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University of Arizona
1.
Chen, Yi-Da.
The Dynamics of Task-related Discussion in the Pursuit of Radical Innovation: Innovation Project Teams as Interpretation Systems
.
Degree: 2013, University of Arizona
URL: http://hdl.handle.net/10150/311106 
► As global competition is increasingly intensified, radical innovation has become more and more important for corporations in high-velocity industries. Thanks to the advances of information…
(more)
▼ As global competition is increasingly intensified, radical innovation has become more and more important for corporations in high-velocity industries. Thanks to the advances of information systems and communication media, corporations can easily reach out to experts all over the world and form project teams dedicated to the innovation effort. However, research shows that while some innovation teams are very successful in achieving significant breakthroughs, many struggle to make their collaborations work. In this dissertation, we aim to provide a comprehensive understanding of the collaboration challenges that an innovation team faces. By considering the simultaneous needs for differentiation and integration in the innovation effort and taking a communication/ interpretive perspective, we develop a theoretical model to investigate how the processes of differentiation and integration are shaped through team communication and influence an innovation team's collaboration outcomes. Specifically, we delineate four structural properties of team communication to capture these two processes - the number of issue streams explored, the number of attention switches initiated, the conceptual linkage between issue streams, and the level of deliberation after each attention switch - and identify four categories of factors that influence the development of these two processes - team composition, semi-structures, communication contexts, and communication environments. We conduct a case study as a preliminary test of our theoretical model, and find that the model provides comprehensive explanations for the collaboration dynamics and issues of these teams. We believe such a theoretical model can contribute to a better understanding of the complexity involved in an innovation project and bring fresh insights to the design of information systems for supporting an innovation team.
Advisors/Committee Members: Brown, Susan A (advisor), Brown, Susan A. (committeemember), Goes, Paulo (committeemember), Galaskiewicz, Joseph (committeemember), Durcikova, Alexandra (committeemember).
Subjects/Keywords: Communication Media;
Information Systems;
Innovation project team;
Interpretation Systems;
Radical innovation;
Management Information Systems;
Collaboration Dynamics
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APA (6th Edition):
Chen, Y. (2013). The Dynamics of Task-related Discussion in the Pursuit of Radical Innovation: Innovation Project Teams as Interpretation Systems
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/311106
Chicago Manual of Style (16th Edition):
Chen, Yi-Da. “The Dynamics of Task-related Discussion in the Pursuit of Radical Innovation: Innovation Project Teams as Interpretation Systems
.” 2013. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/311106.
MLA Handbook (7th Edition):
Chen, Yi-Da. “The Dynamics of Task-related Discussion in the Pursuit of Radical Innovation: Innovation Project Teams as Interpretation Systems
.” 2013. Web. 16 Jan 2021.
Vancouver:
Chen Y. The Dynamics of Task-related Discussion in the Pursuit of Radical Innovation: Innovation Project Teams as Interpretation Systems
. [Internet] [Doctoral dissertation]. University of Arizona; 2013. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/311106.
Council of Science Editors:
Chen Y. The Dynamics of Task-related Discussion in the Pursuit of Radical Innovation: Innovation Project Teams as Interpretation Systems
. [Doctoral Dissertation]. University of Arizona; 2013. Available from: http://hdl.handle.net/10150/311106
University of Arizona
2.
Dang, Yan.
Theory-Informed Design and Evaluation of Web-Based Knowledge Management Systems
.
Degree: 2011, University of Arizona
URL: http://hdl.handle.net/10150/145434
► With the rapid increase in information availability, it is nearly impossible to stay current with advances in knowledge. The overarching question that my dissertation seeks…
(more)
▼ With the rapid increase in information availability, it is nearly impossible to stay current with advances in knowledge. The overarching question that my dissertation seeks to address is how to design Web-based knowledge management systems (KMS) to alleviate this problem by providing search and analysis support for individuals to access and understand the accumulated knowledge in an effective and efficient way. Specifically, designing and implementing consistent representation of heterogeneous data, enabling efficient and user-friendly search support, and supporting advanced user-interactive analysis and visualization are important issues to address. Certain Information Systems and cognitive theories can be leveraged to guide the design and evaluation of these systems. In addition, the evaluation results can further validate and extend theory. This helps to bridge the design-science paradigm and the behavioral-science paradigm.The research studies in my dissertation involve the development of Web-based KMS based on different types of data sources. Such systems aim to support decision making and can be important for researchers, practitioners, business investors, and policy makers. Chapter 2 develops a Web-based KMS,
Arizona Literature Mapper, which allows users to gain comprehensive understanding of bioterrorism research. The data source of
Arizona Literature Mapper is scientific publications. The system integrates techniques for content analysis, network analysis, and information visualization. Two user studies were conducted to evaluate the performance of
Arizona Literature Mapper. Guided by cognitive fit and cognitive load theories, Chapter 3 develops a Web-based KMS, Nano Mapper, to support users' search and analysis of nanotechnology developments. The data sources include patent documents from world leading patent offices and NSF grand documents. Controlled experiments were conducted to evaluate the functions of Nano Mapper. The Web-based KMS developed in Chapters 4 and 5 is the Dark Web Forum Portal (DWFP) which aims to manage user-generated multilingual social media content. In Chapter 4, theories of the mental workload, task-technology fit, and unified theory of acceptance and use of technology (UTAUT) are used to guide the design and development of the system, and a new theoretical model is proposed to extend theory. Chapter 5 conducts two evaluation studies to comprehensively evaluate the performance of the system. The first study compared its performance with the benchmark system based on efficiency, effectiveness, and all the dimensions in the D&M IS Success Model. The second study further tested and validated the D&M IS Success Model in social media context.Overall, these research studies in my dissertation contribute to the literature on system development, knowledge mapping, technology acceptance and adoption, and human cognition and decision making.
