Fr. 69.00

Incentives for Collaboration and Competition - Experimental Evidence on Innovation, Behavior and Performance

English · Paperback / Softback

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Description

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Individuals and firms can improve their performance through collaboration and competition. However, it is still an open question how collaboration and competition schemes can be optimally designed and incentivized in order to exploit their full potential. Jonas Heite investigates this question by assessing efforts to stimulate R&D collaboration and by examining properties as well as underlying mechanisms (e.g., effort, risk, confidence and stress) of ability configurations in contests. Based on three large-scale economic studies covering laboratory, field and natural experiments, the author applies novel and sophisticated econometric methods to provide causal empirical evidence that yields important implications for policymakers, managers and researchers.

List of contents

Subsidized R&D collaboration: The effect of innovation vouchers on innovation activity and performance.- Choking under pressure: The effect of asymmetric contests on effort, stress and performance.- Performance in contests: The role of risk and confidence.

About the author










Dr. Jonas Heite completed his dissertation under supervision of Prof. Dietmar Harhoff, Ph.D. at the Max Planck Institute for Innovation and Competition, the LMU Entrepreneurship Center and Harvard University.


Product details

Authors Jonas Heite
Publisher Springer, Berlin
 
Languages English
Product format Paperback / Softback
Released 01.04.2020
 
EAN 9783658292300
ISBN 978-3-658-29230-0
No. of pages 219
Dimensions 156 mm x 215 mm x 14 mm
Weight 323 g
Illustrations XXVIII, 219 p. 40 illus., 10 illus. in color.
Series Innovation und Entrepreneurship
Subjects Social sciences, law, business > Business > Management

Verhaltensökonomie, Industrielle Anwendungen der wissenschaftlichen Forschung und technologische Innovation, InnovationVouchers; R&Dsubsidies; Individualbehaviorandstressinheterogeneouscontests; Contestdesign; Regressiondiscontinuitydesign; crowdsourcing

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