Purpose
This project was developed as a Master’s Thesis project for the Engineering Management MSc degree at DTU. The Master’s program in Engineering management seeks to shape “engineers capable of working at the interface between business and engineering”. This reinforces the idea that both qualitative and quantitative competencies are relevant for a project of this scope. This research should not only satisfy certain learning objectives but also touch upon more specific fields that were studied during the program. It is believed that the subject of this thesis is highly connected to at least 4 topics that were studied during the above-mentioned degree.
Sustainability is an intricate part of DTU’s strategy, as mentioned in its mission statement: “The University will apply significant research strength to laying the foundations for technologies and processes that promote innovation and sustainability, and which address major societal challenges.”3
Not only as an important part of this particular institution, Sustainability is also a global concern that should be addressed with a high degree of importance. As shown in several research works such as, for example, the work of Karel Mulder where he mentions that various civilizations throughout the world have collapsed as a result of unsustainable practices in different areas such as agriculture.
For this reason, this project focuses on sustainability as a core part of eco-innovation by exploring the knowledge network behind biofuel research and how it can help stakeholders make more transparent and environmentally aware decisions.
Management is another core pillar of the master's degree. It constitutes the qualitative field of research and is made up of several different areas.
This project is highly related to management by focusing on areas such as:
Innovation: By studying the knowledge network behind biofuels, there is an opportunity for understanding not only how it works, but also how companies create and retain value in the context of eco-innovation. For example, patents and publications are quantitative measures of innovation.
Levels: Complex systems can be studied in levels. For example, one can distinguish the world, the national, and the organizational, levels. Throughout this research, all of these levels will be taken into consideration, as well as the complex networks that characterize them and their development through time.
Differentiation: Technology is one of the ways of strategically differentiating a country or an organization. In this research, the factors that differentiate entities will try to be understood, as well as the intricacies of the relationships between countries, organizations and universities.
The data revolution is upon the world - by data it is meant “lose information”. For this reason, it is hard to understand why this revolution should not serve as a catalyzer for solving other problems that may lie in other areas such as management, sustainability, or even innovation.
Preparing, studying and analyzing large data sets is another important characteristic of this project. The dataset that is going to be studied is composed of 4585 patents and 5313 scientific publications; moreover, the complex dataset is stored in a graph database composed of more than 100 countries and 10,000 distinct organizations.
Data science per se is not enough to solve problems, in order to make sense of the vast amount of information that such a database carries, one must apply efficient and effective techniques for the analysis.
One of the reasons why this project exists is to help organizations, policymakers, and researchers to make sense of this type of information. For this reason, the project also focuses on the application of algorithms that would be classified as Unsupervised Learning, as a way of trying to understand the hidden patterns that might lie in the data.
In the context part of the report, more on this will be discussed.
