Matching Items (559)
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
Splicing of digital images is a powerful form of tampering which transports regions of an image to create a composite image. When used as an artistic tool, this practice is harmless but when these composite images can be used to create political associations or are submitted as evidence in the judicial system they become more impactful. In these cases, distinction between an authentic image and a tampered image can become important.
Many proposed approaches to image splicing detection follow the model of extracting features from an authentic and tampered dataset and then classifying them using machine learning with the goal of optimizing classification accuracy. This thesis approaches splicing detection from a slightly different perspective by choosing a modern splicing detection framework and examining a variety of preprocessing techniques along with their effect on classification accuracy. Preprocessing techniques explored include Joint Picture Experts Group (JPEG) file type block line blurring, image level blurring, and image level sharpening. Attention is also paid to preprocessing images adaptively based on the amount of higher frequency content they contain.
This thesis also recognizes an identified problem with using a popular tampering evaluation dataset where a mismatch in the number of JPEG processing iterations between the authentic and tampered set creates an unfair statistical bias, leading to higher detection rates. Many modern approaches do not acknowledge this issue but this thesis applies a quality factor equalization technique to reduce this bias. Additionally, this thesis artificially inserts a mismatch in JPEG processing iterations by varying amounts to determine its effect on detection rates.
Many proposed approaches to image splicing detection follow the model of extracting features from an authentic and tampered dataset and then classifying them using machine learning with the goal of optimizing classification accuracy. This thesis approaches splicing detection from a slightly different perspective by choosing a modern splicing detection framework and examining a variety of preprocessing techniques along with their effect on classification accuracy. Preprocessing techniques explored include Joint Picture Experts Group (JPEG) file type block line blurring, image level blurring, and image level sharpening. Attention is also paid to preprocessing images adaptively based on the amount of higher frequency content they contain.
This thesis also recognizes an identified problem with using a popular tampering evaluation dataset where a mismatch in the number of JPEG processing iterations between the authentic and tampered set creates an unfair statistical bias, leading to higher detection rates. Many modern approaches do not acknowledge this issue but this thesis applies a quality factor equalization technique to reduce this bias. Additionally, this thesis artificially inserts a mismatch in JPEG processing iterations by varying amounts to determine its effect on detection rates.
ContributorsGubrud, Aaron (Author) / Li, Baoxin (Thesis advisor) / Candan, Kasim (Committee member) / Kadi, Zafer (Committee member) / Arizona State University (Publisher)
Created2015
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
The advertising agency, in its variety of forms, is one of the most powerful forces in the modern world. Its products are seen globally through various multimedia outlets and they strongly impact culture and economy. Since its conception in 1843 by Volney Palmer, the advertising agency has evolved into the recognizable—and unrecognizable—firms scattered around the world today. In the United States alone, there are roughly 13.4 thousand agencies, many of which also have branches in other countries. The evolution of the modern advertising agency coincided with, and even preceded, some of the major inflection points in history. Understanding how and why changes in advertising agencies affected these inflection points provides a glimpse of understanding into the relationship between advertising, business, and societal values.
In the pages ahead we will explore the future of the advertising industry. We will analyze our research to uncover the underlying trends pointing towards what is to come and work to apply those explanations to our understanding of advertising in the future.
In the pages ahead we will explore the future of the advertising industry. We will analyze our research to uncover the underlying trends pointing towards what is to come and work to apply those explanations to our understanding of advertising in the future.
