Presenting the development model of technological entrepreneurship in the banking system based on the open innovation approach

Abstract

The purpose of this research is to present a model of technological entrepreneurship development in the banking system based on the open innovation approach. The current research has a fundamental goal and a practical approach, and the research method is mixed and content analysis. The statistical population of the qualitative section includes professors and experts in the field of technological entrepreneurship, and the sampling method in this research is a snowball sampling method, so that the data collection continued until reaching the saturation point, which is 18 people. and also the statistical population in the quantitative part includes managers and assistants of Tejarat Bank in Tehran province, and the sampling method in this research is simple random, and the sample size is 313 people based on Morgan's table. The method and tools of data collection in the qualitative part are semi-structured interviews and in the quantitative part are researcher-made questionnaires. In this research, descriptive statistics and inferential statistics were used to analyze the data and achieve the aforementioned goals. Statistical methods for analyzing and analyzing the information available in the data set is factor analysis or factor analysis, which was used using the structural equation method (SEM) and Lisrel software. Finally, the research model was measured and fitted. The research results showed that the fit of the research model is significant for t-coefficients above ±1.96 to ±2.58 at the 0.05 level, and t-coefficients above ±2.58 are significant at the 0.01 level. The path coefficients and the explained variance of the research variables and the fit indices obtained for the tested model show that the RMSEA index in the estimated model has an acceptable level with a rate of 0.064 and other fit indices such as CFI, GFI, NFI, and AGFI is equal to 0.97, 0.94, 0.95 and 0.92, respectively, and these characteristics of good fit show that the data of this research fits well with the factor structure of this model.