Managers rely on analytics to make decisions and the choice of the analytical method can influence their decision-making. This dissertation considers three cases and examines how the choice of analytical methods influence interpretations and implications. These areas are communication for health-related information in social media, health information technology investment by hospitals as it relates to patient satisfaction, and health related expenditure policies of countries. These studies develop theoretical models and empirically test them on primary or secondary data, comparing the performance of popular analytical methods. The conduct of these three studies contributes to a better understanding about the choice of analytical methods and allow development of a heuristic approach by offering guidelines for selecting an appropriate methodology. They demonstrate the value of heuristic approaches for use with non-traditional and traditional statistical methods, as the information gained from non-traditional methods (NNs) provides insights into traditional statistical methods, similar to insights gained from exploratory data analysis. The studies also show the value in examining any dataset with multiple methods because they either confirm each other or fail to confirm, providing insights.

Ubiquitous computing results in access to vast amounts of data, which is changing the way humans interact with each other, with computers, and with their environments. Information is literally at our fingertips with touchscreen technology, but it is not valuable until it is understood. As a result, selecting which information to use in a decision process is a challenge in the current information environment (Lu & Yuan, 2011). The purpose of this dissertation was to investigate how individual decision makers, in different decision contexts, determine when to stop collecting information given the availability of virtually unlimited information. Decision makers must make an ultimate decision, but also must make a decision that he or she has enough information to make the final decision (Browne, Pitts, & Wetherbe, 2007). In determining how much information to collect, researchers found that people engage in ‘satisficing' in order to make decisions, particularly when there is more information than it is possible to manage (Simon, 1957). A more recent elucidation of information use relies on the idea of stopping rules, identifying five common stopping rules information seekers use: mental list, representational stability, difference threshold, magnitude threshold, and single criterion (Browne et al., 2007). Prior research indicates …

In information systems design there are two schools of thought about what factors are necessary to create a successful information system. The first, conventional view holds that system performance is a key, so that efficiency characteristics such as system usability and task completion time are primary concerns of system designers. The second, emerging view holds that the visual design is also the key, so that visual interface characteristics such as visual appeal, in addition to efficiency characteristics, are critical concerns of designers. This view contends that visual design enhances system use. Thus, this work examines the effects of visual design on computer systems. Visual design exerts its influence on systems through two mechanisms: it evokes affective responses from IT users, such as arousal and pleasure and it influences individuals’ cognitive assessments of systems. Given that both affective and cognitive reactions are significant antecedents of user behaviors in the IT realm, it is no surprise that visual design plays a critical role in information system success. Human-computer-interaction literature indicates that visual aesthetics positively influences such information success factors as usability, online trust, user satisfaction, flow experience, and so on. Although academic research has introduced visual design into the Information Systems (IS) …

Over the past few years, there has been a skyrocketing growth in the use of mobile devices. Mobile devices are ushering in a new era of multi-platform media and a new paradigm of “being-always-connected”. The proliferation of mobile devices, the dramatic growth of cloud computing services, the availability of high-speed mobile internet, and the increase in the functionalities and network connectivity of mobile devices, have led to creation of a phenomenon called BYOD (Bring Your Own Device), which allows employees to connect their personal devices to corporate networks. BYOD is identified as one of the top ten technology trends in 2014 that can multiply the size of mobile workforce in organizations. However, it can also serve as a vehicle that transfers cyber security threats associated with personal mobile devices to the organizations. As BYOD opens the floodgates of various device types and platforms into organizations, identifying different sources of cyber security threats becomes indispensable. So far, there are no studies that investigated how user, device and usage characteristics affect individuals’ protective and risky IT behaviors. The goal of this dissertation is to expand the current literature in IS security by accounting for the roles of user, device, and usage characteristics …

In 2012, the CIA World Fact Book showed that the service sector contributed about 76.6% and 51.4% of the 2010 gross national product of both the United States and Ghana, respectively. Research in the services area shows that a firm's success in today's competitive business environment is dependent upon its ability to deliver superior service quality. However, these studies have yet to address factors that influence customers to remain committed to a mass service in economically diverse countries. In addition, there is little research on established service quality measures pertaining to the mass service domain. This dissertation applies Rusbult's investment model of relationship commitment and examines its psychological impact on the commitment level of a customer towards a service in two economically diverse countries. In addition, service quality is conceptualized as a hierarchical construct in the mass service (banking) and specific dimensions are developed on which customers assess their quality evaluations. Using, PLS path modeling, a structural equation modeling approach to data analysis, service quality as a hierarchical third-order construct was found to have three primary dimensions and six sub-dimensions. The results also established that a country's national economy has a moderating effect on the relationship between service quality and …

AI-enabled information systems (AI-enabled IS) offer enhanced utility and efficiency due to their knowledge-based endowments, enabling human agents to assign and receive tasks from AI-enabled IS. As a result, this leads to improved decision-making, ability to manage laborious jobs, and a decrease in human errors. Despite the performance-based endowments and efficiencies, there are significant ethical concerns regarding the use of and delegation to AI-enabled IS, which have been extensively addressed in the literature on the dark side of artificial intelligence (AI). Notable concerns include bias and discrimination, fairness, transparency, privacy, accountability, and autonomy. However, the Information Systems (IS) literature does not have a delegation framework that incorporates ethics in the delegation mechanism. This work seeks to integrate a mixed deontological-teleological ethical system into the delegation mechanism to (and from) AI-enabled IS. To that end, I present a testable model to ethically appraise various AI-enabled IS as well as ethically evaluate delegation to (and from) AI-enabled IS in various settings and situations.

