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

Shane McLoughlin (), Giovanni Maccani, Abhinay Puvvala and Brian Donnellan
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Shane McLoughlin: Maynooth University
Giovanni Maccani: Maynooth University
Abhinay Puvvala: Maynooth University
Brian Donnellan: Maynooth University

Chapter 9 in Smart Cities and Smart Governance, 2021, pp 189-215 from Springer

Abstract: 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.

Keywords: Organicity; Smart city case study; Urban data business model; City values; Value creation (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:paitcp:978-3-030-61033-3_9

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DOI: 10.1007/978-3-030-61033-3_9

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