Management Information Systems Commons^™

Managerial Mindset And Ai Adoption In Smes. A Systematic Review Of Cognitive, Behavioural, And Institutional Foundations, Shabin Muzibbhai Shaikh, Shivkanya Birla

European Management Studies

Purpose: This study examines how managerial mindset shapes the adoption of artificial intelligence (AI) in small and medium‑sized enterprises (SMEs). While existing research often highlights resource or capability constraints, this review shows that deeper cognitive, behavioral, and institutional foundations strongly influence how managers interpret AI and decide whether to engage with it.

Design, Methodology, and Approach: A systematic literature review (SLR) was conducted using established protocols. Thirty influential studies across managerial cognition, behavioral strategy, institutional theory, and technology adoption were identified, screened, and synthesized. Their insights were integrated into a multilayered conceptual model explaining how mindset shapes AI adoption in …

Operationalizing Supply-Chain Hygiene In Graduate Is Education: A Hands-On Module For Secure Software And Ai/Ml Pipelines, Dominic A. Wilson

Journal of Cybersecurity Education, Research and Practice

Supply-chain attacks (including typosquatting, dependency confusion, compromised builds, dataset poisoning, and backdoored models) pose growing threats to analytics platforms central to Information Systems (IS). While frameworks like the Secure Software Development Framework (SSDF) and Supply-chain Levels for Software Artifacts (SLSA) offer guidance, IS curricula often lack accessible, infrastructure-light modules that build practical skills for mitigating these risks. This experience report presents a two-week module embedded in a graduate Secure Coding course required for a Master’s in Applied Security and Analytics degree. The module operationalizes secure development habits across both traditional software and machine learning (ML) pipelines. The module addresses a …

The Nist Artificial Intelligence Risk Management Framework: Adoption Challenges And Opportunities, Gillian Kennedy, Devin Patel, Humza Sheikh, Paul Wagner, Robert J. Honomichl

Journal of Cybersecurity Education, Research and Practice

Artificial intelligence (AI) is being adopted at an exponential rate to improve efficiency, decision-making, and cybersecurity, but its rapid integration introduces new and often poorly understood risks, including system errors, algorithmic bias, data privacy concerns, security vulnerabilities, and ethical dilemmas. This paper examines how organizations are implementing AI and evaluates the National Institute of Standards and Technology's AI Risk Management Framework (NIST AI RMF) as a tool for managing these risks. It reviews the benefits of AI adoption alongside the risks emerging from its use in business and broader society and examines the legal and ethical challenges organizations face when …

To What Extent Could Quantum Computing Pose A Threat To Global Modern Data Security?, Aniket Maheshwari

Journal of Cybersecurity Education, Research and Practice

Quantum computing has emerged as a transformative technology with the potential to fundamentally disrupt modern cryptographic systems that underpin global data security. This paper examines the extent to which quantum computing could pose a threat to modern global data security by synthesising existing technical, institutional, and policy-oriented literature. Drawing on a narrative review of scholarly research, industry reports, and government frameworks, the analysis focuses on the implications of quantum algorithms such as Shor’s and Grover’s, which challenge the mathematical foundations of widely used cryptographic schemes. The findings suggest that while quantum computing presents a credible long-term threat to asymmetric encryption …

Wearable Technology For Depression Assessment: A Scoping Review Of Datasets, Ml Tlachac, Hayley K. Elsbree, Michael V. Heinz

Information Systems and Analytics Department Faculty Journal Articles

As wearable technology continues to develop, wearable devices are becoming more common and being increasingly used to collect datasets for depression assessment. Documenting the collection procedures, recruitment strategies, and demographics of these datasets is important to allow for synthesis across the datasets and uncover common limitations. As such, in this scoping review, we identify 80 observational datasets collected by wearable devices through the start of 2025 that can be used for depression assessment. Of the 80 datasets, 50% used an actigraph and 47.5% used other wristbands. These wearable devices were used to collect activity, sleep, and heart rate for 87.5%, …

