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Description
Sagebrush Coffee is a small business in Chandler, Arizona that purchases green beans, roasts them in small batches for quality, and ships fresh, gourmet roasted coffee beans across the nation. Deciding which coffee beans to buy and roast is one of the most crucial business decisions Sagebrush and other gourmet

Sagebrush Coffee is a small business in Chandler, Arizona that purchases green beans, roasts them in small batches for quality, and ships fresh, gourmet roasted coffee beans across the nation. Deciding which coffee beans to buy and roast is one of the most crucial business decisions Sagebrush and other gourmet coffee roasters face. Further complicating this decision is the fact that coffee is a crop, and like all crops, has a specific growing season and the exact same product cannot usually be ordered from year to year, even if it proves to be successful. The goal of this research is to use data analytics and visualization to help Sagebrush make better purchasing decisions by identifying consumer purchasing trends and providing a recommendation for their portfolio mix. In the end, I found that Latin American coffees are popular with both returning and first-time customers, but a specific country of origin does not appear to be associated with the top coffee producing countries. Additionally, December is a critical month for Sagebrush and Sagebrush should make sure to target the states with the most sales: California, Pennsylvania, and New York. Arizona has growth potential as it is not one of the top three locations, despite the presence of a physical store. Also included in the following report is a portfolio recommendation suggesting how many of each product based on region, processing type, and roast level to carry in inventory.
ContributorsBlue, Jessica Morgan (Author) / Kellso, James (Thesis director) / Davila, Eddie (Committee member) / Department of Information Systems (Contributor) / Economics Program in CLAS (Contributor) / Department of Supply Chain Management (Contributor) / Morrison School of Agribusiness (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
This project analyzes the tweets from the 2016 US Presidential Candidates' personal Twitter accounts. The goal is to define distinct patterns and differences between candidates and parties use of social media as a platform. The data spans the period of September 2015 to March 2016, which was during the primary

This project analyzes the tweets from the 2016 US Presidential Candidates' personal Twitter accounts. The goal is to define distinct patterns and differences between candidates and parties use of social media as a platform. The data spans the period of September 2015 to March 2016, which was during the primary races for the Republicans and Democrats. The overall purpose of this project is to contribute to finding new ways of driving value from social media, in particular Twitter.
ContributorsMortimer, Schuyler Kenneth (Author) / Simon, Alan (Thesis director) / Mousavi, Seyedreza (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
Monocular is a user engagement application that offers a website owner the opportunity to track user behavior and use the data to better understand the site's strengths and weaknesses in terms of user satisfaction and motivation. This data allows the customer to make improvements to a website, resulting in a

Monocular is a user engagement application that offers a website owner the opportunity to track user behavior and use the data to better understand the site's strengths and weaknesses in terms of user satisfaction and motivation. This data allows the customer to make improvements to a website, resulting in a better user experience and potential for an improved bottom line.
ContributorsHooke, Wade (Co-author) / Ortiz-Monasterio, Diego (Co-author) / Clark, Joseph (Thesis director) / Prince, Linda (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / W. P. Carey School of Business (Contributor)
Created2014-05
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Description
With growing levels of income inequality in the United States, it remains as important as ever to ensure indispensable public services are readily available to all members of society. This paper investigates four forms of public services (schools, libraries, fire stations, and police stations), first by researching the background of

With growing levels of income inequality in the United States, it remains as important as ever to ensure indispensable public services are readily available to all members of society. This paper investigates four forms of public services (schools, libraries, fire stations, and police stations), first by researching the background of these services and their relation to poverty, and then by conducting geospatial and regression analysis. The author uses Esri's ArcGIS Pro software to quantify the proximity to public services from urban American neighborhoods (census tracts in the cities of Phoenix and Chicago). Afterwards, the measures indicating proximity are compared to the socioeconomic statuses of neighborhoods using regression analysis. The results indicate that pure proximity to these four services is not necessarily correlated to socioeconomic status. While the paper does uncover some correlations, such as a relationship between school quality and socioeconomic status, the majority of the findings negate the author's hypothesis and show that, in Phoenix and Chicago, there is not much discrepancy between neighborhoods and the extent to which they are able to access vital government-funded services.
ContributorsNorbury, Adam Charles (Author) / Simon, Alan (Thesis director) / Simon, Phil (Committee member) / Department of Information Systems (Contributor) / Department of English (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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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

