This study explores the question, How are individual adoption and organizational implementation of innovations in higher education related to the context of the organization, the characteristics of the innovation, and the attitudes of adopters? The study uses data collected from a survey of deans and department chairs from U.S. higher education institutions to examine the implementation of data analytics, or the extensive use of data, statistical analysis, data mining and modeling to drive organizational decisions, as an example of an organizational innovation. The findings indicate that individual adoption is associated with the adopter's perception of the usefulness of data analytics in practice and its legitimacy in solving organizational challenges. The usefulness of data analytics is related to the innovation characteristics of usability and functionality, which are in turn related to an organizational context that includes institutional and professional support for adoption, academic leaders engaged in implementation, data and information integrated into existing operations, and an organizational culture that is data-driven. Legitimacy is related to the functionality of data analytics and the existence of a data-driven culture but also the discipline of the adopter and institution type. The findings also indicate that organizational implementation of data analytics is associated with the alignment of data analytics to its organizational culture, the pressure exerted by the external environment, and the organization's dissatisfaction with current external methods or practices in use.
University of Minnesota Ph.D. dissertation. November 2014. Major: Organizational Leadership, Policy, and Development. Advisor: Melissa S. Anderson. 1 computer file (PDF); viii, 165 pages, appendices A-C.
Foss, Lisa Helmin.
Implementing data analytics as an organizational innovation in colleges and universities.
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