Government initiatives called for electronic health records for each individual healthcare consumer by 2014. the purpose of the initiatives is to provide for the common exchange of clinical information between healthcare consumers, healthcare providers, third-party payers and public healthcare officials.This exchange of healthcare information will impact the healthcare industry and enable more effective and efficient application of healthcare so that there may be a decrease in medical errors, increase in access to quality of care tools, and enhancement of decision making abilities by healthcare consumers, healthcare providers and government health agencies. an electronic personal health record (ePHR) created, managed and accessed by healthcare consumers may be the answer to fulfilling the national initiative. However, since healthcare consumers potentially are in control of their own ePHR, the healthcare consumer’s concern for privacy may be a barrier for the effective implementation of a nationwide network of ePHR. a technology acceptance model, an information boundary theory model and a trust model were integrated to analyze usage intentions of healthcare consumers of ePHR. Results indicate that healthcare consumers feel there is a perceived usefulness of ePHR; however they may not see ePHR as easy to use. Results also indicate that the perceived usefulness of …

This work embraces three essays on information privacy: 1) Measures of Personal Information Privacy in Social Networks: Information Control and Situation Awareness, 2) Care to Share your Personal Information? and 3) Privacy Breaches: How Resilient Are You? Every transaction made either online or offline, and every social interaction that is transferred or stored electronically in some way, are generally consumed as big data and ultimately drives the analytics from which consumers benefit. However, this raises some concerns about privacy and ethics. For example, should companies that consumers interact with be allowed to sell their personal information? Consumers derive certain benefits such as personalized content when they choose to offer their data to many websites. However, consumers providing personal data to websites subject themselves to possible privacy invasion when third parties purchase their data. In this case, since the consumer willfully gave away their personal information, is it genuinely personal, and should they retain some, if any, control over it? Theories such as privacy calculus and protection motivation theory (PMT) are a couple of prominent examples that focus on the privacy risks and benefits that drive consumer behavior. However, there is still a lack of research on the instantiation of privacy …

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 …

The data produced and collected by organizations represents both challenges and opportunities for the modern firm. Business intelligence and analytics (BI&A) comprises a wide variety of information management technologies and information seeking activities designed to exploit these information resources. As a result, BI&A has been heralded as a source of improved organizational outcomes in both the academic and practitioner literature, and these technologies are among the largest continuous IT expenditures made over the last decade.Despite the interest in BI&A, there is not enough theorizing about its role in improving firm performance. Scholarly investigations of the link between BI&A and organizational benefits are scarce and primarily exploratory in nature. Further, the majority of the extant research on BI&A is techno-centric, conceptualizing BI&A primarily an organizational technical asset. This study seeks to explicate the relationship between BI&A and improved organizational outcomes by viewing this phenomenon through the lens of dynamic capabilities, a promising theoretical perspective from the strategic management discipline. In so doing, this research reframes BI&A as an organizational capability, rather than simply a technical resource. Guided by a comprehensive review of the BI&A and dynamic capabilities literature, as well as a series of semi-structured focus groups with senior-level business practitioners …

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 …

Extracting meaningful information from large collections of text data is problematic because of the sheer size of the database. However, automated analytic methods capable of processing such data have emerged. These methods, collectively called text mining first began to appear in 1988. A number of additional text mining methods quickly developed in independent research silos with each based on unique mathematical algorithms. How good each of these methods are at analyzing text is unclear. Method development typically evolves from some research silo centric requirement with the success of the method measured by a custom requirement-based metric. Results of the new method are then compared to another method that was similarly developed. The proposed research introduces an experimentally designed testing method to text mining that eliminates research silo bias and simultaneously evaluates methods from all of the major context-region text mining method families. The proposed research method follows a random block factorial design with two treatments consisting of three and five levels (RBF-35) with repeated measures. Contribution of the research is threefold. First, the users perceived a difference in the effectiveness of the various methods. Second, while still not clear, there are characteristics with in the text collection that affect the …

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 …