Advisors/Committee Members: Brown, Susan A (advisor), Chen, Hsinchun (advisor), Schau, Hope J (committeemember).
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APA (6th Edition):
Dang, Y. (2011). Theory-Informed Design and Evaluation of Web-Based Knowledge Management Systems
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/145434
Chicago Manual of Style (16th Edition):
Dang, Yan. “Theory-Informed Design and Evaluation of Web-Based Knowledge Management Systems
.” 2011. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/145434.
MLA Handbook (7th Edition):
Dang, Yan. “Theory-Informed Design and Evaluation of Web-Based Knowledge Management Systems
.” 2011. Web. 16 Jan 2021.
Vancouver:
Dang Y. Theory-Informed Design and Evaluation of Web-Based Knowledge Management Systems
. [Internet] [Doctoral dissertation]. University of Arizona; 2011. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/145434.
Council of Science Editors:
Dang Y. Theory-Informed Design and Evaluation of Web-Based Knowledge Management Systems
. [Doctoral Dissertation]. University of Arizona; 2011. Available from: http://hdl.handle.net/10150/145434
University of Arizona
3.
Yu, Shuo.
Mobile Health Analytics for Senior Care: A Data Mining and Deep Learning Approach
.
Degree: 2019, University of Arizona
URL: http://hdl.handle.net/10150/633148
► Senior citizens confront numerous challenges to their independent living, including chronic physical health conditions and a decline in mobility. With the advancement of mobile sensing…
(more)
▼ Senior citizens confront numerous challenges to their independent living, including chronic physical health conditions and a decline in mobility. With the advancement of mobile sensing technologies, medical professionals and information systems (IS) researchers have sought to apply data mining techniques to provide precise, prompt, and personalized assessment for falls and health conditions including Parkinson’s disease. Given the societal importance of senior care, my dissertation aims to address the following four research questions: (1) how can we promptly detect senior citizens’ adverse events, e.g., falls, to alleviate consequences, (2) how can we precisely assess senior citizens’ health risks, e.g., fall risks, to provide proper interventions, (3) how can we leverage multiple data sources and assess senior citizens’ health risks in a more holistic manner, and (4) how can we profile senior citizens’ long-term health progression for more personalized care.
This dissertation presents four essays to tackle these questions. The essays develop state-of-the-art data mining and deep learning techniques to address selected senior care inquiries. The first essay focuses on a novel hidden Markov model with sensor orientation calibration to detect falls. The second essay presents a two-dimensional heterogeneous convolutional neural network to precisely assess fall risks. The third essay leverages deep multisource multitask learning to achieve sensor fusion and assess multiple health risks and disease severities. The final essay develops an adaptive time-aware convolutional long short term memory model that enables long-term health profiling with time irregularities. Presented frameworks, systems, and design principles not only advance mobile health analytics and deep learning methodologies, but also guide future computational design science research in IS.
Advisors/Committee Members: Chen, Hsinchun (advisor), Nunamaker, Jay F. (committeemember), Brown, Susan A. (committeemember).
Subjects/Keywords: Data Mining;
Deep Learning;
Mobile Health Analytics;
Motion Sensor;
Senior Care
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APA ·
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Export
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Manager
APA (6th Edition):
Yu, S. (2019). Mobile Health Analytics for Senior Care: A Data Mining and Deep Learning Approach
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/633148
Chicago Manual of Style (16th Edition):
Yu, Shuo. “Mobile Health Analytics for Senior Care: A Data Mining and Deep Learning Approach
.” 2019. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/633148.
MLA Handbook (7th Edition):
Yu, Shuo. “Mobile Health Analytics for Senior Care: A Data Mining and Deep Learning Approach
.” 2019. Web. 16 Jan 2021.
Vancouver:
Yu S. Mobile Health Analytics for Senior Care: A Data Mining and Deep Learning Approach
. [Internet] [Doctoral dissertation]. University of Arizona; 2019. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/633148.
Council of Science Editors:
Yu S. Mobile Health Analytics for Senior Care: A Data Mining and Deep Learning Approach
. [Doctoral Dissertation]. University of Arizona; 2019. Available from: http://hdl.handle.net/10150/633148
University of Arizona
4.
Xie, Jiaheng.
Big Data-Based Health Risk Analytics: A Deep Learning Approach
.
Degree: 2020, University of Arizona
URL: http://hdl.handle.net/10150/641367
► Value-based healthcare is an emerging healthcare delivery model which incentivizes and rewards physicians for improved patient outcomes and quality of care, rather than the amount…
(more)
▼ Value-based healthcare is an emerging healthcare delivery model which incentivizes and rewards physicians for improved patient outcomes and quality of care, rather than the amount of services. The objective of value-based healthcare is to move the healthcare delivery system from reactive disease management to proactive care. Such proactive healthcare necessitates an active assessment of multi-dimensional health risks. Major health risks, such as medication nonadherence, disease risk, and hospital readmission, cost the US healthcare systems over $300 billion per year and escalate morbidity and mortality risks. Early detection of those health risks could significantly benefit patients and the health sectors from both disease management and financial perspectives. My dissertation focuses on health risk analytics that serves as the analytical foundation for proactive health risk assessment. This dissertation designs fine-grained deep learning methods leveraging big data, including health social media and clinical claims, to provide analytical capabilities for several critically important health risks: vaping, medication nonadherence, opioid addiction, and hospital readmission.
