Providing an adaptive neuro-fuzzy inference system for the feasibility of e-commerce startups

The digital economy has created new opportunities to create startups and new models based on information technology, but not all startups created, especially in the field of electronic commerce, have been successful and have a high failure rate. As a result, the aim of this research is providing a feasibility model based on adaptive neuro-fuzzy inference system for e-commerce startups in order to help reduce the failure of these startups by identifying the factors and components affecting success. The current research is an applied research in terms of purpose and a survey in terms of data collection. the statistical population of the research is related to the active startups in the field of e-commerce in East Azerbaijan province from 2021 till 2022. the method of research in identifying the factors and indicators uses the content validity ratio (CVR) based on the opinions of experts. in order to predict the success rate of startups using the adaptive neuro-fuzzy inference system, a fuzzy system has been designed and trained. also, in order to generalize the system, the designed system has been validated.The output of the research is an intelligent system and the results of the feasibility study carried out by the adaptive neuro-fuzzy inference system indicate the correctness of the system's efficacy and its reliability in supporting the decisions made in order to create new e-commerce startups.