Matching Items (52)
Description
This paper intends to analyze the National Football League (NFL) and the role stadiums play within it. The NFL, being the nation's largest professional sports league, has experienced a large amount of volatility over the past couple of decades. Teams have relocated a significant number of times and stadium projects have grown in size, cost, and frequency. Because of these observations, we chose to focus in on this particular sports league in order to answer our many questions surrounding the role of a professional sports stadium in the economics of a city. We seek to understand the economics these sports stadiums impact on the league and the cities they reside in. To do this, we compiled data of NFL franchise wins, average ticket prices, stadiums, and franchise values, while researching the stadium building process and referencing the opinions of leading sports economists across the nation. Next, we discussed the process of building a stadium, which entails the core steps of design, construction, cost, and funding. We discuss tax-exempt municipal bonds, and explain what an impact economic analysis is and how teams use them to get cities to support their projects. Moreover, we discuss the threats of relocation and how the NFL can exert pressure on stadium project decisions. Finally, we talk about the future of the NFL, with a new trend of empty stadiums and make predictions for upcoming relocation destinations. Based on these findings, we draw conclusions on the economics of sports stadiums and offer our opinion on the current state of the NFL.
ContributorsGuillen, Sergio (Co-author) / Willms, Jacob (Co-author) / Goegan, Brian (Thesis director) / Eaton, John (Committee member) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
In the last decade, the population of honey bees across the globe has declined sharply leaving scientists and bee keepers to wonder why? Amongst all nations, the United States has seen some of the greatest declines in the last 10 plus years. Without a definite explanation, Colony Collapse Disorder (CCD) was coined to explain the sudden and sharp decline of the honey bee colonies that beekeepers were experiencing. Colony collapses have been rising higher compared to expected averages over the years, and during the winter season losses are even more severe than what is normally acceptable. There are some possible explanations pointing towards meteorological variables, diseases, and even pesticide usage. Despite the cause of CCD being unknown, thousands of beekeepers have reported their losses, and even numbers of infected colonies and colonies under certain stressors in the most recent years. Using the data that was reported to The United States Department of Agriculture (USDA), as well as weather data collected by The National Centers for Environmental Information (NOAA) and the National Centers for Environmental Information (NCEI), regression analysis was used to investigate honey bee colonies to find relationships between stressors in honey bee colonies and meteorological variables, and colony collapses during the winter months. The regression analysis focused on the winter season, or quarter 4 of the year, which includes the months of October, November, and December. In the model, the response variables was the percentage of colonies lost in quarter 4. Through the model, it was concluded that certain weather thresholds and the percentage increase of colonies under certain stressors were related to colony loss.
ContributorsVasquez, Henry Antony (Author) / Zheng, Yi (Thesis director) / Saffell, Erinanne (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Entertainment journalism is a field that is easily misunderstood. Too many times its credibility is overlooked in favor of its hard news and sports counterparts. But the celebrity and gossip reporting industry has been a fixture in American journalism since the early 20th century. Readership and demand has steadily increased in the past 50 years for it to become a booming industry of magazines, news shows, websites and blogs all devoted to covering a unique aspect of the entertainment industry. From news about Angelina Jolie’s pregnancy to the status of production on the Batman reboot, the content covered is as diverse as it is compelling. However, there are many who believe that this genre of journalism consists of untruthful, frivolous fluff crafted by conning liars disguised as writers. The purpose of this thesis is to examine the field of entertainment and celebrity journalism and describe how it should be treated as a serious and respected genre of journalism due to its rigorous standards and the significant impact it has on the industry it covers—Hollywood.
ContributorsKuni, Ellen Marie (Author) / Brown, Aaron (Thesis director) / Gilpin, Dawn (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / Walter Cronkite School of Journalism and Mass Communication (Contributor)
Created2014-05
Description
This project is a business analysis of Corner Archery, a Glendale, AZ Archery shop. It addresses the various roles of the different employee positions within the company with a focus on the owner's responsibilities in particular. It also analyzes the business from an operations and revenue driver standpoint, making proposals to improve each of these areas.
