Management Information Systems Commons^™

Proof Of Recovery: A Model To Enhance Data Integrity In Data Management Systems, Gustaf Barkstrom

Theses and Dissertations

Businesses lose millions of dollars every year when they can’t restore data from backups. Research shows that Disaster Recovery Plan (DRP) testing is not conducted frequently enough, nor are records maintained that demonstrate full data recovery from backups. This work introduces a design science artifact called PRTOK that aims to increase DRP testing. The design science artifact is a software solution that integrates with Data Management Systems (DMS)

such as iRODS and DSpace, and can work with formats such as HDF5 and BagIt. Proof-of- recovery records, or tokens, are recorded in a replicated, resilient, and indelible proof-of- authority blockchain data …

The Soft Target Curriculum: Using Nigeria's 2026 Cascading Breaches To Teach Foundational Cybersecurity Failures, Chinedum Amaechi, Doris Asogwa, Samuel Alade

Journal of Cybersecurity Education, Research and Practice

SourceURL:file:///home/amaechi/Documents/ *Journal of Cybersecurity Education, Research and Practice (JCERP)*. **Title:** The Soft Target Curriculum: Using Nigeria's 2026 Cascading Breaches to Teach Foundational Cybersecurity Failures.docx

Background: Between March and April 2026, a single threat actor allegedly compromised four Nigerian institutions across banking, payment infrastructure, government registry, and power distribution sectors. The breaches exposed millions of records and disrupted critical services, yet all four exploited elementary vulnerabilities taught in introductory cybersecurity courses. Objective: This pedagogical case study analyzes the four breaches as a unified phenomenon of "normalized negligence" and provides ready-to-use teaching materials for cybersecurity educators. Methods: Using open-source intelligence analysis of …

Developing A System Dynamics Framework For Sustained Digital Transformation, Quintal Battle

Graduate Studies Theses and Dissertations 2026

Despite significant organizational investments, more than 70% (Ellmer et al., 2025) of digital transformation initiatives fail. The existing literature evaluates transformation mechanisms as separate factors rather than as interacting, evolving feedback systems. This dissertation addresses this gap by developing and validating a system dynamics framework for sustained digital transformation. Guided by three research questions, the study examined the mechanisms that enable or constrain transformation, identified mechanisms distinctive to digital transformation contexts, and evaluated how existing change management frameworks guide transformation efforts. The study followed a six-phase methodology that combined a systematic literature review of peer-reviewed studies, empirical cases, causal loop …

Two Studies Exploring Signal-Environment Fit In Ai-Assisted Managerial Decision-Making Under Uncertainty, Oleksandr Kondrachuk

Graduate Studies Theses and Dissertations 2026

This dissertation examines how the fit between the characteristics of artificial intelligence systems and the uncertainty environment shapes managerial reliance on AI advice. Organizations increasingly deploy different AI systems, such as predictive and generative, to support management accounting decisions. However, the accounting literature has mainly treated AI as a single undifferentiated entity. This dissertation addresses this gap through two related studies. In the first study, drawing on signaling theory and ecological rationality, I develop a signal-environment fit framework proposing that the reliance on a certain AI system depends on the match between system characteristics (input, process, output) and uncertainty characteristics. …

Cultivating Workplace Happiness In Technology Workers, Cherie A. Herrin

Graduate Studies Theses and Dissertations 2026

Technology workers are central to the innovation and performance of modern organizations and retaining them is a persistent challenge for modern organizations. One important aspect of retention in many contexts is Workplace Happiness, which has been argued to improve worker performance and reduce turnover; however, there is little empirical evidence of the effectiveness of these interventions for technology workers. This dissertation develops a model in which two affective states, Workplace Happiness and Workplace Distress, mediate the relationships between six socio-technical work conditions and two behavioral outcomes: Turnover Intent and Work Execution (i.e., self-rated work performance and quality). A systematic literature …

Bridging Mission And Execution: Integrating Participatory Design In Early-Phase Mission Engineering For Stakeholder Alignment And Mission Clarity, Rafi Soule

Knowledge and Creativity Expo

This research examines mission framing during the early phase of Mission Engineering. Stakeholder interpretations diverge under ambiguity. Interoperability constraints are often not surfaced early. These conditions reduce mission clarity and weaken mission-to-system mapping readiness. The study integrates a participatory design-inspired, artifact-first workflow with RAG-enabled retrieval from a closed corpus to support evidence-grounded reasoning and traceable citations.

