Modeling factors influencing the innovation performance of knowledge-based production companies; Theme network approach and structural-interpretive modeling

In the management literature, understanding the predictors of innovation performance has become an important and ongoing research effort. Despite the efforts made in recent years, the research results do not have the necessary convergence. Therefore, it is necessary to provide models based on special contexts for different types of knowledge-based companies in different geographical regions of the country. According to the qualitative method of the current research based on the techniques of the theme network and structural-interpretive modeling, the number of samples of the theme analysis section based on the number of people interviewed is equal to 16 CEOs and members of the board of directors of knowledge companies. They are type 2 production bases. Qualitative data with conventional content analysis method and through the systematic process of coding analysis and analysis in the form of 53 basic themes and 7 organizing themes including; Financing, commercialization (strategy, resources and capabilities), networking, government, intellectual capital (team building and creative thinking), knowledge management, technology and marketing, and the cultural background of society and the overall theme of category innovation performance. They were tied. Finally, based on the structural-interpretive modeling method, the identified organizing themes were placed in 5 levels. The findings of the research are in harmony with researches that in recent years have placed special emphasis on the innovation performance of small and medium-sized knowledge-based companies, as well as in harmony with the attitude of Gupta et al. (2007) The innovation of knowledge-based production companies, affected by the factors present at both levels; company, and the macro environment.