This dissertation presents four essays to tackle these health risks. The first essay devises a deep learning model to identify health risks of vaping. The second essay develops a sentiment-enriched deep learning method to understand patient medication nonadherence from health social media. The third essay presents a multi-view deep learning approach to discover the treatment barriers of opioid addiction. The fourth essay designs a novel deep learning framework that incorporates an illness trajectory to predict hospital readmission risk. The presented frameworks, systems, and design principles contribute to computational data science, deep learning, and predictive modeling research domains.
Advisors/Committee Members: Zeng, Daniel (advisor), Brown, Susan A. (committeemember), Ge, Yong (committeemember), Chen, Wei (committeemember).
Subjects/Keywords: Data mining;
Deep learning;
Design science;
Health risk analytics;
Text mining
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APA ·
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Export
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APA (6th Edition):
Xie, J. (2020). Big Data-Based Health Risk Analytics: A Deep Learning Approach
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/641367
Chicago Manual of Style (16th Edition):
Xie, Jiaheng. “Big Data-Based Health Risk Analytics: A Deep Learning Approach
.” 2020. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/641367.
MLA Handbook (7th Edition):
Xie, Jiaheng. “Big Data-Based Health Risk Analytics: A Deep Learning Approach
.” 2020. Web. 16 Jan 2021.
Vancouver:
Xie J. Big Data-Based Health Risk Analytics: A Deep Learning Approach
. [Internet] [Doctoral dissertation]. University of Arizona; 2020. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/641367.
Council of Science Editors:
Xie J. Big Data-Based Health Risk Analytics: A Deep Learning Approach
. [Doctoral Dissertation]. University of Arizona; 2020. Available from: http://hdl.handle.net/10150/641367
University of Arizona
5.
Yueh, Rich.
Capturing Self-Efficacy Behavioral Outcomes Through Human-Computer Interaction Devices
.
Degree: 2019, University of Arizona
URL: http://hdl.handle.net/10150/636568
► Mouse cursor tracking (MCT) is increasingly being used in human-computer interaction studies in fields such as information systems, psychology, and cognitive science. MCT allows researchers…
(more)
▼ Mouse cursor tracking (MCT) is increasingly being used in human-computer interaction studies in fields such as information systems, psychology, and cognitive science. MCT allows researchers to more closely study how cognitive processes such as uncertainty are expressed through physical movements like hesitation, speed of performing an action, or switching answers in a multiple-choice response. Researchers have codified these movements into four variables: Additional Distance; Maximum Deviation; Area Under the Curve; and Speed. In this dissertation, we study the effects of mouse cursor movements on the relationship between a user’s self-efficacy score and task performance. We propose that mouse cursor movements moderate this relationship and how well a self-efficacy score can predict successful task performance. We designed three studies and used a proprietary MCT system. We specified the context for each study: mental multiplication in Study 1, verbal concept formation in Study 2, and word-processing software skill assessment in Study 3. In Study 1, we found that changes in Additional Distance and Maximum Deviation significantly influenced the accuracy of using a self-efficacy score to predict task performance. We did not find any significant results in Study 2. In Study 3, we found that changes in Additional Distance and Area Under the Curve significantly influenced the accuracy of using a self-efficacy score to predict task performance. We suggest that Additional Distance may be a fruitful variable for deeper study and analysis. We also identified limitations in the MCT system and in study designs across different contexts. We propose changes and future work avenues to better study cognitive processes using MCT.
Advisors/Committee Members: Valacich, Joseph S (advisor), Brown, Susan A. (committeemember), Jenkins, Jeffrey L. (committeemember), Nunamaker, Jay F. (committeemember).
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APA ·
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MLA ·
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CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Yueh, R. (2019). Capturing Self-Efficacy Behavioral Outcomes Through Human-Computer Interaction Devices
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/636568
Chicago Manual of Style (16th Edition):
Yueh, Rich. “Capturing Self-Efficacy Behavioral Outcomes Through Human-Computer Interaction Devices
.” 2019. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/636568.
MLA Handbook (7th Edition):
Yueh, Rich. “Capturing Self-Efficacy Behavioral Outcomes Through Human-Computer Interaction Devices
.” 2019. Web. 16 Jan 2021.
Vancouver:
Yueh R. Capturing Self-Efficacy Behavioral Outcomes Through Human-Computer Interaction Devices
. [Internet] [Doctoral dissertation]. University of Arizona; 2019. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/636568.
Council of Science Editors:
Yueh R. Capturing Self-Efficacy Behavioral Outcomes Through Human-Computer Interaction Devices
. [Doctoral Dissertation]. University of Arizona; 2019. Available from: http://hdl.handle.net/10150/636568
University of Arizona
6.
Zhu, Hongyi.
Developing Smart and Unobtrusive Mobile Home Care: A Deep Learning Approach
.
Degree: 2019, University of Arizona
URL: http://hdl.handle.net/10150/636595
► Chronic conditions, frailty, dementia, and other diseases or symptoms significantly affect senior citizens’ health, safety, and quality of life. The insufficient labor supply of the…
(more)
▼ Chronic conditions, frailty, dementia, and other diseases or symptoms significantly affect senior citizens’ health, safety, and quality of life. The insufficient labor supply of the home care market requests the involvement of modern information technology such as sensors, Internet of Things, and artificial intelligence. Healthcare providers and information systems (IS) researchers have sought to develop mobile home care approaches that adopt sensing technology to improve their effectiveness and efficiency. However, existing economics and behavioral methodologies for Health Information Technology (HIT) and health data analytics approaches were not designed for mobile data. Novel computational Information Technology (IT) artifacts are required to address significant mobile home care needs. Given the societal importance of mobile home care, this dissertation presents four essays that follow design science guidelines to design IT artifacts for mobile home care applications. Essay I employs a Sequence-to-Sequence model to extract high-level ADLs (e.g., cooking) from multi-modal smart home sensors (e.g., motion, on/off sensors). Essay II develops a hierarchical ADL recognition framework to generate interpretable intermediate results as well as a novel interaction kernel for Convolutional Neural Networks (CNNs) to extract the interaction semantics. Essay III leverages deep transfer learning to address object motion sensor data scarcity and improve human identification performance for customized home care. Essay IV designs an attention mechanism-based framework to better interpret deep learning-based models for mobile home care. Beyond the practical contributions provided to home care practitioners, this dissertation offers numerous design principles to guide future mobile health analytics IS research.
