Local governments have been developing online services, aiming to better serve the public and reduce administrative costs. However, the impact of this work, and the links between governments' online and offline activities, remain uncertain. Using a new full-population dataset of the UK government web, this thesis directly analyses the structure and content of government online. It argues that recent digital-centric public administration theories, typified by the Digital Era Governance quasi-paradigm, are not empirically supported by the UK local government experience. Instead, it argues for a positive but critical attitude to the value of technology in public administration. New methods are developed for full-text empirical analysis of government web crawl data and the use of machine learning approaches for adding attributes to full-population data. Webometric and content analyses of the .gov.uk web are conducted, together with a time-series panel regression of English local government cost, service quality, satisfaction, and an expert assessment of web provision. English local government online is highly heterogeneous and there is remarkably little intrinsic structure to the .gov.uk web. Geography is weakly visible in online government structures, but there is little evidence that online structures closely reflect the offline activities of government. Empirically, English local governments' web development levels are found not to be associated with improvement in the cost of, quality of, or satisfaction with council services, challenging the merit of online approaches to service improvement. Overall, the importance of digital-centric approaches to local government service improvement is challenged. A more nuanced theoretical approach to online service delivery is advocated, which discards utopian enthusiasm and focuses on concrete service improvements. It is recommended that full-population quantitative analyses be used more broadly in political science, with awareness of both the opportunities and the challenges associated with them.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:724888 |
| Date | January 2016 |
| Creators | Nicholls, Tom |
| Contributors | Margetts, Helen ; Nash, Victoria |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://ora.ox.ac.uk/objects/uuid:d85d7964-80d2-4b6d-bfac-418ed4f0fa6a |
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