IQUAL - Idea Quality for Successful Tech Scouting
| Reference number | |
| Coordinator | Stockholms universitet - Institutionen för data och systemvetenskap |
| Funding from Vinnova | SEK 456 164 |
| Project duration | November 2018 - November 2019 |
| Status | Completed |
Important results from the project
The purpose of the project is to contribute to idea generation and evaluation of the quality of ideas. The goal of the project was to design and evaluate an applied machine learning method to improve tech scouting and evaluation of idea quality in the area of autonomous driving. In this project, we have therefore designed and evaluated an applied method, where we utilize a relevant mix of machine learning and visualisation techniques and various data sources. The method has been demonstrated and evaluated by experts in transport, incubator activities and innovation leaders.
Expected long term effects
The main result of this project is a method for supporting idea quality evaluation and generation. This method is designed following design science approach, expert feedback, and literature review. The demonstration of the core part of this method is done through machine learning and visual analytics. The method supports industries to detect emerging technological trends more proactively. Also, it contributes to the UN sustainability goals 8 and 9.
Approach and implementation
The IQUAL method is designed according to the six steps in design scientific research proposed by Peffers et al. (2007). We used a literature study and expert interviews to evaluate the method developed. We interviewed eight experts in digital innovation, technology scouting, incubation and acceleration to identify the need for a tool to aid in idea evaluation and to assess the method´s effectiveness. Design science research has helped us to develop a relevant method and to make the results scientifically publishable.