Global city population has been growing dramatically in the last few decades, with the majority of the growth taking place in less developed countries. In search of effective and efficient solutions for pressing urban issues primarily concerning energy consumption, transportation and climate change, governments have turned to “smart” technologies and data-enabled tools. “Making a city “smart” is emerging as a strategy to mitigate the problems generated by the urban population growth and rapid urbanization” (Chourabi et al., 2012, p. 2289). Cities have rapidly embarked on a “smart city” journey, asserting that people’s and community’s needs are at the heart of this vision and hence make urban communities more “sustainable and resilient”.
Opening public data, citizen participation and collaboration among all stakeholders are considered crucial to solving pressing issues of urbanisation (The Open Data Institute, 2016). The questions remain: who identifies these issues, and how? We have accumulated knowledge about data-driven solutions, but how can we ensure that these solutions benefit citizens? ‘Smart’ approaches are often derisively criticized as solutions looking for problems.
Since 2005, large technology companies such as Cisco and IBM championed the technology to provide governments with necessary “smart city” systems aimed at ensuring public safety and the technologically controlled operation of urban infrastructure and services, such as city planning, building maintenance, transportation, and the distribution of water and electricity (Harrison and Donnelly, 2011). While the most articulated benefits of smart cities are efficiency gains from the use of the technology, it is unclear who benefits most from smart city interventions and how the problems, which smart cities aim to address are formed and framed. Country-specific characteristics including economic development and political agendas also influence the “smartness” of its cities: how smart polices are designed and planned (Neirotti et al., 2014).
The emergence of smart cities presents new opportunities for stakeholder engagement and use of communication technologies and data to inform the design of smart city interventions, which could bring wider benefits to all. Defining citizen-centric in the context of smart cities requires a thorough look at the processes that emerge in the cities, especially as they employ these at a problem definition stage.
The proposed study aims to explore how cities especially in less developed countries such as Tanzania currently employ data-driven approaches in making their cities 'smarter' and more citizen-centric. The research will use grounded theory and qualitative research methods to examine case studies of global cities as to how they engage with city communities in identifying urban problems. The study will focus on smart city instances and draw on the experience of cities in different economic and social contexts to understand how they use data and adopt “citizen-centric” practices to deliver results for their cities.
Overall, the study will contribute to the development of a theoretical basis for citizen-centric smart cities, which is currently mostly grounded in practice. The findings will also provide a basis for a theoretical framework for an initial problem definition in the context of smart cities to design interventions that address the needs of all stakeholders in the political economy of the city.
This author is supported by the Horizon Centre for Doctoral Training at the University of Nottingham (RCUK Grant No. EP/L015463/1) and The Open Data Institute.