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- All Subjects: Behavioral Economics
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- Member of: Barrett, The Honors College Thesis/Creative Project Collection
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Description
This study aims to identify the potential irrationality in the personal investment decision-making habits of university students, as influenced by the framing effect, loss aversion, and related heuristics. Researchers conducted a cross-sectional study of 114 students (n = 102). Participants responded to a survey regarding their willingness to invest in certain hypothetical investment scenarios. Outcome was measured primarily using Likert scales and yes
o binomial options regarding the participant’s willingness to participate in a specific deal. The study was broken into three blocks, the first of which dealt with the framing effect and the subsequent two considered loss aversion. Of the data collected, there were multiple significant results found to support the framing effect and loss aversion. There was a significant difference between responses that were positively and negatively framed, and between varying upside potential in equivalent-risk scenarios. For block one, those participants who received the positive framing condition were more likely to invest in the master’s program than those who received the negative framing condition. For blocks two and three, the majority of participants exhibited loss averse behavior more extreme than the predicted amounts; closer to 4x the upside was required (rather than the predicted 2x) for the participants to participate in the deal. Although the results did replicate the framing effect and loss aversion, college students were more loss averse than was predicted.
o binomial options regarding the participant’s willingness to participate in a specific deal. The study was broken into three blocks, the first of which dealt with the framing effect and the subsequent two considered loss aversion. Of the data collected, there were multiple significant results found to support the framing effect and loss aversion. There was a significant difference between responses that were positively and negatively framed, and between varying upside potential in equivalent-risk scenarios. For block one, those participants who received the positive framing condition were more likely to invest in the master’s program than those who received the negative framing condition. For blocks two and three, the majority of participants exhibited loss averse behavior more extreme than the predicted amounts; closer to 4x the upside was required (rather than the predicted 2x) for the participants to participate in the deal. Although the results did replicate the framing effect and loss aversion, college students were more loss averse than was predicted.
ContributorsKlemish, Colby (Author) / Radway, Debra (Thesis director) / Arrfelt, Mathias (Committee member) / Goldinger, Stephen (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Psychology (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Over 50% of the US population has listened to a podcast as of 2019. That is over 144 million people in the US alone that can potentially generate revenue for a podcast host. In 2017, podcast advertising secured revenues of $314 million. It is expected to grow to $659 million by 2020 (Goldberg). There is a growing market of active podcast listeners for advertisers to tap into. There is so much potential in podcasting that Spotify has recently decided that they are willing to spend $400-500 million on this category alone in 2019. In that large figure they have acquired “Gimlet”, a podcasting company, for 230 million and “Anchor”, a creation/distribution platform (Heater).
These massive amounts of investment in podcasting is assuring for the podcast industry that began as recently as the early 2000’s. There is money to be made for the content creators of podcasts as well. This paper focuses on how podcast hosts can generate the most amount of money. The two forms of producing income is by paid advertisements or donations/crowdfunding. I conducted an experiment using my own podcast to test whether paid advertisements or donations were more effective at making money. My hypothesis for this experiment is if I offer a free podcast for the public to listen to and ask for donations then I think less than 10% of listeners will donate. I believe that paid advertisements will generate more revenue than donations because I believe podcast listeners are not generous enough to donate. My research on how to make the most money podcasting is illustrated in the following pages.
These massive amounts of investment in podcasting is assuring for the podcast industry that began as recently as the early 2000’s. There is money to be made for the content creators of podcasts as well. This paper focuses on how podcast hosts can generate the most amount of money. The two forms of producing income is by paid advertisements or donations/crowdfunding. I conducted an experiment using my own podcast to test whether paid advertisements or donations were more effective at making money. My hypothesis for this experiment is if I offer a free podcast for the public to listen to and ask for donations then I think less than 10% of listeners will donate. I believe that paid advertisements will generate more revenue than donations because I believe podcast listeners are not generous enough to donate. My research on how to make the most money podcasting is illustrated in the following pages.
ContributorsMaldonado, Marcus (Author) / Radway, Debra (Thesis director) / Bonfigilo, Thomas (Committee member) / Department of Finance (Contributor, Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05