Modeling challenges to implement HR analytics in IT sector using ISM

Aiman Zubair () and Aylin Erdogdu ()
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Aiman Zubair: Istanbul Arerl University / Turkiye
Aylin Erdogdu: Istanbul Arel University / Turkiye

JOURNAL OF LIFE ECONOMICS, 1024, vol. 11, issue 2, 49-60

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.

Keywords: Human Resources Management; Information Technology; Interpretive Structural Modeling (search for similar items in EconPapers)
Date: 1024
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Persistent link: https://EconPapers.repec.org/RePEc:jle:journl:jlecon2407

DOI: 10.15637/jlecon.2407

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