Author
Abstract
Human resources are considered a strategic asset for organizations and play a key role in the execution of business processes. Hence, organizations should provide an environment that enables them to operate in an effective and efficient manner. To shape such an environment, an improved understanding and monitoring of the real-life involvement of human resources in processes and the teams in which they operate would be beneficial. Using event data from information systems, process mining can play a role in this respect. Over the years, several human resource mining methods have been developed, i.e., process mining methods that convey insights related to the human resources in a process using an event log. However, there is a lack of a holistic understanding of the breadth of these methods. Against this backdrop, the paper uses a systematic literature review to develop a framework providing an overview of human resource mining use cases. These use cases are classified according to two dimensions: the level of analysis (individual versus multiple human resources) and the focus of analysis (organization-focused versus human-focused). The authors illustrate the versatility of process mining for providing insights into human resources and highlight opportunities for further enriching and extending this area of research to analyze, among other things, how teams of resources can perform better.
Suggested Citation
Niels Martin & Iris Beerepoot, 2025.
"Unveiling Use Cases for Human Resource Mining,"
Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 67(4), pages 531-550, August.
Handle:
RePEc:spr:binfse:v:67:y:2025:i:4:d:10.1007_s12599-024-00894-3
DOI: 10.1007/s12599-024-00894-3
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
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:binfse:v:67:y:2025:i:4:d:10.1007_s12599-024-00894-3. 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.