Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
Displaying 1 - 2 of 2
Filtering by
- Creators: Department of Supply Chain Management
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
The world of business has become increasingly globalized over the years. Companies are seeking business internationally and it has become common to work with people from different parts of the world. It is imperative that those who work in business understand and recognize the differences between their home country and culture, and the country and culture of those with whom they are doing business. With that being said, students who intend on going into business post graduation must keep in mind this globalized mindset when applying for jobs. As a student in the W.P. Carey School of Business at Arizona State University, I learned how important this is after receiving my International Business certificate while studying abroad for a semester in Spain. I found that the skills that I gained and what I learned about myself, and the European culture helped shape the way I view the world of business. I also believe that this helped differentiate me from other applicants when applying for internships. I believe that every business student, if willing and financially able, should study abroad not only to gain an insightful experience, but because it helps place them above other applicants when applying for jobs or internships.This project included research to find evidence that supports this belief through surveys and interviews with business students who have studied abroad in the past, and through interviews with employers and recruiters from all over the country. The creative portion of this thesis includes a promotional video, using the student interviews, as well as my own personal experience, to further promote studying abroad for business students.
ContributorsStebbings, Lauren Ashley (Author) / Koretz, Lora (Thesis director) / Moore, James (Committee member) / Laws, Michelle (Committee member) / School of Art (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12