finer-grained detail: the person-specific approach. In the current article, we (a) detail the purpose of each approach, (b) describe how to determine when each approach is most appropriate, and (c) delineate when the approaches diverge to give differing results. Through achieving these goals, we suggest that no single approach is the “best.” Instead, the choice of approach should be guided by the research question. To further emphasize this point, we provide illustrative examples using real data to answer three distinct research questions. The results show that each research question can be fully addressed only by the appropriate approach. To conclude, we directly suggest certain research areas that may benefit from the application of person-centered and person-specific approaches. Together, we believe that discussing variable-centered, person-centered, and person-specific approaches together may provide a more thorough understanding of each.

28:T4f3,

Person-centered approaches to organizational scholarship can provide critical insights into how sets of related constructs uniquely combine to predict outcomes. Within micro topics, scholars have begun to embrace the use of latent profile analysis (LPA), identifying constellations of constructs related to organizational commitment, turnover intentions, emotional labor, recovery, and well-being, to name a few. Conversely, macro scholars have utilized fuzzy set qualitative comparative analysis (fsQCA) to examine numerous phenomena, such as acquisitions and business strategies, as configurations of explanatory conditions associated with firm-level outcomes. What remains unclear, however, is the extent to which these two approaches deliver similar versus unique insights when applied to the same topic. In this paper, we offer an overview of the ways these two methods converge and diverge, and provide an empirical demonstration by applying both LPA and fsQCA to examine a multidimensional personality construct—core self-evaluations (CSE)—in relation to job satisfaction. In so doing, we offer guidance for scholars who are either choosing between these two methods, or are seeking to use the two methods in a complementary, theory-building manner.

29:T44f,

In the present paper, we introduce k-centres functional clustering (k-centres FC), a person-centered method that clusters people with similar patterns of complex, highly nonlinear change over time. We review fundamentals of the methodology and argue how it addresses some of the limitations of the traditional approaches to modeling repeated measures data. The usefulness of k-centres FC is demonstrated by applying the method to weekly measured commitment data from 109 participants who reported psychological contract breach events. The k-centres FC analysis shows two substantively meaningful clusters, the first cluster showing reaction patterns with general growth in commitment after breach and the second cluster showing general decline in commitment after breach. Further, the reaction patterns in the second cluster appear to be the result of a combination of two interesting reaction logics: immediate and delayed reactions. We conclude by outlining how future organizational research can incorporate this methodology.

2a:T476,

Latent profile analysis (LPA) is a person-centered method commonly used in organizational research to identify homogeneous subpopulations of employees within a heterogeneous population. However, in the case of nested data structures, such as employees nested in work departments, multilevel techniques are needed. Multilevel LPA (MLPA) enables adequate modeling of subpopulations in hierarchical data sets. MLPA enables investigation of variability in the proportions of Level 1 profiles across Level 2 units, and of Level 2 latent classes based on the proportions of Level 1 latent profiles and Level 1 ratings, and the extent to which covariates drawn from the different hierarchical levels of the data affect the probability of a m