The central purpose of this dissertation is to develop and test a theoretical model of mind wandering in a technological setting by integrating the emerging work and theory on mind wandering—a shift of attention from the primary task to the processing of internal goals. This dissertation is intended to advance our understanding on the costs and benefits of mind wandering in information systems (IS) research and in turn, contribute to the literature of cognitive IS research. Understanding the consequences of mind wandering in a technological setting is imperative because mind wandering plays a vital role in influencing various outcomes associated with technology use and/or technology learning, such as technology anxiety, software self-efficacy, and task performance. This dissertation is composed of three essays which examine the determinants and consequences of mind wandering and focus of attention on a number of emotional and cognitive outcomes. A multi-method approach (i.e., online survey and laboratory experiment) across three essays is used to test the research models. Essay 1 focuses on developing the measurement items and estimating the impact of mind wandering on users' emotional outcomes (i.e., technology anxiety and users' satisfaction). Drawing upon the content regulation hypothesis of mind wandering, the content of thoughts …

Understanding information technology and its related products and services is increasingly important because the everyday use of technology continues to expand and broaden. Despite this need for greater understanding, the extant theories that explore the dominant factors that drive intention to use a new technology are limited. The Technology Acceptancy Model (TAM) is the most popular model in explaining traditional technology adoption. The limitations of the TAM in grasping the overall evaluation of technology or service are one of motivations for developing new models in this dissertation. The two antecedents of the TAM- perceived usefulness and perceived ease of use- only capture partial utility of a service (or product). In addition, some researchers argued that key factors used in an initial acceptance model such as perceived usefulness and perceived ease of use are not strong predictors of future continuance intention of the service because they do not consider future switching intention in the later stage. Hence, one goal of this dissertation is to develop and test new models to predict factors that drive intention and continuance intention decisions of new technology related products or services. This research involves three studies that examine different aspects of adoption and continuance intention decisions …

This research study involves three essays and examines CRQ-driven decision making from the points of view of the common firm, social-commerce platform provider, and social-commerce echo-system. It addresses CRQ's progression from traditional business-to-consumer (B2C) initiatives to social platform-specific antecedents and to environment-driven factors lying outside the direct control of the platform provider, yet influencing social commerce business decisions, such as user-generated content from peers (e.g. family, friends) and expert authority (e.g. specialists, experts, professional organizations). The research method used statistical, data mining and computer science techniques. The results suggest that social platform providers should take a proactive approach to CRQ, fully leverage their online platform to improve CRQ while paying special attention to security as a potential barrier, and consider the analysis of elements of the echo-system such as the electronic word of mouth (eWOM) to further drive CRQ and determine the level of alignment between customers and experts, suppliers and products featured, that may lead to value-added managerial insights such as the prioritization, promotion and optimization of such relationships.

In recent years, social media has experienced tremendous growth in the number of users. Facebook alone has more than 1.3 billion active users and Twitter has attracted over 600 million active users. Social media has significantly changed the way humans communicate. Many people use social media to keep in touch with family and friends and receive up-to-date information about what happens around the world. Politicians are using social media to support their campaigns. Use of social media is not restricted to individuals and politicians. Businesses are now using social media to promote their products and services. Many companies maintain Facebook and Twitter accounts to keep in touch with their customers. Consumers also use social media to receive information about products/services. Online product reviews are now an important source of information for consumers. This dissertation aims to address one fundamental research question: how do individual differences among users lead to different levels of performance on social media? More specifically, this dissertation investigates the motivations of use and the predictors of performance in the context of social media. We utilize sentiment mining to predict performance in different types of social media including information diffusion in Twitter and helpfulness and readership of online …

This dissertation consists of three studies that investigate the information privacy & security associated with healthcare technology use. Essay 1 PRISMA-style systematically reviews the existing literature on privacy information disclosure in IoT technology and serves as the theoretical foundation of the current research. It is crucial to comprehend why, how, and under what consequences individuals choose to disclose their personal and health information since doing so is beneficial to the company. This SLR method allows us to find those factors that significantly impact individuals' behavioral intention to disclose personal information while using IoT technologies. Essay 2 posits, develops, and tests a comprehensive theoretical framework built upon the theory of planned behavior and the health belief model to examine factors affecting willingness to disclose PHI in order to use WFDs. A research survey is designed and distributed to a crowdsourcing platform, Mechanical Turk (M-Turk). Research hypotheses are tested using partial least square – structural equation modeling (PLS-SEM). To achieve this purpose, Essay 3 extends the findings from the previous essay and further investigates the caregiver context. Therefore, we developed a novel theoretical model utilizing privacy calculus theory and the technology acceptance model to investigate the willingness of the elderly to disclose …

