Wicked Problems, Problem Solving and Smart Cities: the Impacts of Big Data on Organisational Creativity

This research is an exploratory field, organisational level study, which examines the impact of big data on organisational problem-solving for smart cities. It assesses ways in which big data is used in addressing urban... [ view full abstract ]

This research is an exploratory field, organisational level study, which examines the impact of big data on organisational problem-solving for smart cities. It assesses ways in which big data is used in addressing urban issues, which have been conceived to be wicked problems. The rationale for the research is based on the rise in the preference of people living and working in cities, which has led to the growth (and predicted future growth) of cities. This growth poses challenges for planners and city-dwellers alike, such as in the development of infrastructure and the provision of basic services. The smart city concept is perceived to be a useful way to mitigate against challenges facing urban
areas. Big data analytics provides support and insight for decision makers in order to creatively solve challenges impacting their cities. From a review of the literature there has been no prior work linking big data and organisational problem-solving for addressing urban issues with the big data smart city concepts. This organizational level qualitative study adopts an abductive approach, through the use multiple case studies, to examine the impact of big data on organisational problem-solving in smart cities. The study consists of three smart city initiatives: situated in Bristol, Glasgow (both in the United
Kingdom) and Helsinki (Finland). A multi-source approach – informal discussions, secondary data, semi-structured interviews (nine elite stakeholders were interviewed) and participant observations – was used to achieve the aim and objectives of the research. The analyses carried out for this research was the thematic coding of interviews transcripts, field diaries and secondary data sources. These sources of data were triangulated to increase the validity of research findings. The original contributions to knowledge are two-fold: to theory and practice. To theory they relate
the development of the conceptual framework regarding the use of big data for organisational problem-solving for smart cities. The findings, building on an initial conceptual framework developed, which was re-evaluated in the light of the empirical data. This led to the identification of a set of themes that lead to problem-solving: A) problem identification; B) a decision-making
process that includes; ii) problem reframing and; ii) collaborations and C) problem solutions. These demonstrate that with big and smart cities, stakeholders/problem-solvers are able to deploy heuristics on problem solving: with big data comes problem expansion and smart city initiatives
comes problem reduction. For smart cities, it offers visions for what smart cities could be and what they set out to achieve. Also, the research points out that big data can also be open data and vice versa. To practise, recommendations are made to organisational stakeholders regarding good practices in their use of big data for organsational problem-solving for smart cities.