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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorHeimeriks, dr. G.
dc.contributor.authorVis, J.T.
dc.date.accessioned2020-09-23T18:00:18Z
dc.date.available2020-09-23T18:00:18Z
dc.date.issued2020
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/37725
dc.description.abstractIn 2015, the Sustainable Development Goals were introduced by the United Nations: 17 goals that aim at shared prosperity in a sustainable world for all. In order to achieve these goals by 2030 every country has to take up its pace and a more ambitious response is needed. The importance of scientific research in achieving the SDGs is underpinned by many scholars as well as the UN. This study aims to explain the differences in SDG related knowledge bases among countries. In order to do so, first the SDG related knowledge base of a country has to be established. There are several projects aimed at collecting and mapping SDG research, but the results are ambiguous. To understand the differences among these projects several methods are analysed, and two similar projects are critically compared with each other. Findings show that there is not a ‘best’ method in collecting SDG research, but rather that all methods have advantages and disadvantages, depending on the goal of the project. Being transparent in the choices and assumptions made during the research is of great importance. Secondly, the influence of the characteristics of a country’s knowledge base on its SDG research are analysed. Factors from evolutionary economic geography theories are used: the complexity of a country’s knowledge base and the relatedness density of a country’s knowledge base to the knowledge required for the SDGs. Two regression models are estimated, first one with the SDG research share as dependent variable, which is the SDG research as proportion of the total research of a country, and the complexity score and relatedness density score as dependent variables. Secondly a model with SDG achievement as dependent variable and the SDG research share, complexity score and relatedness density score are estimated. The findings show that there are large differences between SDGs, which are hard to explain. However, for most SDGs the relatedness density score has a positive effect on the SDG research share of a country. The complexity score has either a negative effect on the SDG research share directly, or negatively influences the positive effect of the relatedness density. Differences in the SDG related knowledge bases are explained by the characteristics of the knowledge base, which arise from the (geographic) characteristics of the country itself. This study offers promising insights and lays the foundation for many future research possibilities, in order to expand the knowledge base on the SDGs.
dc.description.sponsorshipUtrecht University
dc.format.extent24642786
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleScientific knowledge on the Sustainable Development Goals - A research on the influence of the existing knowledge base of a country on its SDG related research and achievement
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsSustainable Development Goals, SDGs, knowledge production, smart specialisation
dc.subject.courseuuInnovation Sciences


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