Business Analytics Commons^™

Data Utilization In Facilities’ Performance Management Decision- Making At U.S. Four-Year Public Institutions: A Cross-Sectional Exploratory Study, Tanaporn Supanichrattana

Theses and Dissertations

The growing complexity of higher education finance, aging infrastructure, and rising accountability expectations has intensified demands on facilities organizations to manage institutional assets strategically. As colleges and universities face sustained fiscal constraints and expanding operational pressures, the ability of facilities leaders to use data to inform performance management has become increasingly critical. Despite this importance, limited empirical research has examined how facilities leaders integrate data into decision-making within public higher education contexts.

The quantitative study employed a cross-sectional, exploratory survey design to investigate data utilization practices among facilities leaders at U.S. public four-year institutions. Guided by the Data–Information–Knowledge–Wisdom hierarchy and …

Lied Center For Performing Arts Strategic Analysis, Daniel Cutler

Honors Program: Senior Projects (Public)

This video essay develops a strategic analysis of the Lied Center for Performing Arts through an interview with an associate director at the Center, personal experiences working for the Center, and other external research. It starts with an introduction to the Lied Center, including its mission, vision, and activities. Using strategic frameworks, namely PESTEL analysis and Porter’s Five Framework, a general analysis of the Center’s industry is conducted. These frameworks demonstrate the difficult landscape the Center finds itself in, with some of the more notable struggles stemming from economic factors and competition from other entertainment venues. From there, suggestions and …

Neuroattnfusenet Dual Branch Attention Fusion For Brain Tumor Mri Classification, Md Sanowar Hossain Sabuj, Farzana Sultana, Md Hasan Or Rashid, Rahul Mudhiraj Mullela

Student Publications

Brain tumor MRI classification remains challenging because tumor appearance varies across cases, class boundaries can be visually subtle, and public 2D MRI datasets may contain redundancy or source-specific biases that inflate reported performance. This study proposes NeuroAttnFuseNet, a dual-path attention-guided fusion network for four-class MRI image classification into glioma, meningioma, pituitary, and no tumor. The model combines a Swin-T branch for hierarchical local morphological representation with a frozen DINOv2 ViT-B/14 branch that provides a 768-dimensional global descriptor from the [CLS] token. The Swin and DINOv2 features are concatenated and passed through a channel-attention gate and fusion MLP before final softmax …

An Exploration Of Knowledge-Sharing Behaviour Within A Community-Based Service Provider: A Reflexive Thematic Analysis, Paul Mcmanus

Doctoral

This qualitative research examines the knowledge-sharing (KS) behaviour of employees within a non-profit organisation (NPO) based in Dublin, Ireland. This NPO is a community-based service provider that supports people with disabilities and their families. It operates under the aegis of the Health Service Executive (HSE). The ability of employees to share knowledge is fundamental to the sustained care of society’s most vulnerable. Research on employees’ KS behaviour remains underrepresented within the non-profit sector. This gap in knowledge aligns with the NPO’s view that its KS environment requires improvement. In response to the literature review, a developed taxonomy conceptualises the organisation …

Beyond Words: A Systematic Multimodal Framework For Text, Images, And Extreme Helpfulness In Online Reviews, Alvaro J. Aguado Marin

Dissertations

Online product reviews have become increasingly multimodal, combining text with media-rich elements such as images. However, academic research has largely examined textual features in isolation, overlooking how visual content and its interaction with text shape perceived helpfulness. This dissertation addresses that gap by developing and empirically validating a comprehensive framework capturing how textual, visual, and contextual features collectively influence review evaluation. Grounded in the Elaboration Likelihood Model (ELM) and extended through the Text-Image Elaboration Likelihood Model (TI-ELM), the framework advances understanding of how consumers process content from both user- and business-generated sources. It also lays the foundation for examining emerging …

From Enhancement To Substitution: A Strategic Provocation On Simulation-Based Sport, Grant B. Morgan, Andreas Stamatis

