics cycle: a seven-step process for building evidence-based and ethical HR analytics capabilities. Journal of Work-Applied Management, 13(1), 51-68.
- Ferreira, C., Robertson, J., Chohan, R., Pitt, L., & Foster, T. (2023). The writing is on the wall: predicting customers' evaluation of customer-firm interactions using computerized text analysis. Journal of Service Theory and Practice, 33(2), 309-327.
- Gulati, S. (2021). Social and sustainable: exploring social media use for promoting sustainable behaviour and demand amongst Indian tourists. International Hospitality Review, 36(2), 373-393.
- Lappeman, J., Franco, M., Warner, V., & Sierra-Rubia, L. (2022). What social media sentiment tells us about why customers churn. Journal of Consumer Marketing, 39(5), 385-403.
- Lim, C., Kim, M. J., Kim, K. H., Kim, K. J., & Maglio, P. P. (2018). Using data to advance service: managerial issues and theoretical implications from action research. Journal of Service Theory and Practice, 28(1), 99-128.
- McCartney, S., & Fu, N. (2022). Bridging the gap: why, how and when HR analytics can impact organizational performance. Management Decision, 60(13), 25-47.
- Nourallah, M., Öhman, P., & Amin, M. (2022). No trust, no use: how young retail investors build initial trust in financial robo-advisors. Journal of Financial Reporting and Accounting, 21(1), 60-82.
- Tan, C. J., Lim, T. Y., Bong, C. W., & Liew, T. K. (2017). A multi-objective evolutionary algorithm-based soft computing model for educational data mining: A distance learning experience. Asian Association of Open Universities Journal, 12(1), 106-123.
- Wong, B. T. M. (2017). Learning analytics in higher education: an analysis of case studies. Asian Association of Open Universities Journal, 12(1), 21-40.
- Wu, Q., Zhan, C., Wang, F. L., Wang, S., & Tang, Z. (2016). Clustering of online learning resources via minimum spanning tree. Asian Association of Open Universities Journal, 11(2), 197-215.
Details
| Primary Language | English |
|---|---|
| Subjects | Labor Economics, Microeconomics (Other), Business Administration |
| Journal Section | Articles |
| Authors | |
| Publication Date | December 31, 2024 |
| Submission Date | October 17, 2024 |
| Acceptance Date | December 2, 2024 |
| Published in Issue | Year 2024 Volume: 11 Issue: 2 |
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Research Journal of Business and Management (RJBM) is a scientific, academic, double blind peer-reviewed, semi-annually and open-access online journal. The journal publishes 2 issues a year. The issuing months are June and December. The publication language of the Journal is English. RJBM aims to provide a research source for all practitioners, policy makers, professionals and researchers working in all related areas of business, management and organizations. The editor in chief of RJBM invites all manuscripts that cover theoretical and/or applied researches on topics related to the interest areas of the Journal. RJBM publishes academic research studies only. RJBM charges no submission or publication fee.
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