Phase 1 uses an online survey to establish baseline patterns in practice (N = 86). Shared understanding is positively associated with mission clarity (r = 0.60, p < 0.001). Phase 2 uses a time-bounded comparative workshop with two conditions. Expert reviewers rate mission statement quality higher for the participatory design condition (mean 3.5) than the traditional condition (mean 2.8). Technical feasibility ratings are similar across conditions. Phase 3 demonstrates RAG-enabled, closed-corpus, retrieval-supported traceability using the Referencer tool. It is reported as a proof-of-concept for evidence-grounded rationale and auditability, and as a pathway …

Too Warm To Win Big? Unpacking The Backer Dynamics Behind Female Crowdfunding Success Using A Warmth And Competence Perspective, Dan Liu

Journal of International Technology and Information Management

While crowdfunding is often heralded as a democratized funding avenue that empowers women with higher success rates, this study reveals a more nuanced picture of gender dynamics. The Stereotype Content Model suggests that women are often perceived as warmer but less competent. Using a large dataset from Kickstarter, we find that female-led projects can attract more backers, likely due to warmth-driven appeal, but receive smaller average contributions, potentially due to concerns about risk linked to lower perceived competence. However, the total funding raised by female-led campaigns is comparable to that of male-led ones, showing no clear advantage or disadvantage. This …

Online Community Dynamics: An Analysis Using Louvain During Major Sporting Events, Anushka Jaint, Yashodhan Karulkar, Kashish Jindal, Sri Sai Harshita Gadavarthi, Sanya Gulati

Journal of International Technology and Information Management

With the power of social media transforming the way people connect and interact with each other, the dynamics of community formation on platforms such as X during major events are of crucial importance. While social media is an increasingly key driver in determining interactions, little is known about the online influence forming and developing fan communities in high-stakes events. This study looks into the development of user communities for datasets drawn from Kaggle on two of the world’s largest sporting events: the FIFA World Cup 2022, or football, and the T20 World Cup 2022, or cricket, with the aim of …

Early Stem Impressions, Student Engagement, And Readiness For Digitalization, Myron Sheu

Journal of International Technology and Information Management

This study examines how early impressions of science, technology, engineering, and mathematics (STEM) shape business students’ learning behaviors and, ultimately, their readiness for organizational digitalization. Focusing on gender differences, subgroup identities, and perceived obstacles, the analysis uses survey data processed through correlation matrices, regression models, and subgroup heatmaps to trace the relationship between initial attitudes toward STEM and subsequent engagement patterns. The findings reveal consistent links between positive early impressions and active participation in structured STEM activities, along with gender-based distinctions in action preferences. Subgroup analyses further uncover nuanced patterns where stereotypes or perceived barriers correspond with reduced engagement. Collectively, …

The Crowdfunding Paradox In Crisis: Rising Funder Demand Vs. Declining Entrepreneur Supply, Dan Liu, Guangzhi Shang, Cynthia Fan Yang

Journal of International Technology and Information Management

This study investigates how the crowdfunding marketplace responds to major crises, focusing on behavioral shifts among funders and entrepreneurs. Results show a dual impact on platform dynamics. On the demand side, funders become more engaged, with notable increases in the number of backers, average contributions, and total pledge amounts. This heightened activity suggests stronger altruistic motivations, as individuals view crowdfunding as a way to support others during difficult times. On the supply side, however, entrepreneurs act more cautiously, leading to a decline in new project launches. This drop likely reflects increased risk aversion and uncertainty as creators navigate volatile conditions. …

