Theses and dissertations

This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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Effects of Phonotactic Probability during Early Novel Word Recognition

Description
The goal of this study was to examine whether there is any effect of phonotactic probability during the early phases of novel word recognition. In order to determine this, I performed two experiments. In Experiment 1, 33 adult monolingual English speakers learned 24 novel word-object pairings, half of which were…

The goal of this study was to examine whether there is any effect of phonotactic probability during the early phases of novel word recognition. In order to determine this, I performed two experiments. In Experiment 1, 33 adult monolingual English speakers learned 24 novel word-object pairings, half of which were high English phonotactic probability words and the other half were low English phonotactic probability words. I additionally included three conditions that varied the amount of exposures to each novel word-object pairing (i.e. One Exposure Condition, Two Exposures Conditions, and Five Exposures Condition). Experiment 2 was designed to clarify results found in Experiment 1, with improved randomization and fewer conditions (i.e. One Exposure Condition and Five Exposures Condition). The findings from both experiments were statistically significant in accuracy for Training condition, but not statistically significant for phonotactic probability nor for an interaction between phonotactic probability and Training condition. Although participants demonstrated learning across conditions there is no indication of a relationship between high and low phonotactic probability and novel word recognition. Collectively, these findings suggest that future studies will be necessary to determine if there is indeed an effect of phonotactic probability on early novel word recognition.
ContributorsQuinones, Sara Cristina (Co-author) / Quiñones, Sara (Co-author) / Benitez, Viridiana (Thesis director) / Tecedor Cabrero, Marta (Committee member) / Davis, Mary (Committee member) / Department of Psychology (Contributor) / Dean, W.P. Carey School of Business (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Collaborative Thesis: Software Monetization within the Internet of Things Group

Description
"Company X," a technology company, is known for being one of the world’s largest semiconductor chip manufacturers; however, they are also one of the largest authors of software. In 2019, "Company X" entered a new paradigm where, according to the CEO, while "Company X"’s core strategy has not changed, "Company…

"Company X," a technology company, is known for being one of the world’s largest semiconductor chip manufacturers; however, they are also one of the largest authors of software. In 2019, "Company X" entered a new paradigm where, according to the CEO, while "Company X"’s core strategy has not changed, "Company X" is embracing the transition to a data-centric company from a PC-centric company. The scope that the project examines is--in this transition to a data-centric company and based on the company's current expertise and competitive advantages--should "Company X" be branching into an additional division or leverage existing intellectual property (IP)? The goal of the project is to understand how "Company X" can leverage its expertise in hardware and software service packages to maximize the value of the company.
ContributorsArellano, Andrea (Co-author) / Roos, Bailey (Co-author) / Broas, Joshua (Co-author) / Kotti, Abhigyan (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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IoT Allocation Methodology: Allocation Methodology for Indirect Research and Development Costs for Internet of Things Products

Description
While a fairly new concept, Internet of Things (IoT) has become an important part of the business structure and operating segments of many technology companies in the last decade. IoT refers to the evolution of devices that, connected to the internet, can share and integrate information, becoming an always-growing intelligent…

While a fairly new concept, Internet of Things (IoT) has become an important part of the business structure and operating segments of many technology companies in the last decade. IoT refers to the evolution of devices that, connected to the internet, can share and integrate information, becoming an always-growing intelligent system of systems. As a leader in the semiconductor industry, Company X and its growing IoT division, have constant new challenges and opportunities given the complexity of the IoT field. The business model employed by the IoT division includes adopting and modifying existing technologies and products from its sister groups within Company X. Since these products are being leveraged by the IoT division, it makes indirect research and development allocation for said products much more complex. This thesis will address how the IoT division at Company X can approach this problem in the most beneficial way for the division and company as a whole through the analysis of two allocation methodologies: percentage of revenue (Allocation Basis 1) and percentage of direct research and development (Allocation Basis 2).
ContributorsJerez Casillas, Diana (Author) / Abang, Joycelyn (Co-author) / Stanek, Christopher (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Barrett, The Honors College (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Watts College of Public Service & Community Solut (Contributor)
Created2022-05