Advisors/Committee Members: Chen, Hsinchun (advisor), Brown, Susan A. (committeemember), Nunamaker, Jay F. (committeemember), Chen, Wei (committeemember).
Subjects/Keywords: Activities of Daily Living;
Deep Learning;
Design Science;
Home Care;
Mobile Health Analytics
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APA ·
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Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Zhu, H. (2019). Developing Smart and Unobtrusive Mobile Home Care: A Deep Learning Approach
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/636595
Chicago Manual of Style (16th Edition):
Zhu, Hongyi. “Developing Smart and Unobtrusive Mobile Home Care: A Deep Learning Approach
.” 2019. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/636595.
MLA Handbook (7th Edition):
Zhu, Hongyi. “Developing Smart and Unobtrusive Mobile Home Care: A Deep Learning Approach
.” 2019. Web. 16 Jan 2021.
Vancouver:
Zhu H. Developing Smart and Unobtrusive Mobile Home Care: A Deep Learning Approach
. [Internet] [Doctoral dissertation]. University of Arizona; 2019. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/636595.
Council of Science Editors:
Zhu H. Developing Smart and Unobtrusive Mobile Home Care: A Deep Learning Approach
. [Doctoral Dissertation]. University of Arizona; 2019. Available from: http://hdl.handle.net/10150/636595
University of Arizona
7.
Marquardson, James.
Achieving Alignment: System Design and Attitudinal Considerations to Increase the Persuasive Power of Technology
.
Degree: 2015, University of Arizona
URL: http://hdl.handle.net/10150/556848
► Increasing amounts of data are being produced and consumed on a daily basis. Every mouse movement and click on a website can be analyzed to…
(more)
▼ Increasing amounts of data are being produced and consumed on a daily basis. Every mouse movement and click on a website can be analyzed to discover usage patterns and cognitive load (Jenkins et al., 2014), companies mine purchase histories to discover customer shopping patterns (Brin et al., 1997) and historical business transaction information can be used to improve business processes (Ghattas et al., 2014). Using sophisticated algorithms, data can be turned into information that helps guide marketers, policy makers, business managers, and other decision-makers. However, history has shown that increases in the amount and quality of information do not necessarily lead to better decision outcomes (Dawes et al., 1989). Human decision-makers may fail to understand the information, ignore it, or simply not believe it. Methods for effectively conveying information to humans must be studied so that the full value of information systems can be realized. This dissertation uses three studies to explain the factors that make technology persuasive. In the first study, attitudes toward technology measure how beliefs about technology influence the way people process information. Ordering effects are also examined to determine how people view information from decision support systems, and to find the optimal time to present information to decision-makers. In the second study, the persuasive power of text and audio modalities are compared. Additionally, the loss aversion bias is investigated to determine the utility of leveraging this cognitive bias in a technology context. In the third study, Protection Motivation Theory (Rogers, 1983) is used to extend the loss aversion model from study two. The study also investigates how message vividness and user participation through software personalization influence attitudes and behavior. Together, these experiments extend existing theoretical frameworks while giving actionable guidance to information systems practitioners. The studies demonstrate the importance of understanding cognitive biases, attitudes toward technology, and message delivery in a decision support scenario. These investigations are the first step in creating a more comprehensive model of factors that influence the persuasive power of technology.
Advisors/Committee Members: Nunamaker, Jay F., Jr (advisor), Valacich, Joseph S. (committeemember), Brown, Susan A. (committeemember), Nunamaker, Jay F., Jr. (committeemember).
Subjects/Keywords: decision support;
Management Information Systems;
cognitive biases
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APA ·
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MLA ·
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Export
to Zotero / EndNote / Reference
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APA (6th Edition):
Marquardson, J. (2015). Achieving Alignment: System Design and Attitudinal Considerations to Increase the Persuasive Power of Technology
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/556848
Chicago Manual of Style (16th Edition):
Marquardson, James. “Achieving Alignment: System Design and Attitudinal Considerations to Increase the Persuasive Power of Technology
.” 2015. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/556848.
MLA Handbook (7th Edition):
Marquardson, James. “Achieving Alignment: System Design and Attitudinal Considerations to Increase the Persuasive Power of Technology
.” 2015. Web. 16 Jan 2021.
Vancouver:
Marquardson J. Achieving Alignment: System Design and Attitudinal Considerations to Increase the Persuasive Power of Technology
. [Internet] [Doctoral dissertation]. University of Arizona; 2015. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/556848.
Council of Science Editors:
Marquardson J. Achieving Alignment: System Design and Attitudinal Considerations to Increase the Persuasive Power of Technology
. [Doctoral Dissertation]. University of Arizona; 2015. Available from: http://hdl.handle.net/10150/556848
University of Arizona
8.
Giboney, Justin Scott.
Development And Application Of An Online Tool For Meta-Analyses Using Design Science Principles
.
