Aplikace Checklandovy metodologie měkkých systémů na problematiku rug pullů v oblasti DeFi a kryptoměn

The thesis deals with rug pulls in the field of decentralized finance (DeFi) and cryptocurrencies, which represent a significant risk for investors and undermine trust in the entire crypto and DeFi market. The aim of the thesis is to analyse the causes of rug pulls using Checkland’s Soft Systems Methodology (SSM), identify the factors that contribute to their occurrence, and propose systemic solutions in accordance with the principles of SSM. To achieve this goal, two sets of interviews are conducted, the outputs of which serve to create perspectives of individual actors, formulate root definitions, and develop conceptual models of purposeful activities that subsequently provide a basis for the debate phase with representatives of the identified perspectives. A secondary objective is to determine the extent to which ChatGPT can simulate human responses within individual perspectives. The results show that, according to the representatives of the perspectives, rug pulls arise from a combination of several factors, particularly insufficient regulation, founder anonymity, low financial and technical literacy among investors, and insufficient decentralization of projects. Based on these findings, a set of measures is proposed that reflects the principles of cultural feasibility and systemic desirability, covering areas such as regulation, transparency, education, audit infrastructure, and positive incentives for fraudsters to transition toward legitimate activities. The thesis expands existing research by adding a systemic dimension and represents the first known application of SSM in the context of DeFi and cryptocurrencies. An innovative aspect of the research is the use of the ChatGPT model to simulate the perspectives of selected actors. The findings contribute to a more effective prevention of rug pulls and to strengthening transparency and trust within the DeFi environment.