Matching Items (619)
Description
Mobile applications (Apps) markets with App stores have introduced a new approach to define and sell software applications with access to a large body of heterogeneous consumer population. Several distinctive features of mobile App store markets including – (a) highly heterogeneous consumer preferences and values, (b) high consumer cognitive burden of searching a large selection of similar Apps, and (c) continuously updateable product features and price – present a unique opportunity for IS researchers to investigate theoretically motivated research questions in this area. The aim of this dissertation research is to investigate the key determinants of mobile Apps success in App store markets. The dissertation is organized into three distinct and related studies. First, using the key tenets of product portfolio management theory and theory of economies of scope, this study empirically investigates how sellers’ App portfolio strategies are associated with sales performance over time. Second, the sale performance impacts of App product cues, generated from App product descriptions and offered from market formats, are examined using the theories of market signaling and cue utilization. Third, the role of App updates in stimulating consumer demands in the presence of strong ranking effects is appraised. The findings of this dissertation work highlight the impacts of sellers’ App assortment, strategic product description formulation, and long-term App management with price/feature updates on success in App market. The dissertation studies make key contributions to the IS literature by highlighting three key managerially and theoretically important findings related to mobile Apps: (1) diversification across selling categories is a key driver of high survival probability in the top charts, (2) product cues strategically presented in the descriptions have complementary relationships with market cues in influencing App sales, and (3) continuous quality improvements have long-term effects on App success in the presence of strong ranking effects.
ContributorsLee, Gun Woong (Author) / Santanam, Raghu (Thesis advisor) / Gu, Bin (Committee member) / Park, Sungho (Committee member) / Arizona State University (Publisher)
Created2015
Description
Most existing security decisions for both defending and attacking are made based on some deterministic approaches that only give binary answers. Even though these approaches can achieve low false positive rate for decision making, they have high false negative rates due to the lack of accommodations to new attack methods and defense techniques. In this dissertation, I study how to discover and use patterns with uncertainty and randomness to counter security challenges. By extracting and modeling patterns in security events, I am able to handle previously unknown security events with quantified confidence, rather than simply making binary decisions. In particular, I cope with the following four real-world security challenges by modeling and analyzing with pattern-based approaches: 1) How to detect and attribute previously unknown shellcode? I propose instruction sequence abstraction that extracts coarse-grained patterns from an instruction sequence and use Markov chain-based model and support vector machines to detect and attribute shellcode; 2) How to safely mitigate routing attacks in mobile ad hoc networks? I identify routing table change patterns caused by attacks, propose an extended Dempster-Shafer theory to measure the risk of such changes, and use a risk-aware response mechanism to mitigate routing attacks; 3) How to model, understand, and guess human-chosen picture passwords? I analyze collected human-chosen picture passwords, propose selection function that models patterns in password selection, and design two algorithms to optimize password guessing paths; and 4) How to identify influential figures and events in underground social networks? I analyze collected underground social network data, identify user interaction patterns, and propose a suite of measures for systematically discovering and mining adversarial evidence. By solving these four problems, I demonstrate that discovering and using patterns could help deal with challenges in computer security, network security, human-computer interaction security, and social network security.
ContributorsZhao, Ziming (Author) / Ahn, Gail-Joon (Thesis advisor) / Yau, Stephen S. (Committee member) / Huang, Dijiang (Committee member) / Santanam, Raghu (Committee member) / Arizona State University (Publisher)
Created2014
Description
This thesis research attempts to observe, measure and visualize the communication patterns among developers of an open source community and analyze how this can be inferred in terms of progress of that open source project. Here I attempted to analyze the Ubuntu open source project's email data (9 subproject log archives over a period of five years) and focused on drawing more precise metrics from different perspectives of the communication data. Also, I attempted to overcome the scalability issue by using Apache Pig libraries, which run on a MapReduce framework based Hadoop Cluster. I described four metrics based on which I observed and analyzed the data and also presented the results which show the required patterns and anomalies to better understand and infer the communication. Also described the usage experience with Pig Latin (scripting language of Apache Pig Libraries) for this research and how they brought the feature of scalability, simplicity, and visibility in this data intensive research work. These approaches are useful in project monitoring, to augment human observation and reporting, in social network analysis, to track individual contributions.
