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.

Displaying 21 - 30 of 104
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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

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
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Description
Autonomous vehicles (AV) are capable of producing massive amounts of real time and precise data. This data has the ability to present new business possibilities across a vast amount of markets. These possibilities range from simple applications to unprecedented use cases. With this in mind, the three main objectives we

Autonomous vehicles (AV) are capable of producing massive amounts of real time and precise data. This data has the ability to present new business possibilities across a vast amount of markets. These possibilities range from simple applications to unprecedented use cases. With this in mind, the three main objectives we sought to accomplish in our thesis were to: 1. Understand if there is monetization potential in autonomous vehicle data 2. Create a financial model of what detailing the viability of AV data monetization 3. Discover how a particular company (Company X) can take advantage of this opportunity, and outline how that company might access this autonomous vehicle data.
ContributorsCarlton, Corrine (Co-author) / Clark, Rachael (Co-author) / Quintana, Alex (Co-author) / Shapiro, Brandon (Co-author) / Sigrist, Austin (Co-author) / Simonson, Mark (Thesis director) / Reber, Kevin (Committee member) / School of Accountancy (Contributor) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
The global network, serving as the backbone of the Internet and the flow of all digital information, has evolved since the birth of the internet in 1983 1. From the first generation of networks that supported the first cell phones, the system has matured to the existing fourth generation (4G),

The global network, serving as the backbone of the Internet and the flow of all digital information, has evolved since the birth of the internet in 1983 1. From the first generation of networks that supported the first cell phones, the system has matured to the existing fourth generation (4G), providing greater speed and expanded capabilities beyond basic calling and texting. The goal of our project was to identify how well Company X is positioned to capitalize on the transition to 5G, which will involve almost twice the amount of interconnected devices than today. To do this, we completed the following various tasks: 1. Identify the networking segments to focus our research. 2. Identify the major customers in these segments and how much of the market share each occupies. 3. Analyze the major benchmarks and metrics these customers value when purchasing the microprocessors for their networking devices. 4. Identify Company X's major competitors and their comparable products. 5. Compare the benchmark performances of Company X's offerings and its competitors 6. Create a model that provides a 5-year NPV as well as Company X's market share 7. Employ this model to evaluate various pricing strategies. 8. Determine the optimal pricing strategy and make a final recommendation. As 5G evolves, the demand for high-quality, low-power networking devices (e.g. routers, switches, access points) will increase. After performing our analyses, we will be able to decide how Company X's networking-oriented SoCs (chipset) compare to those of the other major competitors and use this relative performance to determine an appropriate ASP (average selling price) for these SoCs.
ContributorsDimitroff, Alex (Co-author) / Arias, Stephen (Co-author) / Masson, Taylor (Co-author) / McCall, Kyle (Co-author) / Hardy, Sebastian (Co-author) / Simonson, Mark (Thesis director) / Haller, Marcie (Committee member) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Autonomous vehicles (AV) are capable of producing massive amounts of real time and precise data. This data has the ability to present new business possibilities across a vast amount of markets. These possibilities range from simple applications to unprecedented use cases. With this in mind, the three main objectives we

