Abstract

This study introduces privacy intelligence (PQ), a novel construct aimed at addressing both theoretical and practical challenges in privacy decision-making. Traditional approaches focusing on privacy concerns present challenges, such as the privacy paradox, which reveals a mismatch between expressed privacy concerns and actual behavior. We propose PQ, based on cognitive and behavioral abilities, as a more effective approach for explaining, predicting, and improving privacy decisions. Drawing from multiple intelligence theories, we conceptualize four dimensions of PQ: metacognitive, cognitive, motivational, and behavioral. To validate PQ, we developed a measurement scale through expert feedback, Q-sorting, and pilot tests, resulting in a robust 16-item scale (PQ 1.0). In a nomological network, our main study (n = 384) examined the relationship between PQ, privacy concerns, and trusting beliefs using a covariance-based structural equation model (CB-SEM). The results show a significant positive association between PQ and both privacy concerns and trusting beliefs, while privacy concerns were negatively associated with trusting beliefs. These findings suggest that individuals with higher PQ not only express greater privacy concerns but also have higher trust in ICTs and service providers. This research offers a promising new avenue for exploring privacy behaviors and enhancing privacy decision-making in the digital age.

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