Matching Items (10)
Filtering by
- All Subjects: Autonomous Vehicles
- Creators: Simonson, Mark
- Status: Published
Description
The purpose of this thesis was to design a market entrance strategy for Company X to enter the microcontroller (MCU) market within the Internet of Things (IoT). The five IoT segments are automotive; medical; retail; industrial; and military, aerospace, and government. To reach a final decision, we will research the markets, analyze make versus buy scenarios, and deliver a financial analysis on the chosen strategy. Based on the potential financial benefits and compatibility with Company X's current business model, we recommend that Company X enter the automotive segment through mergers & acquisitions (M&A). After analyzing the supply chain structure of the automotive IoT, we advise Company X to acquire Freescale Semiconductor for $46.98 per share.
ContributorsBradley, Rachel (Co-author) / Fankhauser, Elisa (Co-author) / McCoach, Robert (Co-author) / Zheng, Weilin (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Mike (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / School of Accountancy (Contributor) / School of International Letters and Cultures (Contributor) / WPC Graduate Programs (Contributor)
Created2015-05
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
Exchange traded funds (ETFs) in many ways are similar to more traditional closed-end mutual funds, although thee differ in a crucial way. ETFs rely on a creation and redemption feature to achieve their functionality and this mechanism is designed to minimize the deviations that occur between the ETF’s listed price and the net asset value of the ETF’s underlying assets. However while this does cause ETF deviations to be generally lower than their mutual fund counterparts, as our paper explores this process does not eliminate these deviations completely. This article builds off an earlier paper by Engle and Sarkar (2006) that investigates these properties of premiums (discounts) of ETFs from their fair market value. And looks to see if these premia have changed in the last 10 years. Our paper then diverges from the original and takes a deeper look into the standard deviations of these premia specifically.
Our findings show that over 70% of an ETFs standard deviation of premia can be explained through a linear combination consisting of two variables: a categorical (Domestic[US], Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market indicators such as the economic freedom index and investment freedom index are insignificant predictors of an ETFs standard deviation of premia when combined with the categorical variable. These findings differ somewhat from existing literature which indicate that these factors should have a significant impact on the predictive ability of an ETFs standard deviation of premia.
Our findings show that over 70% of an ETFs standard deviation of premia can be explained through a linear combination consisting of two variables: a categorical (Domestic[US], Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market indicators such as the economic freedom index and investment freedom index are insignificant predictors of an ETFs standard deviation of premia when combined with the categorical variable. These findings differ somewhat from existing literature which indicate that these factors should have a significant impact on the predictive ability of an ETFs standard deviation of premia.
ContributorsZhang, Jingbo (Co-author, Co-author) / Henning, Thomas (Co-author) / Simonson, Mark (Thesis director) / Licon, L. Wendell (Committee member) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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 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
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 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
Description
The object of the present study is to examine methods in which the company can optimize their costs on third-party suppliers whom oversee other third-party trade labor. The third parties in scope of this study are suspected to overstaff their workforce, thus overcharging the company. We will introduce a complex spreadsheet model that will propose a proper project staffing level based on key qualitative variables and statistics. Using the model outputs, the Thesis team proposes a headcount solution for the company and problem areas to focus on, going forward. All sources of information come from company proprietary and confidential documents.
ContributorsLoo, Andrew (Co-author) / Brennan, Michael (Co-author) / Sheiner, Alexander (Co-author) / Hertzel, Michael (Thesis director) / Simonson, Mark (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor)
Created2014-05
Description
This thesis examines the value creation potential of renovating an existing commercial real estate asset to a medical office. It begins by examining commercial real estate and the medical sector at a high level. It then discusses the various criteria used to select a subject property for renovation. This renovation is then depicted through a modified pitch book that contains a financial model and pro forma.
ContributorsLarrea, Justin (Co-author) / Berger, Nicholas (Co-author) / Peters, Matthew (Co-author) / Simonson, Mark (Thesis director) / Gray, William (Committee member) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This thesis examines the value creation potential of renovating an existing commercial real estate asset to a medical office. It begins by examining commercial real estate and the medical sector at a high level. It then discusses the various criteria used to select a subject property for renovation. This renovation is then depicted through a modified pitch book that contains a financial model and pro forma.
ContributorsBerger, Nicholas James (Co-author) / Larrea, Justin (Co-author) / Peters, Matthew (Co-author) / Simonson, Mark (Thesis director) / Gray, William (Committee member) / School of Accountancy (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This thesis examines the value creation potential of renovating an existing commercial real estate asset to a medical office. It begins by examining commercial real estate and the medical sector at a high level. It then discusses the various criteria used to select a subject property for renovation. This renovation is then depicted through a modified pitch book that contains a financial model and pro forma.
ContributorsPeters, Matthew Scott (Co-author) / Larrea, Justin (Co-author) / Berger, Nicholas (Co-author) / Simonson, Mark (Thesis director) / Gray, William (Committee member) / Department of Finance (Contributor, Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
By 2030, annual global automobile production is projected to reach over 110 million vehicles with an increasing quantity having autonomous capabilities. Based on this trend, Company X is poised to drive profits by leveraging advancing technology from their subsidiary to gain significant market share within the AV industry. This will solidify Company X’s position as a key player and leader within the AV industry, which is expected to grow to $7 trillion by 2050, and Company X can achieve this by providing a technology suite including a systems on a chip to auto manufacturers and creating partnerships in the technology and automotive industry.
ContributorsAvery, Hailey (Co-author) / Green, Ryan (Co-author) / Hall, Robert (Co-author) / Hummel, Haley (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05