Subordinate-to-supervisor relational identification: A meta-analytic review.


Journal

The Journal of applied psychology
ISSN: 1939-1854
Titre abrégé: J Appl Psychol
Pays: United States
ID NLM: 0222526

Informations de publication

Date de publication:
15 Feb 2024
Historique:
medline: 15 2 2024
pubmed: 15 2 2024
entrez: 15 2 2024
Statut: aheadofprint

Résumé

Although subordinate-to-supervisor relational identification (RI) has gained significant scholarly attention in organizational research, an understanding of its nomological network is incomplete. There have also been recurring discussions about its distinctions with another more extensively researched relational construct-leader-member exchange (LMX). In this meta-analysis, we expand Sluss and Ashforth's (2007) typology, going beyond the influence of the supervisor, to systematically study the antecedents and consequences of RI and its comparison with LMX. Meta-analytic results based on 157 independent samples demonstrate that positive leader behaviors that span role-based and person-based identities (e.g., transformational leadership, supervisor humility) are important antecedents of subordinate-to-supervisor RI, with effects contingent on subordinates' national culture (i.e., collectivism and power distance). Although less hypothesized, relational and organizational contexts as well as subordinate characteristics are also important antecedents of subordinate-to-supervisor RI. The results further show that RI relates to important subordinate behaviors and attitudes. Finally, we test how RI and LMX have differing effects across these important subordinate attitudes and behaviors. We conclude with suggestions to enhance our understanding of RI. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Identifiants

pubmed: 38358682
pii: 2024-53559-001
doi: 10.1037/apl0001169
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Yufei Zhong (Y)

Scheller College of Business, Georgia Institute of Technology.

David M Sluss (DM)

Department of Management, ESSEC Business School.

Katie L Badura (KL)

Scheller College of Business, Georgia Institute of Technology.

Classifications MeSH