ContributorsBecwar, Alea Louise (Author) / Peck, Sidnee (Thesis director) / LePine, Marcie (Committee member) / Ostrom, Lonnie (Committee member) / Barrett, The Honors College (Contributor) / Department of Management (Contributor) / Department of Marketing (Contributor)
Created2013-12
Description
Beginning with the publication of Moneyball by Michael Lewis in 2003, the use of sabermetrics \u2014 the application of statistical analysis to baseball records - has exploded in major league front offices. Executives Billy Beane, Paul DePoedesta, and Theo Epstein are notable figures that have been successful in incorporating sabermetrics to their team's philosophy, resulting in playoff appearances and championship success. The competitive market of baseball, once dominated by the collusion of owners, now promotes innovative thought to analytically develop competitive advantages. The tiered economic payrolls of Major League Baseball (MLB) has created an environment in which large-market teams are capable of "buying" championships through the acquisition of the best available talent in free agency, and small-market teams are pushed to "build" championships through the drafting and systematic farming of high-school and college level players. The use of sabermetrics promotes both models of success \u2014 buying and building \u2014 by unbiasedly determining a player's productivity. The objective of this paper is to develop a regression-based predictive model that can be used by Majors League Baseball teams to forecast the MLB career average offensive performance of college baseball players from specific conferences. The development of this model required multiple tasks: I. Data was obtained from The Baseball Cube, a baseball records database providing both College and MLB data. II. Modifications to the data were applied to adjust for year-to-year formatting, a missing variable for seasons played, the presence of missing values, and to correct league identifiers. III. Evaluation of multiple offensive productivity models capable of handling the obtained dataset and regression forecasting technique. IV. SAS software was used to create the regression models and analyze the residuals for any irregularities or normality violations. The results of this paper find that there is a relationship between Division 1 collegiate baseball conferences and average career offensive productivity in Major Leagues Baseball, with the SEC having the most accurate reflection of performance.
ContributorsBadger, Mathew Bernard (Author) / Goegan, Brian (Thesis director) / Eaton, John (Committee member) / Department of Economics (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
FastStat is a responsive website designed to work on any handheld, laptop, or desktop device. It serves as a first step into statistical calculations, educating the user on the basics of statistical analysis, and guiding them as they perform analyses of their own using built-in calculators. The calculators available can perform z tests, t tests, chi square tests, and analysis of variance tests to determine significant characteristics of the user's data. Outputted data includes means, standard deviations, significance levels, applicable statistics, and worded results indicating the outcome of the performed test. With its clean design, FastStat directs the user in an intuitive manner to fill in the information needed, giving clear indications of what types of values are needed where and flagging descriptive error messages if any inputted values are incorrect. FastStat also implements a halt to calculations if any errors are found, which saves time by avoiding impossible calculations. Once complete, FastStat outputs a variety of information of use to the user in a clearly labeled manner. The calculators are designed in such a way that the user will know what information they will get out of the calculator before performing any calculations at all. Aside from the calculators, FastStat includes introductory pages designed to get users familiar with common statistical terms and the associated tests, solidifying its purpose as an introductory tool. All tests are described by their typical uses, necessary inputs, calculated outputs, and extra notes of importance. Many terms are defined for the purpose of statistics, complete with examples to help educate the user on the concepts. With the information available, even the newest statistician can learn and begin performing tests almost immediately.
ContributorsBroin, Demetri Evan (Author) / Squire, Susan (Thesis director) / Samara, Marko (Committee member) / Graphic Information Technology (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Customer lifetime value has been a popular topic within the marketing field with which many researchers and marketing managers have been dwelling. The topic plays an important role in customer segmentation and has been studied and applied in a variety of business areas. The main objective of customer lifetime value and customer segmentation is to classify the importance level of each client to a company and compare it to other clients. Questions, such as which marketing strategies should be implemented for which customers and how much should be invested in a certain group of customers can all be answered by customer lifetime value and customer segmentation. However, the related literature is missing comparative research on assessing the amount of time from the initial point of acquisition that a client needs to be with the company in order to accurately predict its customer segment. This paper intends to provide a clarification to the problem. Purpose: Analyze customer profitability with clustering analysis and identify how many years does a customer need to be with a company to accurately predict its customer segment. By determining this number, managers can understand their clients better and establish which clients will most likely yield a greater profit at an early stage of the relationship. Methodology: Using data mining to clean and prepare our financial services dataset, we selected young clients who were less than ten years old. Linear regression and K-means clustering analyses then returned five clusters of clients. Next, we predicted the accuracy levels of customers with two to seven data points against the "correct" segment. Lastly, we validated our overall prediction accuracy levels using the chance probability and the desired classification accuracy, calculated from a discriminant analysis. Findings: We found that using five data points or more to cluster returned percentage accuracies greater than the desired classification accuracy. However, this desired classification accuracy and the percentage accuracies were fairly low and not sufficient to use as a base for business decisions and other managerial purposes.