ContributorsMotamarri, Lakshminarayana (Author) / Santanam, Raghu (Thesis advisor) / Ye, Jieping (Thesis advisor) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Information technology (IT) outsourcing, including foreign or offshore outsourcing, has been steadily growing over the last two decades. This growth in IT outsourcing has led to the development of different hubs of services across nations, and has resulted in increased competition among service providers. Firms have been using IT outsourcing to not only leverage advanced technologies and services at lower costs, but also to maintain their competitive edge and grow. Furthermore, as prior studies have shown, there are systematic differences among industries in terms of the degree and impact of IT outsourcing. This dissertation uses a three-study approach to investigate issues related to IT outsourcing at the macro and micro levels, and provides different perspectives for understanding the issues associated with IT outsourcing at a firm and industry level. The first study evaluates the diffusion patterns of IT outsourcing across industries at aggregate level and within industries at a firm level. In addition, it analyzes the factors that influence the diffusion of IT outsourcing and tests models that help us understand the rate and patterns of diffusion at the industry level. This study establishes the presence of hierarchical contagion effects in the diffusion of IT outsourcing. The second study explores the role of location and proximity of industries to understand the diffusion patterns of IT outsourcing within clusters using the spatial analysis technique of space-time clustering. It establishes the presence of simultaneous space and time interactions at the global level in the diffusion of IT outsourcing. The third study examines the development of specialized hubs for IT outsourcing services in four developing economies: Brazil, Russia, India, and China (BRIC). In this study, I adopt a theory-building approach involving the identification of explanatory anomalies, and propose a new hybrid theory called- knowledge network theory. The proposed theory suggests that the growth and development of the IT and related services sector is a result of close interactions among adaptive institutions. It is also based on new knowledge that is created, and which flows through a country's national diaspora of expatriate entrepreneurs, technologists and business leaders. In addition, relevant economic history and regional geography factors are important. This view diverges from the traditional view, wherein effective institutions are considered to be the key determinants of long-term economic growth.
ContributorsMann, Arti (Author) / Kauffman, Robert J. (Thesis advisor) / Santanam, Raghu (Thesis advisor) / St. Louis, Robert (Committee member) / Anselin, Luc (Committee member) / Nault, Barrie R (Committee member) / Arizona State University (Publisher)
Created2012
Description
In this dissertation, two interrelated problems of service-based systems (SBS) are addressed: protecting users' data confidentiality from service providers, and managing performance of multiple workflows in SBS. Current SBSs pose serious limitations to protecting users' data confidentiality. Since users' sensitive data is sent in unencrypted forms to remote machines owned and operated by third-party service providers, there are risks of unauthorized use of the users' sensitive data by service providers. Although there are many techniques for protecting users' data from outside attackers, currently there is no effective way to protect users' sensitive data from service providers. In this dissertation, an approach is presented to protecting the confidentiality of users' data from service providers, and ensuring that service providers cannot collect users' confidential data while the data is processed or stored in cloud computing systems. The approach has four major features: (1) separation of software service providers and infrastructure service providers, (2) hiding the information of the owners of data, (3) data obfuscation, and (4) software module decomposition and distributed execution. Since the approach to protecting users' data confidentiality includes software module decomposition and distributed execution, it is very important to effectively allocate the resource of servers in SBS to each of the software module to manage the overall performance of workflows in SBS. An approach is presented to resource allocation for SBS to adaptively allocating the system resources of servers to their software modules in runtime in order to satisfy the performance requirements of multiple workflows in SBS. Experimental results show that the dynamic resource allocation approach can substantially increase the throughput of a SBS and the optimal resource allocation can be found in polynomial time
ContributorsAn, Ho Geun (Author) / Yau, Sik-Sang (Thesis advisor) / Huang, Dijiang (Committee member) / Ahn, Gail-Joon (Committee member) / Santanam, Raghu (Committee member) / Arizona State University (Publisher)
Created2012
Description
This research compares shifts in a SuperSpec titanium nitride (TiN) kinetic inductance detector's (KID's) resonant frequency with accepted models for other KIDs. SuperSpec, which is being developed at the University of Colorado Boulder, is an on-chip spectrometer designed with a multiplexed readout with multiple KIDs that is set up for a broadband transmission of these measurements. It is useful for detecting radiation in the mm and sub mm wavelengths which is significant since absorption and reemission of photons by dust causes radiation from distant objects to reach us in infrared and far-infrared bands. In preparation for testing, our team installed stages designed previously by Paul Abers and his group into our cryostat and designed and installed other parts necessary for the cryostat to be able to test devices on the 250 mK stage. This work included the design and construction of additional parts, a new setup for the wiring in the cryostat, the assembly, testing, and installation of several stainless steel coaxial cables for the measurements through the devices, and other cryogenic and low pressure considerations. The SuperSpec KID was successfully tested on this 250 mK stage thus confirming that the new setup is functional. Our results are in agreement with existing models which suggest that the breaking of cooper pairs in the detector's superconductor which occurs in response to temperature, optical load, and readout power will decrease the resonant frequencies. A negative linear relationship in our results appears, as expected, since the parameters are varied only slightly so that a linear approximation is appropriate. We compared the rate at which the resonant frequency responded to temperature and found it to be close to the expected value.