Journal of Applied Sport Management

Advances in artificial intelligence, large-scale machine learning, and simulation technologies are rapidly transforming how sport is played, analyzed, and consumed. To date, most scholarly and industry discussions frame these technologies as tools that enhance embodied sport by improving performance, officiating, media production, and fan engagement. This paper extends that conversation by posing a more provocative strategic question: under what conditions might simulation move from enhancement to substitution? Focusing explicitly on sport as a business and entertainment enterprise, we argue that many of sport’s core sources of cultural and economic value—uncertainty of outcome, narrative continuity, legitimacy, and collective meaning—are structurally …

Digital Zakat And Islamic Fintech: A Bibliometric Analysis Of Global Research Trends And Collaboration Networks (2012–2025), Muhamad Dupi, Fauziyah Adzimatinur

Journal Of Middle East and Islamic Studies

This paper examines global research trends, collaborative networks, and prevailing themes in digital zakat and Islamic fintech studies published from 2012 to 2025. We retrieved a total of 194 Scopus-indexed publications using bibliometric methods on September 23, 2025, and analyzed them using VOSviewer version 1.6.20. The analysis set a minimum occurrence threshold of 5 for keywords and a minimum citation threshold of 10 for documents. The results indicate that the number of publications has been steadily rising since 2017, with the most in 2023 (42 documents). Malaysia, Indonesia, and Nigeria were the top contributors, and INCEIF University and the International …

The 2025 Pakistan Floods: Investigating The Human, Agricultural, And Economic Collapse, Abdullah Khan

MSJ Capstone Projects

This project examines the 2025 Pakistan floods as a multidimensional climate disaster that triggered severe human, agricultural, and economic consequences. Moving beyond event-based reporting, the study examines how climate change, weak governance, poor infrastructure planning, and delayed institutional responses intensified the scale of destruction. Using investigative journalism methods, the project combines field reporting from flood-affected areas, in-depth interviews with displaced communities, local activists, and experts, and analysis of official data and policy documents. The findings reveal widespread displacement, loss of livelihoods, food insecurity, and long-term social vulnerability, particularly among marginalized rural populations. Agricultural collapse emerged as a central concern, threatening …

The Conditional Nature Of The Value Premium: Interaction And Cross-Sectional Evidence Across Market Regimes, Samuel L. Klein

Honors Thesis

This thesis examines why value-based investment strategies generate strong returns in some environments yet weaken or collapse in others. Regressions test whether the performance of the book-to-market ratio depends on the investor’s perception of financial health as defined by F-Score and accruals. Across additive regressions, interaction models, cross-sectionals, and heatmap visualizations, a consistent mechanism emerges. The book-to-market effect is strongest when financial information is neither highly reliable nor severely distressed. In these “moderate-quality” environments, investors struggle to fully distinguish the transitory components of earnings from their persistent counterparts. This makes valuation ratios particularly influential. Accrual intensity and financial strength jointly …

Notes From The Editor, Jay Nathan

Journal of Global Awareness

No abstract provided.

Letter From The Editor, Jay Nathan

Journal of Global Awareness

No abstract provided.

Grantspace Beta: Readiness And Strategic Recommendations, Jason B. Cole

Business Analytics Student Projects and Publications

This paper examines the beta readiness of GrantSpace, an AI-powered grant management platform developed by North Light AI, as it pivots from institutional customers to freelance and independent grant writers. As generative AI tools have commoditized basic writing capabilities, competitive advantage in grant technology increasingly depends on supporting creative flow, reducing professional risk, and enabling policy-compliant workflows. Using market analysis, competitive benchmarking, and UX and data-readiness evaluation, this study assesses whether GrantSpace’s current beta experience aligns with freelance grant writer needs.

Spec Ops Tools Point Of Sale (Pos) Data Insights, Liam Mcgovern

Business Analytics Student Projects and Publications

No abstract provided.

Models Of Funding Research And Development Infrastructure In Poland, Marcin Kardas

Studia i Materiały Wydział Zarządzania Uniwersytet Warszawski

Purpose: The aim of this article is to identify and analyse the basic models of funding research and development infrastructure, as well as the challenges associated with them.

