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The purpose of our research was to develop recommendations and/or strategies for Company A's data center group in the context of the server CPU chip industry. We used data collected from the International Data Corporation (IDC) that was provided by our team coaches, and data that is accessible on the

The purpose of our research was to develop recommendations and/or strategies for Company A's data center group in the context of the server CPU chip industry. We used data collected from the International Data Corporation (IDC) that was provided by our team coaches, and data that is accessible on the internet. As the server CPU industry expands and transitions to cloud computing, Company A's Data Center Group will need to expand their server CPU chip product mix to meet new demands of the cloud industry and to maintain high market share. Company A boasts leading performance with their x86 server chips and 95% market segment share. The cloud industry is dominated by seven companies Company A calls "The Super 7." These seven companies include: Amazon, Google, Microsoft, Facebook, Alibaba, Tencent, and Baidu. In the long run, the growing market share of the Super 7 could give them substantial buying power over Company A, which could lead to discounts and margin compression for Company A's main growth engine. Additionally, in the long-run, the substantial growth of the Super 7 could fuel the development of their own design teams and work towards making their own server chips internally, which would be detrimental to Company A's data center revenue. We first researched the server industry and key terminology relevant to our project. We narrowed our scope by focusing most on the cloud computing aspect of the server industry. We then researched what Company A has already been doing in the context of cloud computing and what they are currently doing to address the problem. Next, using our market analysis, we identified key areas we think Company A's data center group should focus on. Using the information available to us, we developed our strategies and recommendations that we think will help Company A's Data Center Group position themselves well in an extremely fast growing cloud computing industry.
ContributorsJurgenson, Alex (Co-author) / Nguyen, Duy (Co-author) / Kolder, Sean (Co-author) / Wang, Chenxi (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Department of Management (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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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

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
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We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones

We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones Industrial Average. The results showed that a tri-gram bag led to a 49% trend accuracy, a 1% increase when compared to the single-gram representation’s accuracy of 48%.

ContributorsBarolli, Adeiron (Author) / Jimenez Arista, Laura (Thesis director) / Wilson, Jeffrey (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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This thesis details our experience assisting BASE Equity Partners, a private equity firm based in New York City, on three prospective agricultural dealership deals over the course of this past academic year. The firm is currently structured as a Fundless Sponsor. This distinct structural trait is common for a type

This thesis details our experience assisting BASE Equity Partners, a private equity firm based in New York City, on three prospective agricultural dealership deals over the course of this past academic year. The firm is currently structured as a Fundless Sponsor. This distinct structural trait is common for a type of private equity firm known among practitioners as pledge funds. This creates an interesting element for our experience as there is very limited academic research on these types of firms, which, since the Great Recession, have become popular players in middle-market private equity deals. We, first, provide some historical context on pledge funds and identify their primary differences with traditional private equity. The remainder of the paper documents our experience working on the agricultural dealership deals. We have organized this portion after the manner in which we received assignments. We go into detail on the specific projects with which we were tasked, our interactions with the partners and the major takeaways we had from this learning experience. This thesis paper will enrich the academic knowledge regarding pledge funds—and private equity generally—by documenting a real experience of what it is like performing analyst-level tasks at a real firm. Additionally, we were privy to information that is highly confidential, and though we have protected the confidentiality of the companies through pseudonyms and redaction of confidential material, all of the financial data shown, models provided and qualitative discussion is real.
ContributorsTang, Ivan (Co-author) / Johnson, Bradley (Co-author) / Panosian, Tro (Co-author) / Simonson, Mark (Thesis director) / Bonadurer, Werner (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of English (Contributor) / School of Accountancy (Contributor) / School of International Letters and Cultures (Contributor)
Created2015-05
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The following thesis discusses the primary drivers of value creation in a leveraged buyout. Value creation is defined by two broad criteria: enterprise value creation and financial value creation. With enterprise value creation, the company itself may be improved, which in turn may have positive implications on the economy at

The following thesis discusses the primary drivers of value creation in a leveraged buyout. Value creation is defined by two broad criteria: enterprise value creation and financial value creation. With enterprise value creation, the company itself may be improved, which in turn may have positive implications on the economy at large. As the analysis of enterprise value creation is outside the scope of publicly available information and data, the core focus of this thesis is financial value creation. Financial value creation is defined as the financial returns to a given private equity firm. Amongst this segment of value creation, there are roughly three primary categories responsible for generating returns: financial engineering, governance improvements, and operational improvements. The attached literature review and subsequent chapters of this thesis discuss the academic drivers of value creation and the outputs of a leveraged buyout model conducted on a public company, Schnitzer Steel, that has been determined to be an ideal candidate for a buyout.
ContributorsAlivarius, Chadwick (Author) / Simonson, Mark (Thesis director) / Stein, Luke (Committee member) / Department of Finance (Contributor) / Department of Economics (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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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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Technology is everywhere. It touches every industry and nearly every aspect of our lives. It is paving the way to exciting innovations, solving long-standing problems, and helping us as humans learn at a faster rate than ever before. The Tech Industry is booming, generating an ever-increasing amount of jobs within

