Business Intelligence Commons^™

Does Green Pay Less? Global Corporate Bond Evidence On Primary And Secondary Yields, Youssef El Kenawy

Theses and Dissertations

The greenium, or green premium, refers to the lower yield that arises from a bond’s green label, conditional on otherwise identical contractual features and credit risk. In our study, we estimate the greenium by combining causal matching techniques with a neural network–based propensity score approach to construct a closely comparable set of green and conventional bonds. Our empirical framework incorporates issuer fixed effects and currency × issuance-year fixed effects, ensuring that our estimates reflect the impact of the green label itself rather than differences in macro-financial conditions or issuer composition.

Our findings indicate that, once currency-specific issuance-year conditions are absorbed, …

Overcoming Adversity With Resilience: A Phenomenological Examination Of African American Women Leaders Facing Microaggressions In Corporate Spaces, Dionne Trenise Johnson

Electronic Theses and Dissertations

African American women leaders in Fortune 500 companies experience persistent challenges of subtle yet pervasive systems of discrimination in the form of microaggressions that cause negative impacts to their psychological well-being, workplace performance, and career advancement. These women exhibit incredible resilience that enable them to thrive at work, mitigate mental health challenges, and navigate their careers successfully. However, unlike people who fall into either a racial minority group or a gender minority group, African American women experience compounded effects of microaggressions due to the intersection of their race and gender. As a result of microaggressions, these women experience impacts to …

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 …

Silicon Rivalry: Understanding The U.S.-China Ai Competition In Southeast Asia, Daniel Christopher Kent

Master in Public Policy Theses

In the rising global strategic competition between China and the United States, artificial intelligence (AI) has taken on a special significance given its potentially transformative impact upon economics and security. Yet while the dialogue around the “AI race” is typically centered on foundational model capability enhancement, application in security contexts, and chip design and manufacturing, there is much less attention paid to its impact on geopolitics. In particular, AI diplomacy—the work of a state to spread its model of AI governance, evangelize its AI companies, and develop critical AI interdependencies and linkages around the world—is far less studied. Nowhere is …

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 …

A Forecasting Framework For Distribution Center Capacity Utilization: An Applied Industry Study, Jordan J. Shortt

Data Science Undergraduate Honors Theses

This project develops and evaluates a predictive modeling framework for forecasting distribution center capacity utilization at Company Y, with monthly forecast horizons up to one year. Motivated by the operational challenges of seasonal demand volatility, promotional cycles, and the absence of a formally defined capacity metric, the study first constructs a historical capacity utilization measure from raw warehouse management system data — reconciling item volumes, location dimensions, and utilization factors across all DCs — which serves as the target variable for all modeling work. Four models are developed and evaluated against a naïve seasonal baseline: SARIMA, LightGBM, LSTM, and a …

Developing Tracking Compliance Standards For Inbound Freight: A Data-Driven Industry Application At O’Reilly Automotive, Jackson Endacott

Data Science Undergraduate Honors Theses

Visibility of inbound freight is critical for managing operational efficiency, yet many organizations lack standardized compliance metrics for third-party carriers to uphold, preventing them from utilizing tracking data to make data-driven decisions. During a summer internship with the Transportation Department at O’Reilly Automotive, data inconsistencies were addressed in the Transportation Management System (TMS), and that data was utilized to create tracking compliance standards for third-party carriers. Data populated from various sources within O’Reilly’s TMS was cleaned, validated, and utilized to create a Tracking Scorecard that evaluates message transmission rates, timeliness, and errors. This tool provides actionable insights to improve tracking …

Escaping The Promotion Trap: A Machine Learning Framework For Brand Equity Preservation In Beverage Cpg, Lucas P. Jones

Data Science Undergraduate Honors Theses

When companies acquire beverage brands, they typically value them based on total sales revenue. This traditional approach treats all sales equally over time, whether they are driven by genuine consumer demand or temporary discounts. This is important because while promotions can boost short-term sales, they tend to erode brand value over long periods of time. The measurement problem extends to acquisitions, where buyers lack the tools to distinguish real consumer demand from artificial promotional inflation.