The increasing demand for mobile apps is out the current capability of mobile app developers. In addition, the growing trend in smartphone ownership and the time people spend on mobile apps has raised several opportunities and risks for users and developers. The average time everyday a user spend on smartphones to use mobile apps is more than two hours. The worldwide mobile app revenue increase is estimated to grow 33%, $19 billion. Three quarter of the time used on mobile apps is solely for using game and social networking apps. To provide more customized services and function to users, mobile apps need to access to personal information. However, 80% of mobile apps put people's information privacy at risk. There is a major gap in the literature about the privacy concerns of mobile device users in the context of mobile apps. This dissertation addresses one fundamental research question: how does individuals' privacy change in the context of mobile apps? More precisely, the focus of this dissertation is on information privacy role in individuals' and mobile app developers' protective behaviors. We investigate the information sensitivity level influence on mobile app developers' emphasis on privacy across mobile app categories. The results show information …

Today's environment is filled with the proliferation of cyber-attacks that result in losses for organizations and individuals. Hackers often use compromised websites to distribute malware, making it difficult for individuals to detect. The impact of clicking through a link on the Internet that is malware infected can result in consequences such as private information theft and identity theft. Hackers are also known to perpetrate cyber-attacks that result in organizational security breaches that adversely affect organizations' finances, reputation, and market value. Risk management approaches for minimizing and recovering from cyber-attack losses and preventing further cyber-attacks are gaining more importance. Many studies exist that have increased our understanding of how individuals and organizations are motivated to reduce or avoid the risks of security breaches and cyber-attacks using safeguard mechanisms. The safeguards are sometimes technical in nature, such as intrusion detection software and anti-virus software. Other times, the safeguards are procedural in nature such as security policy adherence and security awareness and training. Many of these safeguards fall under the risk mitigation and risk avoidance aspects of risk management, and do not address other aspects of risk management, such as risk transfer. Researchers have argued that technological approaches to security risks are rarely …

Artificial intelligence (AI) is quickly transforming business operations and society, as AI capabilities are incorporated into applications ranging from mobile personal assistants to self-driving cars. The potentially disruptive nature of AI calls for an extensive investigation into all aspects of AI-human interactions at individual, group, organizational and market levels. However, there is paucity of academic information systems (IS) research in this area that goes beyond the development and testing of specific narrow AI capabilities. AI represents an important opportunity for organizational and behavioral IS researchers, but also presents challenges associated with the underlying complexity of AI technologies and the diversity of AI applications. Understanding how existing AI research and business practice relate to traditional areas of IS research is an important step towards creating a comprehensive behavioral and organizational AI research agenda. This dissertation seeks to achieve a dual purpose in a series of three essays. Essay 1 seeks to understand the current state of business AI research and practice in business through a quantitative literature review, relate the findings to traditional IS research areas, and identify potentially fruitful research areas for AI-focused IS research. Essays 2 and 3 seek to address specific research questions related to one of such …

This research sought to shed light on information systems security (ISS) by conceptualizing an organization's use of countermeasures using general deterrence theory, positing a non-recursive relationship between threats and countermeasures, and by extending the ISS construct developed in prior research. Industry affiliation and organizational size are considered in terms of differences in threats that firms face, the different countermeasures in use by various firms, and ultimately, how a firm's ISS effectiveness is affected. Six information systems professionals were interviewed in order to develop the appropriate instruments necessary to assess the research model put forth; the final instrument was further refined by pilot testing with the intent of further clarifying the wording and layout of the instrument. Finally, the Association of Information Technology Professionals was surveyed using an online survey. The model was assessed using SmartPLS and a two-stage least squares analysis. Results indicate that a non-recursive relationship does indeed exist between threats and countermeasures and that countermeasures can be used to effectively frame an organization's use of countermeasures. Implications for practitioners include the ability to target the use of certain countermeasures to have desired effects on both ISS effectiveness and future threats. Additionally, the model put forth in this research …

In the Information Age, a proliferation of unstructured text electronic documents exists. Processing these documents by humans is a daunting task as humans have limited cognitive abilities for processing large volumes of documents that can often be extremely lengthy. To address this problem, text data computer algorithms are being developed. Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are two text data computer algorithms that have received much attention individually in the text data literature for topic extraction studies but not for document classification nor for comparison studies. Since classification is considered an important human function and has been studied in the areas of cognitive science and information science, in this dissertation a research study was performed to compare LDA, LSA and humans as document classifiers. The research questions posed in this study are: R1: How accurate is LDA and LSA in classifying documents in a corpus of textual data over a known set of topics? R2: How accurate are humans in performing the same classification task? R3: How does LDA classification performance compare to LSA classification performance? To address these questions, a classification study involving human subjects was designed where humans were asked to generate and classify documents …