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

Student thesis: Doctoral ThesisDoctor of Philosophy

Abstract

It is the purpose of this dissertation to explore the extent to which data-rich firms operating two-sided platform-ecosystem business models are able to use Big Data to gain an innovation advantage over established one-sided companies.
The paper undertakes an analysis of business model theory and identifies that there are two viewpoints relating to business model innovation 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. This is followed by a critique of the resource-based view of strategy and the relevance of dynamic capabilities and the knowledge-based view.

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.
Date of Award18 Apr 2018
Original languageEnglish
Awarding Institution
  • Coventry University
SupervisorZulf Khan (Supervisor), Leonid Smalov (Supervisor) & Neil Pyper (Supervisor)

Keywords

  • Ecosystem business model
  • platform
  • Big Data
  • business model
  • two-sided firm
  • one-side business

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