Looking at the bigger picture: on the relevance of null effects of model differences across time

Abstract Longitudinal research traditionally aims to detect and quantify change in outcomes such as attitudes, behaviors, or performance over time. Nonsignificant results, particularly in regards to longitudinal research designs, are however often overlooked, despite their potential theoretical and managerial relevance. This research contributes to addressing this gap by examining the stability of a theoretically grounded model across five independent time points. Adopting a model-logic approach to longitudinal analysis, time is conceptualized as a contextual dimension (e.g., a moderator) rather than as a predictor. Multigroup PLS-SEM is employed to assess the difference between the theoretically established relationships across years. The results do not reveal statistically significant differences in key structural paths, indicating a high degree of temporal stability. These null results provide evidence for the robustness and generalizability of the underlying theoretical mechanisms across varying economic and societal contexts. The study furthermore situates its design in the broader open science movement by framing longitudinal model comparisons as a form of structured temporal replication. Implications and guidelines for theory development, longitudinal modeling, and future research on replication and robustness in structural equation modeling are discussed.