Matching Items (14)
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- All Subjects: Supply Chain
- Creators: Department of Finance
- Creators: School of Accountancy
Description
The process of producing enormous amounts of ephemeral clothing at accelerated rates, known as fast fashion, creates significant environmental and societal issues. The phenomenon of fast fashion rose due to globalization, economic factors, lack of legislation, and the advancement of technology. Governments, companies, and consumers must work together to create more sustainable retail supply chains. I have gathered information from interviews with individuals in the sustainable fashion industry, books, case studies, online reports, and newspaper articles. Based on my research, I recommend that companies should target wealthier consumers, develop a common language concerning sustainability, invest in sustainable fibers, and listen to factory employees for solutions to improve their working conditions. I also advise that the U.S governments should revise fashion copyright laws and international governments should emphasize regulations concerning the fashion industry. Lastly, consumers should adopt a price-per-wear mindset and utilize resale options. Overall, while perfect sustainability is improbable, consumers, governments, and companies should not use this as an excuse to avoid responsibility.
ContributorsWillner, Allison (Author) / Koretz, Lora (Thesis director) / Moore, James (Committee member) / Department of Management and Entrepreneurship (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This project did a deep dive on AI, business applications for AI and then my team and I built an AI model to better understand shipping patterns and inefficiencies of different porting regions.
ContributorsFreudenberger, Evan Martin (Author) / Wiedmer, Robert (Thesis director) / Duarte, Brett (Committee member) / Thunderbird School of Global Management (Contributor) / Department of Supply Chain Management (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Graytech Operations Management Simulation is an educational videogame that teaches the fundamental principles of operations management. It was coded from scratch in Java and is playable as an executable jar file. Designing the game required creating a business case, designing a production process, and turning that process into a playable program. The simulation serves as a simplified version of what the player will face in their professional careers, giving them a solid way to practice and experiment with introductory operations management principles in a low pressure setting. The game puts the player in charge of a simple factory floor. The player controls direct materials ordering, manages the capacities of each process, and identifies and responds to changing bottlenecks, all while managing limited financial resources. Using the principles and strategies taught in their introductory supply chain courses, the player will attempt to maximize profits by manipulating the production system. Through playing this simulation, the player will gain a higher understanding of operations management principles while also having fun in the process. The finished game, supplementary tutorial videos, and source code can be freely accessed online at www.graytechsimulation.wixsite.com/download.
ContributorsGray, Carson (Author) / Van Orden, Joseph (Thesis director) / Sopha, Matthew (Committee member) / Department of Finance (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
Only an Executive Summary of the project is included.
The goal of this project is to develop a deeper understanding of how machine learning pertains to the business world and how business professionals can capitalize on its capabilities. It explores the end-to-end process of integrating a machine and the tradeoffs and obstacles to consider. This topic is extremely pertinent today as the advent of big data increases and the use of machine learning and artificial intelligence is expanding across industries and functional roles. The approach I took was to expand on a project I championed as a Microsoft intern where I facilitated the integration of a forecasting machine learning model firsthand into the business. I supplement my findings from the experience with research on machine learning as a disruptive technology. This paper will not delve into the technical aspects of coding a machine model, but rather provide a holistic overview of developing the model from a business perspective. My findings show that, while the advantages of machine learning are large and widespread, a lack of visibility and transparency into the algorithms behind machine learning, the necessity for large amounts of data, and the overall complexity of creating accurate models are all tradeoffs to consider when deciding whether or not machine learning is suitable for a certain objective. The results of this paper are important in order to increase the understanding of any business professional on the capabilities and obstacles of integrating machine learning into their business operations.
The goal of this project is to develop a deeper understanding of how machine learning pertains to the business world and how business professionals can capitalize on its capabilities. It explores the end-to-end process of integrating a machine and the tradeoffs and obstacles to consider. This topic is extremely pertinent today as the advent of big data increases and the use of machine learning and artificial intelligence is expanding across industries and functional roles. The approach I took was to expand on a project I championed as a Microsoft intern where I facilitated the integration of a forecasting machine learning model firsthand into the business. I supplement my findings from the experience with research on machine learning as a disruptive technology. This paper will not delve into the technical aspects of coding a machine model, but rather provide a holistic overview of developing the model from a business perspective. My findings show that, while the advantages of machine learning are large and widespread, a lack of visibility and transparency into the algorithms behind machine learning, the necessity for large amounts of data, and the overall complexity of creating accurate models are all tradeoffs to consider when deciding whether or not machine learning is suitable for a certain objective. The results of this paper are important in order to increase the understanding of any business professional on the capabilities and obstacles of integrating machine learning into their business operations.
