희귀도와 속성에 따른 수집품 NFT의 잠재계층 분류 및 가치 분석

Abstract

A new approach was attempted to analyze the value of NFT, which is emerging as a major field in the digital environment along with cryptocurrency and metaverse. From the point of view that heterogeneous groups may exist in an NFT collection, latent class analysis, an object-oriented methodology, was applied. Existing NFT value studies focus on finding significant variables mainly through regression analysis, so there is a limitation in not considering the heterogeneity within the group. As an analysis result of the representative NFT, BAYC(Bored Ape Yacht Club), it can be divided into 8 heterogeneous groups (latent class) by NFT properties and rarity, and it was confirmed that the average value of each group differs by more than two times.