Data management plan for the grant, "Exploring the Relative Risk Severity of Phishing Techniques on Individual Phishing Susceptibility: A Mixed Approach."

Data management plan for the grant, "Applying Game Theory for Improving and Optimizing the US Political Asylum Process"

Data management plan for the grant, "Exploiting machine learning for cybersecurity tasks to talent mapping and exploring credentialing ecosystem"

Article describes how identity theft poses a significant threat to mobile users, yet mobile identity protection is often overlooked in cybersecurity literature. This study adopts a mixed-methods approach and draws on expectancy-value theory to address these gaps and explore the impact of expectations, capabilities, motivational values, technical measures, and awareness on individuals' intentions to achieve mobile identity protection.

Article describes how in Machine Learning, prediction quality is usually measured using different techniques and evaluation methods. This paper will introduce a simple regularization term to manage the number of over-predicted/under-predicted instances in a regression model.

Article asserts that the most significant government-mandated technology is the implementation of Electronic Health Records (EHRs). The present research examines EHR through the lens of Resource Advantage Theory –– to empirically assess how partial and comprehensive implementation levels of EHR adoption influence quality management and financial performance of hospitals.

Article asserts that spare parts inventory management is complex due to the combined impact of intermittent and variable demand patterns. This study proposes a novel nonparametric Bayesian forecasting approach with its roots in the empirical Bayes paradigm.

Article examining the domains of social determinants of health, specifically the social and community context per Healthy People 2030 objectives. These mechanisms of social interaction, in the form of group activities, community engagement, and virtual interactions via email or text message, were assessed using hierarchical regression analysis to find out their association with wellbeing, depression symptoms, and cognition of older adults.

Data management plan for the grant, "Enhancing Cybersecurity TKSs (Tasks, Knowledge, and Skills) for Cybersecurity Education and Workforce Development."

Data management plan for the grant, "Enhancing Techniques for Ontologies Mapping for the Cybersecurity Workforce Development Applications."

Data management plan for the grant, "Predicting Criminal Activities in Darknet Markets: Advancing Knowledge and Tools for Activities Monitoring."

Article presents a textual analysis of news articles about cyberbullying to provide input for prevention and training efforts to combat the issue.

Article explores the importance of investigating the impact of trust on intention to purchase from both successful and unsuccessful purchase cases in order to provide a more balanced view of the critical role of trust in e-commerce transaction decisions.

This article is an introduction to the Minitrack on Artificial Intelligence and Big Data Analytics Management, Governance, and Compliance at the 53rd Hawaii International Conference on System Sciences.

Article is a study examining how emotional arousal influences information diffusion in social media using a sentiment mining approach. The authors propose a research model and test it using data collected from Twitter.

This article uses the virtue (ethics) theory and cyber attribution to argue that there exists a dichotomy among offensive security engineers, one that appreciates organizational security practices, but at the same time violates ethics in how to retaliate against a malicious attacker.

Article presents an integrated model to explain the learning process and provide essential antecedents of eHealth behavioral intention.

Article presents a sample of dynamic interactive visualizations of relatively complex quantitative topics in statistics, operations management, and management science and discuss their implications for pedagogy for undergraduate and graduate students.

This article investigates the six cognitive biases resulting from the use of the representativeness heuristic, namely, insensitivity to prior probability of outcomes, insensitivity to sample size, misconception of chance, insensitivity to predictability, the illusion of validity, and misconception of regression. Specifically, the authors examine how cognitive reflection and training affect these six cognitive biases in the operations management context.

This article builds on agency theory and identify factors that increase the risk of an agency problem between a principal (a human or an organization) and an AI agent and propose a framework for AI agency problem analysis. The framework is illustrated through AI use cases and industry examples. Implications for AI governance research and practice are discussed. It was presented at the 52nd Hawaii International Conference on System Sciences.

This article's research builds a continuance usage and location disclosure model from the expectation-confirmation perspective. The effect of benefit expectations on usefulness and satisfaction is hypothesized. In addition, the positive effect of usefulness on satisfaction and continuance intention is postulated. Findings contribute to the current literature in business intelligence by focusing on location disclosure behavior in the context of LBAs and the necessity of this type of information for location intelligence. This article was presented at the 52nd Hawaii International Conference on System Sciences.

Presented at the 2017 International Conference on Knowledge Management. This poster demonstrates the utility of text analytic for theory building and validation in information science.

Poster paper for the 2017 International Conference on Knowledge Management. This paper demonstrates the utility of text analytic for theory building and validation in information science.

Poster paper for the 2017 International Conference on Knowledge Management. This paper proposes a dimensional model with "aspects of a corpus, such as topic or opinion, as derived star schema dimensions." Focusing on a case study on Twitter the paper demonstrates how the derived dimensions, combined with transactional facts and derived facts can uncover "the collective tacit knowledge in Twitter communities."