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An Urban Data Business Model Framework for Identifying Value Capture in the Smart City: The Case of OrganiCity

In: Smart Cities and Smart Governance

Author

Listed:
  • Shane McLoughlin

    (Maynooth University)

  • Giovanni Maccani

    (Maynooth University)

  • Abhinay Puvvala

    (Maynooth University)

  • Brian Donnellan

    (Maynooth University)

Abstract

Governments’ objective to transition to “smart cities” heralds new possibilities for urban data business models to sustain and scale urban data-driven solutions that address pressing city challenges and digital transformation imperatives. Urban data business models are not well understood due to such factors as the maturity of the market and limited existing research within this domain. Understanding the barriers and challenges in urban data business model development as well as the types of opportunities in the ecosystem is essential for researchers as well as practitioners from incumbents to new entrants. Therefore, this chapter introduces a framework for understanding and classifying urban data business models (UDBM). We furthermore illustrate the application of this framework to a heterogeneous sample of emerging smart city solutions. An embedded case study method was used to derive the framework by analyzing 40 publicly funded and supported urban data focused experiments that address pressing city challenges under the H2020 OrganiCity initiative. This research contributes to the scholarly discourse on business model innovation within the context of smart cities.

Suggested Citation

  • Shane McLoughlin & Giovanni Maccani & Abhinay Puvvala & Brian Donnellan, 2021. "An Urban Data Business Model Framework for Identifying Value Capture in the Smart City: The Case of OrganiCity," Public Administration and Information Technology, in: Elsa Estevez & Theresa A. Pardo & Hans Jochen Scholl (ed.), Smart Cities and Smart Governance, chapter 9, pages 189-215, Springer.
    • Handle: RePEc:spr:paitcp:978-3-030-61033-3_9
    DOI: 10.1007/978-3-030-61033-3_9
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