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Ride Devil: Ride-Sharing for University Campuses

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In this thesis a community-based ride sharing mobile application, Ride Devil, will be introduced and created to provide services for communities such as Arizona State University and its students, faculty, and other affiliates to find safe rides around campus because campus population problem exists. This causes increased transportation costs, decreased…

In this thesis a community-based ride sharing mobile application, Ride Devil, will be introduced and created to provide services for communities such as Arizona State University and its students, faculty, and other affiliates to find safe rides around campus because campus population problem exists. This causes increased transportation costs, decreased parking space availability, and more transportation issues. The Ride Devil application itself is based off on the ride-sharing concept of transportation as introduced, above. Students, faculty, and other university affiliates will drive their own vehicles and use the Ride Devil services in order to coordinate pick-ups with members of its community. Not only is this form of transportation more cost effective than competing transportation models, taxis, but it also promotes safety, community, and educational assistance.
ContributorsVan Hook, Ryan Leo (Author) / Lin, Elva (Thesis director) / Peck, Sidnee (Committee member) / Barrett, The Honors College (Contributor) / Department of Supply Chain Management (Contributor) / W. P. Carey School of Business (Contributor) / Department of Management (Contributor)
Created2014-05
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Timing, Diligence, and Innovation: A Case-Study Determining Mobile Application Success

Description
The purpose of this thesis was to develop a tool to provide information and data for design teams to use throughout the mobile application design process. Ideally, this would enable teams to see patterns in iterative design, and ultimately use data-driven analysis to make their own decisions. The initial problem…

The purpose of this thesis was to develop a tool to provide information and data for design teams to use throughout the mobile application design process. Ideally, this would enable teams to see patterns in iterative design, and ultimately use data-driven analysis to make their own decisions. The initial problem was a lack of available information offered by mobile application design teams—the initial goal being to work closely with design teams to learn their decision-making methodology. However, every team that was reached out to responded with rejection, presenting a new problem: a lack of access to quality information regarding the decision-making process for mobile applications. This problem was addressed by the development of an ethical hacking script that retrieves reviews in bulk from the Google Play Store using Python. The project was a success—by feeding an application’s unique Play Store ID, the script retrieves a user-specified amount of reviews (up to millions) for that mobile application and the 4 “recommended” applications from the Play Store. Ultimately, this thesis proved that protected reviews on the Play Store can be ethically retrieved and used for data-driven decision making and identifying patterns in an application’s iterative design. This script provides an automated tool for teams to “put a finger on the pulse” of their target applications.
ContributorsDyer, Mitchell Patrick (Author) / Lin, Elva (Thesis director) / Giles, Charles (Committee member) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12