Identification and Ranking of Factors Affecting Innovation Ecosystem of Communication Technology industry

Till now, the elements influencing the communication technology sector's innovation ecosystem have not been explored in a systematic and independent way in the form of a quantitative model, independent of the information technology industry innovation ecosystem.

To identify and prioritize the factors affecting the Iranian communication technology sector's innovation ecosystem, as well as to examine the influence of each on the final model of the ecosystem for use by government institutions and industry activists in this industry.

In terms of purpose, the research employs a survey as a descriptive method. The experts in this study were carefully chosen from among the top executives and senior managers of private enterprises and governmental bodies in the Iranian communication technology industry. The fuzzy Delphi method (FDM) approach was used in three steps to discover the elements influencing the innovation ecosystem. In addition, data analysis, validation, and fit of the research model, as well as question analysis, were carried out using AMOS software's confirmatory factor analysis and structural equations, respectively.

This study's findings reveal that institutional factors, innovation management, business, national and regional, science and technology, and financial and economic variables all have a substantial influence on the communication technology industry's innovation ecosystem model. The final model offered is also well-fitting.

The analysis of coefficients of determination reveals that the innovation management component has the most influence, while the national and regional variables have the least impact on the CT industry's innovation ecosystem model. It is suggested that, due to the dynamics of industry and technology, the prioritization of factors affecting the ecosystem model be considered, as well as the establishment of an ICT Science and Technology Observatory with the goal of assisting the knowledge-based innovation ecosystem and predicting science and technology trends on the agenda of relevant institutions.