Exploring justice judgment patterns in Asia: a four country multi-group latent class analysis

We explore workers’ justice judgment patterns to understand how they use information to assess fair treatment at work. Justice judgment patterns are the unique set of information that individuals draw upon and use when evaluating the overall fairness of an entity. Data from four samples of workers from Malaysia, Cambodia, the Philippines, and China were analyzed using a multi-group latent class analysis. Results suggest four classes of justice judgment processes, three of which represent different patterns of heuristic processing. Comprehensive processors use a wide range of information when making justice judgments, while minimalist processors consider a limited range of information. Reward-focused processors focus on distributive justice cues and treatment-focused processors specifically attend to interpersonal justice cues while neglecting distributive justice cues. The latent class structure shared conceptual meaning across countries but the patterns had different rates of representation. Findings suggest that individuals do not always use complete information when assessing how fairly they are treated at work. Many appear to use heuristics that emphasize minimizing information processing, instrumental outcomes, or more relational outcomes. Results and implications are discussed.