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Researchers often combine longitudinal panel data analysis with tests of interactions (i.e., moderation). A popular example is the cross-lagged panel model (CLPM). However, interaction tests in CLPMs and related models require caution because stable (i.e., between-level, B) and dynamic (i.e., within-level, W) sources of variation are present in longitudinal data, which can conflate estimates of interaction effects. We address this by integrating literature on CLPMs, multilevel moderation, and latent interactions. Distinguishing stable B and dynamic W parts, we describe three types of interactions that are of interest to researchers: 1) purely dynamic or WxW; 2) cross-level or BxW; and 3) purely stable or BxB. We demonstrate estimating latent interaction effects in a CLPM using a Bayesian SEM in Mplus to apply relationships among work-family conflict and job satisfaction, using gender as a stable B variable. We support our approach via simulations, demonstrating that our proposed CLPM approach is superior to a traditional CLPMs that conflate B and W sources of variation. We describe higher-order nonlinearities as a possible extension, and we discuss limitations and future research directions.

We extend organizational justice theory by investigating the justice perceptions of academic entrepreneurs regarding interactions with their universities. We assess how these justice perceptions influence the propensity of academic entrepreneurs to engage in different forms of commercialization, as well as the moderating role of entrepreneurial identity and prosocial motivation. We test our predictions using data from 1,329 academic entrepreneurs at 25 major U.S. research universities. Our results indicate that organizational justice is positively associated with intentions to engage in formal (i.e., sanctioned) technology transfer, and negatively associated with intentions to engage in informal (unsanctioned and noncompliant) technology transfer, which we characterize as a form of organizational deviance. Our findings also show that entrepreneurial identity and prosocial motivation (i.e., a focus on oneself vs. others) amplify and attenuate, respectively, the relationship between justice perceptions and technology transfer intentions. Finally, although intentions to engage in formal technology transfer predict subsequent behavior, intentions to engage in informal technology transfer do not.