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
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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

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
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Description
Data is ever present in the world today. Data can help predict presidential elections, Super Bowl champions, and even the weather. However, it's very hard, if not impossible, to predict how people feel unless they tell us. This is when impulse spending with data comes in handy. Companies are constantly

Data is ever present in the world today. Data can help predict presidential elections, Super Bowl champions, and even the weather. However, it's very hard, if not impossible, to predict how people feel unless they tell us. This is when impulse spending with data comes in handy. Companies are constantly looking for ways to get honest feedback when they are doing market research. Often, the research obtained ends up being unreliable or biased in some way. Allowing users to make impulse purchases with survey data is the answer. Companies can still gather the data that they need to do market research and customers can get more features or lives for their favorite games. It becomes a win-win for both users and companies. By adding the option to pay with information instead of money, companies can still get value out of frugal players. Established companies might not care so much about the impulse spending for purchases made in the application, however they would find a great deal of value in hearing about what customers think of their product or upcoming event. The real value from getting data from customers is the ability to train analytics models so that companies can make better predictions about consumer behavior. More accurate predictions can lead to companies being better prepared to meet the needs to the customer. Impulse spending with data provides the foundation to creating a software that can create value from all types of users regardless of whether the user is willing to spend money in the application.
ContributorsYotter, Alexandria Lee (Author) / Olsen, Christopher (Thesis director) / Sopha, Matthew (Committee member) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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Home advantage affects the game in almost all team sports across the world. Due to<br/>COVID and all of the precautions being taken to keep games played, more extensive research is able to be conducted about what factors truly go into creating a home advantage. Some common factors of home advantage

Home advantage affects the game in almost all team sports across the world. Due to<br/>COVID and all of the precautions being taken to keep games played, more extensive research is able to be conducted about what factors truly go into creating a home advantage. Some common factors of home advantage include the crowd, facility familiarity, and travel. In the English Premier League, there are no fans allowed at any of the games; furthermore, in the NBA, a bubble was created at one neutral venue with no fans in attendance. Even with the NBA being at a neutral site, there was still a “home team” at every game. The sports betting industry struggled due to failing to shift betting lines in accordance with this decreased home advantage. With these leagues removing some of the factors that are frequently associated with home advantage, analysts are able to better see what the results would be of removing these variables. The purpose of this research is to determine if these adjustments made due to COVID had an impact on the home advantage in different leagues around the world, and if they did, to what extent. Individual game data from the past 10 seasons were used for analysis of both the NBA and the Premier League. The results show that there is a significant difference in win percentage between prior seasons and seasons behind closed doors. In addition to win percentage, many other game statistics see a significant shift as well. Overall, the significance of being the home team disappears in games following the COVID-19 break.

ContributorsOsborne, Ashley A (Author) / Sopha, Matthew (Thesis director) / McIntosh, Daniel (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

In recent years, advanced metrics have dominated the game of Major League Baseball. One such metric, the Pythagorean Win-Loss Formula, is commonly used by fans, reporters, analysts and teams alike to use a team’s runs scored and runs allowed to estimate their expected winning percentage. However, this method is not

