ETDs

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.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.

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Progressibility: Why Can Some Technologies Improve More Rapidly Than Others?

Description
Over the last few hundred years, best practice in some fields of human action—e.g., the treatment of heart disease, the transportation of persons, goods, and messages, and the destruction of landscapes, structures, and lives—has become dramatically more effective. At the same time, best practice in other fields, e.g., the…

Over the last few hundred years, best practice in some fields of human action—e.g., the treatment of heart disease, the transportation of persons, goods, and messages, and the destruction of landscapes, structures, and lives—has become dramatically more effective. At the same time, best practice in other fields, e.g., the amelioration of poverty or the teaching of reading, writing, or math, has improved more slowly, if at all. I argue that practice and technology (“know-how”) can only improve rapidly under rather special conditions: that, at any given point in time, some fields are more “progressible” than others.I articulate a conceptual framework describing several characteristics of practice in a field that may facilitate rapid progress. These characteristics, while not fixed, tend to remain fairly stable for long periods of time. I argue that know-how can improve more quickly 1) when offline “vicarious trial” of variations in practice is feasible and useful; 2) when practice is formal and standardized; 3) when practice is substantially performed by artifacts rather than by humans; 4) when outcomes of variations in practice may be rapidly evaluated; 5) when goals of practice are consistently agreed upon; 6) when contexts and objects of practice may be treated as, or have been made, consistent for the purposes of intervention; 7) when components of task systems are not heavily interdependent; and 8) when labor is finely and sharply divided. I illustrate and elaborate this framework through comparative case studies on efforts to improve practice in three differentially “progressible” fields. I examine rapid improvement in a COVID-19 testing lab, inconsistent improvement in undergraduate algebra instruction, and ambiguous improvement in regional water modeling to support municipal water management. These cases indicate that my theory may inform judgments about the plausibility of rapid advance within a field of practice, absent disruptive change in methods or problem formulation. My theory may also shed light on which varieties of innovative effort may and may not foreseeably contribute to improving practice in a given field—more formal, theoretical, and context-independent work in high-progressibility domains, more tacit, grounded, and localized work in low-progressibility ones.
ContributorsNelson III, John Paul (Author) / Sarewitz, Daniel (Thesis advisor) / Bozeman, Barry (Committee member) / Guston, David (Committee member) / Arizona State University (Publisher)
Created2023
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State R&D Tax Credits: Social and Economic Outcomes

Description
Research and Development (R&D) tax credits are one of the most widely adopted policies state governments use to incentivize R&D spending by firms operating in a state. R&D spending is associated with increases in firm productivity, innovation, and higher wages. However, most studies into these tax credits examine only the…

Research and Development (R&D) tax credits are one of the most widely adopted policies state governments use to incentivize R&D spending by firms operating in a state. R&D spending is associated with increases in firm productivity, innovation, and higher wages. However, most studies into these tax credits examine only the effect the credit has on firm-based R&D spending and assume the increases in R&D spending mean states are receiving the social and economic benefits endogenous growth theory predicts. This dissertation connects R&D tax credits with the expected outcomes of R&D spending increases to evaluate the efficacy of the tax credits. Specifically, the dissertation connects R&D tax credits to the movement of researchers between states, innovative activity, and state fiscal health. The study uses a panel of U.S. PhD graduates and a fixed-effects linear probability model to show R&D tax credits have a small but statistically significant impact on PhDs moving to states that have the tax credit. Using a structural equation model and a latent innovation variable, the dissertation shows R&D tax credits have a small but significant impact on innovative activity mediated by R&D spending. Finally, the dissertation examines the effect of R&D tax credits on a state’s short- and long-run fiscal health by using a distributed lag model to illustrate R&D tax credits are associated with decreases with fiscal health.
ContributorsSelby, John David (Author) / Bretschneider, Stuart (Thesis advisor) / Bozeman, Barry (Committee member) / Siegel, Don (Committee member) / Swindell, David (Committee member) / Arizona State University (Publisher)
Created2020