Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.779458
Title: Innovation management in digital platforms
Author: Kaushik, Nilam
ISNI:       0000 0004 7965 1542
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2019
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Abstract:
Digital platforms are increasingly gaining prevalence as orchestrators of innovation, spawning new value chains, business models and organisational forms. Platforms have also changed the way firms manage various aspects of their innovation process. Improving innovation success is imperative for organizations in a growing platform-based economy. To contribute to our understanding of innovation management in these emerging contexts, I present three original research projects that provide an empirically based understanding of the operational drivers of successful innovation management in emerging digital platforms with econometric studies and field experiments. In the second chapter, I quantify and characterize product evolution in mobile app development and examine the market performance implications of sequential innovation. I take a "search" perspective on how firms add new features and attributes into their digital products in successive product versions and find conditions under which search is associated with higher market performance. Increasing participation from marginal users who bring diverse skills, knowledge and experience can be instrumental for innovation success involving distant search through crowdsourcing. In the third chapter, I provide insights from a randomized controlled trial from a technology-based crowdsourcing platform and investigate whether and to what extent gender based preferences explain the under-representation of women in technology-based work. My findings provide counter-intuitive insights into heterogeneous gender preferences for tech-based work. In the fourth chapter, using a natural language processing technique, I study the recombinant breadth and atypicality of crowdsourced contributions to complex problems and explore which patterns and knowledge configurations are more or less likely to be associated with proposal success.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.779458  DOI: Not available
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