Autonomous vehicles (AV) are capable of producing massive amounts of real time and precise data. This data has the ability to present new business possibilities across a vast amount of markets. These possibilities range from simple applications to unprecedented use cases. With this in mind, the three main objectives we sought to accomplish in our thesis were to: Understand if there is monetization potential in autonomous vehicle data Create a financial model of what detailing the viability of AV data monetization Discover how a particular company (Company X) can take advantage of this opportunity, and outline how that company might access this autonomous vehicle data. First, in order to brainstorm how this data could be monetized, we generated potential use cases, defined probable customers of these use cases, and how the data could generate value to customers as a means to understand what the "price" of autonomous vehicle data might be. While we came up with an extensive list of potential data monetization use cases, we evaluated our list of use cases against six criteria to narrow our focus into the following five: Government, Insurance Companies, Mapping, Marketing purposes, and Freight. Based on our research, we decided to move forward with the insurance industry as a proof of concept for autonomous vehicle data monetization. Based on our modeling, we concluded there is a significant market for autonomous vehicle data monetization moving forward. Data accessibility is a key driver in how profitable a particular company and their competitors can be in this space. In order to effectively monetize this data, it would first be important to understand the method by which a company obtains access to the data in the first place. Ultimately, based on our analysis, Company X has positioned itself well to take advantage of the new trends in autonomous vehicle technology. With more strategic investments and innovation, Company X can be a key benefactor of this unprecedented space in the near future.
ContributorsShapiro, Brandon (Co-author) / Quintana, Alex (Co-author) / Sigrist, Austin (Co-author) / Clark, Rachael (Co-author) / Carlton, Corrine (Co-author) / Simonson, Mark (Thesis director) / Reber, Kevin (Committee member) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Company X has developed minicomputing products that can change the way people think about minicomputer. The Product A (PRODUCT A) and Product B are relatively new products on the market that have the ability to change the way some industries use technology and increase end-user convenience. The key issue for

Company X has developed minicomputing products that can change the way people think about minicomputer. The Product A (PRODUCT A) and Product B are relatively new products on the market that have the ability to change the way some industries use technology and increase end-user convenience. The key issue for Company X is finding targeted use cases to which Company X can market these products and increase sales. This thesis reports how our team has researched, calculated, and financially forecasted use cases for both the PRODUCT A and Product B. The Education and Healthcare industries were identified as those providing significant potential value propositions and an array of potential use cases from which we could choose to evaluate. Key competitors, market dynamics, and information obtained through interviews with a Product Line Analyst were used to size the available, obtainable, and attainable market numbers for Company X. The models built for this research provided insight into the PRODUCT A and Product B's potential growth in the education and healthcare industries. This led to the selection of education and healthcare use cases for the Product B and the PRODUCT A use cases for healthcare. This report concludes with recommendations for success in education and healthcare with the PRODUCT A and Product B.
ContributorsHoward, James (Co-author) / Kazmi, Abbas (Co-author) / Ralston, Nicholas (Co-author) / Salamatin, Mikkaela Alexis (Co-author) / Simonson, Mark (Thesis director) / Hopkins, David (Committee member) / W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
I will determine what the Average Handle Time goal should be for the company and establish why the Average Handle Time has increased over time. I am looking at data compiled from July 1st 2012 to June 30th 2013 in order to assist the company so it can budget resources

I will determine what the Average Handle Time goal should be for the company and establish why the Average Handle Time has increased over time. I am looking at data compiled from July 1st 2012 to June 30th 2013 in order to assist the company so it can budget resources more effectively in the future. For this project, there are a few questions I aim to answer. The questions are as followed: 1. What should the budgeted Average Handle Time be for the company in future time periods? 2. What are some improvements that can be made in order to manage Average Handle Time in the future time periods? Employees in the department spend their time answering client inquires over the phone, these questions are vital for the business to answer. Average Handle Time is the average duration of time it takes for the employee to answer questions from clients on each phone call. The company budgets the department based on how many calls they have answered in prior periods as well as the Average Handle Time goal for the entire department. They use this information for scheduling as well as hiring purposes to predict the number of employees needed to answer phone calls in future periods. I will attempt to answer these questions by using multiple data sources. I will gather information from multiple reports generated from the department software and data mine in order to answer some of the questions related to the project. I will also gain management feedback in terms of what is viewed as important as well as what they believe can be used to improve the Average Handle Time number in the future. These quantitative and qualitative measures will help narrow down on what the Average Handle Time should be budgeted for the department as well as what management could do to improve it in future periods.
ContributorsKing, Dylan Michael Hiroshi (Author) / Simonson, Mark (Thesis director) / Luna, David (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / W. P. Carey School of Business (Contributor)
Created2014-05
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Description
This paper seeks to put a spotlight on much that is wrong in the United States with cancer drug development, pricing, marketing and outcomes. Roche Pharmaceutical's cancer drug, Avastin will be used as an example to highlight these issues. Drug patents, Medicare policies, weak metrics of efficacy and ceaseless demand—allow