Methodology: The research methods used include interdisciplinary literature studies (economics, law, management), regulations and reports, as well as interviews with stakeholders.

Results: Four models for financing R&D infrastructures embedded in the state aid regime were identified: scientific, mixed, experimental, and economic. National experiences with their application were discussed. Their characteristics, challenges, and risks were presented. Discrepancies in terminology were noted, and directions for their interpretation were suggested.

Research limitations/implications …

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 …

Warehouse Reconfiguration With Ats Lab, Ed Cantor, Dana Pazhouhesh, Mathew Oshinski, Samantha Sanchez

Senior Design Project For Engineers

The ATS Lab Warehouse Reconfiguration project is a collaborative effort between Kennesaw State University’s Department of Industrial and Systems Engineering and ATS Lab, located in Marietta, GA. The goal of this project is to redesign the current warehouse layout to enhance operational efficiency, reduce travel time, and implement sustainable inventory management practices, including 5S and Kanban. Aaron Roob, ATS Operations Manager, and Franklin Hungerford, Continuous Improvement Manager, led this initiative. Our team, “Sick Sigma’s,” is composed of Ed Cantor, our Project Manager, who is working as an intern at ATS during this process; Dana Pazhouhesh (Process Engineer); Matthew Oshinski (Quality …

Modeling Private Debt Using U.S. Consumer Expenditure Data, Stsiapan Dziamentsyeu

Honors Capstones

This project models private household debt among U.S. consumers using data from the Consumer Expenditure Survey (CES) between 2013 and 2023. The analysis focuses on identifying how demographic and economic characteristics, such as income, housing expenditures, education, and occupation, relate to non-mortgage “other” loan balances. After initial model development produced poor residual behavior due to zero-inflation from imputed debt values, the analysis was refined to include only households reporting verifiable debt. Multiple modeling techniques, including AIC-based variable selection and Lasso regularization, were compared under a five-fold cross-validation framework. The Lasso model achieved superior predictive accuracy (RMSE = 1.55, MAE = …

The Impact Of Parking Services On Mental Health At Bowling Green State University, Callie Oyster

Honors Projects

The current research investigates the effects of parking on daily stress and emotional stability and perceptions of equity at Bowling Green State University (BGSU). It draws from the perspective of students, faculty, and staff via a quantitative survey of over 500 respondents that assessed parking behaviors, mental health indicators, and institutional trust. The results indicate that unpredictability, rather than simply lack of space, is the largest source of stress related to parking. Commuter and resident students reported arriving at least 20-30 minutes earlier than expected. Faculty, staff, and students reported feelings of anticipatory anxiety about driving to BGSU, with emotional …

An Assessment And Comparison Of Expert System Performance And Large Language Model Performance, Carter A. Lange

ATU Honors Projects

This study compares the performance of knowledge-based expert systems (KBES) and large language models (LLMs) in narrow-domain tasks. Using Akinator as the representative KBES and ChatGPT as the representative LLM, fifty character-identification trials were conducted. Results show that both systems ultimately succeeded in identifying all characters, but their efficiency and accuracy differ. Akinator required fewer incorrect guesses and produced no identifiable total failures, or “errors,” while ChatGPT occasionally erred beyond possible continuation despite similar average guess counts. Statistical analysis revealed no significant difference in the number of questions required before success, but McNemar’s test indicated that ChatGPT made significantly more …

The Artificial Intelligence (Ai) Economy In The Mountain West, 2025, Dre Boyd-Weatherly, Sean Curry, Krish Sharma, Kristian Thymianos, William E. Brown Jr.

Economic Development & Workforce

This fact sheet reports on the artificial intelligence (AI) readiness of five Mountain West metropolitan statistical areas (MSAs): Phoenix-Mesa-Chandler, AZ; Salt Lake City-Murray, UT; Denver-Aurora-Centennial, CO; Las Vegas-Henderson-North Las Vegas, NV; and Albuquerque, NM. Using data from the Brookings Institution's “Mapping the AI Economy” report, the MSAs are benchmarked based on their overall population, employment, talent, adoption, and innovation.