Provide a Model for Identifying the Challenges of Virtual Currencies in the Marketing of the Iranian Banking Industry

The aim of this study was to develop a framework for identifying the challenges of virtual currencies in the marketing of the Iranian banking industry.

In the qualitative stage, the foundation data theory was used. Qualitative stage sampling started with the available method and then continued with the snowball method. Data saturation was also obtained in 16 interviews. A total of 10 categories and 82 concepts were identified. In the quantitative stage, the first and second confirmatory factor analysis methods based on SPSS software and structural equation modeling were used.

The results showed that the findings of the quality department have been fully confirmed by users. In addition, the results showed that causal conditions have a positive and significant effect on the main category. The main category has a positive and significant effect on strategies. Strategies have a positive and significant effect on outcomes. The interventionist conditions have a positive and significant effect on the consequences and finally the bed conditions have a positive and significant effect on the consequences.

 Based on the results obtained using the data-based approach in this study, causal conditions have been identified as one of the important dimensions of digital currencies. The causal conditions identified in this study are a combination of three categories of technological, economic, and regulatory factors, and in particular, regulatory factors are of great importance in terms of application.