Degree: 2014, University of Arizona
URL: http://hdl.handle.net/10150/333036
► Nations are becoming increasingly sensitive about securing their borders, leading border security organizations to investigate systems designed to detect deception through linguistic analysis. As research…
(more)
▼ Nations are becoming increasingly sensitive about securing their borders, leading border security organizations to investigate systems designed to detect deception through linguistic analysis. As research about linguistic deception still has resulted in competing hypotheses, this dissertation uses a design science, information systems approach to build a system that synthesizes research on the linguistics of deception. It also performs a systematic review and meta-analysis to provide information about linguistics of deception to border security organizations. This dissertation outlines features that should be included in collaborative meta-analysis tools: process restriction, task organization, information sharing, task coordination, terminology definition, and simple interfaces. These features are discussed and implemented in a new system www.OrionShoulders.com. Through a systematic review and a behavioral experiment on linguistic of deception using the new system, this dissertation identified seven behavioral and cognitive constructs that could be measured through linguistics during deception: cognitive load, event recollection, guilt, credibility portrayal, distancing, dominant behavior, and hedging. This dissertation contributes a theoretical model that explains these seven constructs and how they are measured. The results of the systematic review and the behavioral experiment showed that hedging terms, first-person pronouns, negative emotion, generalizing terms, and the quantity of words were significantly correlated with deception.
Advisors/Committee Members: Nunamaker, Jay F. Jr (advisor), Nunamaker, Jay F. Jr (committeemember), Brown, Susan A. (committeemember), Valacich, Joseph S. (committeemember).
Subjects/Keywords: Linguistics;
Meta-Analysis Software;
Management Information Systems;
Deception
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APA ·
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MLA ·
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Export
to Zotero / EndNote / Reference
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APA (6th Edition):
Giboney, J. S. (2014). Development And Application Of An Online Tool For Meta-Analyses Using Design Science Principles
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/333036
Chicago Manual of Style (16th Edition):
Giboney, Justin Scott. “Development And Application Of An Online Tool For Meta-Analyses Using Design Science Principles
.” 2014. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/333036.
MLA Handbook (7th Edition):
Giboney, Justin Scott. “Development And Application Of An Online Tool For Meta-Analyses Using Design Science Principles
.” 2014. Web. 16 Jan 2021.
Vancouver:
Giboney JS. Development And Application Of An Online Tool For Meta-Analyses Using Design Science Principles
. [Internet] [Doctoral dissertation]. University of Arizona; 2014. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/333036.
Council of Science Editors:
Giboney JS. Development And Application Of An Online Tool For Meta-Analyses Using Design Science Principles
. [Doctoral Dissertation]. University of Arizona; 2014. Available from: http://hdl.handle.net/10150/333036
University of Arizona
9.
Twyman, Nathan W.
Automated Human Screening for Detecting Concealed Knowledge
.
Degree: 2012, University of Arizona
URL: http://hdl.handle.net/10150/222874
► Screening individuals for concealed knowledge has traditionally been the purview of professional interrogators investigating a crime. But the ability to detect when a person is…
(more)
▼ Screening individuals for concealed knowledge has traditionally been the purview of professional interrogators investigating a crime. But the ability to detect when a person is hiding important information would be of high value to many other fields and functions. This dissertation proposes design principles for and reports on an implementation and empirical evaluation of a non-invasive, automated system for human screening. The screening system design (termed an automated screening kiosk or ASK) is patterned after a standard interviewing method called the Concealed Information Test (CIT), which is built on theories explaining psychophysiological and behavioral effects of human orienting and defensive responses. As part of testing the ASK proof of concept, I propose and empirically examine alternative indicators of concealed knowledge in a CIT. Specifically, I propose kinesic rigidity as a viable cue, propose and instantiate an automated method for capturing rigidity, and test its viability using a traditional CIT experiment. I also examine oculomotor behavior using a mock security screening experiment using an ASK system design. Participants in this second experiment packed a fake improvised explosive device (IED) in a bag and were screened by an ASK system. Results indicate that the ASK design, if implemented within a highly controlled framework such as the CIT, has potential to overcome barriers to more widespread application of concealed knowledge testing in government and business settings.
Advisors/Committee Members: Nunamaker, Jay F. Jr (advisor), Burgoon, Judee K (advisor), Brown, Susan A. (committeemember), Patton, Mark W. (committeemember), Nunamaker, Jay F. Jr. (committeemember), Burgoon, Judee K. (committeemember).
Subjects/Keywords: deception detection;
eye tracking;
oculometrics;
security screening;
Management Information Systems;
body movement;
CIT
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APA (6th Edition):
Twyman, N. W. (2012). Automated Human Screening for Detecting Concealed Knowledge
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/222874
Chicago Manual of Style (16th Edition):
Twyman, Nathan W. “Automated Human Screening for Detecting Concealed Knowledge
.” 2012. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/222874.
MLA Handbook (7th Edition):
Twyman, Nathan W. “Automated Human Screening for Detecting Concealed Knowledge
.” 2012. Web. 16 Jan 2021.
Vancouver:
Twyman NW. Automated Human Screening for Detecting Concealed Knowledge
. [Internet] [Doctoral dissertation]. University of Arizona; 2012. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/222874.
Council of Science Editors:
Twyman NW. Automated Human Screening for Detecting Concealed Knowledge
. [Doctoral Dissertation]. University of Arizona; 2012. Available from: http://hdl.handle.net/10150/222874
10.
Zhang, Yulei.
Knowledge Discovery in Social Media: Physical World, Online World, and Virtual World
.