ContributorsDiaz, Heriberto Chacon (Author) / Mauskopf, Philip (Thesis director) / McCartney, Martha (Committee member) / Department of Physics (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This paper considers what factors influence student interest, motivation, and continued engagement. Studies show anticipated extrinsic rewards for activity participation have been shown to reduce intrinsic value for that activity. This might suggest that grade point average (GPA) has a similar effect on academic interests. Further, when incentives such as scholarships, internships, and careers are GPA-oriented, students must adopt performance goals in courses to guarantee success. However, performance goals have not been shown to correlated with continued interest in a topic. Current literature proposes that student involvement in extracurricular activities, focused study groups, and mentored research are crucial to student success. Further, students may express either a fixed or growth mindset, which influences their approach to challenges and opportunities for growth. The purpose of this study was to collect individual cases of students' experiences in college. The interview method was chosen to collect complex information that could not be gathered from standard surveys. To accomplish this, questions were developed based on content areas related to education and motivation theory. The content areas included activities and meaning, motivation, vision, and personal development. The developed interview method relied on broad questions that would be followed by specific "probing" questions. We hypothesize that this would result in participant-led discussions and unique narratives from the participant. Initial findings suggest that some of the questions were effective in eliciting detailed responses, though results were dependent on the interviewer. From the interviews we find that students value their group involvements, leadership opportunities, and relationships with mentors, which parallels results found in other studies.
ContributorsAbrams, Sara (Author) / Hartwell, Lee (Thesis director) / Correa, Kevin (Committee member) / Department of Psychology (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This study estimates the capitalization effect of golf courses in Maricopa County using the hedonic pricing method. It draws upon a dataset of 574,989 residential transactions from 2000 to 2006 to examine how the aesthetic, non-golf benefits of golf courses capitalize across a gradient of proximity measures. The measures for amenity value extend beyond home adjacency and include considerations for homes within a range of discrete walkability buffers of golf courses. The models also distinguish between public and private golf courses as a proxy for the level of golf course access perceived by non-golfers. Unobserved spatial characteristics of the neighborhoods around golf courses are controlled for by increasing the extent of spatial fixed effects from city, to census tract, and finally to 2000 meter golf course ‘neighborhoods.’ The estimation results support two primary conclusions. First, golf course proximity is found to be highly valued for adjacent homes and homes up to 50 meters way from a course, still evident but minimal between 50 and 150 meters, and insignificant at all other distance ranges. Second, private golf courses do not command a higher proximity premia compared to public courses with the exception of homes within 25 to 50 meters of a course, indicating that the non-golf benefits of courses capitalize similarly, regardless of course type. The results of this study motivate further investigation into golf course features that signal access or add value to homes in the range of capitalization, particularly for near-adjacent homes between 50 and 150 meters thought previously not to capitalize.
ContributorsJoiner, Emily (Author) / Abbott, Joshua (Thesis director) / Smith, Kerry (Committee member) / Economics Program in CLAS (Contributor) / School of Sustainability (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The objective of this paper is to provide an educational diagnostic into the technology of blockchain and its application for the supply chain. Education on the topic is important to prevent misinformation on the capabilities of blockchain. Blockchain as a new technology can be confusing to grasp given the wide possibilities it can provide. This can convolute the topic by being too broad when defined. Instead, the focus will be maintained on explaining the technical details about how and why this technology works in improving the supply chain. The scope of explanation will not be limited to the solutions, but will also detail current problems. Both public and private blockchain networks will be explained and solutions they provide in supply chains. In addition, other non-blockchain systems will be described that provide important pieces in supply chain operations that blockchain cannot provide. Blockchain when applied to the supply chain provides improved consumer transparency, management of resources, logistics, trade finance, and liquidity.
ContributorsKrukar, Joel Michael (Author) / Oke, Adegoke (Thesis director) / Duarte, Brett (Committee member) / Hahn, Richard (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The Super Catalan numbers are a known set of numbers which have so far eluded a combinatorial interpretation. Several weighted interpretations have appeared since their discovery, one of which was discovered by William Kuszmaul in 2017. In this paper, we connect the weighted Super Catalan structure created previously by Kuszmaul and a natural $q$-analogue of the Super Catalan numbers. We do this by creating a statistic $\sigma$ for which the $q$ Super Catalan numbers, $S_q(m,n)=\sum_X (-1)^{\mu(X)} q^{\sigma(X)}$. In doing so, we take a step towards finding a strict combinatorial interpretation for the Super Catalan numbers.
ContributorsHouse, John Douglas (Author) / Fishel, Susanna (Thesis director) / Childress, Nancy (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05