The importance-performance analysis of lean human resource management themes

Mohammad Hossein Azadi, Mohammad Hakkak, Reza Sepahvand and Seyed Najmodin Mousavi

International Journal of Information and Decision Sciences, 2024, vol. 16, issue 4, 360-382

Abstract: Applying lean management to human resources (HR) talks about a technique that makes different organisation departments, particularly the human resources management (HRM), adhere to a set of executive policies and processes. This descriptive research of applied type was conducted on a statistical population including 23 senior managers working at the Social Security Organization (SSO) in Fars Province, Iran. In the qualitative phase of the study, semi-structured interviews were employed to collect the data, whose validity and reliability were endorsed using content validity ratio (CVR) and Cohen's kappa coefficient (κ), respectively. To analyse the qualitative findings, thematic analysis was also exercised. Upon examining the existing literature and the expert opinions, seven global themes, as well as 27 and 85 organising and basic themes were respectively identified. In the quantitative phase, a questionnaire was administered to collect the data. Afterwards, the themes obtained were investigated using the importance-performance analysis (IPA).

Keywords: human resource management; HRM; importance-performance analysis; IPA; fuzzy numbers; lean human resources; thematic analysis. (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=142639 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijidsc:v:16:y:2024:i:4:p:360-382

Access Statistics for this article

More articles in International Journal of Information and Decision Sciences from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().