Degree: 2011, University of Arizona
URL: http://hdl.handle.net/10150/145420
► Social media have grown tremendously, making the Internet a new platform for community-based social interaction. The rich and vast amount of social media data provides…
(more)
▼ Social media have grown tremendously, making the Internet a new platform for community-based social interaction. The rich and vast amount of social media data provides valuable resources for understanding various social phenomena. Different from the world where people physically live, the new media bring additional types of worlds into people's lives: online worlds and virtual worlds. Examples of online worlds include Web forums, blogs, and online reviews, while the most famous example of a virtual world is Second Life. My dissertation is trying to address the overarching questions about how people adapt to social media to share information and exchange opinions, and what factors influence their activities in the new media. I adopt Web mining, machine learning, and computational linguistics techniques to analyze aspects of people and their behavior, such as gender differences, emotional differences, avatar activity differences, and avatar social interaction differences in online and virtual worlds.Chapter 2 develops a feature-based text classification framework to examine online gender differences between Web forum posters by analyzing writing styles and topics of interest. Guided by the stereotyping and social roles theories, Chapter 3 examines the emotional differences between men and women in text-based online communications. A research framework for automatic emotion detection is developed using sentiment analysis techniques. In the framework, different algorithms are developed to analyze the sentence-level subjectivity and phrase- and word-level polarity. Chapters 4 and 5 focus on investigating avatar behavior in the virtual world. Guided by the theories of social presence, social role, and gender role, Chapter 4 examines the effects of avatar virtual gender, virtual age, and region theme on avatars' physical activities. Chapter 5 further examines avatars' gender and age differences in their social interactions in help-seeking regions in the virtual world. The overall gender and age difference analyses and detailed investigations by comparing three types of interaction networks based on gender or age are conducted.Overall, my dissertation contributes to the literature on social media analytics, knowledge discovery, virtual world research, and text and Web mining.
Advisors/Committee Members: Chen, Hsinchun (advisor), Brown, Susan A (committeemember), Nunamaker, Jay F (committeemember).
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APA (6th Edition):
Zhang, Y. (2011). Knowledge Discovery in Social Media: Physical World, Online World, and Virtual World
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/145420
Chicago Manual of Style (16th Edition):
Zhang, Yulei. “Knowledge Discovery in Social Media: Physical World, Online World, and Virtual World
.” 2011. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/145420.
MLA Handbook (7th Edition):
Zhang, Yulei. “Knowledge Discovery in Social Media: Physical World, Online World, and Virtual World
.” 2011. Web. 16 Jan 2021.
Vancouver:
Zhang Y. Knowledge Discovery in Social Media: Physical World, Online World, and Virtual World
. [Internet] [Doctoral dissertation]. University of Arizona; 2011. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/145420.
Council of Science Editors:
Zhang Y. Knowledge Discovery in Social Media: Physical World, Online World, and Virtual World
. [Doctoral Dissertation]. University of Arizona; 2011. Available from: http://hdl.handle.net/10150/145420
11.
Jiang, Shan.
Statistical Modeling of Multi-Dimensional Knowledge Diffusion Networks: An ERGM-Based Framework
.
Degree: 2015, University of Arizona
URL: http://hdl.handle.net/10150/555946
► Knowledge diffusion networks consist of individuals who exchange knowledge and knowledge flows connecting the individuals. By studying knowledge diffusion in a network perspective, it helps…
(more)
▼ Knowledge diffusion networks consist of individuals who exchange knowledge and knowledge flows connecting the individuals. By studying knowledge diffusion in a network perspective, it helps us understand how the connections between individuals affect the knowledge diffusion processes. Existing research on knowledge diffusion networks mostly adopts a uni-dimensional perspective, where all the individuals in the networks are assumed to be of the same type. It also assumes that there is only one type of knowledge flow in the network. This dissertation proposes a multi-dimensional perspective of knowledge diffusion networks and examines the patterns of knowledge diffusion with Exponential Random Graph Model (ERGM) based approaches. The objective of this dissertation is to propose a framework that effectively addresses the multi-dimensionality of knowledge diffusion networks, to enable researchers and practitioners to conceptualize the multi-dimensional knowledge diffusion networks in various domains, and to provide implications on how to stimulate and control the knowledge diffusion process. The dissertation consists of three essays, all of which examine the multi-dimensional knowledge diffusion networks in a specific context, but each focuses on a different aspect of knowledge diffusion. Chapter 2 focuses on how structural properties of networks affect various types of knowledge diffusion processes in the domain of commercial technology. The study uses ERGM to simultaneously model multiple types of knowledge flows and examine their interactions. The objective is to understand the impacts of network structures on knowledge diffusion processes. Chapter 3 focuses on examining the impact of individual attributes and the attributes of knowledge on knowledge diffusion in the context of scientific innovation. Based on social capital theory, the study also utilizes ERGM to examine how knowledge transfer and knowledge co-creation can be affected by the attributes of individual researchers and the attributes of scientific knowledge. Chapter 4 considers the dynamic aspect of knowledge diffusion and proposes a novel network model extending ERGM to identify dynamic patterns of knowledge diffusion in social media. In the proposed model, dynamic patterns in social media networks are modeled based on the nodal attributes of individuals and the temporal information of network ties.
Advisors/Committee Members: Chen, Hsinchun (advisor), Chen, Hsinchun (committeemember), Goes, Paulo B. (committeemember), Brown, Susan A. (committeemember), Lin, Mingfeng (committeemember).
