Management Information Systems Commons^™

The Impact Of Value Homophily, Rational And Emotional Persuasion On Information Passing Of Social Media Advertisements: A Model Comparison Approach, Gloria Hui Wen Liu, Cecil Eng Huang Chua, Neil Chueh An Lee, Jenny Hua Jen Wu

Business and Information Technology Faculty Research & Creative Works

Increasingly, businesses collaborate with influencers and content creators (the source) to advertise on social media, with social media users being exposed to an environment saturated with unsolicited advertisements. With social contacts remaining the most trusted advertisement sources, users' passing of such advertisements helps their dissemination and creates a specific kind of electronic word of mouth called information passing. Information passing involves users forwarding advertisements about products/services to someone else. Prior studies have found at least three factors influence information passing, including value homophily (similarity with the source as perceived by users), rational appeal (information about how a product can meet …

From Ai Ethics To Ethical Misalignment: Understanding Emerging Risks In Agentic Ai Systems, Deb Tech, Aravindh Sekar

Research & Publications

The emergence of Agentic AI systems is reshaping organizational processes through continuous adaptation, autonomous coordination, and real-time operational execution. Unlike traditional artificial intelligence applications focused on discrete decision-making tasks, Agentic AI systems operate continuously and interact dynamically with organizational environments. Existing AI ethics literature has primarily emphasized issues such as fairness, bias, transparency, and accountability within static or decision-centric AI contexts. Similarly, traditional AI alignment research has largely focused on ensuring that AI systems pursue intended goals and remain controllable under specified operational conditions. However, these approaches may be insufficient for explaining how ethical risks evolve with continuously operating autonomous …

Enhancing Hospital Length Of Stay Using Ai Agent Modular Capabilities, Dami Fred

Theses and Dissertations

Hospital Length of Stay (LOS) analysis is essential for managing hospital efficiency and financial performance, yet the analytical depth required remains inaccessible to many organizations due to technical and resource constraints. This thesis introduces the AI Agent Modular Capabilities (AIAM) framework, which decomposes LOS analysis into discrete, codifiable capabilities integrated into a single skill activatable with one prompt. Seven AI Agent Modular Capabilities were developed using a Work Breakdown Structure and tested against a simulated hospital scenario across three successive skill versions. Results demonstrate that the packaged AIAM skill produces comprehensive, consistent, multi-section LOS analyses from a single interaction, outperforming …

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 …

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 …

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 …

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 2020 - Present

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 …

Towards Resilient Data Governance: An Industry Study On Practitioner Perspectives On The Current State Of Data Governance, Anthony Mazzarella Iii

Theses and Dissertations

Experts agree that data governance is crucial for managing data as an asset, yet in practice, it remains inconsistently defined, unevenly implemented, and poorly understood. Earlier industry studies offered valuable descriptive benchmarks of governance adoption and professional roles, but provided limited theoretical insight and little empirical evidence explaining how governance functions within organizations. Building on this foundation, the current research offers a more substantial and analytically rigorous contribution by transforming descriptive observations into empirical explanations. Through a collaborative academic–industry partnership, the study utilizes a global survey of 565 respondents (348 valid cases) to analyze governance structures, motivations, challenges, and the …

Feedback Strategies In The Market With Uncertainties, Mustapha Nyenye Issah

Graduate Theses and Dissertations (2019 - present)

This paper explores how established firms use strategic advertising to deter new competitors in uncertain markets. Specifically, it models a situation where market demand evolves unpredictably - captured by the CKLS stochastic process, and the incumbent firm may be either strong or weak, a fact hidden from potential entrants. For a company already in the market, advertising is not just about driving immediate sales, it is a strategic tool to project an image of strength and deter potential new competitors. On the other side, a business thinking about entering that market faces a high-stakes, irreversible decision. It will typically hold …

A Study Of Configuration Management Database (Cmdb) Adoption In It Service Management (Itsm) Implementations Within Nj Community Colleges, Fredrick Dande

All-Inclusive List of Electronic Theses and Dissertations

This study examines the adoption of Configuration Management Databases (CMDBs) in IT Service Management (ITSM) implementations within New Jersey (NJ) community colleges. Despite the well-documented benefits of CMDBs—such as faster issue resolution, improved compliance, and greater visibility across IT infrastructures—implementation success rates remain low. As technology continues to enhance production capabilities and expand access to information, the need for centralized configuration visibility has become critical. A CMDB provides a single system of record for IT assets and services, helping organizations manage outages, assess changes, maintain compliance, and improve asset tracking. This research used an online survey to collect data from …

An Active Learning Simulation For Teaching Hadoop In An Undergraduate Business Curriculum, Ruben A. Mendoza Ph.D., Liyuan Liu Ph.D.

