From Tourist Complaint Constraints to TCC 2.0: Reframing Tourist Complaint Behavior in AI-Mediated Service Recovery

Service failures remain inevitable in tourism and hospitality, yet complaint behavior is often suppressed, particularly in non-routine, time-bound travel contexts. The Tourist Complaint Constraints (TCC) framework explains this silence through five tourism-specific constraints. However, it does not explicitly account for how platform-based and AI-mediated service environments reshape post-failure behavior. This paper revisits TCC and introduces TCC 2.0, a conceptual extension that reframes complaint constraints as structurally generated within platform-mediated recovery architectures. Drawing on justice theory and emerging research on AI-enabled service systems, the framework positions distributive, procedural, and interactional justice as central mediators linking complaint constraints to behavioral outcomes. It further incorporates platform/AI process constraints and algorithmic trust constraints as additional structural dimensions, while identifying recovery channel and failure magnitude as boundary conditions. A key contribution is the concept of platform-mediated silence, defined as a structurally induced form of non-complaining behavior shaped by constrained agency and recovery system design rather than satisfaction. The paper advances a set of propositions to guide empirical testing and future scale development in AI-mediated tourism contexts. By extending complaint behavior theory into digitally mediated service environments, TCC 2.0 offers a foundation for understanding how platform architectures shape customer voice, silence, and post-failure responses.

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