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This thesis was conducted to study and analyze the fund allocation process adopted by different states in the United States to reduce the impact of the Covid-19 virus. Seven different states and their funding methodologies were compared against the case count within the state. The study also focused on development

This thesis was conducted to study and analyze the fund allocation process adopted by different states in the United States to reduce the impact of the Covid-19 virus. Seven different states and their funding methodologies were compared against the case count within the state. The study also focused on development of a physical distancing index based on three significant attributes. This index was then compared to the expenditure and case counts to support decision making.
A regression model was developed to analyze and compare how different states case counts played out against the regression model and the risk index.

ContributorsJaisinghani, Shaurya (Author) / Mirchandani, Pitu (Thesis director) / Clough, Michael (Committee member) / McCarville, Daniel R. (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Department of Information Systems (Contributor) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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This paper explores the history of sovereign debt default in developing economies and attempts to highlight the mistakes and accomplishments toward achieving debt sustainability. In the past century, developing economies have received considerable investment due to higher returns and a degree of disregard for the risks accompanying these investments. As

This paper explores the history of sovereign debt default in developing economies and attempts to highlight the mistakes and accomplishments toward achieving debt sustainability. In the past century, developing economies have received considerable investment due to higher returns and a degree of disregard for the risks accompanying these investments. As the former Citibank chairman, Walter Wriston articulated, "Countries don't go bust" (This Time is Different, 51). Still, unexpected negative externalities have shattered this idea as the majority of developing economies follow a cyclical pattern of default. As coined by Reinhart and Rogoff, sovereign governments that fall into this continuous cycle have become known as serial defaulters. Most developed markets have not defaulted since World War II, thus escaping this persistent trap. Still, there have been developing economies that have been able to transition out of serial defaulting. These economies are able to leverage debt to compound growth without incurring the protracted consequences of a default. Although the cases are few, we argue that developing markets such as Chile, Mexico, Russia, and Uruguay have been able to escape this vicious cycle. Thus, our research indicates that collaborative debt restructurings coupled with long term economic policies are imperative to transitioning out of debt intolerance and into a sustainable debt position. Successful economies are able to leverage debt to create strong foundational growth rather than gambling with debt in the hopes of achieving rapid catch- up growth.
ContributorsPitt, Ryan (Co-author) / Martinez, Nick (Co-author) / Choueiri, Robert (Co-author) / Goegan, Brian (Thesis director) / Silverman, Daniel (Committee member) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Politics and Global Studies (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
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Marijuana is the most commonly used illicit substance in the United States with over two million pounds seized annually and with a usage rate estimated at 19.8 million people in 2013 (SAMSHA, 2014). Currently there is a nationwide movement for the legalization of recreational marijuana via referendum at the state

Marijuana is the most commonly used illicit substance in the United States with over two million pounds seized annually and with a usage rate estimated at 19.8 million people in 2013 (SAMSHA, 2014). Currently there is a nationwide movement for the legalization of recreational marijuana via referendum at the state level. Three states and the District of Columbia have already adopted amendments legalizing marijuana and over a dozen more currently have pending ballots. This report explores what would be the impact of legalizing marijuana in Arizona through the examination of data from Colorado and other governmental sources. Using a benefit/cost analysis the data is used to determine what the effect the legalization of marijuana would have in Arizona. I next examined the moral arguments for legalization. Finally I propose a recommendation for how the issue of the legalization of recreational marijuana should be approached in Arizona.
ContributorsDiPietro, Samuel Miles (Author) / Kalika, Dale (Thesis director) / Lynk, Myles (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor)
Created2015-05
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Developed a business product with a team of CS Students

ContributorsHernandez, Maximilliano (Co-author) / Schneider, Kaitlin (Co-author) / Perri, Cole (Co-author) / Call, Andy (Thesis director) / Hunt, Neil (Committee member) / School of Accountancy (Contributor) / School of Sustainability (Contributor) / Department of Information Systems (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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The esports scene has been constantly evolving ever since its inception in the early 1970s, growing from small arcade based tournaments to the multibillion dollar industry that can be observed today (Bountie Gaming, 2018). In fact, the term esports was not widely used until the early 2000s, decades after the

