Abstract
The use of network analysis has made it possible to understand the variables that affect highlycomplex phenomena such as agricultural innovation. The objective of this thesis is to evaluate the
innovative performance of agricultural innovation systems in Colombia, through the construction and
application of a multidimensional framework of indicators. To meet this objective, we broke with the
methodological tradition of analyzing the innovative performance of IS focused on patent networks
and executed a study based on networks of scientific papers. This thesis addressed the individual and
collective levels of AIS by assessing the status of the complete network structure and of the individual
networks of institutional actors in AIS.
This thesis makes three contributions to knowledge. First, it contributes to the IS research field from
the conceptualization of regional agricultural innovation systems, AIS. Second, it departs from
traditional qualitative methodologies for the study of AIS (case studies) and assumes a quantitative
approach. Third, based on a functional and multilevel orientation, it incorporates methods, measures
and concepts of social network analysis to explain the relationships between actor and system
characteristics and agricultural innovation performance.
Finally, it offers a critical assessment of how the AIS approach can be read and understood by policy
actors to justify and shape certain policy mixes that encourage a narrow focus on the promotion and
exploitation of agricultural research among various types of actors based on nonlinear models of
innovation. We found evidence that a linear approach focusing on agricultural research funding
strategies as the main mechanism for innovation has limited results.
Date of Award | 19 Jul 2024 |
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Original language | Spanish |
Awarding Institution |
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Supervisor | Cesar Dario Guerrero Santander (Supervisor) |
Keywords
- social cognitive structure
- collaboration
- complete networks
- co-authorship
- spatial scientometrics
- agricultural innovation
- social network analysis
- agricultural innovation systems
- individual networks