Subjects/Keywords: knowledge diffusion;
Multi-dimensionality;
Network dynamics;
Social media;
Social network analysis;
Management Information Systems;
Exponential random graph model
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APA ·
Chicago ·
MLA ·
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CSE |
Export
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APA (6th Edition):
Jiang, S. (2015). Statistical Modeling of Multi-Dimensional Knowledge Diffusion Networks: An ERGM-Based Framework
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/555946
Chicago Manual of Style (16th Edition):
Jiang, Shan. “Statistical Modeling of Multi-Dimensional Knowledge Diffusion Networks: An ERGM-Based Framework
.” 2015. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/555946.
MLA Handbook (7th Edition):
Jiang, Shan. “Statistical Modeling of Multi-Dimensional Knowledge Diffusion Networks: An ERGM-Based Framework
.” 2015. Web. 16 Jan 2021.
Vancouver:
Jiang S. Statistical Modeling of Multi-Dimensional Knowledge Diffusion Networks: An ERGM-Based Framework
. [Internet] [Doctoral dissertation]. University of Arizona; 2015. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/555946.
Council of Science Editors:
Jiang S. Statistical Modeling of Multi-Dimensional Knowledge Diffusion Networks: An ERGM-Based Framework
. [Doctoral Dissertation]. University of Arizona; 2015. Available from: http://hdl.handle.net/10150/555946
12.
Wilson, David W.
Overcoming Information Privacy Concerns: Learning from Three Disclosure Contexts
.
Degree: 2015, University of Arizona
URL: http://hdl.handle.net/10150/555938
► Advances in information technology have amplified issues related to privacy and the disclosure of personal information. New technologies have enabled an explosion in the amount…
(more)
▼ Advances in information technology have amplified issues related to privacy and the disclosure of personal information. New technologies have enabled an explosion in the amount and variety of information created, stored, and potentially shared about people, and there has been a corresponding explosion in privacy-related concerns and conversations in academic and non-academic forums. This dissertation contributes to one such conversation, adding to our understanding of the mechanisms that shape individuals' privacy concerns in the context of disclosure of personal information. Individuals must overcome their information privacy concerns in order for personal information disclosure to take place, but the mechanisms surrounding this process are highly dependent on the context of disclosure. Accordingly, this research seeks to build understanding around the ways in which privacy concerns are mitigated or counterbalanced in three different disclosure contexts. Essay 1, positioned in the e-commerce context, contributes uniquely to an emerging stream of disclosure research that considers irrationality within the privacy disclosure decision process. Essay 2 is focused on a less frequently examined disclosure context - online social networks - and examines the tension between individuals' privacy concerns and their desire for social benefits and personal expression, focusing especially on the social network technology's ability to support impression management behavior. Finally, Essay 3 examines the mitigation of privacy concerns in the context of involuntary disclosure - increasingly common in the modern online environment - wherein the primary goal is to reduce concerns or anxiety regarding the information already disclosed. In comparing disclosure processes across these contexts, this research provides insights regarding consistencies and distinctions among the different domains. Insights gained, both within and across these contexts, are valuable to both privacy researchers and professional stakeholders.
Advisors/Committee Members: Nunamaker, Jay F. Jr (advisor), Valacich, Joseph S (advisor), Nunamaker, Jay F. Jr (committeemember), Valacich, Joseph S. (committeemember), Brown, Susan A. (committeemember).
Subjects/Keywords: control;
disclosure;
identity;
irrational;
privacy;
Management Information Systems;
calculus
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APA ·
Chicago ·
MLA ·
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CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Wilson, D. W. (2015). Overcoming Information Privacy Concerns: Learning from Three Disclosure Contexts
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/555938
Chicago Manual of Style (16th Edition):
Wilson, David W. “Overcoming Information Privacy Concerns: Learning from Three Disclosure Contexts
.” 2015. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/555938.
MLA Handbook (7th Edition):
Wilson, David W. “Overcoming Information Privacy Concerns: Learning from Three Disclosure Contexts
.” 2015. Web. 16 Jan 2021.
Vancouver:
Wilson DW. Overcoming Information Privacy Concerns: Learning from Three Disclosure Contexts
. [Internet] [Doctoral dissertation]. University of Arizona; 2015. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/555938.
Council of Science Editors:
Wilson DW. Overcoming Information Privacy Concerns: Learning from Three Disclosure Contexts
. [Doctoral Dissertation]. University of Arizona; 2015. Available from: http://hdl.handle.net/10150/555938
University of Arizona
13.
Wilkerson, Jerod W.
Closing the Defect Reduction Gap between Software Inspection and Test-Driven Development: Applying Mutation Analysis to Iterative, Test-First Programming
.
Degree: 2008, University of Arizona
URL: http://hdl.handle.net/10150/195160
► The main objective of this dissertation is to assist in reducing the chaotic state of the software engineering discipline by providing insights into both the…
(more)
▼ The main objective of this dissertation is to assist in reducing the chaotic state of the software engineering discipline by providing insights into both the effectiveness of software defect reduction methods and ways these methods can be improved. The dissertation is divided into two main parts. The first is a quasi-experiment comparing the software defect rates and initial development costs of two methods of software defect reduction: software inspection and test-driven development (TDD). Participants, consisting of computer science students at the
University of
Arizona, were divided into four treatment groups and were asked to complete the same programming assignment using either TDD, software inspection, both, or neither. Resulting defect counts and initial development costs were compared across groups. The study found that software inspection is more effective than TDD at reducing defects, but that it also has a higher initial cost of development. The study establishes the existence of a defect-reduction gap between software inspection and TDD and highlights the need to improve TDD because of its other benefits.The second part of the dissertation explores a method of applying mutation analysis to TDD to reduce the defect reduction gap between the two methods and to make TDD more reliable and predictable. A new change impact analysis algorithm (CHA-AS) based on CHA is presented and evaluated for applications of software change impact analysis where a predetermined set of program entry points is not available or is not known. An estimated average case complexity analysis indicates that the algorithm's time and space complexity is linear in the size of the program under analysis, and a simulation experiment indicates that the algorithm can capitalize on the iterative nature of TDD to produce a cost savings in mutation analysis applied to TDD projects. The algorithm should also be useful for other change impact analysis situations with undefined program entry points such as code library and framework development.An enhanced TDD method is proposed that incorporates mutation analysis, and a set of future research directions are proposed for developing tools to support mutation analysis enhanced TDD and to continue to improve the TDD method.
