Why do people want to work in semi-autonomous agencies? Exploring latent classes and the role of structural and individual factors

  • Rutger Blom*
  • , Peter Kruyen
  • , Beatrice Van der Heijden
  • , Sandra van Thiel
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Purpose – 

Much attention has been paid to identify why people want to work in government vs business. However, existing research has largely ignored job choices in semi-autonomous agencies operating in between government and business. This study aimed to explore job choices in these agencies, by examining (1) people’s evaluations of work attributes in relation to their decision to work for an agency and (2) how structural and individual factors are related to these evaluations. 

Design/methodology/approach – 

Based on survey data from 422 employees who started working at an agency, we performed latent class analysis to identify clusters of employees based on how they evaluated work attributes. Furthermore, we tested the degree to which specific structural and individual factors are related to cluster membership of employees using multinomial logistic regression analysis. 

Findings – 

The results revealed three employee clusters based on which work attributes were important for their choice to work for an agency: “job-dominant identifiers”, “job and organization identifiers” and “non-identifiers”. Cluster membership was significantly related to three structural factors (the legal independence of the agency, the perceived societal impact potential of the job and the pay level) and one individual factor (the level of public service motivation). Thus, groups of people differ in their reasons why they choose to work in agencies, and their job choice is influenced by several structural and individual determinants. 

Originality/value – 

This study contributes to public administration literature on job choices by focusing on agencies that operate in between government and business, entities that have received little attention while being of great economic and societal importance.

Original languageEnglish
Number of pages23
JournalInternational Journal of Public Sector Management
DOIs
Publication statusPublished - 4 Nov 2025

Bibliographical note

Publisher Copyright:
© 2025 Emerald Publishing Limited

Research programs

  • ESSB PA

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