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Description
Adopting smart city tactics is important because it allows cities to develop sustainable communities through efficient policy initiatives. This study exemplifies how data analytics enables planners within smart cities to gain a better understanding of their population, and can make more informed choices based on these consumer choices. As a rising share of the millennial generation enters the workforce, cities across the world are developing policy initiatives in the hopes of attracting these highly educated individuals. Due to this generation's strength in driving regional economic vitality directly and indirectly, it is in the best interests of city planners to understand the preferences of millennials so this information can be used to improve the attractiveness of communities for this high-purchasing power, productive segment of the population. Past research has revealed a tendency within this demographic to make location decisions based on the degree of ‘livability’ in an area. This degree represents a holistic approach at defining quality of life through the interconnectedness of both the built and social environments in cities.
Due to the importance of millennials to cities around the globe, this study uses 2010 ZIP code area data and the Phoenix metropolitan area as a case study to test the relationships between thirteen parameters of livability and the presence of millennials after controlling for other correlates of millennial preference.
The results of a multiple regression model indicated a positive linear association between livability parameters within smart cities and the presence of millennials. Therefore, the selected parameters of livability within smart cities are significant measures in influencing location decisions made by millennials. Urban planners can consequently increase the likelihood in which millennials will choose to live in a given area by improving livability across the parameters exemplified in this study. This mutually beneficial relationship provides added support to the notion that planners should develop solutions to improve livability within smart cities.
Due to the importance of millennials to cities around the globe, this study uses 2010 ZIP code area data and the Phoenix metropolitan area as a case study to test the relationships between thirteen parameters of livability and the presence of millennials after controlling for other correlates of millennial preference.
The results of a multiple regression model indicated a positive linear association between livability parameters within smart cities and the presence of millennials. Therefore, the selected parameters of livability within smart cities are significant measures in influencing location decisions made by millennials. Urban planners can consequently increase the likelihood in which millennials will choose to live in a given area by improving livability across the parameters exemplified in this study. This mutually beneficial relationship provides added support to the notion that planners should develop solutions to improve livability within smart cities.
ContributorsBobman, Mitchell Cole (Author) / Mack, Elizabeth (Thesis director) / Koschinsky, Julia (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Geographical Sciences and Urban Planning (Contributor)
Created2015-05
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 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