ContributorsVerma, Ria (Author) / Goegan, Brian (Thesis director) / Moore, James (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
In order to graduate with honors from Barrett, the Honors College at Arizona State University, I have completed the following thesis under the direction of Dr. Craig Carter and Dr. John Eaton. The purpose of this thesis is to perform preliminary and proprietary research on the sustainability of components of the supply chain of local business within the greater Phoenix, Arizona area in order to determine practices that can lead to and even increase success in a competitive niche of already competitive industries, especially during times of supply chain stress. My hypothesis is that preliminary and proprietary research will both display that the consumer aspect of the supply chain of local business is the most essential, especially if other aspects of the supply chain experience distress. My preliminary research involved breaking down the title of this thesis into four parts: sustainability, supply chain, local business, and the Phoenix local business market and then performing internet research and interviews in order to form a solid understanding of such concepts. Then, I performed my proprietary research, which involved conducting a consumer survey and three interviews with local business owners. Though my hypothesis is not supported, I have learned a lot on the topic of this thesis itself, as well as on the thesis writing process.
ContributorsBrunacini, Maria Abigail (Author) / Carter, Craig (Thesis director) / Eaton, John (Committee member) / WPC Graduate Programs (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / School of Accountancy (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The Supply Chain of a company is the most critical component of a business as it directly impacts a company’s ability to deliver products/services to customers is a timely, cost effective method. With this amount of importance, a resilient supply chain is pivotal for positive future earnings in each successive quarter. Two pivotal metrics to gauge a Supply Chain include Production Delays and Excess Inventory. Through in-depth analysis, it was found that these metrics had caused abnormal amounts of price volatility with a stock’s performance. Understanding these metrics, the impact and lesson that COVID had taught, and analyzing earnings transcripts of publicly traded company’s demonstrates the use of Supply Chain health in comparison to company performance. This thesis aims to examine how a company's supply chain affects its performance, by analyzing different metrics and disruptions that have caused significant volatility in the stock market. The objective is to help investors maximize their profitability or reduce their risk by identifying the key factors that impact a company's supply chain.
ContributorsNatarajan, Tharun (Author) / Printezis, Antonios (Thesis director) / Licon, Lawrence (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / Department of Finance (Contributor)
Created2023-05
Description
Nike, the largest athletic apparel company in the world, has a very complex wide-reaching supply chain. As pioneers of outsourcing production and products, they have dealt with many challenges and problems since their beginning in 1964. As Nike has faced their controversial history of labor strikes, protests, boycotts, and much more, they began to restructure their business model and supply chain practices. Following this came audits, minimum age requirements, factory condition monitoring, and public disclosures of locations. With these new initiatives and growth in Nike’s supply chain, an overarching analysis of Ports of Lading, Shipment Origins, Ports of Unlading, Shippers/Suppliers, and Carriers can give a glimpse into the world-wide network of their apparel. Finally, through my data analysis and secondary source research, I will explain how Nike's supply chain emerged, adjusted, and changed given different textile regulatory environments over the years.
ContributorsCrippen, Julia (Author, Co-author) / Wiedmer, Robert (Thesis director) / Sewell, Dennita (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / Department of Finance (Contributor)
Created2023-05
Description
This thesis examines real experiences of how small businesses responded to the COVID-19 pandemic in order to generate recommendations for said businesses post pandemic from a finance and supply chain perspective. A literature review finds that several trends that emerged over the pandemic, such as supply and demand changes, workforce difficulties, financing struggles, and the effectiveness of the Payment Protection Program. Next, we conducted a survey of local small businesses based on the findings in the literature review. The survey aimed to examine managers’ struggles, strategies, and responses to the pandemic. The survey responses were examined and then analyzed to find how they compare to the statistics from the literature review. The findings from the results and other sources served as the basis for which small business recommendations are made on how to prepare for future unprecedented economic crises and better situate themselves to respond.
ContributorsOnyszchuk, Ethan (Author) / Thomas, Ryan (Co-author) / Simonson, Mark (Thesis director) / Printezis, Antonios (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / School of Accountancy (Contributor) / Department of Information Systems (Contributor)
Created2022-05
Description
Supply chain sustainability has become an increasingly important topic for corporations
due to consumer demands, regulatory requirements, and employee retention and productivity.
Since more and more stakeholders are beginning to care about sustainability, companies are
looking at how they can reduce their carbon footprint without it leading to higher costs. Although
sustainable supply chain operations are often associated with higher costs, new technology has
surfaced within the last decade that makes this association come into question. This paper serves as an investigation on whether or not implementation of recent technology will not only make for more sustainable supply chains, but also bring cost savings to a company. For the sake of simplicity, this paper analyzes the topic within the context of the consumer packaged goods (CPG) industry. The three categories of technology that were evaluated are artificial intelligence, Internet of Things, and data integration systems. Internship projects and/or published case studies and articles were examined to explore the relationship between the technology, supply chain sustainability, and costs. The findings of this paper indicate that recent technology offers companies innovative sustainability solutions to supply chains without sacrificing cost. This calls for CPG companies to invest in and implement technology that allows for more sustainable supply chains. Shying away from this because of cost concerns is no longer necessary.
ContributorsDixon, Logan (Author) / Printezis, Antonios (Thesis director) / Macias, Jeff (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Dean, W.P. Carey School of Business (Contributor)
Created2024-05