Digitization and urban governance: The city as a reflection of its data infrastructure
| Author | Ali Bayat,Peter Kawalek |
| DOI | http://doi.org/10.1177/00208523211033205 |
| Published date | 01 March 2023 |
| Date | 01 March 2023 |
| Subject Matter | Articles |
Digitization and urban
governance: The city as
areflection of its data
infrastructure
Ali Bayat
University of Aberdeen, UK
Peter Kawalek
Loughborough University, UK
Abstract
This article introduces the ‘House Model’, an integrated framework consisting of four
data governance modes, based on the urban and smart city vision, context, and big
data technologies. The model stems from engaged scholarship, synthesizing and extend-
ing the academic debates and evidence from existing smart city initiatives. It provides a
means for comparing cities in terms of their digitization efforts, helps the planning of
more effective urban data infrastructures and guides future empirical research in this
area. The article contributes to the literature examining the issue of big data and its gov-
ernance in local government and smart cities.
Points for practitioners
Data is a vital part of smart city initiatives. Where the data comes from, who owns it
and how it is used are all important questions. Data governance is therefore important
and has consequences for the overall governance of the city. The House Model pre-
sented in this article provides a means for organizing data governance. It relates ques-
tions of data governance to the history and vision of smart city initiatives, and provides
a typology organizing these initiatives.
Keywords
big data, citizen participation, digital-era governance, digitization, smart cities, urban
governance
Corresponding author:
Ali Bayat,University ofAberdeen, Room 733,MacRobert Building,Kings College, Aberdeen, AB24 5UA,Scotland.
Email: ali.bayat@abdn.ac.uk
Article
International
Review of
Administrative
Sciences
International Review of Administrative
Sciences
2023, Vol. 89(1) 21–38
© The Author(s) 2021
Article reuse guidelines:
sagepub.com/journals-permissions
DOI: 10.1177/00208523211033205
journals.sagepub.com/home/ras
Introduction
Modern cities are ‘datafied’(Meijer, 2018). Data is central to modern citizenry and is
likely to originate bottom-up from the carriers of mobile phones, the users of dash-cams
and sensors, and not just from a top-down, central governance structure. Digital-era gov-
ernance can be centralized through the integration and centralization of government pro-
cesses, or it can be decentralized and public services organized around the needs of the
citizens (Dunleavy et al., 2006; Margetts and Dunleavy, 2013). Urban data is a key
feature of digital-era governance and how it is planned can substantially determine the
outcome of modern governance systems(Brown and Toze, 2017). An issue facing policy-
makers is, then, how to plan urban data to ensure citizen participation in the co-production
of solutions in public service design and delivery.
Today, local governments’attempts to manage urban data have mostly flourished in
the form of smart city initiatives (SCIs). The global market for smart city solutions is esti-
mated to grow with a compound annual rate of more than 28% and is forecast to be worth
US$2.27 trillion by the end of 2023 (Netscribes, 2018). Evidence suggests that smart
cities are heterogeneous in terms of their governance outcomes. While previous studies
have highlighted this heterogeneity (e.g. Hollands, 2008, 2015; Neirotti et al., 2014;
Söderström et al., 2014), less attention has been paid to the characteristics that give
rise to such differences and, from such an analysis, to providing policy guidelines on
the design and planning of more effective initiatives.
This research synthesizes fragmentedviews about the institutionalization of urban data
and provides a more coherent frameworkfor understanding the strategic planning of SCIs.
This framework, named the ‘House Model’, drawsupon a government-sponsored research
project into questions of governance and data infrastructure (Kawalek and Bayat,
2017). The study relies upon the key principles of engaged scholarship (Van De Ven,
2007, 2018). The framework is developed through insight gained from direct discussions
with practitioners, plus evidence across the literature,and was validated as part of engage-
ment with a government agency.
Basedonemergentfindings, the framework brings together factors such as urban and
smart city vision, context, and big data technologies, which, alongside different data arrange-
ments, forman assemblage. The merits of sucha framework are threefold: first, it provides a
lens through which cities can be compared through their digitization efforts; second, it
sketches a roadmap useful to those policymakers who are in the process of designing and
planning an SCI; and, third, it provides a foundation for future empirical research into the
issue of governance in SCIs.
The main contribution of this article is to the literature examining the issue of data gov-
ernance in local government and smart cities (e.g. Gupta et al., 2020; Micheli et al., 2020;
Paskaleva et al., 2017). Figure 1 depicts the agenda followed in the article. The article is
organized as follows. The second section provides an overview of urban digitization and
its potential impact on urban governance, and reviews the data governance literature. The
third section elaborates on the definition of the smart city. The fourth section introduces
the House Model. Finally, the last section concludes and provides recommendations for
future research.
22 International Review of Administrative Sciences 89(1)
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