Matching Items (7)
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- All Subjects: Data Analytics
- Creators: Department of Economics
- Creators: Department of Management
Description
For our collaborative thesis we explored the US electric utility market and how the Internet of Things technology movement could capture a possible advancement of the current existing grid. Our objective of this project was to successfully understand the market trends in the utility space and identify where a semiconductor manufacturing company, with a focus on IoT technology, could penetrate the market using their products. The methodology used for our research was to conduct industry interviews to formulate common trends in the utility and industrial hardware manufacturer industries. From there, we composed various strategies that The Company should explore. These strategies were backed up using qualitative reasoning and forecasted discounted cash flow and net present value analysis. We confirmed that The Company should use specific silicon microprocessors and microcontrollers that pertained to each of the four devices analytics demand. Along with a silicon strategy, our group believes that there is a strong argument for a data analytics software package by forming strategic partnerships in this space.
ContributorsLlazani, Loris (Co-author) / Ruland, Matthew (Co-author) / Medl, Jordan (Co-author) / Crowe, David (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Mike (Committee member) / Department of Economics (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor) / Hugh Downs School of Human Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The following creative project was a two part study regarding the wedding and event planning industry. Part one consisted of planning and executing an event followed by an analysis of the event in terms of strengths, weaknesses, and customer feedback. Part two consisted of evaluating a potential wedding planning company by the standards of the Business Model Canvas Method. The overall goal of this project was to determine if I would be pursuing a career as an independent wedding and event consultant or exploring other career options based on the research conducted and which option would be best aligned with my desires and career aspirations.
ContributorsHawbaker, Christina Elizabeth (Author) / Peck, Sidnee (Thesis director) / LePine, Marcie (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor) / W. P. Carey School of Business (Contributor) / Department of Management (Contributor)
Created2013-12
Description
The Barrett, the Honors College Internships and Research Department provides information regarding internship and research position availabilities, generates greater exposure to various companies and organizations seeking student help, and offers students assistance in applying for employment. The office's current objectives are to increase student engagement and escalate student success in internship and research involvement. The application of marketing resources requires evaluation and improvement in order to increase attendance at the events held by the office each semester, which have consistently received disappointing turnouts. This study examines the marketing communication channels currently used in order to productively correlate these channels with event attendance.
ContributorsVillemez, Hallie Katherine (Author) / Eaton, John (Thesis director) / Olsen, Doug (Committee member) / Russo, Lianne (Committee member) / Barrett, The Honors College (Contributor) / W. P. Carey School of Business (Contributor) / Department of Marketing (Contributor)
Created2013-12
Description
As the use of Big Data gains momentum and transitions into mainstream adoption, marketers are racing to generate valuable insights that can create well-informed strategic business decisions. The retail market is a fiercely competitive industry, and the rapid adoption of smartphones and tablets have led e-commerce rivals to grow at an unbelievable rate. Retailers are able to collect and analyze data from both their physical stores and e-commerce platforms, placing them in a unique position to be able to fully capitalize on the power of Big Data. This thesis is an examination of Big Data and how marketers can use it to create better experiences for consumers. Insights generated from the use of Big Data can result in increased customer engagement, loyalty, and retention for an organization. Businesses of all sizes, whether it be enterprise, small-to-midsize, and even solely e-commerce organizations have successfully implemented Big Data technology. However, there are issues regarding challenges and the ethical and legal concerns that need to be addressed as the world continues to adopt the use of Big Data analytics and insights. With the abundance of data collected in today's digital world, marketers must take advantage of available resources to improve the overall customer experience.
ContributorsHaghgoo, Sam (Author) / Ostrom, Amy (Thesis director) / Giles, Bret (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor) / W. P. Carey School of Business (Contributor) / Department of Management (Contributor)
Created2014-05
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
League of Legends is a Multiplayer Online Battle Arena (MOBA) game. MOBA games are generally formatted where two teams of five, each player controlling a character (champion), will try to take each other's base as quickly as possible. Currently, with about 70 million, League of Legends is number one in the digital entertainment industry with $1.63 billion dollars of revenue in year 2015. This research analysis scopes in on the niche of the "Jungler" role between different tiers of player in League of Legends. I uncovered differences in player strategy that may explain the achievement of high rank using data aggregation through Riot Games' API, data slicing with time-sensitive data, random sampling, clustering by tiers, graphical techniques to display the cluster, distribution analysis and finally, a comprehensive factor analysis on the data's implications.
ContributorsPoon, Alex (Author) / Clark, Joseph (Thesis director) / Simon, Alan (Committee member) / Department of Information Systems (Contributor) / Department of Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The United States has an institutional prison system built on the principle of retributive justice combined with racial prejudice that despite countless efforts for reform currently holds 2.3 million individuals, primarily minorities, behind bars. This institution has remained largely unchanged, meanwhile 83.4% of those who enter the system will return within one decade and it currently costs nearly $39 billion each year (Alper 4). Because the prison institution consistently fails to address the core root of crime, there is a great need to reconsider the approach taken towards those who break our nation’s laws with the dual purpose of enhancing freedom and reducing crime. This paper outlines an original theoretical framework being implemented by Project Resolve that can help to identify and implement solutions for our prison system without reliance on political, institutional, or societal approval. The method focuses on three core goals, the first is to connect as much of the data surrounding prisoners and the formerly incarcerated as possible, the second is to use modern analytic approaches to analyze and propose superior solutions for rehabilitation, the third is shifting focus to public interest technology both inside prisons and the parole process. The combination of these objectives has the potential to reduce recidivism to significantly, deter criminals before initial offense, and to implement a truly equitable prison institution.
ContributorsGilchrist, Troy (Author) / Martin, Thomas (Thesis director) / Wenrick, Lukas (Committee member) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05