In recent years, advanced metrics have dominated the game of Major League Baseball. One such metric, the Pythagorean Win-Loss Formula, is commonly used by fans, reporters, analysts and teams alike to use a team’s runs scored and runs allowed to estimate their expected winning percentage. However, this method is not perfect, and shows notable room for improvement. One such area that could be improved is its ability to be affected drastically by a single blowout game, a game in which one team significantly outscores their opponent.<br/>We hypothesize that meaningless runs scored in blowouts are harming the predictive power of Pythagorean Win-Loss and similar win expectancy statistics such as the Linear Formula for Baseball and BaseRuns. We developed a win probability-based cutoff approach that tallied the score of each game once a certain win probability threshold was passed, effectively removing those meaningless runs from a team’s season-long runs scored and runs allowed totals. These truncated totals were then inserted into the Pythagorean Win-Loss and Linear Formulas and tested against the base models.<br/>The preliminary results show that, while certain runs are more meaningful than others depending on the situation in which they are scored, the base models more accurately predicted future record than our truncated versions. For now, there is not enough evidence to either confirm or reject our hypothesis. In this paper, we suggest several potential improvement strategies for the results.<br/>At the end, we address how these results speak to the importance of responsibility and restraint when using advanced statistics within reporting.

ContributorsIversen, Joshua Allen (Author) / Satpathy, Asish (Thesis director) / Kurland, Brett (Committee member) / Department of Information Systems (Contributor) / Walter Cronkite School of Journalism and Mass Comm (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

In the end, an increase in repurchases of company stock will also influence the rate of dividends to increase. This means, an investor should not necessarily worry about the dividends they receive, but rather to see if the company is making profit at a consistent rate and reinvesting into value-added

In the end, an increase in repurchases of company stock will also influence the rate of dividends to increase. This means, an investor should not necessarily worry about the dividends they receive, but rather to see if the company is making profit at a consistent rate and reinvesting into value-added activities. Through the major pillars of finance, technology, legal, and human resources, the budget for reinvestment can be optimized by investing into these respective categories with percentages that are mindful of the specific companies needs and functions. Any firm that chooses to ensure proven methods of growth will enact a combination of these four verticals. A larger emphasis on finance will branch out efficiency in the entire organization, as finance control everything from the toilet paper to the acquisitions the company is making. The more technology is used to reduce redundancy and inefficient or costly operations, the more capability the organization will have. IT, however, comes with its technical challenges; having a team on-hand or even outsourced, to solve the critical problems to help the business continue operation. Over-reliance into technology can be detrimental to a business as well if clear processes are not set about straight to counteract problems the business will face like IT ticketing systems or recovery and continuity support. Therefore, technology will require a larger chunk of attention as well.

The upcoming legal and HR investments a company will make will depend upon its current position and thus the restructuring will differ for every firm. Each company has its own flavour and style of work. In that regard, the required legal counsel will vary; different problems will require different solutions for risk control and management, which are often professionally advised by intelligent corporate counsel. This ability to hire efficient legal counsel would not arise in the first place if a firm were to give out dividends; the leftover profit would have gone towards the shareholders and not back into growing the equity of the business. Lastly, nothing is possible without the contribution of people, and their efforts. A quality that long-lasting, successful businesses have, is they are investing in their people and development. Paying salaries, insurances, bonuses, all requires extra capital that is needed to be set aside in order to grow human capital. Good people, better people. There are qualities for each role that need to be defined and a process for attracting talent needs to be invested in. This process can also include outsourcing to an external firm who specializes in these strategies. By retaining profits internally, the company is able to stretch its legs to have further reach upon the market they work in. Financially and statistically, dividends are likely to grow as well with the increase in equity due to the increase in security an investor feels with more cash reserve and liquidity within the company.

All in all, a company should not be pressured into giving out periodic payments in predetermined timeframes, in other words a dividend, to investors even when they are insisting. Rather, pitch and prove, a new method for reinvestment within the company that will raise the value of the company, through proven methods like the value chain model, to increase the equity in the company. By expanding the scope and capability, the company is allowing for a larger target market which will reap more benefits; none of it would be possible if it had continued to give out large percentages of capital to investors as dividends. Companies, and investors, should not be worried about dividends at all as a matter of fact; an increase in stock buyback, in other words reinvesting into the company, will increase the rate of dividends anyway, due to increased confidence and capital within the company.

ContributorsKabra, Dev (Author) / Ahern, James (Thesis director) / Kabra , J. (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / School of Politics and Global Studies (Contributor) / Department of Finance (Contributor)
Created2022-05