Integrating Bibliometrics with Design Thinking to Enhance Technological Innovation
The integration of bibliometrics into an innovation process such as design thinking has the potential to enhance innovation engineering management by providing a comprehensive understanding and valuable insights of the research landscape in a particular domain to support divergent problem and solution phases. This research paper examines and demonstrates the potential benefits and practicability of methodically and operatively incorporating bibliometric scanning into the design thinking process. Thereby, an adapted approach consisting of bibliometric problem and solution scanning is presented and applied to the fields of fuel tank maintenance and robot locomotion in confined spaces. The approach generated a general overview of scientific production based on total publications as well as average citations and identified key concepts and collaborations in the respective fields through cooccurrence and co-authorship network analyses. Two hypotheses regarding the content-related advances respectively the applicability from the innovation team perspective were developed and tested. The results supported both hypotheses and revealed that bibliometrics can complement and enhance the design thinking process by providing data driven knowledge to divergent problem understanding and solution ideation phases. By leveraging the insights obtained from bibliometric scanning, innovation teams can efficiently build on existing knowledge, uncover new opportunities and make more informed and comprehensible decisions to ultimately create more impactful solutions.
Authors
- Gerko Wende (ORCID: https://orcid.org/0000-0003-2368-2369)
- Alireza Dadashi (ORCID: https://orcid.org/0000-0003-2704-1251)
Institutions
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE)
Publication Details
- Published
- 2024-11-04
- DOI
- https://doi.org/10.1109/ictmod63116.2024.10878178
- Citations
- 1
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.53