Thesis

Opportunities through text mining in strategic management – Quantitative analysis of innovation ecosystems with the help of advanced text mining approaches

Key Info

Basic Information

Group:
Lehrstuhl für Innovation, Strategie und Organisation
Level:
Master

Supervisor

The ecosystem theory has been recognized in strategy research and practice for several decades as a possible explanation for superior firm performance. The theory is based on the view that, in addition to the industry in which an organization is located and the resources at its disposal, the relationships with other organizations determine its success. These relationships extend the resources of the focal organization and sustain its competitive advantage (Dyer and Singh, 1998). Therefore, awareness about the ties between the focal company and external organizations (i.e. ecosystem actors) is crucial for a successful business strategy. The strategy must consider both formal and informal relationships.

However, analyzing these relationships proves challenging simply because of their large number. For this reason, text-based, quantitative methods are particularly suitable for a detailed evaluation. Networks of relevant ecosystem actors can be constructed by collecting external website links and scraping relevant websites. Advanced text mining methods (e.g., topic modeling) can then be employed to analyse the written texts of the scraped website data. In sum, this approach could lead to a data-based description of the investigated ecosystem.

This offered work aims to implement the described approach as a model, based on eligible innovation ecosystems in Germany. The scientist should then derive strategic implications based on this virtual model. A comprehensive network of websites with their respective (German) texts and first programmed functions are available as a basis.

Since the successful completion of this interdisciplinary topic requires not only advanced programming knowledge but also an understanding of business strategies, we would like to explicitly mention that required business skills can be built up while working on the topic.


The applicant should have the following skills:
- Experience in Natural Language Processing
- Programming experience in Python and its relevant packages (e.g. nltk, spaCy, scikit-learn or keras)
- Affinity for Strategy Management and especially for Ecosystem Theory
- Willingness to work in a motivated team
- Equivalent German language skills of >= B2

What we offer:
- Intensive collaboration in current BMBF projects, such as "Change through Innovation in the Region (WIR!)".
- You will be part of the team, you will have a workplace at the institute, and you will be invited to our project meetings and team events.
- Interviews, meetings with politicians, meetings with alliances
- You will investigate interesting research topics in future industries - it's not for nothing that innovation fields are more highly funded than ever before
- Room for your own ideas and interests - both methodologically and in terms of content
- For your further career, you can make contacts in politics and the private sector through your practical work, or recommend yourself for a doctorate with us

If you are enthusiastic about the topic, please send your CV, a short cover letter and a recent grade summary to grimm@time.rwth-aachen.de.

Keywords: Ecosystem, Quantitative, Text Mining, Web Scraping, Python, Strategy, Management, regional, innovation