Barrett, The Honors College Thesis/Creative Project Collection
Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.
Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.
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- Creators: Department of Economics
Description
Company X has developed RealSenseTM technology, a depth sensing camera that provides machines the ability to capture three-dimensional spaces along with motion within these spaces. The goal of RealSense was to give machines human-like senses, such as knowing how far away objects are and perceiving the surrounding environment. The key issue for Company X is how to commercialize RealSense's depth recognition capabilities. This thesis addresses the problem by examining which markets to address and how to monetize this technology. The first part of the analysis identified potential markets for RealSense. This was achieved by evaluating current markets that could benefit from the camera's gesture recognition, 3D scanning, and depth sensing abilities. After identifying seven industries where RealSense could add value, a model of the available, addressable, and obtainable market sizes was developed for each segment. Key competitors and market dynamics were used to estimate the portion of the market that Company X could capture. These models provided a forecast of the discounted gross profits that could be earned over the next five years. These forecasted gross profits, combined with an examination of the competitive landscape and synergistic opportunities, resulted in the selection of the three segments thought to be most profitable to Company X. These segments are smart home, consumer drones, and automotive. The final part of the analysis investigated entrance strategies. Company X's competitive advantages in each space were found by examining the competition, both for the RealSense camera in general and other technologies specific to each industry. Finally, ideas about ways to monetize RealSense were developed by exploring various revenue models and channels.
ContributorsDunn, Nicole (Co-author) / Boudreau, Thomas (Co-author) / Kinzy, Chris (Co-author) / Radigan, Thomas (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / WPC Graduate Programs (Contributor) / Department of Psychology (Contributor) / Department of Finance (Contributor) / School of Accountancy (Contributor) / Department of Economics (Contributor) / School of Mathematical and Statistical Science (Contributor) / W. P. Carey School of Business (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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
This paper classifies private equity groups (PEGs) seeking to engage in public to private transactions (PTPs) and determines (primarily through an examination of the implied merger arbitrage spread), whether certain reputational factors associated with the private equity industry affect a firm's ability to acquire a publicly-traded company. We use a sample of 1,027 US-based take private transactions announced between January 5, 2009 and August 2, 2018, where 333 transactions consist of private-equity led take-privates, to investigate how merger arbitrage spreads, offer premiums, and deal closure are impacted based on PEG- and PTP-specific input variables. We find that the merger arbitrage spread of PEG-backed deals are 2-3% wider than strategic deals, hostile deals have a greater merger arbitrage spread, larger bid premiums widen spreads and markets accurately identify deals that will close through a narrower spread. PEG deals offer lower premiums, as well as friendly deals and larger deals. Offer premiums are 8.2% larger among deals that eventually consummate. In a logistic regression, we identified that PEG deals are less likely to close than strategic deals, however friendly deals are much more likely to close and Mega Funds are more likely to consummate deals among their PEG peers. These findings support previous research on PTP deals. The insignificance of PEG-classified variables on arbitrage spreads and premiums suggest that investors do not differentiate PEG-backed deals by PEG due to most PEGs equal ability to raise competitive financing. However, Mega Funds are more likely to close deals, and thus, we identify that merger arbitrage spreads should be narrower among this PEG classification.
