A Framework for Identifying and Analyzing Drivers Affecting the Futures of Cryptocurrency FinTechs in Iran with Fuzzy Delphi and Fuzzy Dematel

The present research aimed to identify and analyze effective drivers in the future of crypto fintechs using a fuzzy approach. The research was applied in terms of purpose and had a quantitative methodology. The theoretical population consisted of financial experts in fintechs and blockchain technology. Judgmental sampling was performed based on the expert's expertise. A sample size of ۱۰ was studied. Two quantitative techniques, fuzzy Delphi and DEMATEL, were utilized in the study, and the expert and effect assessment questionnaires, which had desired validity and reliability, were used to collect data. The research had three stages; first, ۲۲ drivers were obtained using the literature review and interviews with experts. Second, the drivers were screened by distributing expert assessment questionnaires and the fuzzy Delphi method. Third, ۱۰ drivers were selected for the final analysis due to the suitable deffuzification number. Such drivers were evaluated by distributing effect assessment questionnaires and the fuzzy DEMATEL technique. The drivers of national regulatory policies, the development of national RegTechs, and the development of smart contracts in the financial industry respectively had the highest net effects. Practical suggestions were extracted based on prior drivers and interviews with focus groups.

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Keywords: driver , future , Crypto FinTech , fuzzy decision making