The Role Of Ict In Enhancing National Logistics Performance And Economic Productivity, Jin Ho Kim

Journal of International Technology and Information Management

This study sheds light on the transformative impact of Information and Communication Technology (ICT) on national productivity via logistics performance. By distinguishing between mobile and wired Internet speeds, the research demonstrates how these technologies influence logistics performance and, in turn, national productivity across different economic contexts. The findings reveal a nuanced relationship between ICT and logistics performance, with mobile ICT playing a more significant role in developing countries due to its accessibility and cost-effectiveness. In contrast, developed countries benefit from a balanced integration of both mobile and wired ICT. Moreover, the study highlights the mediating role of logistics performance in …

Blockchain As A Digital Coordination Infrastructure For Project Management: A Systematic Review And Integrative Framework, Cherie Bakker Noteboom, Sai Neelima Seru, Aravindh Sekar

Journal of International Technology and Information Management

Blockchain technology has gained increasing attention as a digital infrastructure capable of improving transparency, trust, and coordination in complex, multi-organizational project environments. However, existing research on blockchain-enabled project management remains fragmented and industry-focused, providing limited guidance for organizational adoption and integration. This study addresses this gap through a systematic literature review of 29 peer-reviewed studies, following PRISMA guidelines, to examine how blockchain capabilities are incorporated into project management practices across industries and maturity stages.

Grounded in Resource-Based View and Coordination Theory, the analysis employs a feature-to-process mapping approach to link six core blockchain capabilities—decentralization, transparency, immutability, smart contracts, traceability, and …

The Value Of Personal Data Ecosystems: A Flemish Media Sector Case Study, Maarten De Mildt, Melanie Verstraete, Sofie Verbrugge, Didier Colle

Journal of International Technology and Information Management

Personal Data Stores (PDSs) have been proposed as a privacy-preserving approach to data sharing that increases individual control over personal data while enabling new forms of cross-organizational collaboration. This collaboration leads to the emergence of Personal Data Ecosystems (PDEs). Despite growing interest in PDEs, limited research has examined how the organizational and economic barriers identified in prior studies manifest in practice. This paper investigates these challenges through a case study of the Flemish media sector within the Solid4Media project, which explores the use of PDSs to support data sharing and personalization across media organizations. Using a qualitative research design, data …

Responsible People Analytics For Remote-Work Decisions: A Machine-Learning Benchmark For Classifying Perceived Productivity, Ruth Menjivar, Nima Molavi, Narges Mashhadi Nejad

Journal of International Technology and Information Management

This study examines whether employee-perception survey data can support responsible people-analytics decisions about remote-work productivity. Using the public New South Wales (NSW) Remote Working Survey 2021 (N=1,512), the study benchmarks statistical and machine-learning classifiers for self-reported perceived productivity classes (same, less, or more productive when working remotely relative to onsite work), not objective output, under default, class-weighted, and resampling protocols. Main evidence comes from 5×5 repeated stratified cross-validation using macro F1 and balanced accuracy with fixed model specifications. Class-balanced separability is modest. Random Forest, CatBoost, and LightGBM form a leading cluster with overlapping confidence intervals (macro F1 ≈0.51–0.52). Affective/well-being items, …

Towards Developing A Career Technology Fit Framework And Analyzing Its Influence On Work-Related Outcomes Among It Professionals, Gunjan Tomer

Journal of International Technology and Information Management

With growing attrition rate and significant demand for skilled IT professionals, the importance of studying their behaviour has become important for both academia and industry. Despite ample amount of research, there is still a gap between theory and practice. Based on our qualitative study conducted on Indian IT professionals we propose that technology allocation might contribute in understanding the behaviour of IT professionals. We found that IT professionals evaluate the technology allocated to them based on their individual career motives. This evaluation, either positive or negative, influences their job outcomes. Further, we explored the factors that make a technology preferable …

