Matching Items (4)
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- All Subjects: Analytics
- All Subjects: Economy
- Creators: Goegan, Brian
Description
This thesis project provides a thorough cost-benefit analysis of the golf industry in Arizona. We begin by examining the economic, environmental, and social costs that the industry requires. One of the largest costs of the industry is water consumption. Golf courses in Arizona are currently finding ways to reduce water consumption through various methods, such as turf reduction and increasing the usage of drip irrigation. However, even at current levels of consumption, golf only consumes 1.9% of water in Arizona, compared to the 69% consumed by agriculture. Of the water consumed by the golf industry, 26.3% is wastewater, otherwise known as effluent water. Since the population in Arizona is projected to grow significantly over the next decade, the amount of effluent water produced will also increase. Due to this, we recommend that the golf industry move towards using as much effluent water as possible to conserve clean water sources. Additionally, we examine land allocation and agricultural tradeoffs to the state. Most golf courses are built in urban areas that would not be suitable for agriculture. The same land could be used to build a public park, but this would not provide as many economic benefits to the state. Many courses also act as floodplains which protect the communities surrounding them from flooding. These floodplains have proven to be crucial to protect from occasional flash floods by diverting the excess water away from homes. We also discuss golf's primary social cost in terms of its perception as being a sport played exclusively by privileged and wealthy people. This is proven to be false due to many non-profit organizations centered around the game, as well as municipal courses that provide affordable options for all citizens who want to play. We provide an in-depth analysis of the benefits that the industry provides to the state and its citizens primarily through business and tax revenue, employment, and property values. Including multiplier effects, the golf industry contributed 42,000 full- and part-time jobs, $3.9 billion in sales, $1.5 billion in labor income, and $2.1 billion value added in 2014. An estimated $72 million in state and local taxes were generated from golf facilities alone, without including taxes from indirectly impacted businesses. This tax revenue provides a great benefit to the public sector and increases Arizona's GDP. Also, much of this economic contribution is from the golf tourism industry, which brings new revenue into the state that would otherwise not exist. Golf courses also increase the surrounding real estate prices anywhere from 4.8% to 28%, providing a positive externality to community members in addition to scenic views. Finally, we provide a case study of the Waste Management Phoenix Open (WMO) to illustrate the impact of Arizona's single largest golf event each year. In 2017, the event brought an estimated $389 million into Arizona's economy in one week alone. Also, it regularly hosts massive crowds with a record-breaking 719,179 people attending the event in 2018. The WMO has also taken a "Zero Waste Challenge" to promote eco-friendly and sustainable practices by diverting all of the waste and materials produced by the tournament from landfills. The WMO has been dubbed both the "Greatest Show On Grass" and the "Greenest Show On Grass" due to the entertainment value provided as well as its effort to improve the environment.
ContributorsShershenovich, Andrew (Co-author) / Wilhelm, Spencer (Co-author) / Goegan, Brian (Thesis director) / Van Poucke, Rory (Committee member) / Department of Finance (Contributor) / W.P. Carey School of Business (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This paper attempts to introduce analytics and regression techniques into the National Hockey League. Hockey as a sport has been a slow adapter of analytics, and this can be attributed to poor data collection methods. Using data collected for hockeyreference.com, and R statistical software, the number of wins a team experiences will be predicted using Goals For and Goals Against statistics from 2005-2017. The model showed statistical significance and strong normality throughout the data. The number of wins each team was expected to experience in 2016-2017 was predicted using the model and then compared to the actual number of games each team won. To further analyze the validity of the model, the expected playoff outcome for 2016-2017 was compared to the observed playoff outcome. The discussion focused on team's that did not fit the model or traditional analytics and expected forecasts. The possible discrepancies were analyzed using the Las Vegas Golden Knights as a case study. Possible next steps for data analysis are presented and the role of future technology and innovation in hockey analytics is discussed and predicted.
ContributorsVermeer, Brandon Elliot (Author) / Goegan, Brian (Thesis director) / Eaton, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
A global trend towards cashlessness following the increase in technological advances in financial transactions lends way to a discussion of its various impacts on society. As part of this discussion, it is important to consider how this trend influences crime rates. The purpose of this project is to specifically investigate the relationship between a cashless society and the robbery rate. Using data collected from the World Bank’s Global Financial Inclusions Index and the United Nations Office of Drugs and Crime, we implemented a multilinear regression to observe this relationship across countries (n = 29). We aimed to do this by regressing the robbery rate on cashlessness and controlling for other related variables, such as gross domestic product and corruption. We found that as a country becomes more cashless, the robbery rate decreases (β = -677.8379, p = 0.071), thus providing an incentive for countries to join this global trend. We also conducted tests for heteroscedasticity and multicollinearity. Overall, our results indicate that a reduction in the amount of cash circulating within a country negatively impacts robbery rates.
ContributorsChoksi, Aashini S (Co-author) / Elliott, Keeley (Co-author) / Goegan, Brian (Thesis director) / McDaniel, Cara (Committee member) / School of International Letters and Cultures (Contributor) / Department of Economics (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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