加密貨幣迷因幣與龐式騙局之異質性結構分析：從資產屬性、資訊擴散與參與動機視角探討

A Structural Differentiation Analysis of Cryptocurrency Meme Coins and Ponzi Schemes: Asset Attributes, Information Diffusion, and Participation Incentives

本研究旨在釐清加密資產領域中迷因幣與龐式騙局之間在結構性、功能性與風險屬性上的異質性。透過資產屬性、資訊擴散機制與參與動機三維分析架構，對兩者進行系統性比較，並輔以Dogecoin、Shiba Inu與Pepe Coin等代表性迷因幣，以及BitConnect、OneCoin與PlusToken等典型龐式騙局個案進行剖析。研究發現迷因幣雖展現高度非理性與波動性，然多建構於文化參與與社群認同之基礎，其資訊來源去中心且開放，參與動機偏向遊戲化與情緒性；龐式騙局則基於資金鏈條之結構性操控與欺瞞話術，資訊來源集中並具封閉性，參與者多因高報酬預期與認知偏誤而進場。研究進一步指出現行風險評估與監理機制未能有效區辨此兩類資產類型，導致法制適用困難與治理資源錯置。本文建議應建立動態監管架構與分層風險辨識模型，並強化科技治理工具與投資人教育體系，以提升數位資產治理能力與市場風險防衛效能。

This study explores the structural and functional heterogeneity between meme coins and Ponzi schemes within the cryptocurrency ecosystem. Employing a tripartite analytical framework, asset attributes, information diffusion, and participation incentives, this research compares and contrasts the two asset types, supported by case studies of Dogecoin, Shiba Inu, and Pepe Coin for meme coins, and BitConnect, OneCoin, and PlusToken for Ponzi schemes. The findings reveal that while meme coins exhibit high volatility and speculative behavior, they are largely driven by cultural participation, social symbolism, and decentralized communication flows. Conversely, Ponzi schemes are structurally centralized, rely on fabricated returns and hierarchical recruitment mechanisms, and involve participants lured by misinformation and unrealistic return expectations. The study further highlights the limitations of existing regulatory and risk assessment frameworks in distinguishing between these heterogeneous asset forms. It calls for adaptive regulatory structures, differentiated risk classification models, the integration of regulatory technologies, and enhanced investor literacy programs to improve governance capacity and mitigate systemic risks in digital financial markets.