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    • 2017 Dissertations (MU)
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    Bureaucratic organization and innovation : a mixed-methods study of U.S. state department of transportation website adoption

    Million, A. J.
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    [PDF] public.pdf (2.182Kb)
    [PDF] research.pdf (1.427Mb)
    [PDF] short.pdf (35.92Kb)
    Date
    2017
    Format
    Thesis
    Metadata
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    Abstract
    [ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This study explores bureaucratic organization and innovation in U.S. state department of transportation (DOT) websites. To determine if working with third parties fosters change in state DOT websites, it employs a two-part, explanatory sequential mixed-methods design. In phase one, an online survey was disseminated to IT managers and communications officers in all 50 states to collect data regarding agency demographics, bureaucratic models, and Web infrastructure. In total, 45 valid responses (or 90 percent) were received from DOTs indicating that most built, hosted, and managed their websites in-house, but that state-level IT consolidations required many to pool resources with third parties. In research phase two, 12 semi-structured interviews were conducted of a maximum variation sample of survey respondents. These interviews were conducted to explain why DOTs built and operated their websites with the support of third parties. Employing a grounded theoretical approach, analysis revealed 6 themes explaining website adoption and showed that working with third parties can foster innovation; however, not all change is positive. Therefore, a need exists for governments to selectively work with others, ascertain future barriers to change, and ensure that adopted innovations meet desired ends. Finally, five best practices informed by study findings are presented that may help decision-makers and civil servants provide e-government services in a flexible manner.
    URI
    https://hdl.handle.net/10355/61886
    Degree
    Ph. D.
    Thesis Department
    Information science and learning technologies (MU)
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    • Information Science and Learning Technologies electronic theses and dissertations (MU)
    • 2017 MU dissertations - Access restricted to MU

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