Technological Innovation System: A powerful Framework for Technology Intelligence Professionals?

Technology intelligence is a part of competitive intelligence dedicated to innovation issues. One of its main purposes is to provide strategic information regarding technological fields. Maturity level, main actors and drivers, … are key elements to identify opportunities and threats to technological progress. In this context, a general methodology is missing and technology intelligence professionals can encounter difficulties in applying a structured and logical analysis approach.


Yet, academia, and in particular researchers in innovation economics have developed for several decades models, concepts and frameworks for the understanding of innovation dynamics. In particular, we believe that the technological innovation system (TIS) framework[1] can be useful in the following ways :

  • It has a practical scope. It has been developed as a policy tool to assist decision-makers in the public sector to foster the growth of new technological fields.
  • It brings a dynamic and a socio-technical approach of innovation. It emphasizes the permanent interrelatedness of social, technical, institutional and political factors for the emergence and diffusion of innovation.
  • It gives a structured and sequential method for analysis:
  1. TIS delimitation (temporal, geographical, content aspects.),
  2. Identification of structural components (technology, actors, network and institutions),
  3. Identification and evaluation of functions: a set of key processes which contribute to generation, diffusion and utilization of technology (Knowledge development, legitimation, market formation, etc.)
  4. dentification of blocking and inducements mechanisms in the development of technology  
  5. Translation of main results in recommendations for decision-makers to overcome barriers


  • Improve of the quality of their analyses thanks to a more elaborated conceptualization of innovation dynamics that has been validated by theoretical and empirical works
  • More credible analyses
  • Help in the formulation of recommendations for decision-makers

Speaker profiles

Marina Flamand achieved a PhD thesis in 2016, funded by PSA Group; this thesis was dedicated to the enhancement of technology intelligence practices within large industrial groups. In particular, Marina studied the informational benefits of patent and financial data to support decision making in innovation processes. She is now the scientific manager of the VIA Inno Platform. This academic project from the University of Bordeaux is dedicated to the development and spreading of data mining methods for the understanding of scientific and innovation dynamics.