ContributorsSliwicki, Austin James (Co-author) / Schifman, Eli (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Economics (Contributor) / School of Accountancy (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This paper examines the qualitative and quantitative effects of the 2008 financial crisis on the current landscape of the investment banking industry. We begin by reviewing what occurred during the financial crisis, including which banks took TARP money, which banks became bank holding companies, and significant mergers and acquisitions. We then examine the new regulations that were created in reaction to the crisis, including the Dodd-Frank Act. In particular, we focus on the Volcker Rule, which is a section of the act that prohibits proprietary trading and other risky activities at banks. Then we shift into a quantitative analysis of the changes that banks made from the years 2005-2016. To do this, we chose four banks to be representative of the industry: Goldman Sachs, Morgan Stanley, J.P. Morgan, and Bank of America. We then analyze four metrics for each bank: revenue mix, value at risk, tangible common equity ratio, and debt to equity ratio. These provide methods for analyzing how banks have shifted their revenue centers to accommodate new regulations, as well as how these shifts have affected banks' risk levels and leverage. Our data show that all four banks that we observed shifted their revenue centers to flatter revenue areas, such as investment management, wealth management, and consumer banking operations. This was paired with fairly flat investment banking revenues across the board when controlling for overall market changes in the investment banking sector. Additionally, trading-focused banks significantly shifted their operations away from proprietary trading and higher risk activities. These changes resulted in lower value at risk measures for Goldman Sachs and Morgan Stanley with very minor increases for J.P. Morgan and Bank of America, although these two banks had low levels of absolute value at risk when compared to Goldman Sachs and Morgan Stanley. All banks' tangible common equity ratios increased and debt to equity ratios decreased, indicating a safer investment for shareholders and lower leverage. We conclude by offering a forecast of our expectations for the future, particularly in light of a Trump presidency. We expect less regulation going forward and the potential reversal of the Volcker Rule. We believe that these changes would result in more revenue coming from trading and riskier strategies, increasing value at risk, decreasing tangible common equity ratios, and increasing debt to equity ratios. While we do expect less regulation and higher risk, we do not expect these banks to reach pre-crisis levels due to the significant amount of regulations that would be particularly difficult for the Trump administration to reverse.
ContributorsPatel, Aashay (Co-author) / Goulder, Gregory (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Department of Economics (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
The goal of this thesis was to provide in depth research into the semiconductor wet-etch market and create a supplier analysis tool that would allow Company X to identify the best supplier partnerships. Several models were used to analyze the wet etch market including Porter's Five Forces and SWOT analyses. These models were used to rate suppliers based on financial indicators, management history, market share, research and developments spend, and investment diversity. This research allowed for the removal of one of the four companies in question due to a discovered conflict of interest. Once the initial research was complete a dynamic excel model was created that would allow Company X to continually compare costs and factors of the supplier's products. Many cost factors were analyzed such as initial capital investment, power and chemical usage, warranty costs, and spares parts usage. Other factors that required comparison across suppliers included wafer throughput, number of layers the tool could process, the number of chambers the tool has, and the amount of space the tool requires. The demand needed for the tool was estimated by Company X in order to determine how each supplier's tool set would handle the required usage. The final feature that was added to the model was the ability to run a sensitivity analysis on each tool set. This allows Company X to quickly and accurately forecast how certain changes to costs or tool capacities would affect total cost of ownership. This could be heavily utilized during Company X's negotiations with suppliers. The initial research as well the model lead to the final recommendation of Supplier A as they had the most cost effective tool given the required demand. However, this recommendation is subject to change as demand fluctuates or if changes can be made during negotiations.
ContributorsSchmitt, Connor (Co-author) / Rickets, Dawson (Co-author) / Castiglione, Maia (Co-author) / Witten, Forrest (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Company X once dominated the server chip market, but its share has begun to diminish due to numerous competitors, product delays, and smaller profit margins. This market will only keep growing as advancement and demand for server technologies continues to expand, therefore, regaining market share is of utmost importance for Company X. This project analyzes how Company X can look into regaining server market share through a diversion of funds into emerging markets. The paper highlights the importance of being an early entrant into a relatively untapped, promising regional market by addressing the economics, potential consumers, and competition. Analysis of these factors shows the potential net present value (NPV) that can be achieved by increasing investments in India.
ContributorsNguyen, Andre (Author) / Kam, Manton (Co-author) / Amundson, Tegan (Co-author) / Johnson, Tyler (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Economics (Contributor)
Created2023-05
Description
This project analyzed the utilization rates of respective factories for Company X compared to the Manufacturing Utilization Policy to identify discrepancies in the policy baseline trigger and when the factories are ramped to full utilization. The current policy bases three different factory types, ATM, DS/DP, and FSM all on the same baseline of FSM. This was originally set in place from a lack of sufficient data for the other factories and now that there is enough data to identify the utilization rates of each factory type, a more suitable baseline for each can be determined. If continuing to use the FSM baseline, Company X will be designating certain factories as underutilized, triggering the manufacturing utilization policy and inefficiently allocating the building expenses, thus increasing the cost per unit of products produced.
ContributorsTang, Tuan (Author) / Micheels, Jordan (Co-author) / Harris, Olivia (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Thunderbird School of Global Management (Contributor) / Department of Economics (Contributor)
Created2022-05