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Attendance Elasticity of Win Percentage in the NBA: An Exploration of the Effects of Team Performance on Home Game Attendance

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

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.

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Agent

Created

Date Created
2018-05

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Monetization of Autonomous Vehicle Data

Description

Autonomous vehicles (AV) are capable of producing massive amounts of real time and precise data. This data has the ability to present new business possibilities across a vast amount of markets. These possibilities range from simple applications to unprecedented use

Autonomous vehicles (AV) are capable of producing massive amounts of real time and precise data. This data has the ability to present new business possibilities across a vast amount of markets. These possibilities range from simple applications to unprecedented use cases. With this in mind, the three main objectives we sought to accomplish in our thesis were to: 1. Understand if there is monetization potential in autonomous vehicle data 2. Create a financial model of what detailing the viability of AV data monetization 3. Discover how a particular company (Company X) can take advantage of this opportunity, and outline how that company might access this autonomous vehicle data.

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Agent

Created

Date Created
2018-05

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The Data Arms Race: Reimagining Data Transparency, Ethics and Regulations

Description

Data has quickly become a cornerstone of society. Across our daily lives, industry, policy, and more, we are experiencing what can only be called a “data revolution” igniting ferociously. While data is gaining more and more importance, consumers do not

Data has quickly become a cornerstone of society. Across our daily lives, industry, policy, and more, we are experiencing what can only be called a “data revolution” igniting ferociously. While data is gaining more and more importance, consumers do not fully understand the extent of its use and subsequent capitalization by companies. This paper explores the current climate relating to data security and data privacy. It aims to start a conversation regarding the culture around the sharing and collection of data. We explore aspects of data privacy in four tiers: the current cultural and social perception of data privacy, its relevance in our daily lives, its importance in society’s dialogue. Next, we look at current policy and legislature in place today, focusing primarily on Europe’s established GDPR and the incoming California Consumer Privacy Act, to see what measures are already in place and what measures need to be adopted to mold more of a culture of transparency. Next, we analyze current data privacy regulations and power of regulators like the FTC and SEC to see what tools they have at their disposal to ensure accountability in the tech industry when it comes to how our data is used. Lastly, we look at the potential act of treating and viewing data as an asset, and the implications of doing so in the scope of possible valuation and depreciation techniques. The goal of this paper is to outline initial steps to better understand and regulate data privacy and collection practices. Our goal is to bring this issue to the forefront of conversation in society, so that we may start the first step in the metaphorical marathon of data privacy, with the goal of establishing better data privacy controls and become a more data-conscious society.

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Date Created
2019-05

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Investigating the Relationship between Neighborhood Socioeconomic Status and Proximity to Public Services

Description

With growing levels of income inequality in the United States, it remains as important as ever to ensure indispensable public services are readily available to all members of society. This paper investigates four forms of public services (schools, libraries, fire

With growing levels of income inequality in the United States, it remains as important as ever to ensure indispensable public services are readily available to all members of society. This paper investigates four forms of public services (schools, libraries, fire stations, and police stations), first by researching the background of these services and their relation to poverty, and then by conducting geospatial and regression analysis. The author uses Esri's ArcGIS Pro software to quantify the proximity to public services from urban American neighborhoods (census tracts in the cities of Phoenix and Chicago). Afterwards, the measures indicating proximity are compared to the socioeconomic statuses of neighborhoods using regression analysis. The results indicate that pure proximity to these four services is not necessarily correlated to socioeconomic status. While the paper does uncover some correlations, such as a relationship between school quality and socioeconomic status, the majority of the findings negate the author's hypothesis and show that, in Phoenix and Chicago, there is not much discrepancy between neighborhoods and the extent to which they are able to access vital government-funded services.

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Agent

Created

Date Created
2018-05

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Social Media Sentiment as a Comparative Business Metric - Using Logical Appeals Among Businesses to Understand Consumer Reaction and Engagement with Various Brands

Description

With the discovery of “Big Data” and the positive impacts properly using data can have on any and every business, it is no wonder that there has been an explosion of companies choosing to implement many possible uses of data.

With the discovery of “Big Data” and the positive impacts properly using data can have on any and every business, it is no wonder that there has been an explosion of companies choosing to implement many possible uses of data. Consumers and any people who may not fully understand the process of collecting, analyzing, and visualizing data may be more easily swayed towards believing something that might not necessarily be true or represented accurately. Often it may feel like every hot topic issue has groups on both sides of the issues using seemingly objective data to prove why their side is correct. Seeing two contradictory sides with seemingly factual data can leave many people confused and unsure what the correct course of action is. With this in mind, I realized that there was a chance the businesses could be creating similar misrepresentations of data to sway customers that the company’s product or service is absolutely a necessity in their lives. After all, the world of marketing and understanding consumer preference is a wildly changing and constant moving target that companies have to navigate. Using data surrounding their products and services to create a desire in consumers to buy and use their offerings seems like a surefire way to successfully target market segments.
As I researched and conducted initial analysis for this project, I quickly ran into a few roadblocks that lead to me needing to pivot off of certain ideas and adapt my initial plans to fit what was actually being done in the current marketing environment. In reality, most businesses are not up for taking the risk of explicitly giving real metrics of their products and services to customers. Due to this, my thesis evolved into finding other ways that companies would use logical appeals to represent their products and comparatively analyze how these companies choose to represent themselves on a social media platform.