This thesis develops a framework to separate genuine baseline demand from promotional dependence using Nielsen scanner data covering 189 beverage brands across 188,304 weekly observations …

Exploring The Transformative Effects Of Executive Coaching On Leaders: A Qualitative Study, Dwayne Norman

Theses & Dissertations

This qualitative dissertation examines the transformative effects of executive coaching on leaders’ development, personal growth, decision-making, and overall effectiveness across varied organizational contexts. Grounded in authentic leadership theory and employing a generic qualitative inquiry design, the study investigated how leaders who completed executive coaching describe changes in their behavior and mindset. Eleven experienced leaders participated in semi-structured interviews selected through purposive sampling. Thematic analysis, guided by the cyclical and inductive coding methods of Saldana (2021), generated 187 initial codes, which were distilled into 72 final codes. These final codes were then further refined into twelve categories and four overarching themes: …

Investigating Machine Learning As An Anomaly Detection Tool In College Basketball, Eli G. Whitaker

Honors College Theses

Artificial Intelligence (AI) and Machine Learning (ML) are more commonly becoming tools that organizations use to prevent, detect, and deter fraud. Like other organizations, the amount of fraud that the National Collegiate Athletic Association (NCAA) faces is growing at an alarming rate. The primary issue involves athletes that undermine the integrity of their sport by purposefully playing below their true potential as participants in broader betting-related schemes. This thesis focused on Division 1 Men’s Basketball evaluates the viability of using supervised ML to detect anomalies in team performance over games in recent seasons. Anomalies, like red flags in the context …

Design And Implementation Of A Customer Retention And Voice Ai System For El Nopal, Brando Medina

Undergraduate Theses

This Honors Applied Thesis documents the design and implementation of a live Customer Retention and Voice AI System for El Nopal, a full-service restaurant, to improve customer follow-up, routine communication handling, and cross-channel engagement. The project was developed for El Nopal’s Tyler Center location on Taylorsville Road and focused on building a practical artifact rather than primarily evaluating long-term business outcomes. The completed v1 system consists of three modules: a Customer Retention System centered on a QR-based VIP rewards workflow, a Voice AI System for routine phone support, and a Cross-Channel Integration Layer that connects voice interactions to CRM-based SMS …

The Impact Of Targeted Marketing On The Health Of Teenagers In America: Regulatory Safeguards And Implications, Katelyn Overbay

Senior Theses

The rise of digital marketing has transformed how companies engage with consumers, particularly those that fall within the adolescent age group. Teenagers represent a uniquely vulnerable demographic due to the developmental stage they are in, making them especially susceptible to targeted advertising strategies that leverage data analytics, social media algorithms, and behavioral tracking. The aim of this study is to examine the direct and indirect impacts of targeted marketing on the physical, mental, and social health of teenagers in the United States. Drawing on existing literature, case studies, recent lawsuits, and regulatory analysis, the research gathered explores how industries such …

Leveraging Accounting Analytics To Enhance Payroll Accuracy And Fraud Detection In U.S. Public Sector Institutions: A Case Study Approach, Regina Debrah

Beacom School of Business Student Publications

This study explores how accounting analytics can be leveraged to enhance payroll accuracy and improve fraud detection in U.S. public-sector institutions, addressing persistent irregularities amid rising demands for fiscal transparency. The research employs a qualitative design with secondary sources including academic literature, reports, and case studies. The literature identifies successful analytics implementation, such as Treasury OPI’s machine learning for data integration for unemployment claims. These precedents demonstrate direct transferability to payroll’s high volume and rules-based structure. Findings show that analytics significantly reduce improper payments through real-time screening, data integration, and risk prioritization when embedded in workflows. The findings also show …

A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines

Dissertations

Artificial Intelligence (AI) is transforming Supply Chain Management (SCM), yet many organizations struggle to assess their readiness for AI adoption and to understand how AI capabilities develop across maturity stages. This dissertation addresses this gap by developing a Capability Maturity Model (CMM) for AI integration in SCM, grounded in Organizational Information Processing Theory (OIPT), the Resource-Based View, and related capability frameworks. The model provides a structured approach for evaluating an organization's information-processing requirements, resource configurations, and alignment needed for effective AI-enabled supply chain operations.