Advisors/Committee Members: Nunamaker, Jr., Jay F (advisor), Brown, Susan A. (committeemember), Moon, Bongki (committeemember).
Subjects/Keywords: Software Inspection;
Test-Driven Development;
Automated Testing;
Mutation Analysis;
Change Impact Analysis;
Software Quality
Record Details
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Wilkerson, J. W. (2008). Closing the Defect Reduction Gap between Software Inspection and Test-Driven Development: Applying Mutation Analysis to Iterative, Test-First Programming
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/195160
Chicago Manual of Style (16th Edition):
Wilkerson, Jerod W. “Closing the Defect Reduction Gap between Software Inspection and Test-Driven Development: Applying Mutation Analysis to Iterative, Test-First Programming
.” 2008. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/195160.
MLA Handbook (7th Edition):
Wilkerson, Jerod W. “Closing the Defect Reduction Gap between Software Inspection and Test-Driven Development: Applying Mutation Analysis to Iterative, Test-First Programming
.” 2008. Web. 16 Jan 2021.
Vancouver:
Wilkerson JW. Closing the Defect Reduction Gap between Software Inspection and Test-Driven Development: Applying Mutation Analysis to Iterative, Test-First Programming
. [Internet] [Doctoral dissertation]. University of Arizona; 2008. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/195160.
Council of Science Editors:
Wilkerson JW. Closing the Defect Reduction Gap between Software Inspection and Test-Driven Development: Applying Mutation Analysis to Iterative, Test-First Programming
. [Doctoral Dissertation]. University of Arizona; 2008. Available from: http://hdl.handle.net/10150/195160
University of Arizona
14.
Fadel, Kelly John.
Infusion of Information Systems: The Role of Adaptation and Individual Cognitions
.
Degree: 2007, University of Arizona
URL: http://hdl.handle.net/10150/195745
► Each year, organizations invest billions of dollars in large information systems (IS) that support business processes. These systems are implemented with the hope that they…
(more)
▼ Each year, organizations invest billions of dollars in large information systems (IS) that support business processes. These systems are implemented with the hope that they will bring increased efficiency and productivity to operations, decision making, and collaboration, thus strengthening competitive advantage in an increasingly aggressive global marketplace. Unfortunately, empirical evidence demonstrates that despite prodigious investment in these systems, their purported benefits often lag behind expectations, or fail to materialize at all. While many causes may contribute to these failures, a common theme in empirical studies is that information systems are rarely infused into individuals' work practices, thus undermining their benefits to the organization. IS infusion refers to the degree to which the technology is fully integrated into an individual's or organization's work systems. Although theoretical and practical interest in IS infusion is growing, little is understood about the factors that lead to IS infusion at the individual level.This dissertation integrates research and theory in information systems acceptance, adaptation, and infusion to develop a theoretical model of IS infusion at the individual level. To test the model, a survey instrument was developed and tested at the health care facility of a large public
university. The revised survey was then deployed at a large technology firm in the northwestern United States, from which 195 individual responses were obtained. Results indicate that adaptation behaviors engaged in by IS users significantly impact the degree to which they infuse the IS in their work. Moreover, these adaptation behaviors are shaped by cognitive appraisals of the IS, which are, in turn, influenced by key acceptance-related IS perceptions.This study contributes to research by integrating previously disparate theories into a holistic framework of individual-level IS infusion. For practice, this research sheds light on specific factors that contribute to IS adaptation and infusion, thereby assisting IS managers to promote these outcomes within their organization.
Advisors/Committee Members: Brown, Susan A (advisor), Tanniru, Mohan R. (committeemember), Weisband, Suzanne (committeemember).
Subjects/Keywords: information system;
infusion;
adaptation;
coping;
use;
adoption
Record Details
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Record Details
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Fadel, K. J. (2007). Infusion of Information Systems: The Role of Adaptation and Individual Cognitions
. (Doctoral Dissertation). University of Arizona. Retrieved from http://hdl.handle.net/10150/195745
Chicago Manual of Style (16th Edition):
Fadel, Kelly John. “Infusion of Information Systems: The Role of Adaptation and Individual Cognitions
.” 2007. Doctoral Dissertation, University of Arizona. Accessed January 16, 2021.
http://hdl.handle.net/10150/195745.
MLA Handbook (7th Edition):
Fadel, Kelly John. “Infusion of Information Systems: The Role of Adaptation and Individual Cognitions
.” 2007. Web. 16 Jan 2021.
Vancouver:
Fadel KJ. Infusion of Information Systems: The Role of Adaptation and Individual Cognitions
. [Internet] [Doctoral dissertation]. University of Arizona; 2007. [cited 2021 Jan 16].
Available from: http://hdl.handle.net/10150/195745.
Council of Science Editors:
Fadel KJ. Infusion of Information Systems: The Role of Adaptation and Individual Cognitions
. [Doctoral Dissertation]. University of Arizona; 2007. Available from: http://hdl.handle.net/10150/195745
. 
Open Access Theses and Dissertations