ContributorsHarris, Chase (Co-author) / Potthoff, Zachary (Co-author) / Gray, Nancy (Thesis director) / Samper, Adriana (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Herberger Institute for Design and the Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The town of Guadalupe, Arizona has a long history of divided residents and high poverty rates. The high levels of poverty in the town can be attributed to numerous factors, most notably high rates of drug abuse, low high school graduation rates, and teen pregnancy. The town has named one of its most pressing issues of today to be youth disengagement. There are currently a handful of residents and community members passionate about finding a solution to this issue. After working with Guadalupe's Ending Hunger Task Force and resident youth, I set out to create a program design for a Guadalupe Youth Council. This council will contribute to combating youth disengagement. The program design will assist the task force in creating a standing youth council and deciding on the structure and role the council has in the town. I will offer learning outcomes and suggestions to the Task Force, youth council staff, and the youth of the youth council. This study contains an analysis of relevant literature, youth focus group results and data, and how the information gathered has contributed to the design of the youth council. The results of this study contain recommendations about four themes within the program design of a youth council: size, recruitment, activities and engagement, and adult support. The results also explore how the youth council will impact the power, policy, and behavior of Guadalupe youth.
ContributorsBalderas, Erica Theresa (Author) / Wang, Lili (Thesis director) / Avalos, Francisco (Committee member) / School of Community Resources and Development (Contributor) / Department of Information Systems (Contributor) / W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This thesis project was conducted to create a practical tool to help micro and small local food enterprises identify potential strategies and sources of finance. Currently, many of these enterprises are unable to obtain the financial capital needed to start-up or maintain operations.
Sources and strategies of finance studied and ultimately included in the tool were Loans, Equity, Membership, Crowdfunding, and Grants. The tool designed was a matrix that takes into account various criteria of the business (e.g. business lifecycle, organizational structure, business performance) and generates a financial plan based on these criteria and how they align with the selected business strategies. After strategies are found, stakeholders can search through an institutional database created in conjunction with the matrix tool to find possible institutional providers of financing that relate to the strategy or strategies found.
The tool has shown promise in identifying sources of finance for micro and small local food enterprises in practical use with hypothetical business cases, however further practical use is necessary to provide further input and revise the tool as needed. Ultimately, the tool will likely become fully user-friendly and stakeholders will not need the assistance of another expert helping them to use it. Finally, despite the promise of the tool itself, the fundamental and underlying problem that many of these businesses face (lack of infrastructure and knowledge) still exists, and while this tool can also help capacity-building efforts towards both those seeking and those providing finance, an institutional attitude adjustment towards social and alternative enterprises is necessary in order to further simplify the process of obtaining finance.
Sources and strategies of finance studied and ultimately included in the tool were Loans, Equity, Membership, Crowdfunding, and Grants. The tool designed was a matrix that takes into account various criteria of the business (e.g. business lifecycle, organizational structure, business performance) and generates a financial plan based on these criteria and how they align with the selected business strategies. After strategies are found, stakeholders can search through an institutional database created in conjunction with the matrix tool to find possible institutional providers of financing that relate to the strategy or strategies found.
The tool has shown promise in identifying sources of finance for micro and small local food enterprises in practical use with hypothetical business cases, however further practical use is necessary to provide further input and revise the tool as needed. Ultimately, the tool will likely become fully user-friendly and stakeholders will not need the assistance of another expert helping them to use it. Finally, despite the promise of the tool itself, the fundamental and underlying problem that many of these businesses face (lack of infrastructure and knowledge) still exists, and while this tool can also help capacity-building efforts towards both those seeking and those providing finance, an institutional attitude adjustment towards social and alternative enterprises is necessary in order to further simplify the process of obtaining finance.
ContributorsDwyer, Robert Francis (Author) / Wiek, Arnim (Thesis director) / Forrest, Nigel (Committee member) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
RecyclePlus is an iOS mobile application that allows users to be knowledgeable in the realms of sustainability. It gives encourages users to be environmental responsible by providing them access to recycling information. In particular, it allows users to search up certain materials and learn about its recyclability and how to properly dispose of the material. Some searches will show locations of facilities near users that collect certain materials and dispose of the materials properly. This is a full stack software project that explores open source software and APIs, UI/UX design, and iOS development.
ContributorsTran, Nikki (Author) / Ganesh, Tirupalavanam (Thesis director) / Meuth, Ryan (Committee member) / Watts College of Public Service & Community Solut (Contributor) / Department of Information Systems (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05