Browsing by Subject "Smartphone"

Now showing 1 - 3 of 3
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    Essays on the economics of the Smartphone and application industry
    (2013-09) Kim, Min Jung
    This dissertation is in two parts. In Chapter 1, I empirically quantify the consumer welfare gains created by free smartphone apps that have recently emerged as one of the most used digital goods. I use a unique dataset of smartphone apps and transform sales ranks into quantities to overcome a lack of data on quantity. In the process, I suggest a new methodology of utilizing Google search data, which can also be used in future research. The estimation results show that smartphone apps created $5.7~10.9 billion and $13.5~23.3 billion of annual consumer benefits in 2010 and 2011, respectively -- which can be translated into $134~260 in 2010 and $157~271 in 2011 per smartphone user on average -- and more than 90% of the welfare gain is from free apps. In Chapter 2, I examine how the contributing effects of mobile applications on smartphone adoption differ across smartphone operating systems and the extent to which this difference is explained by the role of platforms, focusing on the case of Apple vs. Google. I estimate a model of consumer demand for both smartphones and compatible apps where I specify the benefit provided by apps as the sum of individual app utilities. It is first shown that the selection of different types of consumers onto platforms should be accounted for in estimating app demand and thereby measuring the complementary effects. I take a novel approach to constructing geographically disaggregated sales panel by using Google web search data, as a way of addressing the selection issue. After controlling for the user heterogeneity, the results still suggest that Apple provided more app benefits to users and Android's stronger sales over the sample period come entirely from advantages in the price-adjusted quality of hardware. The overall quality of apps in Google Play was not inferior to that of the App Store, but Google is estimated to have delivered lower utility for a given set of apps possibly due to its open strategy.
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    An Integrated Assistive System to Support Wayfinding and Situation Awareness for People with Vision Impairment
    (2016-05) Liao, Chen-Fu
    People with vision impairment usually use a white cane as their primary tool for wayfinding and obstacle detection. Environmental cues, though not always reliable, are used to support the decision making of the visually impaired at various levels of navigation and situation awareness. Due to differences in spatial perception as compared to sighted people, they often encounter physical as well as information barriers along a trip. In order to improve their mobility, accessibility and level of confidence in using our transportation system, it is important to remove not only the physical barriers but also the information barriers that could potentially impede their mobility and undermine safety. Many assistive systems have been developed in the past for visually impaired users to navigate and find their way. However, most of these systems were not adopted by users mostly due to the inconvenience of using such systems. In this research, we developed a mobile accessible information system that allows people with vision impairment to receive transportation information at key locations where decision making is necessary. A smartphone-based personal assistive system, called MAPS (Mobile Accessible Pedestrian System), was developed to provide intersection geometry and signal timing information, not available from other apps in the market for people with vision impairment. In addition, the MAPS incorporates a geospatial database with Bluetooth beacon information that allows the MAPS to provide navigation assistance, situation awareness, and wayfinding to users even when a GPS solution is not available. The MAPS app communicates with the traffic signal controller through a secured wireless link to obtain real-time Signal Phasing and Timing (SPaT) information, which together then inform visually impaired pedestrians with their current locations and when to cross streets. A self-monitoring infrastructure using a network of Bluetooth Low Energy (BLE) beacons was developed to ensure the information integrity of the network. The key contributions of this dissertation include the development of: • A smartphone-based navigation and decision support system that incorporates intersection geometry and traffic signal information for people with vision impairment, • A simple user’s interface (using a single or double-tap on a smartphone screen) that is easy for the visually impaired to learn and use, • Standardized message elements for an audible work zone bypass routing information system, • A self-monitoring infrastructure using a network of commercial off-the-shelf (COTS) low-cost BLE beacons, (including customized firmware allowing BLE beacons to monitor each other), • A crowdsourcing approach using users’ smartphones to monitor the status of BLE beacons and update messages associated with beacons, • A cloud-based geospatial database to support navigation by incorporating BLE beacon localization information when a GPS solution is not available, • A Singular Value Decomposition (SVD) based Multivariable Regression (MR) algorithm together with an Extended Kalman Filter (EKF) technique using beacon localization to provide a positioning solution by the smartphone even if a GPS solution is unavailable, and • Statistical methodologies and wireless signal fingerprinting techniques to monitor BLE beacons in a network in order to determine when a beacon is moved, removed or disappears. The intent of the MAPS is not to undermine the maintenance of skills and strategies that people with vision impairment have learned for navigation and wayfinding. Instead, the system aims to support their wayfinding capability, extend mobility and accessibility, and improve safety for the blind and visually impaired. This self-monitoring infrastructure ensures that correct information is provided to users at the right location when needed. This thesis also introduces the idea of using the same system to warn sighted pedestrians about approaching an intersection when they are distracted by looking at their smartphone.
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    SmarTrAC: A Smartphone Solution for Context-Aware Travel and Activity Capturing
    (2015-02) Fan, Yingling; Wolfson, Julian; Adomavicius, Gediminas; Vardhan Das, Kirti; Khandelwal, Yash; Kang, Jie
    The use of mobile phones in collecting travel behavior data has rapidly increased, especially after GPS tracking technology became widely available in commercial smartphones. Existing smartphone-based tools in the field have generally focused on capturing the “when”, “where”, and “how” of travel, i.e., using the smartphone’s automatic sensing functionality to detect travel mode and to collect position and route data. Although locations and modes of transportation derived from sensing data represent important travel behavior information, travel behavior has many other important dimensions—such as trip purpose, travel experience, and travel companionship (i.e., the “why”, “how”, and “who” of travel)—all of which are critical for understanding people’s travel choices. Some of these dimensions may be inferable from pure sensory data, but reliable inference will generally require long-term use data from a very large number of subjects. Other dimensions are simply inaccessible to passive sensing tools. In contrast, traditional travel diary methods and some first-generation smartphone-based travel survey tools enable the collection of multi-dimensional data through high-intensity sampling and qualitative survey techniques. However, these methods are often burdensome to study subjects and impractical for use in a diverse, mobile, and increasingly time-stressed population.