Matching Items (658)
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
This study asks the question: does gender-based discrimination exists within Arizona State University's Army Reserve Officer Training Corps (ROTC), and if so, what are the effects of such discrimination? Within this study, discrimination is defined as: the treatment or consideration of, or making a distinction in favor of or against, a person or thing based on the group, class, or category to which that person or thing belongs, rather than on individual merit. The researcher predicted that this study would show that gender-based discrimination operates within the masculine military culture of Army ROTC at ASU, resulting from women's hyper-visibility and evidenced by their lack of positive recognition and disbelief in having a voice in the program. These expectations were based on background research claiming that the token status of women in military roles causes them to be more heavily scrutinized, and they consequentially try to attain success by adapting to the masculine military culture by which they are constantly measured. For the purposes of this study, success is defined as: the attainment of wealth, favor, or eminence . This study relies on exploratory interviews and an online survey conducted with male and female Army ROTC cadets of all grade levels at Arizona State University. The interviews and survey collected demographic information and perspectives on individual experiences to establish an understanding of privilege and marginalization within the program. These results do support the prediction that women in Army ROTC at ASU face discrimination based on their unique visibility and lack of positive recognition and voice in the program. Likewise, the survey results indicate that race also has a significant impact on one's experience in Army ROTC, which is discussed later in this study in regard to needs for future research. ASU Army ROTC includes approximately 100 cadets, and approximately 30-40 of those cadets participated in this study. Additionally, the University of Arizona and the Northern Arizona University Army ROTC programs were invited to participate in this study and declined to do so, which would have offered a greater sample population. Nonetheless, the results of this research will be useful for analysis and further discussion of gender-equality in Army ROTC at Arizona State University.
ContributorsAllemang, Lindsey Ann (Author) / Wood, Reed (Thesis director) / Switzer, Heather (Committee member) / School of Politics and Global Studies (Contributor) / School of Social Transformation (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Genocide studies have traditionally focused on the perpetrator’s intent to eradicate a particular identity-based group, using the Holocaust as their model and point of comparison. Although some aspects of the Holocaust were undoubtedly unique, recent scholars have sought to challenge the notion that it was a singular phenomenon. Instead, they draw attention to a recurring pattern of genocidal events throughout history by shifting the focus from intent to structure. One particular branch of scholars seeks to connect the ideology and tactics of imperialism with certain genocidal events. These anti-imperialist genocide scholars concede that their model cannot account for all genocides, but still claim that it creates meaningful connections between genocides committed by Western colonialist powers and those that have occurred in a neoimperialist world order shaped according to Western interests. The latter includes genocides in postcolonial states, which these scholars believe were shaped by the scars of their colonial past, as well as genocides in which imperial hegemons assisted local perpetrators. Imperialist and former colonial powers have contributed meaningfully to all of these kinds of genocides, yet their contributions have largely been ignored due to their own influence on the creation of the current international order. Incorporating the anti-imperialist perspective into the core doctrine of genocide studies may lead to breakthroughs in areas of related policy and practice, such as prevention and accountability.
ContributorsParker, Ashleigh Mae (Author) / Thies, Cameron (Thesis director) / Sivak, Henry (Committee member) / School of Politics and Global Studies (Contributor) / School of Social Transformation (Contributor) / Department of English (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Political polarization is the coalescence of political parties -- and the individuals of which parties are composed -- around opposing ends of the ideological spectrum. Political parties in the United States have always been divided, however, in recent years this division has only intensified. Recently, polarization has also wound its way to the Supreme Court and the nomination processes of justices to the Court. This paper examines how prevalent polarization in the Supreme Court nomination process has become by looking specifically at the failed nomination of Judge Merrick Garland and the confirmations of now-Justices Neil Gorsuch and Brett Kavanaugh. This is accomplished by comparing the ideologies and qualifications of the three most recent nominees to those of previous nominees, as well as analysing the ideological composition of the Senate at the times of the individual nominations.
ContributorsJoss, Jacob (Author) / Hoekstra, Valerie (Thesis director) / Critchlow, Donald (Committee member) / Computer Science and Engineering Program (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
As the U.S. reckons with the reality of sexual assault and harassment in the wake of the #MeToo movement, it is particularly important to consider sexual assault in the military, an institution that is a massive employer and the face of the U.S. abroad. Media coverage is a catalyst for change, and the nature and scope of coverage is indicative of public and political attitudes. This thesis uses both quantitative and qualitative data to analyze characteristics of military sexual assault cases that complicate media coverage and to identify strengths and weaknesses of the media's approach to such stories. On the quantitative side, it takes advantage of nearly 600 case reports of sexual assault from U.S. military bases in Japan that were categorized to identify themes such as disposition outcomes, alcohol involvement and victim participation in investigations. Qualitatively, this thesis includes interviews with military officials, victims' advocates, journalists and other stakeholders that help to create a more holistic understanding of how media cover military sexual assault. Notably, this thesis finds that a lack of public interest in the military, a lack of congruency between military and civilian systems, and a highly complex hierarchy that limits journalists' access to military sources and data all complicate coverage. Drawing from these conclusions, it recommends that the media avoid episodic reporting, focus on personalizing stories in an institutional context, embrace accountability journalism and dedicate resources to pursuing complex investigations. It also acknowledges the important role of non-traditional media in the future of information sharing on the topic of military sexual assault.
ContributorsArmstrong, Mia Anne (Author) / Warner, Carolyn (Thesis director) / Gilger, Kristin (Committee member) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05