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- All Subjects: sports
- Creators: Department of Information Systems
- Status: Published
Description
This paper is intended to identify a correlation between the winning percentage of sports teams in the four major professional sports leagues in the United States and the GDP per capita of their respective cities. We initially compiled fifteen years of franchise performance along with economic data from the Federal Reserve Bank of St. Louis to analyze this relationship. After converting the data into a language recognized by Stata, the regression tool we used, we ran multiple regressions to find relevant correlations based off of our inputs. This paper will show the value of the economic impact of strong or weak performance throughout various economic cycles through data analysis and conclusions drawn from the results of the regression analysis.
ContributorsAndl, Tyler (Co-author) / Shirk, Brandon (Co-author) / Goegan, Brian (Thesis director) / Eaton, John (Committee member) / School of Accountancy (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
We were driven by the question: what is happening to the popularity of Major League Baseball? In order to answer this question we compared the league structure of Major League Baseball with that of the National Football League. We were able to speak with five former or current members of the respective leagues in order to gain some insight into how the two leagues operate. The main focus of our research was around the payroll structures of the two leagues as well as their revenue sharing policies. In the end, we discovered that Major League Baseball is becoming highly regionalized. The sport is still growing in popularity in terms of revenue and fan involvement, but it is becoming less popular on a national stage. The league is benefitting greatly from factors like the increasing importance of "TiVo proof programming" and a lack of competition. Each league is very different in its own right. While the NFL promotes a perception of competitive balance, Major League Baseball can be plagued by the negative perception it creates surrounding some of its smaller market teams.
ContributorsHeath, Cameron (Co-author) / Linamen, John (Co-author) / Eaton, John (Thesis director) / Mokwa, Michael (Committee member) / Barrett, The Honors College (Contributor) / WPC Graduate Programs (Contributor) / Department of Marketing (Contributor) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / School of Accountancy (Contributor)
Created2015-05
Description
Over the course of six months, we have worked in partnership with Arizona State University and a leading producer of semiconductor chips in the United States market (referred to as the "Company"), lending our skills in finance, statistics, model building, and external insight. We attempt to design models that help predict how much time it takes to implement a cost-saving project. These projects had previously been considered only on the merit of cost savings, but with an added dimension of time, we hope to forecast time according to a number of variables. With such a forecast, we can then apply it to an expense project prioritization model which relates time and cost savings together, compares many different projects simultaneously, and returns a series of present value calculations over different ranges of time. The goal is twofold: assist with an accurate prediction of a project's time to implementation, and provide a basis to compare different projects based on their present values, ultimately helping to reduce the Company's manufacturing costs and improve gross margins. We believe this approach, and the research found toward this goal, is most valuable for the Company. Two coaches from the Company have provided assistance and clarified our questions when necessary throughout our research. In this paper, we begin by defining the problem, setting an objective, and establishing a checklist to monitor our progress. Next, our attention shifts to the data: making observations, trimming the dataset, framing and scoping the variables to be used for the analysis portion of the paper. Before creating a hypothesis, we perform a preliminary statistical analysis of certain individual variables to enrich our variable selection process. After the hypothesis, we run multiple linear regressions with project duration as the dependent variable. After regression analysis and a test for robustness, we shift our focus to an intuitive model based on rules of thumb. We relate these models to an expense project prioritization tool developed using Microsoft Excel software. Our deliverables to the Company come in the form of (1) a rules of thumb intuitive model and (2) an expense project prioritization tool.
ContributorsAl-Assi, Hashim (Co-author) / Chiang, Robert (Co-author) / Liu, Andrew (Co-author) / Ludwick, David (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Department of Economics (Contributor) / Department of Supply Chain Management (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / WPC Graduate Programs (Contributor)
Created2015-05
Description
Coherent vortices are ubiquitous structures in natural flows that affect mixing and transport of substances and momentum/energy. Being able to detect these coherent structures is important for pollutant mitigation, ecological conservation and many other aspects. In recent years, mathematical criteria and algorithms have been developed to extract these coherent structures in turbulent flows. In this study, we will apply these tools to extract important coherent structures and analyze their statistical properties as well as their implications on kinematics and dynamics of the flow. Such information will aide representation of small-scale nonlinear processes that large-scale models of natural processes may not be able to resolve.