Advancing Cybersecurity Practice: Explainable Machine Learning For Network Intrusion Detection, Adam Grabowski, Shengjie Xu

Journal of Cybersecurity Education, Research and Practice

This research investigates explainable artificial intelligence (XAI) integration within machine learning (ML)-based intrusion detection systems (IDS), focusing on distinguishing malicious from benign network activities. We employed Random Forest and XGBoost models evaluated on widely recognized datasets, including NSL-KDD and UNSW-NB15, using both binary and multi-class classification tasks. The objective was to enhance cybersecurity operations through improved model transparency and interpretability. By integrating SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-Agnostic Explanations), the study offers comprehensive global and local insights into model decision-making processes. Results demonstrate SHAP's effectiveness in providing a broad, dataset-wide understanding of feature interactions and importance, while …

Using It And Accounting Education Pedagogy To Address Smaller Firms' Cybersecurity Concerns, Darlene A. Adkins, William Lyle, Walter Smith

The North American Accounting Studies

This study begins by exploring the cybersecurity activities and practices of small public accounting firms. It also examined how a cross-disciplinary curriculum design could be useful to accounting programs that are challenged to integrate cybersecurity-related content while preserving the core accounting knowledge valued by smaller accounting firms. Through interviews with current practitioners from small and regional firms, the research investigated the extent to which cybersecurity concerns impact their practice, how cybersecurity activities are staffed, and the perceptions of current practitioners on the state of accounting education related to information technology (IT) and cybersecurity. The participants expressed a desire for accounting …

Forecasting Aviation Carbon Emissions With Tree-Based Machine Learning: A Case Study Of Turkish Airlines Operational Data, Demet Dağlı Phd, Ednan Ayvaz Phd

International Journal of Aviation, Aeronautics, and Aerospace

The global aviation industry plays a critical role in economic development and international connectivity. However, it also contributes significantly to environmental challenges, particularly through fuel consumption and carbon emissions. The aviation sector is responsible for approximately 1–2% of global CO₂ emissions, and its environmental impact is expected to increase substantially by 2050. This study proposes a machine learning (ML)-based decision support framework to forecast carbon emissions in the airline sector. Using Turkish Airlines’ quarterly operational data from 2008 to 2023, Decision Trees, Random Forest, XGBoost, and Extra Trees models were applied to predict carbon emissions. Key variables include revenue passenger …

Exploring The Impact Of Negative Ewom On Hotel Booking Intention Through The Lens Of Attribution Theory And The Moderating Role Of Recovery Justice, Antonio Jose Ogaz-Muñoz

Electronic Theses and Dissertations

Negative electronic word-of-mouth (EWOM) has emerged as a critical factor influencing customer behavior, particularly in the hospitality industry. Despite extensive research grounded in failure attributions and service recovery theories, few studies examine the combined impact of failure attribution and recovery justice on hotel booking intentions. Using a 2x2x2x2 between-subjects experimental design with 373 responses, this research investigates how customers' perceptions of failure attribution influence their booking intention after exposure to negative EWOM, and if perceived recovery justice can mitigate the negative effects of these attributions. Results show that booking intention declined most when reviews framed the failure as hotel-caused and …

Probabilistic Deep Learning For Traffic Density Prediction, Pedro Cesar Lopes Gerum, Andrew Reed Benton, Melike Baykal-Gursoy

Business Faculty Publications

Real time, accurate predictions of recurrent and nonrecurrent traffic congestion are essential for optimizing transportation systems and ensuring a smooth user experience. Traditional models often focus on long-term point estimates, limiting their use in scenarios requiring short-term predictions or probabilistic assessments (e.g., traffic signal optimization, dynamic tolling, and emergency response). This study explores probabilistic deep learning (DL) for real time traffic density distribution prediction. This study demonstrates that an adapted multi-quantile recurrent neural network (MQRNN), termed MQRNN-monotonic, outperforms traditional time series methods, particularly when handling nonrecurrent disruptions. A novel loss function is introduced to address quantile crossing issues, ensuring valid …