The esports scene has been constantly evolving ever since its inception in the early 1970s, growing from small arcade based tournaments to the multibillion dollar industry that can be observed today (Bountie Gaming, 2018). In fact, the term esports was not widely used until the early 2000s, decades after the first gaming tournaments had taken place. Decades prior, the earliest large-scale gaming tournament was hosted by Atari in 1980 for the game ​Space Invaders ​ . While still primitive by today’s standards, games such as ​Space Invaders ​ inspired fierce competition and effectively laid the foundation for what would grow into the booming industry that we see today (Edwards, 2013).

ContributorsCollins, Neil Andrew (Author) / Mendez, Jose (Thesis director) / Foster, William (Thesis director) / Pierce, John (Committee member) / Department of Economics (Contributor) / WPC Graduate Programs (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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This project was organized to analyze a multitude of data in order to determine the economic impact of a professional sports team starting in a particular location, or “market”. The thesis group (“group”) collected historical data on professional sports teams from 1975 to present, state economic data as applicable, and

This project was organized to analyze a multitude of data in order to determine the economic impact of a professional sports team starting in a particular location, or “market”. The thesis group (“group”) collected historical data on professional sports teams from 1975 to present, state economic data as applicable, and data indicating sports fan preferences and behavior. This data was collected, cleaned, and analyzed in order to understand trends and impacts of sports teams in local economies. The group looked at a number of statistical factors including team performance, championships, state GDP and employment, and digital trends regarding the sports teams. Using economic models and statistics, the group was able to derive insights on the factors that cause sports teams to influence the economy they are located in. Additionally, the group analyzed reporting on teams in particular markets, as well as the financing surrounding stadiums to provide a diverse perspective on the topic. At a high level, starting a professional sports team in a new market does not have a significant impact on the economy: the data did not demonstrate statistical significance and qualitative analysis proved that the impact of a new team is negligible. The following serves as documentation and explanation of the group’s analysis on this topic.
ContributorsFriedman, Jared Davidson (Co-author) / Conner, Joshua (Co-author) / McClain, Jacob (Co-author) / Foster, William (Thesis director) / Lee, Christopher (Committee member) / Department of Information Systems (Contributor) / School of Accountancy (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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This study aims to examine how the use of consensus-based transactions, smart contracts,and interoperability, provided by blockchain, may benefit the blood plasma industry. Plasmafractionation is the process of separating blood into multiple components to garner benefitsof increased lifespan, specialized allocation, and decreased waste, thereby creating a morecomplex and flexible supply

This study aims to examine how the use of consensus-based transactions, smart contracts,and interoperability, provided by blockchain, may benefit the blood plasma industry. Plasmafractionation is the process of separating blood into multiple components to garner benefitsof increased lifespan, specialized allocation, and decreased waste, thereby creating a morecomplex and flexible supply chain. Traditional applications of blockchain are developed onthe basis of decentralization—an infeasible policy for this sector due to stringent governmentregulations, such as HIPAA. However, the trusted nature of the relations in the plasmaindustry’s taxonomy proves private and centralized blockchains as the viable alternative.Implementations of blockchain are widely seen across pharmaceutical supply chains to combatthe falsification of possibly afflictive drugs. This system is more difficult to manage withblood, due to the quick perishable time, tracking/tracing of recycled components, and thenecessity of real-time metrics. Key attributes of private blockchains, such as digital identity,smart contracts, and authorized ledgers, may have the possibility of providing a significantpositive impact on the allocation and management functions of blood banks. Herein, we willidentify the economy and risks of the plasma ecosystem to extrapolate specific applications forthe use of blockchain technology. To understand tangible effects of blockchain, we developeda proof of concept application, aiming to emulate the business logic of modern plasma supplychain ecosystems adopting a blockchain data structure. The application testing simulates thesupply chain via agent-based modeling to analyze the scalability, benefits, and limitations ofblockchain for the plasma fractionation industry.
ContributorsVallabhaneni, Saipavan K (Author) / Boscovic, Dragan (Thesis director) / Kellso, James (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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RecyclePlus is an iOS mobile application that allows users to be knowledgeable in the realms of sustainability. It gives encourages users to be environmental responsible by providing them access to recycling information. In particular, it allows users to search up certain materials and learn about its recyclability and how to

