Matching Items (2)
Filtering by

Clear all filters

157272-Thumbnail Image.png
Description
Despite the societal importance of activism, the understanding of activist intentions remained limited (Liebert, Leve, & Hu, 2011; Klar & Kasser, 2009). The current study used the Theory of Planned Behavior (TPB) to examine two structural models of low-risk activist intentions and high-risk activist intentions (Ajzen, 1991). The

Despite the societal importance of activism, the understanding of activist intentions remained limited (Liebert, Leve, & Hu, 2011; Klar & Kasser, 2009). The current study used the Theory of Planned Behavior (TPB) to examine two structural models of low-risk activist intentions and high-risk activist intentions (Ajzen, 1991). The traditional TPB model was tested against a hybrid commitment model that also assessed past activist behaviors and activist identity. Participants (N = 383) were recruited through social media, professional list-serves, and word of mouth. Results indicated a good model fit for both the traditional TPB model (CFI = .98; RMSEA = .05; SRMR = .03; χ2(120) = 3760.62, p < .01) and the commitment model (CFI = .97; RMSEA = .05; SRMR = .04; χ2(325) = 7848.07, p < .01). The commitment model accounted for notably more variance in both low-risk activist intentions (78.9% in comparison to 26.5% for the traditional TPB model) and high-risk activist intentions (58.9% in comparison to 11.2% for the traditional TPB model). Despite this, the traditional TPB model was deemed the better model as the higher variance explained in the commitment model was almost entirely due to the inclusion of past low-risk activist behaviors and past high-risk activist behaviors. A post-hoc analysis that incorporated sexual orientation and religious affiliation as covariates into the traditional model also led to a good-fitting model (CFI = .98; RMSEA = .04; SRMR = .04; χ2(127) = 217.18, p < .01) and accounted for increased variance in low-risk activist intentions (29.7%) and high-risk activist intentions (18.7%) compared to the traditional model. The merits of each of the structural models and the practical implications for practice and research were discussed
ContributorsJew, Gilbert (Author) / Tran, Alisia (Thesis advisor) / Tracey, Terence (Committee member) / Capielo Rosario, Cristalís (Committee member) / Arizona State University (Publisher)
Created2019
135122-Thumbnail Image.png
Description
Bitcoin is a form of virtual currency that can be used as a medium of exchange for goods or services. Different from other forms of virtual payment, bitcoin is de-centralized and puts all of the power in the hands of the user, rather than a banking institution. However, bitcoin's ability

Bitcoin is a form of virtual currency that can be used as a medium of exchange for goods or services. Different from other forms of virtual payment, bitcoin is de-centralized and puts all of the power in the hands of the user, rather than a banking institution. However, bitcoin's ability to develop as a renowned medium of exchange has been impeded, potentially due to a lack of knowledge, active bitcoin platforms, and support. In this paper, I conduct a survey to understand factors that affect households' adoption of bitcoin. In particular, I focus on factors that capture the potential benefit and cost of adopting bitcoin. Through a public survey, participants are asked a series of questions on their willingness to adopt bitcoin. I found significant results stating that subjects were more inclined toward bitcoin contingent upon the number of platforms accepting it, the number of acquaintances using bitcoin, and the degree of personal knowledge participants have about bitcoin. These findings suggest that perceived benefit captured by network effect and convenience of use, as well as the potential cost captured by uncertainty help shape the adoption of bitcoin.
ContributorsMorrissey, Michael Joshua (Author) / Wang, Jessie (Thesis director) / Ray, Colter (Committee member) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12