International Journal for Business Education

This paper shows the effectiveness of an experiential learning activity for teaching core Hadoop concepts to undergraduate business students across all majors (Finance, Marketing, etc.). The complexity of Hadoop, with its distributed computing model and deep technical requirements, presents significant challenges in educational settings. The simulation was developed for an introductory course in a Business Intelligence & Analytics (BI&A) curriculum and adapted for use in a Database Management (DB) course. Results show significantly higher performance on questions centered on the topic in an online test preparation game with a total of 236 students in 11 different offerings of the course. …

Does Employees’ Meaningfulness Of Work Mediate The Link Between Their Cognitive Diversity And Creative Process Engagement?, Mohammad Tamzid Hossain, Sabrin Sultana, Salma Begum, Md. Sahidur Rahman, Md. Aftab Uddin

Management Dynamics

This study aims to investigate how employees' cognitive diversity affects their creative process engagement, with a focus on the role of their meaningfulness of work as a mediator in this connection. A survey was used with a quantitative method to collect responses from 207 employees of small, medium, and large service and manufacturing businesses in Bangladesh that were registered with the Chittagong Chamber of Commerce and Industry. The collected data were then analyzed using Smart PLS 4 to evaluate the hypotheses and examine the mediating effect of the study. The findings reveal that employees’ cognitive diversity has a significant impact …

Shaping Smarter Supply Chains With Robotics And Automation, Daniel Delucio

Honors Projects

The purpose of this study is to analyze how companies operate their logistics processes from the procurement of raw materials to the delivery of the final product to customers. By examining current methodologies, the study identifies best practices, emerging trends, and challenges shaping modern supply chain management. Specifically, this research investigates how artificial intelligence (AI), robotics, and automation can be integrated to improve efficiency, transparency, and resilience.

From Prompt To Prejudice: Visual Evidence From Ai Image Generation Platforms, Jinu K. Varghese, Padma Rani

Markets, Globalization & Development Review

This study examines how AI image generation systems perpetuate digital orientalism through systematic cultural representation patterns that increasingly shape global digital markets and international development discourse. Using visual social semiotics methodology, we conducted comparative analysis of Midjourney and ChatGPT platforms across nine culturally specific prompts examining religious imagery, contemporary social dynamics, and power structures in Indian cultural contexts. Our findings reveal that both platforms consistently reproduce colonial-era representational frameworks despite culturally sensitive prompting and advanced technical capabilities. The analysis identifies three systematic patterns: temporal displacement strategies that acknowledge modernity while containing it within orientalist categories, institutional validation requirements that privilege …

Social Media Marketing And Business Performance Of Small And Medium Fashion Enterprises In Tanzania: The Moderating Role Of Social Media Strategic Capabilities, Pamela Kishimbo, Juma James Masele, Dev Jani

Business Management Review

This study examines the influence of social media marketing (SMM) on the business performance of small and medium fashion enterprises (SMFEs) in Tanzania, with social media strategic capabilities (SMSCs) as a moderating variable in this relationship. The study is grounded in the Uses and Gratification Theory (UGT) and Resource-Based View (RBV). The study used a cross-sectional survey design, collecting data from 397 SMFEs through structured questionnaires. Data were analysed using descriptive statistics and structural equation modelling (SEM). The findings revealed a significant positive relationship between SMM and the business performance of SMFEs in Tanzania. Furthermore, the findings show that SMSCs …

Software-Defined Networking Powered By Ai-Driven Anomaly Detection, Dina Moloja, Vusumuzi Malele Prof

Journal of Cybersecurity Education, Research and Practice

Software Defined Networking (SDN) revolutionizes network control by separating the control plane from the data plane. Although the latter improves SDN agility and scalability, it creates a security hole, particularly in a central control plane, leading to SDN environments becoming high-profile targets for advanced cybersecurity threats. Due to static and signature-based point-in-time behavior, traditional security methods are unable to keep up with modern attacks that are an anomaly to SDNs. Artificial Intelligence (AI) with its different applications and techniques, has the capability of detecting SDN cyber threats’ anomalies. This paper presents the results of a literature scoping exercise that used …

Evolution Of A New Strategic Orientation In The Ai Era: Exploring The Determinants Of Ai Orientation, Sreelakshmy Geethakumari

Dissertations

The field of AI has undergone significant evolution over the past few decades. While AI is heralded as one of the most transformative technologies, scholars caution that its strategic impact may still not be fully realized. Given the strategic importance of AI in today's firms, it is essential to consider AI as a strategic orientation and understand its determinants in detail. Our study examines AI Orientation, defined as a firm's deliberate application of AI technologies to achieve its strategic objectives. Drawing on multiple theoretical perspectives, this study investigates the determinants that shape a firm’s AI orientation. This study employs a …

From The Editors, Rully Karim Dr.

Journal of Project Management & Construction

The Journal of Project Management and Construction (JPMC) is a peer-reviewed publication dedicated to advancing the field of project management and construction, grounded in the principles outlined in the PMBOK 6th Edition. Our focus encompasses the ten knowledge areas essential to successful project management: Integration, Scope, Schedule, Cost, Quality, Resource, Communications, Risk, Procurement, and Stakeholder Management.

JPMC publishes original research papers written in English that provide deeper insights into these knowledge areas and contribute to the development of best practices in project management and construction. Submissions may include theoretical analyses, computational models, experimental observations, or a combination of both theoretical …