RecyclePlus is an iOS mobile application that allows users to be knowledgeable in the realms of sustainability. It gives encourages users to be environmental responsible by providing them access to recycling information. In particular, it allows users to search up certain materials and learn about its recyclability and how to properly dispose of the material. Some searches will show locations of facilities near users that collect certain materials and dispose of the materials properly. This is a full stack software project that explores open source software and APIs, UI/UX design, and iOS development.
ContributorsTran, Nikki (Author) / Ganesh, Tirupalavanam (Thesis director) / Meuth, Ryan (Committee member) / Watts College of Public Service & Community Solut (Contributor) / Department of Information Systems (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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This study examines the economic impact of the opioid crisis in the United States. Primarily testing the years 2007-2018, I gathered data from the Census Bureau, Centers for Disease Control, and Kaiser Family Foundation in order to examine the relative impact of a one dollar increase in GDP per Capita

This study examines the economic impact of the opioid crisis in the United States. Primarily testing the years 2007-2018, I gathered data from the Census Bureau, Centers for Disease Control, and Kaiser Family Foundation in order to examine the relative impact of a one dollar increase in GDP per Capita on the death rates caused by opioids. By implementing a fixed-effects panel data design, I regressed deaths on GDP per Capita while holding the following constant: population, U.S. retail opioid prescriptions per 100 people, annual average unemployment rate, percent of the population that is Caucasian, and percent of the population that is male. I found that GDP per Capita and opioid related deaths are negatively correlated, meaning that with every additional person dying from opioids, GDP per capita decreases. The finding of this research is important because opioid overdose is harmful to society, as U.S. life expectancy is consistently dropping as opioid death rates rise. Increasing awareness on this topic can help prevent misuse and the overall reduction in opioid related deaths.
ContributorsRavi, Ritika Lisa (Author) / Goegan, Brian (Thesis director) / Hill, John (Committee member) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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The prevalence of bots, or automated accounts, on social media is a well-known problem. Some of the ways bots harm social media users include, but are not limited to, spreading misinformation, influencing topic discussions, and dispersing harmful links. Bots have affected the field of disaster relief on social media as

The prevalence of bots, or automated accounts, on social media is a well-known problem. Some of the ways bots harm social media users include, but are not limited to, spreading misinformation, influencing topic discussions, and dispersing harmful links. Bots have affected the field of disaster relief on social media as well. These bots cause problems such as preventing rescuers from determining credible calls for help, spreading fake news and other malicious content, and generating large amounts of content which burdens rescuers attempting to provide aid in the aftermath of disasters. To address these problems, this research seeks to detect bots participating in disaster event related discussions and increase the recall, or number of bots removed from the network, of Twitter bot detection methods. The removal of these bots will also prevent human users from accidentally interacting with these bot accounts and being manipulated by them. To accomplish this goal, an existing bot detection classification algorithm known as BoostOR was employed. BoostOR is an ensemble learning algorithm originally modeled to increase bot detection recall in a dataset and it has the possibility to solve the social media bot dilemma where there may be several different types of bots in the data. BoostOR was first introduced as an adjustment to existing ensemble classifiers to increase recall. However, after testing the BoostOR algorithm on unobserved datasets, results showed that BoostOR does not perform as expected. This study attempts to improve the BoostOR algorithm by comparing it with a baseline classification algorithm, AdaBoost, and then discussing the intentional differences between the two. Additionally, this study presents the main factors which contribute to the shortcomings of the BoostOR algorithm and proposes a solution to improve it. These recommendations should ensure that the BoostOR algorithm can be applied to new and unobserved datasets in the future.
ContributorsDavis, Matthew William (Author) / Liu, Huan (Thesis director) / Nazer, Tahora H. (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12