ContributorsOng, Kaitlyn (Co-author) / Tsen, Canh (Co-author) / Hollmann, Thomas (Thesis director) / Han, Sang Pil (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
With 2016 marking the 100th Anniversary of the National Park Service (NPS), important discussions regarding the future of America's beloved parks and respective government funding must take place. Imagine all the money, including tax revenue, flowing through America's national parks system, and where is that money destined for in the future? National park funding will factor greatly into determining the future of America's NPS and individual parks. Therefore, it is imperative to investigate where and how government funding, for the present and future, is distributed throughout the parks protected under the NPS. Through personal experiences as a child, national parks consistently provide a unique exposure to and an education of the natural world, which are rare finds when growing up in suburban or metropolitan regions. Narrowing down, this analysis will focus on government disbursements to Yellowstone National Park (Yellowstone) and Isle Royale National Park (Isle Royale) with specifics on two budgeted projects crucial to park survival. Yellowstone and Isle Royale each request funding for a project crucial to the park's ecosystem and a project intended to improve guest services for visitors. Closing comments will provide recommendations for Yellowstone, Isle Royale and the NPS, including effects of President Trump's 2018 Government Proposed Budget, in an attempt to offer forward thinking about national parks. The projects and respective funding as detailed in this analysis have a forward-thinking focus as other projects included in the NPS requested funding budgets consider as well. Current actions and efforts are crucial to the long-term life and of this country's national parks for future generations to come.
ContributorsHager, Madeline (Author) / Samuelson, Melissa (Thesis director) / Kenchington, David (Committee member) / Department of Marketing (Contributor) / School of Accountancy (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
One of the most notable composers of the twentieth century, Krzysztof Penderecki played a vital role in the development of new sonorities and compositional movements in the latter half of the century. Penderecki wrote two sonatas for violin and piano, one in his student days in 1953 and the second in the twilight of his career in 1999. Given the almost fifty years that separate the two works, these sonatas provide valuable insight to Penderecki’s development as a composer over the course of his career as well as give evidence that his own unique compositional style was in place at a very early age. Despite the large span of time between the completions of these two great works, these sonatas share many commonalities. With regards to key aspects such as form, tonality, rhythm, texture, articulation, and more, this paper will analyze and compare the two works to define the ways in which they are similar as well as the ways in which they differ.
ContributorsRamchandani, Micah David (Author) / McLin, Katherine (Thesis advisor) / DeMars, James (Committee member) / Landschoot, Thomas (Committee member) / Arizona State University (Publisher)
Created2016
Description
In the past 10 to 15 years, there has been a tremendous increase in the amount of photovoltaic (PV) modules being both manufactured and installed in the field. Power plants in the hundreds of megawatts are continuously being turned online as the world turns toward greener and sustainable energy. Due to this fact and to calculate LCOE (levelized cost of energy), it is understandably becoming more important to comprehend the behavior of these systems as a whole by calculating two key data: the rate at which modules are degrading in the field; the trend (linear or nonlinear) in which the degradation is occurring. As opposed to periodical in field intrusive current-voltage (I-V) measurements, non-intrusive measurements are preferable to obtain these two key data since owners do not want to lose money by turning their systems off, as well as safety and breach of installer warranty terms. In order to understand the degradation behavior of PV systems, there is a need for highly accurate performance modeling. In this thesis 39 commercial PV power plants from the hot-dry climate of Arizona are analyzed to develop an understanding on the rate and trend of degradation seen by crystalline silicon PV modules. A total of three degradation rates were calculated for each power plant based on three methods: Performance Ratio (PR), Performance Index (PI), and raw kilowatt-hour. These methods were validated from in field I-V measurements obtained by Arizona State University Photovoltaic Reliability Lab (ASU-PRL). With the use of highly accurate performance models, the generated degradation rates may be used by the system owners to claim a warranty from PV module manufactures or other responsible parties.
ContributorsRaupp, Christopher (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2016