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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

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.
ContributorsQueen, Adrianna Louise (Author) / Prince, Linda (Thesis director) / Olsen, Christopher (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Data is ever present in the world today. Data can help predict presidential elections, Super Bowl champions, and even the weather. However, it's very hard, if not impossible, to predict how people feel unless they tell us. This is when impulse spending with data comes in handy. Companies are constantly

Data is ever present in the world today. Data can help predict presidential elections, Super Bowl champions, and even the weather. However, it's very hard, if not impossible, to predict how people feel unless they tell us. This is when impulse spending with data comes in handy. Companies are constantly looking for ways to get honest feedback when they are doing market research. Often, the research obtained ends up being unreliable or biased in some way. Allowing users to make impulse purchases with survey data is the answer. Companies can still gather the data that they need to do market research and customers can get more features or lives for their favorite games. It becomes a win-win for both users and companies. By adding the option to pay with information instead of money, companies can still get value out of frugal players. Established companies might not care so much about the impulse spending for purchases made in the application, however they would find a great deal of value in hearing about what customers think of their product or upcoming event. The real value from getting data from customers is the ability to train analytics models so that companies can make better predictions about consumer behavior. More accurate predictions can lead to companies being better prepared to meet the needs to the customer. Impulse spending with data provides the foundation to creating a software that can create value from all types of users regardless of whether the user is willing to spend money in the application.
ContributorsYotter, Alexandria Lee (Author) / Olsen, Christopher (Thesis director) / Sopha, Matthew (Committee member) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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Description

The current study examined heterogeneity in emerging adult children's routine and self-disclosure to parents using mixture modeling and explored predictors and outcomes associated with the patterns of disclosure. Participants consisted of 449 emerging adults (49% male, 68% European American, 65% college students, 33% single-parent families) who completed questionnaires every year

The current study examined heterogeneity in emerging adult children's routine and self-disclosure to parents using mixture modeling and explored predictors and outcomes associated with the patterns of disclosure. Participants consisted of 449 emerging adults (49% male, 68% European American, 65% college students, 33% single-parent families) who completed questionnaires every year across three waves (Mage at Time 1 = 18.4 years). Latent profile analyses suggested that large groups of emerging adults reported moderate levels of routine disclosure and low levels of self-disclosure to both mothers (79%) and fathers (36%), while other groups (20%) reported high levels of routine and self-disclosure to both parents. Profile membership was associated with predictors (parental autonomy granting, self-disclosure to friend, gender, family structure, college attendance) at Time 1 and outcomes (delinquency, depression, and prosocial behavior) at Time 3. Implications regarding the continued parent-child relationship and disclosure to parents in the third decade of life are discussed.

ContributorsDaye, Son (Author)
Created2019-04-11