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: Simonson, Mark
Description
Opening a business is often an exciting time in one’s life, as they take their business idea into the marketplace. But, most individuals fail to adequately address whether their business can actually succeed before entering the marketplace. The thesis, Creating a Successful Gluten-Free Bakery: A Financial Model and Analysis analyzes whether or not a gluten-free bakery is a viable business to open in today’s marketplace. By costing the main financial variables, creating a financial model of a gluten-free bakery, and running scenario analysis, I was able to find whether or not opening a gluten-free bakery was a viable business in today’s marketplace.
ContributorsDantonio, Adam (Author) / Simonson, Mark (Thesis director) / Arthur, Budolfson (Committee member) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
I will begin my paper by briefly describing the background which led to this paper, as well as stating my thesis. Next, I will define the term terrorism and explain the difference between it and the associated terms of insurgency and guerrilla warfare. Further, I will briefly go over the history of terrorism and the methods employed by terrorist organizations. After this introductory element, I will proceed to explore how terrorism has been funded in the past and how it is being funded at present. Lastly, I will present an overview of future methods of financing and make a proposal as to how the United States and the rest of the world could possibly disrupt these forms of financing. This paper is not intended to be comprehensive in nature, as this would be too large in scope, but rather use specific examples to illustrate certain methods and uses of terrorist financing
ContributorsWonderly, Frank (Author) / Simonson, Mark (Thesis director) / Smith, Geoffrey (Committee member) / Department of Military Science (Contributor) / School of Accountancy (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
This thesis investigates the use of MS Power BI in the case company’s heterogeneous computing environment. The empirical evidence was collected through the authors’ own observations and exposure to the modeling of dashboards, other supported external findings from interviews, published articles, academic journals, and speaking with leading experts at the WA ‘Dynamic Talks Seattle/Redmond: Big Data Analytics’ conference. Power BI modeling is effective for advancing the development of statistical thinking and data retrieving skills, finding trends and patterns in data representations, and making predictions. Computer-based data modeling gave meaning to math results, and supported examining implications of these results with simple charts to improve perception. Querying and other add-ins that would be seen as affordances when using other BI softwares, with some complexity removed in Power BI, make modeling data an easier undertaking for report builders. Using computer-based qualitative data analysis software, this paper details opportunities and challenges of data modeling with dashboards. Simple linear regression is used for case study use only.
ContributorsKusen, Alexandra Jeshua (Co-author) / Briones, Jared (Co-author) / Fugleberg, Aaron (Co-author) / Lin, Amy (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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
Description
This thesis discusses the case for Company X to improve its vast supply chain by implementing an artificial intelligence solution in the management of its spare parts inventory for manufacturing-related machinery. Currently, the company utilizes an inventory management system, based on previously set minimum and maximum thresholds, that doesn’t use predictive analytics to stock required spares inventory. This results in unnecessary costs and redundancies within the supply chain resulting in the stockout of spare parts required to repair machinery. Our research aimed to quantify the cost of these stockouts, and ultimately propose a solution to mitigate them. Through discussion with Company X, our findings led us to recommend the use of Artificial Intelligence (A.I.) within the inventory management system to better predict when stockouts would occur. As a result of data availability, our analysis began on a smaller scale, considering only a single manufacturing site at Company X. Later, our findings were extrapolated across all manufacturing sites. The analysis includes the cost of stockouts, the capital that would be saved with A.I. implementation, costs to implement this new A.I. software, and the final net present value (NPV) that Company X could expect in 10 years and 25 years. The NPV calculations explored two scenarios, an external partnership and the purchase of a small private company, that lead to our final recommendations regarding the implementation of an A.I. software solution in Company X’s spares inventory management system. Following the analysis, a qualitative discussion of the potential risks and market opportunities associated with the explored implementation scenarios further guided the determination of our final recommendations.
ContributorsHolohan, Joseph Michael Houston (Co-author) / Shahriari, Rosie (Co-author) / Aun, Jose (Co-author) / Heineke, Christopher (Co-author) / Gurrola, Macario (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Abstract: Handling the multiple functions of monetary policy that protect the U.S. economy not only on a short term, but also long-term scale is a complicated responsibility assigned to Federal Reserve, in which their actions present a profound impact on consumer confidence towards financial markets and global economies. Specifically, one of the most important goals of the Federal Reserve is to mitigate the risk of the United States to enter a recession, while maintaining a balanced approach when making those policy decisions. In this thesis, we focus on the monetary policy of the Federal Reserve, particularly, their role in controlling interest rates to prevent recessionary sentiment in the current state of the economy. Since 2008, markets have been stronger and previous policies like Dodd-Frank have ensured that market collapses during the Great Recession do not repeat itself. Yet, fluctuations in the yield curve, polarizing investment views, and unsettled consumer confidence has pointed to another recession in the near future. In this case, we will look at the way the Fed has implemented short term policies to lower this risk in order to fight volatile markets, however, fluctuating interest rates has its consequences. The goal of this thesis is to analyze the various ways the Fed has managed interest rates in the past and present, and further, to offer a framework to serve as the most effective policy to combat volatility and recessionary sentiment in the U.S. economy.
ContributorsPatel, Dylan (Author) / Sacks, Jana (Thesis director) / Simonson, Mark (Committee member) / Economics Program in CLAS (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
"Company X," a technology company, is known for being one of the world’s largest semiconductor chip manufacturers; however, they are also one of the largest authors of software. In 2019, "Company X" entered a new paradigm where, according to the CEO, while "Company X"’s core strategy has not changed, "Company X" is embracing the transition to a data-centric company from a PC-centric company. The scope that the project examines is--in this transition to a data-centric company and based on the company's current expertise and competitive advantages--should "Company X" be branching into an additional division or leverage existing intellectual property (IP)? The goal of the project is to understand how "Company X" can leverage its expertise in hardware and software service packages to maximize the value of the company.
ContributorsArellano, Andrea (Co-author) / Roos, Bailey (Co-author) / Broas, Joshua (Co-author) / Kotti, Abhigyan (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05