Cyber-Ready Libraries, Building Digital Fortresses For Tomorrow, Adeyinka B. Tella, Oluchi Precious Ogbonna Dr, Adebola Aderemi Olatoye Mrs

Journal of Cybersecurity Education, Research and Practice

Background and Purpose: Libraries are evolving into highly networked information ecosystems in this age of fast digital transformation, which increases their susceptibility to cybersecurity risks. The study "Cyber-Ready Libraries: Building Digital Fortresses for Tomorrow" looks into how prepared libraries are to face cyber threats and considers methods for creating information systems that are safe, robust, and ready for the future. To safeguard digital assets and user data, the study aims to assess existing cybersecurity practices in library settings and offer a roadmap for combining technological, human, and governance solutions.

Design/Method: The existing literature, case studies, and policy frameworks pertaining …

The Intersection Between Mindfulness And Cybersecurity: A Tool To Reduce Burnout And Improve Operational Effectiveness, Ivo Ricardo Dias Rosa

Journal of Cybersecurity Education, Research and Practice

Abstract: This paper offers a conceptual discussion of how mindfulness, understood as present moment awareness and deliberate attention regulation, can support cybersecurity professionals. Drawing on a narrative synthesis of workplace mindfulness, burnout, and high pressure decision making literature, we map plausible self regulation mechanisms to typical cyber defense tasks. Rather than presenting new empirical data, we develop an explanatory framework linking attention, reactivity, and recovery to decision quality, team communication, and adherence to incident playbooks. We focus on two connected outcomes: reducing burnout in roles with sustained cognitive and emotional demands, and improving operational effectiveness during critical situations such as …

Predicting Cybermindfulness With The Cyber-Health Belief Model, James Robinson, Yan Tian, Thomas Skill

Journal of Cybersecurity Education, Research and Practice

This study describes the development of a Cyber-Health Belief Model (CHBM). The health belief model (HBM) is a message strategy that is widely and successfully used in public health research [1] and has been extended into phish training. Most phish training programs assume  end users are victimized because they have insufficient information to defend themselves. While near-term training effectiveness has shown to be effective, evidence for sustained behavioral change is thin [4]-[7].  This problem indicates that the traditional approaches need to be reconsidered and that new models are needed.  Recent research suggests attentional deficits, cyber-fatigue and fatalism and a sense …

Next-Generation Dns Rpz For Automated Threat Intelligence, Risk-Aware Filtering, And User-Centric Security, Jinu S, Kishore V. Krishnan, Rajarshi Middya, Annasamy Bagubali

Journal of Cybersecurity Education, Research and Practice

The Domain Name System (DNS) remains a critical attack vector exploited by adversaries for command-and-control (C2) communication, data exfiltration, and phishing campaigns. DNS Response Policy Zones (RPZ) have emerged as an effective defense mechanism by enabling the redirection or blocking of queries to malicious domains. However, current RPZ implementations encounter significant challenges related to scalability, adaptability, and user awareness, often resulting in static policies, delayed updates, and a high incidence of false positives. To address these limitations, this paper proposes an enhanced RPZ framework that integrates adaptive threat intelligence, machine learning-driven dynamic policy updates, and user-context-aware security controls. The proposed …

Trends In Non-Profit Cybersecurity: Analyzing Three Years Of Incident Data From The Npcir, Stanley Mierzwa, Joanna Paliszkiewicz, Edyta Skarzyńska

Center for Cybersecurity

This study analyzes cyberattack trends targeting non-profit organizations using longitudinal data collected over a three-year period within the Non-Profit Cybersecurity Incident Repository (NPCIR). Developed through a National Security Agency Center of Academic Excellence in Cyber Defense (NSA CAE-CD) designated center, the NPCIR applies an open-source intelligence (OSINT) methodology to systematically document cybersecurity incidents affecting the global non-profit sector. This study examines attack types, threat actor characteristics, sectoral distribution, and cybersecurity impacts using the Confidentiality–Integrity–Availability (CIA) triad framework. The results indicate that availability-related incidents, particularly ransomware and distributed denial-of-service (DDoS) attacks, constitute the most prevalent threats, while confidentiality breaches remain highly …

