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Modeling challenges to implement HR analytics in IT sector using ISM

Author

Listed:
  • Aiman Zubair

    (Istanbul Arerl University / Turkiye)

  • Aylin Erdogdu

    (Istanbul Arel University / Turkiye)

Abstract

This research paper delves into the intricate landscape of modeling challenges that hinder the integration of Human Resources (HR) analytics within the Information Technology (IT) sector. Employing a qualitative research methodology, the study conducts structured interviews to unravel the nuanced layers of impediments faced by organizations aspiring to harness the power of HR analytics. The research primarily employs Interpretive Structural Modeling (ISM) to map the interdependencies among these challenges, offering a comprehensive understanding of their hierarchical nature. The findings of this study contribute significantly to the existing body of knowledge by identifying key challenges ranging from data privacy concerns to the integration of analytics into HR decision-making processes. By illuminating the intricacies of these challenges, the research aims to guide the creation of strategic frameworks capable of overcoming them. Ultimately, this study seeks to pave the way for the effective implementation of HR analytics in the IT sector, fostering a culture where data-driven insights drive organizational decisions and enhance workforce management. Keywords: HR Analytics, Challenges of Implementing HR analytics, HR in IT sector, ISM technique.

Suggested Citation

  • Aiman Zubair & Aylin Erdogdu, 1024. "Modeling challenges to implement HR analytics in IT sector using ISM," JOURNAL OF LIFE ECONOMICS, Holistence Publications, vol. 11(2), pages 49-60.
    • Handle: RePEc:jle:journl:jlecon2407
    DOI: 10.15637/jlecon.2407
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