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Description
In this paper, I have designed a business model for a new type of fashion retail
store. This store will perfect the personal styling experience by utilizing customer and
apparel data to make individualized apparel recommendations. The format of this store
will heavily reduce the amount of search time for customers by only

In this paper, I have designed a business model for a new type of fashion retail
store. This store will perfect the personal styling experience by utilizing customer and
apparel data to make individualized apparel recommendations. The format of this store
will heavily reduce the amount of search time for customers by only showing clothing
pieces that each person is likely to purchase, based on predictive analytics. In order to
plan this business model and determine whether a company of this style could be
successful, this paper includes research on the current environment of the fashion
industry, the company’s potential target market segmentation, and tactics for developing
the best customer offering.
ContributorsTrevino, Alexandra (Author) / Riker, Elise (Thesis director) / Schlacter, John (Committee member) / WPC Graduate Programs (Contributor) / School of International Letters and Cultures (Contributor) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
In the wide world of sports, not all fan bases are created equally—especially in the NBA. Differences in factors like tradition, history, team performance amongst teams make each fan base distinctly unique. This paper will analyze how team performance effects one component of fan behavior: home game attendance. Using win-loss

In the wide world of sports, not all fan bases are created equally—especially in the NBA. Differences in factors like tradition, history, team performance amongst teams make each fan base distinctly unique. This paper will analyze how team performance effects one component of fan behavior: home game attendance. Using win-loss data and home game attendance data for each NBA team from 2001 to 2017, I will construct statistical models to estimate how great of an impact team performance has on each team’s home game attendance. I expect each team’s fan base to respond differently to changes in their team’s win-loss record. This paper will also attempt to quantify other facts that impact attendance at NBA games, including year-to-year changes in team salary expenditures, regional income, and the number of star players playing for the team. Finally, this paper will explore the factors that affect home game attendance for specific games within a given season—things like weather, strength of opponent, and win streaks. Ultimately, the goal of this paper will be to provide NBA business analysts with resources to more precisely anticipate their team’s home game attendance. The ability to understand what motivates the behavior of a fan base is invaluable in creating a marketing strategy that drives fans to the arena. This paper will help to identify teams that are most susceptible to significant fluctuations in attendance and outline alternative strategies to positioning their product offering effectively to fans.
ContributorsSloan, Jacob Marlow (Author) / Lee, Christopher (Thesis director) / Eaton, John (Committee member) / Department of Marketing (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description

Hundreds of thousands of archaeological investigations in the United States conducted over the last several decades have documented a large portion of the recovered archaeological record in the United States. However, if we are to use this enormous corpus to achieve richer understandings of the past, it is essential that

Hundreds of thousands of archaeological investigations in the United States conducted over the last several decades have documented a large portion of the recovered archaeological record in the United States. However, if we are to use this enormous corpus to achieve richer understandings of the past, it is essential that both CRM and academic archaeologists change how they manage their digital documents and data over the course of a project and how this information is preserved for future use. We explore the nature and scope of the problem and describe how it can be addressed. In particular, we argue that project workflows must ensure that the documents and data are fully documented and deposited in a publicly accessible, digital repository where they can be discovered, accessed, and reused to enable new insights and build cumulative knowledge.

Cientos de miles de investigaciones arqueológicas en los Estados Unidos realizado en las últimas décadas han documentado una gran parte del registro arqueológico recuperado en los Estados Unidos. Sin embargo, si vamos a utilizar este enorme corpus para lograr entendimientos más ricos del pasado, es esencial que CRM y los arqueólogos académicos cambian cómo administran sus documentos digitales y los datos en el transcurso de un proyecto y cómo se conserva esta información para uso en el futuro. Exploramos la naturaleza y el alcance del problema y describimos cómo se pueden abordarse. En particular, sostenemos que los flujos de trabajo de proyecto deben asegurarse que los documentos y datos son totalmente documentados y depositados en un repositorio digital de acceso público, donde puede ser descubiertos, acceder y reutilizados para activar nuevos conocimientos y construir conocimiento acumulativo.

ContributorsMcManamon, Francis P. (Author) / Kintigh, Keith W. (Author) / Ellison, Leigh Anne (Author) / Brin, Adam (Author)
Created2017-08