ContributorsCass, Brentlee Jerry (Author) / Tang, Wenbo (Thesis director) / Kostelich, Eric (Committee member) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Exchange traded funds (ETFs) in many ways are similar to more traditional closed-end mutual funds, although thee differ in a crucial way. ETFs rely on a creation and redemption feature to achieve their functionality and this mechanism is designed to minimize the deviations that occur between the ETF’s listed price and the net asset value of the ETF’s underlying assets. However while this does cause ETF deviations to be generally lower than their mutual fund counterparts, as our paper explores this process does not eliminate these deviations completely. This article builds off an earlier paper by Engle and Sarkar (2006) that investigates these properties of premiums (discounts) of ETFs from their fair market value. And looks to see if these premia have changed in the last 10 years. Our paper then diverges from the original and takes a deeper look into the standard deviations of these premia specifically.
Our findings show that over 70% of an ETFs standard deviation of premia can be explained through a linear combination consisting of two variables: a categorical (Domestic[US], Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market indicators such as the economic freedom index and investment freedom index are insignificant predictors of an ETFs standard deviation of premia when combined with the categorical variable. These findings differ somewhat from existing literature which indicate that these factors should have a significant impact on the predictive ability of an ETFs standard deviation of premia.
Our findings show that over 70% of an ETFs standard deviation of premia can be explained through a linear combination consisting of two variables: a categorical (Domestic[US], Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market indicators such as the economic freedom index and investment freedom index are insignificant predictors of an ETFs standard deviation of premia when combined with the categorical variable. These findings differ somewhat from existing literature which indicate that these factors should have a significant impact on the predictive ability of an ETFs standard deviation of premia.
ContributorsZhang, Jingbo (Co-author, Co-author) / Henning, Thomas (Co-author) / Simonson, Mark (Thesis director) / Licon, L. Wendell (Committee member) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
In this research paper I explore former male athletes, specifically professional football players entering local journalism. Research paired with interviews in regards to the topic explain why there are nearly 10 former NFL players in local markets where an NFL team is present, and why local journalists along with future journalists should not be worried about the number of former male athletes in local journalism. The paper also dives into the side-by-side statistics of why there is significantly more former college athletes in local journalism than former NFL players. The research focused on more than 100 television stations, revealing that 100 former or current collegiate or pro athletes are journalists for local stations where an NFL team is present. The data is solely reliant on the information that the journalists provided in their bios on the station websites. This could be seen as a possible limitation, however, the likelihood of these journalists either lying or not identifying as a former athlete is minimal due to the size of the accomplishment of actually participating in college as an athlete. The basis of my research is to figure out if former NFL players and former athletes in general are taking journalism jobs from aspiring journalists. I conclude that future journalists are not at risk of losing jobs when it comes to retired football players entering the field of local journalism. With that said, aspiring journalists need to continue to develop their social media skills to compete with athletes’ audiences on social networks.
ContributorsTotri, Anthony Matthew (Author) / Kurland, Brett (Thesis director) / Reed, Sada (Committee member) / Walter Cronkite School of Journalism & Mass Comm (Contributor, Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The object of the present study is to examine methods in which the company can optimize their costs on third-party suppliers whom oversee other third-party trade labor. The third parties in scope of this study are suspected to overstaff their workforce, thus overcharging the company. We will introduce a complex spreadsheet model that will propose a proper project staffing level based on key qualitative variables and statistics. Using the model outputs, the Thesis team proposes a headcount solution for the company and problem areas to focus on, going forward. All sources of information come from company proprietary and confidential documents.
ContributorsLoo, Andrew (Co-author) / Brennan, Michael (Co-author) / Sheiner, Alexander (Co-author) / Hertzel, Michael (Thesis director) / Simonson, Mark (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor)
Created2014-05
Description
Cognitive technology has been at the forefront of the minds of many technology, government, and business leaders, because of its potential to completely revolutionize their fields. Furthermore, individuals in financial statement auditor roles are especially focused on the impact of cognitive technology because of its potential to eliminate many of the tedious, repetitive tasks involved in their profession. Adopting new technologies that can autonomously collect more data from a broader range of sources, turn the data into business intelligence, and even make decisions based on that data begs the question of whether human roles in accounting will be completely replaced. A partial answer: If the ramifications of past technological advances are any indicator, cognitive technology will replace some human audit operations and grow some new and higher order roles for humans. It will shift the focus of accounting professionals to more complex judgment and analysis.
The next question: What do these changes in the roles and responsibilities look like for the auditors of the future? Cognitive technology will assuredly present new issues for which humans will have to find solutions.
• How will humans be able to test the accuracy and completeness of the decisions derived by cognitive systems?
• If cognitive computing systems rely on supervised learning, what is the most effective way to train systems?
• How will cognitive computing fair in an industry that experiences ever-changing industry regulations?
• Will cognitive technology enhance the quality of audits?
