IDEAS home Printed from https://ideas.repec.org/h/spr/lnichp/978-3-031-66801-2_25.html
   My bibliography  Save this book chapter

Big and Small Data in Corporate Human Resource Management

In: The Future of Industry

Author

Listed:
  • Ainura Kocherbaeva

    (Kyrgyz Russian Slavic University named after First President of Russia B.N. Yeltsin)

  • Ainur Osmonova

    (Scientific Research University Kyrgyz Economic University named after Musa Ryskulbekov (SRU KEU))

  • Guzalbegim Rakhimova

    (National Research University “Tashkent Institute of Irrigation and Agricultural Mechanization Engineers” (TIIAME National Research University))

  • Evgeny Kuzmin

    (Institute of Economics of the Ural Branch of the Russian Academy of Sciences)

Abstract

The authors explore the influence of Big Data and Small Data concepts on human resource management. They emphasize that, despite a widespread use of Big Data in the context of digitalization, Small Data have significant potential as they make it possible to do a more detailed analysis and achieve goals in time. The main objective of the research is to clarify how Big and Small Data integration might be applied to achieve more efficient human resource management, what opportunities they provide and what risks may accompany this process. The authors reviewed the cases reported by leading companies that have successfully integrated data analytics into their HR management strategies and demonstrated extensive prospects in human capital development. The paper includes details on main characteristics and applications of Big and Small Data in human resource management. It also includes a comparison of these concepts by a number of parameters to understand their application specifics. The research is aimed at a deeper theoretical and practical understanding of data applications in human resource management. It highlights strategic importance of Big Data and operational importance of Small Data in this field. The authors show how integration of Big Data and Small Data can contribute to the development of more efficient strategies in human capital management and how this helps enterprises adjust to ever-changing requirements in the labour market, contributing to better sustainability of enterprises.

Suggested Citation

  • Ainura Kocherbaeva & Ainur Osmonova & Guzalbegim Rakhimova & Evgeny Kuzmin, 2024. "Big and Small Data in Corporate Human Resource Management," Lecture Notes in Information Systems and Organization, in: Andrea Appolloni & Vikas Kumar & Evgeny Kuzmin & Victoria Akberdina (ed.), The Future of Industry, pages 377-394, Springer.
  • Handle: RePEc:spr:lnichp:978-3-031-66801-2_25
    DOI: 10.1007/978-3-031-66801-2_25
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:lnichp:978-3-031-66801-2_25. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.