This paper seeks to put a spotlight on much that is wrong in the United States with cancer drug development, pricing, marketing and outcomes. Roche Pharmaceutical's cancer drug, Avastin will be used as an example to highlight these issues. Drug patents, Medicare policies, weak metrics of efficacy and ceaseless demand—allow drug manufacturers to price their oncology treatments as they choose, regardless of results, and with virtually no competition, avenue or institution that serves to lower prices in the United States. Avastin will be established as an oncology drug that is overpriced and poorly evaluated based on its effectiveness. Facts, opinions and study analytics will be offered (from industry experts, insiders, doctors and scientists) that in almost all cases show that patients treated with Avastin receive marginal benefit. Allowing Medicare to negotiate drug prices with manufacturers, reducing conflicts of interest for doctors, setting research & development investment requirements and creating more relevant clinical metrics for use in FDA approvals would help reduce the financial burden on cancer patients and taxpayers.
ContributorsTrettin, Michael William (Author) / Simonson, Mark (Thesis director) / Budolfson, Arthur (Committee member) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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Description
The purpose of this research project is to develop a recommendation for Company X on the strategies it should use to enter a new market. This was done through the compilation and interpretation of data from the company and the construction of a financial model capable of analyzing our different

The purpose of this research project is to develop a recommendation for Company X on the strategies it should use to enter a new market. This was done through the compilation and interpretation of data from the company and the construction of a financial model capable of analyzing our different proposed strategies. Company X is a leading producer of silicon chips which seeks to remain one of the leading forces in new technologies. Currently Company X wants to assess the value and risks associated with introducing a new packaging technology (FO-WLP) into their products either by developing the technology in-house or outsourcing production. The first portion of the research consisted mostly of gathering the necessary business acumen to be able to to fully understand our research findings. Market research was conducted to discover what competitors exist and what inputs should be included for the model with help from employees at Company X. The research then proceeded with the identification of three possible strategies and construction of financial models to analyze these options. Using the results from our analysis we were able to develop our recommendation for Company X and lay out the next steps which the Company needs to take before investing in the new technology.
ContributorsRubenzer, Jack (Co-author) / Galaviz, Roberto (Co-author) / Mariani, Stephanie (Co-author) / Mecinas, Freddy (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Mike (Committee member) / Department of Finance (Contributor) / Department of Economics (Contributor) / Department of Supply Chain Management (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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Description
The basis of this project was to analyze the potential cost savings derived from the implementation of an ultrasonic flaw detector for gas pipes in factories. The group began by researching the market of the Industrial Internet of Things. IIoT is a very attractive market for investment, as connected technologies

The basis of this project was to analyze the potential cost savings derived from the implementation of an ultrasonic flaw detector for gas pipes in factories. The group began by researching the market of the Industrial Internet of Things. IIoT is a very attractive market for investment, as connected technologies are become both more advanced and more affordable. Factory automation also saves costs of human capital, maintenance, and bad product cost as well as safety. After doing this preliminary research, the group continued by identifying potential solutions to current shortcomings of the manufacturing status quo. After narrowing down the options, the ultrasonic flaw detector appeared to have the highest potential for success in Company X's factories. The group began doing research on what physical components would go into this solution. They found pricing for all of the various parts of such a device as well as estimated labor, maintenance, and implementation costs. After estimating these costs, the team began the construction of a detailed financial model to generate the hypothetical net present value of such a tool. After presenting two times to a panel of Company X employees, the group decided to focus only on cost savings for Company X, and not the potential revenues of selling the whole solution. They ran a sensitivity analysis on all of the factors that contributed to the NPV of the project, and discovered that the estimated percentage of scrapped product resulting from gas leaks and the percentage of gas lost to leaks contributed the most to the NPV.
ContributorsFlick, Jacob (Co-author) / Alam, Mustafa (Co-author) / Nguyen, Mong (Co-author) / Zhang, Zihan (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / WPC Graduate Programs (Contributor) / School of International Letters and Culture (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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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

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