Unraveling consumer resistance to innovative marketing in web 3.0: empirical findings and large language model insights

Abstract

The rise of blockchain technology has introduced Non-Fungible Tokens (NFTs) as innovative tools in digital marketing, yet consumer resistance hinders their widespread adoption. This study applies innovation resistance theory to investigate the barriers to NFT marketing adoption, as well as the moderating role of consumer knowledge. Using a dual-method framework, Covariance-Based Structural Equation Modeling (CB-SEM) of survey data (n=610) and insights from eight large language models identify perceived risk as the primary barrier, amplified by higher consumer knowledge. As the first study combining empirical analysis with AI-driven insights, it provides actionable strategies to mitigate resistance and advance blockchain-based marketing.