A Profile of Profiles: A Meta-Analysis of the Nomological Net of Commitment Profiles Adam H. Kabins Hay Group/Korn Ferry, Dallas, Texas Xiaohong Xu and Mindy E. Bergman Texas A&M University Christopher M. Berry Indiana University Victor L. Willson Texas A&M University Although the majority of empirical commitment research has adopted a variable-centered approach, the person-centered or profiles approach is gaining traction. One challenge in the commitment profiles literature is that names are attached to profiles based on the within-study comparison among profiles and their relative levels and shapes. Thus, it is possible that different studies name the same profiles differently or different profiles similarly because of the context of the other profiles in the study. A meta-analytic approach, combined with multilevel latent profile analysis (LPA) that accounts for both within- and between-sample variability, is used in this study to examine the antecedents and outcomes of commitment profiles. This helps solve the naming problem by examining multiple data sets (K = 40) with a large sample (N = 16,052), obtained by contacting commitment researchers who voluntarily supplied primary data to bring further consensus about the phenomenology of profiles. LPA results revealed 5 profiles (Low, Moderate, AC-dominant, AC/ NC-dominant, and High). Meta-analytic results revealed that high levels of bases of commitment were associated with value-based profiles whereas low levels were associated with weak commit- ment profiles. Additionally, value-based profiles were associated with older, married, and less educated participants than the weak commitment profiles. Regarding outcomes of commitment, profiles were found to significantly relate to focal behaviors (e.g., performance, tenure, and turnover) and discretionary behaviors (e.g., organizational citizenship behaviors). Value-based profiles were found to have higher levels of both focal and discretionary behaviors for all analyses. Implications for the commitment and profile literature are discussed. Keywords: organizational commitment, commitment profiles, profile analysis, latent profile analysis, meta-analysis Organizational commitment has traditionally been investigated with three mindsets: affective (AC), normative (NC), and contin- uance (CC) commitments; respectively, they reflect bonds based in desire, obligation, and need (Meyer & Allen, 1997; Meyer & Herscovitch, 2001). Most research to date has investigated the three mindsets of commitment in terms of the effects that each one individually has on outcomes (i.e., variable-centered approach), with the rare article examining interactions among the mindsets and their effects on outcomes (e.g., Gellatly, Meyer, & Luchak, 2006; Meyer, Stanley, & Parfyonova, 2012; Wasti, 2005). Re- cently, commitment research has begun to utilize person-centered approaches, whereby commitment profiles are defined by grouping individuals into homogenous subsets based on relative endorse- ment of AC, NC, and CC (Meyer & Parfyonova, 2010) using methods such as cluster analysis (Wasti, 2005), median splits (Gellatly et al., 2006), or latent profile analysis (LPA; Meyer et al., 2012). Although there is growing consensus regarding the commitment profiles that occur (Meyer et al., 2012), there are a number of factors that limit the previous research on profiles. First, although many profile studies have relatively large sample sizes, profile analyses segment the sample into homogenous subgroups, oftentimes leading to comparisons between small groups. While this segmentation is the purpose of profile creation, segmented subpopulations in relatively small studies can significantly limit a researcher’s ability to make inferences from the results. Second, virtually all profile studies have focused on outcomes of commitment profiles, largely ignoring pre- dictors of commitment. As a result, a number of theoretical questions about how commitment profiles develop are left unanswered. Third, the few studies that have taken a person-centered approach to com- mitment have used a variety of profile-generating techniques, some of This article was published Online First March 7, 2016. Adam H. Kabins, Hay Group/Korn Ferry, Dallas, Texas; Xiaohong Xu and Mindy E. Bergman, Department of Psychology, Texas A&M Univer- sity; Christopher M. Berry, Kelley School of Business, Indiana University; Victor L. Willson, Department of Educational Psychology, Texas A&M University. Correspondence concerning this article should be addressed to Adam H. Kabins, Hay Group/Korn Ferry, 5001 Spring Valley Rd #800, Dallas, TX 75244. E-mail: Ahk325@gmail.com This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly. Journal of Applied Psychology © 2016 American Psychological Association 2016, Vol. 101, No. 6, 881–904 0021-9010/16/$12.00 http://dx.doi.org/10.1037/apl0000091 881