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Agent

Created

Date Created
2020-05

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Personalizing the In-Store Shopping Experience

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

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.

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Agent

Created

Date Created
2020-05

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Sagebrush Coffee: Applying Data Analytics to Customer Purchases

Description

Sagebrush Coffee is a small business in Chandler, Arizona that purchases green beans, roasts them in small batches for quality, and ships fresh, gourmet roasted coffee beans across the nation. Deciding which coffee beans to buy and roast is one

Sagebrush Coffee is a small business in Chandler, Arizona that purchases green beans, roasts them in small batches for quality, and ships fresh, gourmet roasted coffee beans across the nation. Deciding which coffee beans to buy and roast is one of the most crucial business decisions Sagebrush and other gourmet coffee roasters face. Further complicating this decision is the fact that coffee is a crop, and like all crops, has a specific growing season and the exact same product cannot usually be ordered from year to year, even if it proves to be successful. The goal of this research is to use data analytics and visualization to help Sagebrush make better purchasing decisions by identifying consumer purchasing trends and providing a recommendation for their portfolio mix. In the end, I found that Latin American coffees are popular with both returning and first-time customers, but a specific country of origin does not appear to be associated with the top coffee producing countries. Additionally, December is a critical month for Sagebrush and Sagebrush should make sure to target the states with the most sales: California, Pennsylvania, and New York. Arizona has growth potential as it is not one of the top three locations, despite the presence of a physical store. Also included in the following report is a portfolio recommendation suggesting how many of each product based on region, processing type, and roast level to carry in inventory.

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Created

Date Created
2018-05

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Twitter Analytics

Description

Twitter is one of the most powerful communication tools ever created. There are over 1.3 billion registered Twitter users (Smith, 2016). 100 million daily people actively use Twitter every day. 6,000 tweets are tweeted every second. Communication has never been

Twitter is one of the most powerful communication tools ever created. There are over 1.3 billion registered Twitter users (Smith, 2016). 100 million daily people actively use Twitter every day. 6,000 tweets are tweeted every second. Communication has never been so abundant, public, and chronicled. Not only is there a gigantic population to market to, but also a wealth of information about that population to record and draw insights from. However, many companies' Twitter accounts fail to generate popular posts on a regular basis. The content that they produce is ineffective and uninteresting. In my opinion, these companies are failing to take advantage of a huge opportunity. I decided to dive into the Twitter accounts of some of my favorite companies to see what they were doing wrong and how they could improve. My thesis investigates 18 different company Twitter accounts from four different industries: Athletic Apparel, Technology, Online Entertainment, and Car Manufacturing. I pulled 200 tweets from each company and cleaned and organized the data into an Excel spreadsheet. I investigated how certain variables impacted tweet popularity across the four industries. First, I looked at tweet format to determine whether posts, retweets, or replies were the best format. Then, I analyzed how different elements of a tweet's content could impact the tweet's popularity. Specifically, I looked at the effects of including links, hashtags, and questions into the tweet. Next, I tried to determine the optimal tweet length for each industry. And finally, I compared each industry's tweet sentiment preferences. I then summarized my findings into a series of recommendations for companies to improve their tweet popularity.

Contributors

Agent

Created

Date Created
2016-05

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Value of Twitter: Using Text Mining Methods to Gain Insight into the 2016 Presidential Race

Description

This project analyzes the tweets from the 2016 US Presidential Candidates' personal Twitter accounts. The goal is to define distinct patterns and differences between candidates and parties use of social media as a platform. The data spans the period of

This project analyzes the tweets from the 2016 US Presidential Candidates' personal Twitter accounts. The goal is to define distinct patterns and differences between candidates and parties use of social media as a platform. The data spans the period of September 2015 to March 2016, which was during the primary races for the Republicans and Democrats. The overall purpose of this project is to contribute to finding new ways of driving value from social media, in particular Twitter.

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Created

Date Created
2016-05

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A Study on Occupational Fraud within Small Businesses

Description

The main goal of this study was to understand the awareness of small business owners regarding occupational fraud, meaning fraud committed from within an organization. A survey/questionnaire was used to gather insight into the knowledge and perceptions of small business

The main goal of this study was to understand the awareness of small business owners regarding occupational fraud, meaning fraud committed from within an organization. A survey/questionnaire was used to gather insight into the knowledge and perceptions of small business owners, while also obtaining information about the history of fraud and the internal controls within their business. Twenty-four owners of businesses with less than 100 employees participated in the study. The results suggest that small business owners overestimate their knowledge regarding internal controls and occupational fraud, while also underestimating the risk of fraud within their own business. In fact, 92% of participants were not at all familiar with the popular Internal Control \u2014 Integrated Framework published by the Committee of Sponsoring Organizations of the Treadway Commission. The results also show that small business owners tend to overestimate the protection provided by their currently implemented controls in regard to their risk of fraud. Overall, through continued knowledge of internal controls and occupational fraud, business owners can better protect their businesses from the risk of occupational fraud by increasing their awareness of fraud.

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Date Created
2014-05