Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.768815
Title: The impact of big data on organisational problem solving : evidence from two UK smart cities initiatives
Author: Okwechime, Ekene
ISNI:       0000 0004 7655 5678
Awarding Body: Glasgow Caledonian University
Current Institution: Glasgow Caledonian University
Date of Award: 2018
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Abstract:
The preference for people to live and work in cities has led to the growth (and predicted future growth) of urban areas. 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 the challenges facing urban areas. Big data analytics provides support and insight for decision makers to creatively solve challenges affecting their cities. Therefore, the central question posed in this thesis explores to what extent big data impacts on organisational problem solving in smart city initiatives. Thus, the aim of this research is to investigate the impact of big data in public sector organisations on problem solving for the creation of smart cities. There has been no prior work on how city authorities identify the most efficient mechanisms to coordinate their problem solving activities for the creation of smart cities. Ultimately, this research draws from Volkema’s (1983) heuristics on problem solving in planning and design: problem expansion and problem reduction. The central argument of the thesis is that organisational stakeholders can deploy big data to carry out problem expansion and with the smart city concept they can carry out problem reduction. It is also argued that organisational stakeholders can deploy both heuristics with the smart city and big data concepts in smart city initiatives concurrently. This qualitative and interpretative study adopts an abductive approach, using multiple case studies, to examine the impact of big data on organisational problem solving for the creation of smart cities. The study consists of two smart city initiatives: situated in Bristol, England and Glasgow, Scotland. A multi-source approach - informal discussions, secondary data, in-depth semi-structured interviews (with ten elite stakeholders) and participant observations - was central to achieving the aim and objectives of the research. The analyses carried out for this research involved the thematic coding of interview transcripts, field notes and secondary data sources. These sources of data were triangulated to ensure the validity of research findings. The research findings centre on the development of an empirically informed conceptual framework on the impact of big data on organisational problem solving for the creation of smart cities. The original contributions to knowledge are two-fold: to theory and practice. To theory, it centres on the development of an empirically informed conceptual framework on the impact of big data for problem solving in public sector organisations for the creation of smart cities. To practice, contributions are made to (public sector) organisational stakeholders regarding good practices in their use of big data for problem solving in the creation of smart cities.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.768815  DOI: Not available
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