Trust And Pre-Employment Background Checks When Onboarding And Maintaining Information Security And Cybersecurity Staff, Stanley Mierzwa

Center for Cybersecurity

The realm of trust is broad and can include many facets that are difficult to capture and catalog. In relation to the work roles of information security and cybersecurity, the intersection of trust in human resource management is critical and an evolving area within most modern organizations, in almost any sector, and of any size. A foundational element of trust is fundamental to effective mission and work roles in information security and cybersecurity, as well as to every employee tasked with contributing to the security of an organization’s assets. This chapter will include sections on the role trust can and …

Technology Disruptions In Platform Ecosystems: Ai, Market Adaptation, And Digital Resignation, Eunah Cho

Dissertations, Theses, and Capstone Projects

This dissertation examines how technological disruptions reshape behavior, competition, and user response in platform ecosystems. Bringing together two studies of generative AI in digital labor market and one study of mandatory privacy disclosure in mobile app ecosystems, it argues that platform technologies do not affect participants uniformly. Instead, their effects are mediated by market structures, competitive dynamics, and platform dependence.

The first study shows that ChatGPT shifts workers’ human capital strategies by reducing investment in specialized depth while increasing skill diversity, revealing a move from exploitation toward exploration. Yet market rewards remain uneven, as workers who integrate AI with deep …

Ai-Augmented Financial Advisors: Comparing Ai And Human Analyst Investment Recommendations In Agreement, Performance, And Firm Size Effects, Crystal Chen

Honors College Theses

This study examines the level of agreement and performance between artificial intelligence (AI) generated investment recommendations and human analyst recommendations across U.S. publicly traded firms. Using a sample of twelve companies categorized by firm size (large, mid, and small), the study collects buy, hold, or sell recommendations from generative AI systems and human analysts. Agreement between AI-to-AI and AI-to-human recommendations is measured using Cohen’s Kappa agreement. Portfolio performance is evaluated by constructing equal-weighted portfolios for each recommendation source and size category. Risk-adjusted returns are measured using the Sharpe ratio over 1-, 2-, and 3-month periods. Furthermore, the study tests whether …

Determinants Of Public Trust In E-Government: A Comprehensive Review And Conceptual Framework Over The Past Decade, Andrean Nathaniel, Sumartono Sumartono, Abd. Qadir Muslim

BISNIS & BIROKRASI: Jurnal Ilmu Administrasi dan Organisasi

The evolution of digital governance has heightened the strategic significance of public trust in the implementation of e-government. Despite numerous empirical investigations, the results concerning the factors influencing trust remain fragmented and largely centered on technological aspects. This study seeks to systematically identify, categorize, and synthesize the determinants of trust in e-government through a structured literature review of 21 Scopus-indexed articles published between 2015 and 2025. Utilizing an evidence-based synthesis methodology, the study organizes determinants of trust into four main categories: citizen-related, technological, institutional, and risk-related factors. The findings indicate that technological and citizen-related factors are the most significant predictors …

A Govsecops-Oriented Governance, Risk, And Compliance Platform For Continuous Authorization In Dod Il4/Il5 Environments, Anand Janjal

Journal of Cybersecurity Education, Research and Practice

Department of Defense (DoD) Impact Level 4 and Impact Level 5 (IL4/IL5) systems require continuous assurance of cybersecurity posture under stringent operational and regulatory constraints. While the NIST Risk Management Framework (RMF) and DoD DevSecOps guidance emphasize continuous authorization supported by real-time evidence, many existing Governance, Risk, and Compliance (GRC) platforms remain documentation-centric and insufficiently integrated with operational telemetry. This paper presents a GovSecOps-oriented GRC architecture that integrates vulnerability ingestion, automated Plan of Action and Milestones (POA&M) lifecycle management, dynamic risk scoring, and continuous authorization dashboards within IL4/IL5 environments. Using a Design Science Research methodology, the study develops and evaluates …

