A latent profile analysis of work passion: structure, antecedent, and outcomes

Jingjing Li, Jian Zhang, Bo Shao, Chunxiao Chen

Research output: Contribution to journalArticleResearchpeer-review

4 Citations (Scopus)


Purpose: Previous research draws on the dualistic model of passion (harmonious and obsessive passion) overlooks how the different two types of passion interact within individuals using a variable-centered approach. The purpose of this paper is to identify work passion profiles and their antecedent and consequences adopting a person-centered approach, and to explain inconsistences in previous studies. Design/methodology/approach: This paper conducts three studies (n=2,749 in total) using a latent profile analysis. Study 1 identifies three work passion profiles, namely, dual passion, pro harmonious passion and pro obsessive passion; study 2 examines dialectical thinking as an antecedent to work passion profile membership; study 3 examines how each profile relates to work performance and well-being. Findings: This paper finds that the participants with a dual passion profile showed higher task performance and subjective well-being than the participants with the other two profiles; the participants with a pro obsessive passion profile were higher in task performance, interpersonal performance and psychological well-being than the participants with a pro harmonious profile. Originality/value: This paper is the first that uses a latent profile analysis approach to examining work passion configurations. It provides a unique perspective to investigate how different types of passion configure and interact within individuals; it explores an antecedent (i.e. dialectical thinking) and outcomes (i.e. performance and well-being) of the three work passion profiles.

Original languageEnglish
Pages (from-to)846-863
Number of pages18
JournalPersonnel Review
Issue number3
Publication statusPublished - 2019


  • Human resource management
  • Management development
  • Organizational behaviour
  • Quantitative
  • Work performance

Cite this