Walton, Nigel (2017) The Extent to Which Data-Rich Firms Operating Two-Sided Platform - Ecosystem Business Models Are Able to Use Data to Gain an Innovation Advantage Over Established One-Sided Companies. PhD thesis, Coventry University.
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Abstract
It is the purpose of the dissertation to explore the extent to which data-rich firms operating two-sided platform-ecosystem business models are able to use data to gain an innovation advantage over established one-sided companies.
The dissertation begins with an analysis of business model theory and identifies two viewpoints based on the static and transformational perspectives. The transformational perspective is analysed in more depth and how data is playing a key role in creating an innovation advantage for two-sided platform ecosystem firms.
A detailed explanation of how the platform ecosystem model works in provided in addition to a definition of the four platform typologies and how they compare and contrast with the one-sided business model. This is followed by a critique of the resource-based view of strategy and the relevance of dynamic capabilities, the knowledge-based view and the value chain approaches to strategy.
A comprehensive innovation audit questionnaire (based on a sample of one hundred companies) is used to test whether the two-sided firms have a data-driven innovation advantage over the one-sided firms or not. The results reveal a clear innovation advantage for the two-sided firms who score consistently higher marks across all the dimensions of the innovation audit survey.
Item Type: | Thesis (PhD) |
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Additional Information: | A thesis submitted in partial fulfilment of the University’s requirements for the Degree of Doctor of Philosophy, Coventry University. |
Uncontrolled Discrete Keywords: | data-rich firms, internert, strategy and dynamic capabilities, static and transformational perspective |
Subjects: | H Social Sciences > HB Economic Theory |
Divisions: | College of Business, Psychology and Sport > Worcester Business School |
Depositing User: | Nigel Walton |
Date Deposited: | 16 Jan 2018 10:21 |
Last Modified: | 17 Jun 2020 17:21 |
URI: | https://eprints.worc.ac.uk/id/eprint/6313 |
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