National innovation systems as analytical frameworks for knowledge transfer and learning in plant biotechnology: A comparative study.

摘要

This research addresses the issue of whether government policies and national institutional differences are responsible for the dissimilarities observed in innovation trajectories between nations. Using plant biotechnology as an example technology, the economic issue examined is the degree to which national innovation systems affect technological innovation by facilitating learning and knowledge transfer processes. To address this issue a new theoretical framework is developed and a number of research hypotheses are empirically tested by using both new (network analysis) and traditional (regression analysis) methodologies.The study was initiated after observing the existence of differences between US and Europe in the development of the plant biotechnology industry. It was believed that these differences were originated from national idiosyncrasies and a framework that placed importance on national borders was consequently adopted. The main hypothesis is that national innovation systems affect learning processes, which in turn affect innovation. Then the first issue to be addressed referred to the appropriability of such a framework in a globalized world, where national borders become increasingly permeable. To answer this question a theoretical model was constructed that revealed the nature of national innovation systems. According to this model, such systems consist of knowledge flows---representing the linkages between the system's actors---and stocks, which every actor aims at increasing by means of learning. Each national innovation system is therefore in essence a knowledge network differences in the structuring of such networks create different national innovation systems.This theoretical framework was tested for the national innovation systems of US and Europe, using plant biotechnology as a case. The number of plant biotechnology patents filed represent the innovation output of each system and the knowledge stock that each actor holds at any period of time. Knowledge flows in the system are represented by the public private interactions, which consist of collaboration agreements between private firms and the public sector, in particular universities and public research institutes. The data used, have been gathered from several different sources: reviews of newspaper and journal articles, on-line and other databases, specialized journals, corporate annual reports, specialized directories, university publications as well as data published by government agencies.The data analysis performed---using network analysis and traditional regression analysis methods---supported the main hypothesis that national innovation systems affect learning which in turn affects innovation. It was shown that knowledge is the basic element of national innovation systems, and learning a basic process within such systems.