SAIM | A Scientific Approach to Innovation Management

Summary
There is strong evidence that managers and entrepreneurs have poor methods to make decisions under uncertainty. This is a serious problem that discourages innovation and the success of many start-ups. At the aggregate level it sties economic growth and the returns from many public and private incentives to innovation or entrepreneurship. This project studies whether managers and entrepreneurs can improve their ability to make these decisions by adopting a scientic approach based on the formulation of models tested with data, such as scientists do. The project develops a framework that explains the mechanisms and implications of this approach, and tests them through a large-scale RCT in six international sites. The framework shows that a scientic approach improves performance by pursuing valuable innovations and by terminating unsuccessful projects earlier. It also helps decision-makers to interpret signals: in particular, they understand better how to change a project in response to negative signals. The RCT tests mechanisms and performance of the scientic approach against current practice in innovation management, and its coverage ensures a good assessment of its validity across contexts and conditions. The results of this RCT are potentially ground-breaking because they can: (i) change the way we think innovation management and entrepreneurship; (ii) encourage the practical application of many economic and managerial theories ignored by managers or entrepreneurs in spite of their practical prescriptions; (iii) help to rethink the curricula of business schools by making a scientic approach to management more prominent and by revamping the application of economic and managerial theories; (iv) improve the mentorship of the many public and private initiatives that support innovation and entrepreneurship worldwide.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101021061
Start date: 01-09-2021
End date: 31-08-2026
Total budget - Public funding: 1 978 213,00 Euro - 1 978 213,00 Euro
Cordis data

Original description

There is strong evidence that managers and entrepreneurs have poor methods to make decisions under uncertainty. This is a serious problem that discourages innovation and the success of many start-ups. At the aggregate level it sties economic growth and the returns from many public and private incentives to innovation or entrepreneurship. This project studies whether managers and entrepreneurs can improve their ability to make these decisions by adopting a scientic approach based on the formulation of models tested with data, such as scientists do. The project develops a framework that explains the mechanisms and implications of this approach, and tests them through a large-scale RCT in six international sites. The framework shows that a scientic approach improves performance by pursuing valuable innovations and by terminating unsuccessful projects earlier. It also helps decision-makers to interpret signals: in particular, they understand better how to change a project in response to negative signals. The RCT tests mechanisms and performance of the scientic approach against current practice in innovation management, and its coverage ensures a good assessment of its validity across contexts and conditions. The results of this RCT are potentially ground-breaking because they can: (i) change the way we think innovation management and entrepreneurship; (ii) encourage the practical application of many economic and managerial theories ignored by managers or entrepreneurs in spite of their practical prescriptions; (iii) help to rethink the curricula of business schools by making a scientic approach to management more prominent and by revamping the application of economic and managerial theories; (iv) improve the mentorship of the many public and private initiatives that support innovation and entrepreneurship worldwide.

Status

SIGNED

Call topic

ERC-2020-ADG

Update Date

27-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.1. EXCELLENT SCIENCE - European Research Council (ERC)
ERC-2020
ERC-2020-ADG ERC ADVANCED GRANT