In order to answer these questions and many more, I plan on examining how cognitive technologies evolved into their use today. Based on this historic trajectory, stakeholder interviews, and industry research, I will forecast what auditing jobs may look like in the near future taking into account rapid advances in cognitive computing.
The conclusions forecast a future in auditing that is much more accurate, timely, and pleasant. Cognitive technologies allow auditors to test entire populations of transactions, to tackle audit issues on a more continuous basis, to alleviate the overload of work that occurs after fiscal year-end, and to focus on client interaction.
The next question: What do these changes in the roles and responsibilities look like for the auditors of the future? Cognitive technology will assuredly present new issues for which humans will have to find solutions.
• How will humans be able to test the accuracy and completeness of the decisions derived by cognitive systems?
• If cognitive computing systems rely on supervised learning, what is the most effective way to train systems?
• How will cognitive computing fair in an industry that experiences ever-changing industry regulations?
• Will cognitive technology enhance the quality of audits?
In order to answer these questions and many more, I plan on examining how cognitive technologies evolved into their use today. Based on this historic trajectory, stakeholder interviews, and industry research, I will forecast what auditing jobs may look like in the near future taking into account rapid advances in cognitive computing.
The conclusions forecast a future in auditing that is much more accurate, timely, and pleasant. Cognitive technologies allow auditors to test entire populations of transactions, to tackle audit issues on a more continuous basis, to alleviate the overload of work that occurs after fiscal year-end, and to focus on client interaction.
ContributorsWitkop, David (Author) / Dawson, Gregory (Thesis director) / Munshi, Perseus (Committee member) / School of Accountancy (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Our research encompassed the prospect draft in baseball and looked at what type of player teams drafted to maximize value. We wanted to know which position returned the best value to the team that drafted them, and which level is safer to draft players from, college or high school. We decided to look at draft data from 2006-2010 for the first ten rounds of players selected. Because there is only a monetary cap on players drafted in the first ten rounds we restricted our data to these players. Once we set up the parameters we compiled a spreadsheet of these players with both their signing bonuses and their wins above replacement (WAR). This allowed us to see how much a team was spending per win at the major league level. After the data was compiled we made pivot tables and graphs to visually represent our data and better understand the numbers. We found that the worst position that MLB teams could draft would be high school second baseman. They returned the lowest WAR of any player that we looked at. In general though high school players were more costly to sign and had lower WARs than their college counterparts making them, on average, a worse pick value wise. The best position you could pick was college shortstops. They had the trifecta of the best signability of all players, along with one of the highest WARs and lowest signing bonuses. These were three of the main factors that you want with your draft pick and they ranked near the top in all three categories. This research can help give guidelines to Major League teams as they go to select players in the draft. While there are always going to be exceptions to trends, by following the enclosed research teams can minimize risk in the draft.
ContributorsValentine, Robert (Co-author) / Johnson, Ben (Co-author) / Eaton, John (Thesis director) / Goegan, Brian (Committee member) / Department of Finance (Contributor) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / School of Accountancy (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
The National Basketball Association is the world's most recognized professional basketball league. Athletes such as Kobe Bryant and Lebron James have transcended from being high school standouts to global icons, but their careers might not have panned out the same way if they weren't allowed to declare for the draft immediately upon graduating high school. In 2005, the NBA and the NBA Players Association agreed to implement an age limit for athletes declaring for the NBA Draft. Although this was supposed to reduce the quantity of younger players declaring for the draft, the rule has been ineffective as the average age of lottery picks, also known as the first 14 picks of the draft, has decreased since the rule's implementation. Adam Silver, the current commissioner of the NBA, has been vocal about potentially raising the minimum draft-eligible age once more because of NBA team executives calling recent draft picks unfit for the NBA. The purpose of this research is to examine if lottery picks are indeed "NBA ready" upon being drafted, and if there is a correlation between the age at which they are drafted, the pick at which they were selected, the length of their career, and their career success. Various statistical analysis techniques are utilized, such as the calculation of R-squared values and correlation coefficients, and the usage of t-tests and multiple regressions. Box score statistics such as minutes per game, points per game, rebounds, and assists as well as advanced metrics such as player efficiency rating, win shares, box plus/minus, and value over replacement player were the focal point of this study. Players drafted with lottery selections from the 1985-2016 drafts had their career statistics compiled and examined for this analysis in order to adequately conduct the regressions. The results indicate that although lottery picks are having a decreasing immediate impact upon being drafted, the younger an athlete is drafted, the more long-term success they can expect to achieve in the NBA.
ContributorsKender, Mitchell Edward (Author) / McIntosh, Daniel (Thesis director) / Eaton, John (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05