A Practical Leadership Guide For Student Organization President And Officers, Adrian Hernandez

Honors Capstones

This capstone project focuses on the development of a leadership playbook designed to support student organization leaders through practical guidance, organizational strategies, and leadership systems grounded in real experiences. The project was inspired by my experience serving as President of Pi Sigma Epsilon and the leadership challenges commonly faced within student organizations. Throughout my time in leadership, I observed how communication, structure, accountability, and organizational culture directly impacted the success and sustainability of organizations. These experiences motivated the creation of a resource that could help future student leaders navigate leadership responsibilities more effectively while building stronger and more sustainable organizations. …

Large Language Models As A Detector For Political Deepfakes, Gracie L. Roberts

Honors Theses

The advancement of generative artificial intelligence has allowed for the creation of highly realistic political deepfakes, posing significant threats to democratic integrity and trust in governmental institutions. This study investigates the effectiveness of Large Language Models (LLMs) as detectors for political deepfakes, specifically exploring their ability to address the transferability, interpretability, and robustness limitations inherent in traditional detection systems.

The research was conducted in four steps including data collection, model selection, experimental testing, and evaluation. Two datasets were used in this study. The first dataset uses 833 fake images from the Political Deepfake Incidents Database (PDID) and 833 real images …

Small Businesses: A Comprehensive Investigation Into Data Quality's Impact On Security, Privacy, And Governance, Deveeshree Nayak

Theses and Dissertations

This dissertation investigates the extent to which deficiencies in data quality, specifically accuracy, completeness, consistency, timeliness, validity, and uniqueness, undermine data security, privacy compliance, and governance effectiveness in small businesses (fewer than 200 employees and annual revenues under $10 million) in Washington State. Although data are increasingly viewed as a strategic asset, empirical research on how poor data quality amplifies cyber risks and regulatory exposure in resource-constrained environments remains limited. A convergent mixed-methods design was employed. A purposive survey captured practitioner perceptions from nine small-business professionals regarding the impact of data quality on security (CIA triad), privacy (accuracy and transparency …

Examining Data Quality Management Practices In Light Of The Adoption Of Llms And Genai: Closing The Gap Between Iq Theory And Iq Practice, Venant Habamungu

Theses and Dissertations

The rapid adoption of Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) has intensified longstanding data quality concerns while exposing important gaps in current Data Quality Management (DQM) practice. This dissertation examines whether widely used DQM frameworks sufficiently address semantic data quality dimensions that are critical for trustworthy GenAI and LLM applications. Guided by Information Quality (IQ) theory, particularly the Wang and Strong conceptualization of data quality, the study evaluates selected DQM frameworks used in practice to determine the extent to which they emphasize semantic dimensions such as accuracy, value-added, relevancy, objectivity, reputation, believability, security, and appropriate amount of …

Digital Transformation And Adaptive Capacity Of Banks In Tanzania: The Mediating Effect Of Knowledge Sharing, Sospeter Muchunguzi, Ulingeta O. L. Mbamba, Victor G. Wilson

Business Management Review

Amid rising competition and uncertainty, banks are increasingly adopting digital technologies to sustain adaptive capacity and competitiveness. This study examines the mediating effect of knowledge sharing in the influence of digital transformation on adaptive capacity. Drawing on an integrative theoretical framework combining the Dynamic Capability Theory, the Affordance Theory and the Adaptive Structuration Theory, a deductive approach was used, involving a sample size of forty-three (43) banks in Tanzania. Data were collected using a questionnaire administered through a drop-off and pick-up-later method and analyzed with PLS-SEM using SmartPLS software. We found that digital transformation of customer touchpoints makes banks more …