This study explores consumer behavior regarding the disclosure of personal information to GenAI systems, examining how potential benefits influence their willingness to share such information. The study adopts the conservation of resources theory, framing personal information as a resource that consumers aim to protect.
Latent Profile Analysis (LPA) was employed to segment consumers based on their willingness to disclose specific types of information to GenAI in hotels. The analysis identified distinct consumer profiles and analyzed the way they became receptive to offers and engagement with GenAI-powered systems.
Three unique consumer profiles were identified, each exhibiting different behaviors regarding information disclosure and engagement with GenAI systems. Significant differences were observed in the willingness of these profiles to pay for AI-personalized products or information. However, general demographics and behavioral variables showed minimal variance across profiles.
This study contributes to the literature on personal information disclosure in opaque systems like GenAI. It relies on a novel segmentation strategy using LPA and offers insights that challenge traditional demographic or behavioral segmentation models. The study highlights the potential superiority of LPA-based segmentation over traditional demographic or behavioral approaches.
