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Monitoring innovation with key performance indicators in quadruple helix collaboration

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A thesis on Quadruple Helix (QH) collaborations for the project RiConfigure

I am Anne Noordenbos, I study Food Technology at the Wageningen University and Research (WUR). I chose the master specialization ‘Food innovation and management’ in which I combine courses in the area of innovation management, with advanced food technology courses.

While looking for a thesis assignment, the thesis coordinator of the Business Management and Organisation (BMO) chair group draw my attention to a research proposal about Quadruple Helix (QH) collaborations for the project RiConfigure. Both the WUR and ISPT participate in this European project.

Innovation collaborations

My research focuses on innovation collaborations between four sectors: academic research, industry, government and civil society – a quadruple helix collaboration. The set-up and execution of large innovation programs always comes with a demand for monitoring. A common way of monitoring is with the use of key performance indicators (KPIs). It is important that the right indicators are chosen to gain insight in the set-up, progress and achieved results. The main aim of the current research was to investigate the use of KPIs derived from cross-sectoral monitoring efforts for programs covering industry-initiated QH innovation projects (II-QH-IP).

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Conclusions

A set of 20 KPIs was composed based on monitoring efforts that are used in comparable cross-sectoral innovation programs. The KPI set was tested on its applicability in 41 II-QH-IP cases and compared with important aspects of QH collaborations that are identified in literature. The application of this KPI set on the completed QH projects provided some useful insights as to where current measures of the indicators lack to capture performance. Besides, in the comparison with literature was found that the KPI set does not cover important interaction aspects as well as the intangible results of the collaboration.

Contribution to the cluster

The KPI set can provide a means of benchmarking for organizations involved in QH collaborations to identify the best practices in projects and set goals to emulate them. Moreover, it can be interesting to find out whether the scope of the current monitoring efforts covers the aspects of QH collaborations examined to be important in literature.

I would like to thank the Institute for Sustainable Process Technology for the collaboration. I got access to some digital archives which supported my literature study with data. In addition, I learned about the large and important projects ISPT is involved in, which I think is very impressive.

Acknowledgement

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 788047