This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

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Description
Organizational classifications are critical to a wide variety of stakeholders. Within the domain of higher education, researchers use established classifications for sample selection or within empirical models to account for unobserved organizational characteristics. Colleges and universities, as well as their political principals, often use classifications to form peer-groups and reference

Organizational classifications are critical to a wide variety of stakeholders. Within the domain of higher education, researchers use established classifications for sample selection or within empirical models to account for unobserved organizational characteristics. Colleges and universities, as well as their political principals, often use classifications to form peer-groups and reference sets through which organizational performance is assessed. More broadly, classifications provide aspirational archetypes to an organizational field.

Using American higher education as the empirical context, this dissertation introduces Latent Profile Analysis (LPA) as a method to identify the structure of an organizational field and to classify organizations within this structure. Using measures of model fit and concerns for interpretability, this investigation determined that 13 distinctive organizational designs are present in the field of American higher education. Derived groupings are compared to the 2018 Basic Classification from the Carnegie Classification of Institutions of Higher Education. Opportunities and challenges for operationalizing this derived classification are discussed.
ContributorsWhitman, Kyle Joseph (Author) / Crow, Michael M. (Thesis advisor) / Anderson, Derrick M (Thesis advisor) / Maroulis, Sprio J (Committee member) / Arizona State University (Publisher)
Created2020