Technology is everywhere. It touches every industry and nearly every aspect of our lives. It is paving the way to exciting innovations, solving long-standing problems, and helping us as humans learn at a faster rate than ever before. The Tech Industry is booming, generating an ever-increasing amount of jobs within the workforce. The number of women filling these new jobs, however, has remained static – if not declined. As a female student studying Computer Information Systems, this fact has concerned me for some time and propelled me to dig deeper and get to the root of the problem. It has been no secret that there is a lack of gender equality within the technology industry. Silicon Valley – the tech hub of the United States – has time and again been accused of creating an overwhelming sense of “bro culture”. The numbers are staggeringly obvious – women are entering into the industry at a lower rate than men, women are leaving the industry at a higher rate than men, and women are not being advanced within technology-based careers at the same rate as men. My objective with this creative project was to go beyond the numbers and to understand why this gender gap is still prevalent within the industry and, more importantly, what can be done to shrink the gap. As such, I decided to put faces to the numbers by creating a documentary in which I interviewed eight diverse female professionals with varying backgrounds that are in different stages within their careers in the technology industry. I was able to get real and raw opinions, ideas, and advice from these knowledgeable women to construct my responses to these complex issues. This paper has been structured to outline and analyze the ideas and concepts generated from my interviews of these women.
ContributorsFarias, Isabella Maria (Author) / Moser, Kathleen (Thesis director) / Scott, Kimberly (Committee member) / Department of Information Systems (Contributor) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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For students on a college campus, many courses can present challenges to them academically. Some universities have taken an initiative to respond to this by offering tutoring opportunities at a central location. Generally this provides help for some struggling students, but others are left with many questions unanswered. Two primary

For students on a college campus, many courses can present challenges to them academically. Some universities have taken an initiative to respond to this by offering tutoring opportunities at a central location. Generally this provides help for some struggling students, but others are left with many questions unanswered. Two primary reasons for this are that some tutoring services are broad in scope and that there may not be sufficient one-on-one time with a tutor. With the development of a mobile application, a solution is possible to improve upon the tutoring experience for all students. The concept revolves around the formation of a labor market of freelancers, known as a gig economy, to create a large supply of tutors who can provide their services to a student looking for help in a specific course. A strategic process was followed to develop this mobile application, called Tuzee. To begin, an early concept and design was drafted to shape a clear vision statement and effective user experience. Planning and research followed, where technical requirements including an efficient database and integrated development environment were selected. After these prerequisites, the development stage of the application started and a working app produced. Subsequently, a business model was devised along with possible features to be added upon a successful launch. With a peer-to-peer approach powering the app, monitoring user engagement lies as a core principle for consistent growth. The vision statement will frequently be referred to: enhance university academics by enabling the interaction of students with each other.
ContributorsArcaro, Daniel James (Author) / Ahmad, Altaf (Thesis director) / Sopha, Matthew (Committee member) / Department of Information Systems (Contributor) / WPC Graduate Programs (Contributor) / Department of Management and Entrepreneurship (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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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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Leveraged buyouts have gone in and out of popularity over the last four decades. The first wave began in the 1980's with the rising popularity of junk bonds, followed by years of economic downturn, and then a rise and respective fall from the dot com era. However, in the 2000's,

Leveraged buyouts have gone in and out of popularity over the last four decades. The first wave began in the 1980's with the rising popularity of junk bonds, followed by years of economic downturn, and then a rise and respective fall from the dot com era. However, in the 2000's, attitudes were high and a period of low interest rates, covenant-lite loans, and relaxed lending conditions gave rise to some of the largest leveraged buyouts in US history. As the name implies, leveraged buyouts are predominantly structured with debt, around 70% of the total transaction value. Private equity firms execute leveraged buyouts on companies in strong industries, who have proven, stable cash flows, with the intent of cutting costs, divesting unneeded assets, and making the chain more efficient. After a time period of five to seven years, the private equity firm exits the deal through an initial public offering of the target company, a sale to another buyer, or dividend recapitalization. The Blackstone Group is one of the largest private equity firms in the US, and, with the favorable leveraged buyout conditions, especially in the real estate market, it wanted to build its real estate portfolio with an acquisition of Hilton Hotels & Resorts. At the time of consideration, Hilton was one of the largest hotel companies in the world, but was beginning to lag compared to its competitors Marriott and Starwood. After months of talks, Hilton agreed to be bought out by Blackstone at $47.50/share, for a total purchase price of $26bn. Blackstone had injected $5.7 of its own equity into the deal. The Great Recession caused a lot of investors to worry about Hilton's debt obligations, and Blackstone was able to restructure a significant portion of the debt to benefit both themselves and their creditors. As new CEO, Christopher J. Nassetta was able to strengthen Hilton by rearranging management, increasing franchising fees, expanding its capital-lite segments, and building more rooms internationally, Hilton was able to grow quicker than its competitors from 2007-2013 while minimizing operating expenses. On December 2, 2013, Hilton went public on the NYSE as HLT. Its enterprise value increased from $26bn to $33bn, and Blackstone was able to achieve an internal rate of return of 19%, while continuing to own 75% of Hilton's shares.
ContributorsNelson, Corey Mitchell (Author) / Simonson, Mark (Thesis director) / Aragon, George (Committee member) / School of Accountancy (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05