Trajectory classes of job performance: The role of self-efficacy and organizational tenure

Mariella Miraglia, Guido Alessandri, Laura Borgogni

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
6 Downloads (Pure)


Purpose – Previous literature has recognized the variability of job performance, calling attention to the inter-individual differences in performance change. Building on Murphy’s (1989) theoretical model of performance, the purpose of this paper is to verify the existence of two distinct classes of performance, reflecting stable and increasing trends, and to investigate which personal conditions prompt the inclusion of individuals in one class rather than the other.
Design/methodology/approach – Overall job performance was obtained from supervisory ratings for four consecutive years for 410 professionals of a large Italian company going through significant reorganization. Objective data were merged with employees’ organizational tenure and self-efficacy. Growth Mixture Modeling was used.
Findings – Two main groups were identified: the first one started at higher levels of performance and showed a stable trajectory over time (stable class); the second group started at lower levels and reported an increasing trajectory (increasing class). Employees’ with stronger efficacy beliefs and lower tenure were more likely to belong to the stable class.
Originality/value – Through a powerful longitudinal database, the nature, the structure and the inter-individual differences in job performance over time are clarified. The study extends Murphy’s (1989) model, showing how transition stages in job performance may occur also as a result of organizational transformation. Moreover, it demonstrates the essential role of self-efficacy in maintaining high performance levels over time.
Original languageEnglish
Pages (from-to)424-442
Number of pages19
JournalCareer Development International
Issue number4
Publication statusPublished - 2015


  • Organizational tenure
  • Self-efficacy
  • Job performance
  • Longitudinal
  • Latent Growth Mixture Modelling

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