Abstract

Background and Objectives: The main purpose of this research is to design an innovation ecosystem model in the field of biotechnology in Tabriz and to determine the components of the innovation ecosystem that has been done by the ecosystem data method. Material and Methods: This study was conducted by grounded theory. Semi-structured interviews were used for data collection and data analysis was performed using Strauss and Corbin method and paradigm model. The statistical population of this study consisted of 18 faculty members of Tabriz University of Medical Sciences, directors of research and technology and higher education planning, and the university's relationship with industry and innovation institute of the province, managers of knowledge-based companies and experts of Iran's Scientific and Industrial Research Organization, managers of Zahravi Pharmaceutical Factories, Razi Serum Manufacturing, Dana Pharmaceutical Compan., whichwas done through purposive sampling and snowball method. The interviews were continued until saturation was achieved. Results: The components affecting the innovation ecosystem led to the creation of a data-based theory in the field of health innovation ecosystem by analyzing the results of the content of the interviews during the open, pivotal and selected coding process. The model designed in this study includes effective dimensions and components, barriers and strategies, causal, contextal, mediating and constituent elements that show the pivotal phenomenon, consequences and strategies. The identifiers and factors of the innovation ecosystem of 150 codes and 40 concepts, 5 main components of interviews and research literature were developed in the form of a conceptual model of data foundation. Based on the results of the research, causal factors (government, financial capital), central issue (university and research institutes), strategies (establishment of universities and research-based institutions, shortening the process of obtaining necessary permits, government support for research and development, material and spiritual incentives and increasing risky investment), consequences (economic development and growth) and underlying factors (attractiveness of place, banking services, intellectual property rights) intervening conditions (culture) were identified. Conclusion: The studied process was explained in the form of a story line of data foundation theory. Finally, the model of biotechnology innovation ecosystem was designed and analyzed

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