Multilevel Latent Polynomial Regression for Modeling (In)Congruence Across Organizational Groups: The Case of Organizational Culture Research. (January 2016)

• Record Type: Journal Article
• Authors: Zyphur, Michael J.; Zammuto, Raymond F.; Zhang, Zhen
• Is Part Of: Organizational research methods. Volume 19:Number 1(2016:Jan.)
• Page Start: 53
• Page End: 79
• Publication Date: 2016-01
• Subjects: organizational culture -- congruence -- multilevel latent polynomial regression -- multilevel structural equation modeling -- multilevel moderation; Organization -- Research -- Methodology -- Periodicals; Organizational sociology -- Research -- Methodology -- Periodicals; Management -- Research -- Methodology -- Periodicals; 302.350721
• DOI: 10.1177/1094428115588570
• Languages: English
• ISSNs: 1094-4281

Abstract

This article addresses (in)congruence across different kinds of organizational respondents or "organizational groups"—such as managers versus non-managers or women versus men—and the effects of congruence on organizational outcomes. We introduce a novel multilevel latent polynomial regression model (MLPM) that treats standings of organizational groups as latent "random intercepts" at the organization level while subjecting these to latent interactions that enable response surface modeling to test congruence hypotheses. We focus on the case of organizational culture research, which usually samples managers and excludes non-managers. Reanalyzing data from 67 hospitals with 6, 731 managers and non-managers, we find that non-managers perceive their organizations' cultures as less humanistic and innovative and more controlling than managers, and we find that less congruence between managers and non-managers in these perceptions is associated with lower levels of quality improvement in organizations. Our results call into question the validity of findings from organizational culture and other research that tends to sample one organizational group to the exclusion of others. We discuss our findings and the MLPM, which can be extended to estimate latent interactions for tests of multilevel moderation/interactions.