Providing an optimal model of financial transaction tax (FTT) with interpretive structural modeling (ISM)

The idea of receiving tax from cash or bank transactions (BTT) (not new) has been used many times in different economic and political fields during the decades since the introduction of financial transaction tax (FTT). This study examines the provision of the optimal model of financial transaction tax (FTT) with an interpretive structural model (ISM). The method of the current research is practical in terms of its purpose and it is mixed (qualitative-quantitative) in terms of data collection. The qualitative research method was qualitative content analysis with an inductive approach. The participants in the qualitative part of the research were experts in the tax field, and 12 people were interviewed using the theoretical snowball sampling method. The estimation of the desired sample size was done based on the theoretical saturation of the data. The data collection tool in the qualitative part was a semi-structured interview. The triangulation method and Christiansen angle technique were used to check the validity of the qualitative part. At first, research components were identified through literature and semi-structured interviews with experts. The interviews were coded with three coding methods, open, central and selective, and finally, fifteen components were identified and in the quantitative part, an interpretive structural model was created using MATLAB software to provide an optimal model for financial transaction tax. After that, the position of the identified components was determined using Mikmak software based on influence and dependence. The results show that the structural interpretation model of the study can be presented in five levels. Micmac analysis also showed that the components of the optimal tax pattern are divided into the group of dual, regulatory, independent, leveraged and influential variables. The findings show that the optimal tax model is an unstable system.