Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.747112
Title: How to improve innovation success : customers, employees, and the search process
Author: Cornelius, Philipp Benjamin
ISNI:       0000 0004 7228 5244
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2017
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Abstract:
Innovation is at the heart of many firms’ operations and it is a key determinant of firm performance. Understanding how to improve innovation success is critical for organisations to survive in fast moving modern markets. To contribute to our understanding of successful innovation, I present three original research projects on stakeholder involvement and the search process. Specifically, I study customer involvement in crowdfunded innovation projects, involvement of non-R&D employees in corporate innovation, and component recombination during the search process. In the first part of this thesis, I study the involvement of customers in crowdfunded innovation projects. Entrepreneurs increasingly use crowdfunding to finance innovation projects through direct customer investments. The existing literature has predominantly studied factors driving crowd investments and whether the crowd makes rational funding decisions. I show that entrepreneurs also benefit from customer involvement during crowdfunding campaigns, as the customers turn investors and provide some of the support usually received from institutional investors. In the second part, I study the involvement of regular employees in organisational innovation projects (“employee innovation”). The previous literature has shown that employee innovation is an important driver of competitive advantage. I show how and when serendipitous intrafirm mobility (within the firm) increases employee innovation through learning and the integration of disparate knowledge. In the third part, I study the recombination of new and existing components during the search process for new products. I use a new computational method to decompose the descriptions of a large set of consumer products into components. I then show that certain component recombinations predict product success.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.747112  DOI: Not available
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