Using a design science research approach, the AI-SCM CMM and its associated assessment instrument were derived …

Enhancing Military Health System Organizational Efficiency And Quality Of Care Through A Social-Ecological Framework, Eric L. Peipelman

College of Graduate Studies: Theses & Dissertations

Timely and fair adjudication of incivility-related actions within the Department of Defense (DoD) and Military Health System (MHS) is increasingly crucial for maintaining accountability, mission readiness, and quality of care. Ongoing delays in resolving workplace complaints and inefficiencies in resource-heavy adjudications highlight the need to shift from reactive complaint handling toward proactive civility promotion and transparent decision-making. This Integrated Learning Experience (ILE) introduces the Peipelman Civility Discussion and Assessment Toolkit (PCDAT)—a comprehensive, evidence-based framework designed to improve civility, optimize resources, and enhance communication, even in the MHS. Based on the Social-Ecological Model (SEM) and adapted from the Workplace Power and …

Pillpetz: A Smarter Way To Encourage Medication Adherence In Children, John H. Begley

CMC Senior Theses

Medication adherence is usually framed as a problem of patient behavior, but this thesis argues that it is equally a problem of design. Children who take daily medication face barriers that adults often do not: developing executive function, dependence on caregivers, shifting school and home routines, privacy concerns, and stigma around being perceived as different. The standard prescription bottle, by contrast, was designed primarily for dispensing efficiency, safety, and accidental ingestion prevention—not for sustained daily use by a developing child.

This thesis proposes PillPetz, a smart pill case and digital companion that uses routine, play, dose confirmation, and caregiver-connected support …

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

Business Analytics Student Projects and Publications

No abstract provided.

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 …

Beyond Compliance: Rethinking Ethical Accounting Through Ai And Esg, Rafael L. Portillo

Honors Program Theses and Research Projects

With the increasing adoption of these modern technologies in world markets while maintaining these ethical principles, there is an increasing need for alignment between technology development and ethical responsibility. For instance, in the world of accounting, there is an increasing demand to maintain alignment between technology development and ethics. It is for this reason that these researchers have chosen to explore the link between Artificial Intelligence, ESG, and financial reporting ethics.

The goal of this study is to look at new concerns and moral risks that appear when ESG expectations, AI systems, and accounting practices interact. Earlier research usually studies …

The Impact Of The Covid-19 Pandemic On National Hockey League Fan Attendance, Ramon E. Rivera

Electronic Theses, Projects, and Dissertations

The COVID-19 pandemic struck swiftly around the world, causing several societal functions and normalcies to adapt or shut down completely. This culminating project explores the effects of COVID-19 on arena fan attendance of the National Hockey League (NHL). This project was guided by the following three research questions: Q1 – How did the NHL arena closures affect fan attendance during the COVID-19 pandemic? Q2 – What factors influenced NHL fan arena attendance before the start of the COVID-19 pandemic? Q3 – What factors impacted the NHL arena fan attendance after the conclusion of the COVID-19 pandemic? An empirical model developed …

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 …

A Monte Carlo Analysis Of Cost Competitiveness Of Chinese And U.S. Fine Chemical Exports To Europe Under Europe’S Energy Crisis, Lin Luo

Dissertations

The European energy crisis, driven by geopolitical conflicts, has created a significant supply-demand gap in Europe’s fine chemical sector, necessitating reliance on imports from the United States and China. This quantitative study examined how energy, labor, and logistics costs interacted to shape the cost competitiveness of U.S. and Chinese fine chemical exports to Europe, using a Monte Carlo simulation parameterized with historical data from 2015-2023, to provide a probabilistic forecast of competitive outcomes. The findings revealed that while China holds a 76.55% probability of being the lower-cost supplier, its advantage is characterized by high volatility primarily due to its logistics …

Multi-Theoretic Perspective Of Backer Decision-Making In Crowdfunding: Interplay Of Backer, Founder And Ai, Maliha Alam

Theses and Dissertations

Crowdfunding has become a transformative mechanism for financing innovation, connecting creators directly with backers while bypassing traditional funding barriers. Despite its rapid global growth, only about 33.7% of campaigns succeed, largely due to ineffective communication of value propositions and lack of backer engagement. This dissertation investigates the complex interplay between project founders, backers, and emerging AI technologies to understand the factors influencing donation intention and to enhance crowdfunding success prediction.

Adopting the behavioral decision-making framework, I draw on multiple theoretical perspectives- signaling theory, the dual-process model of persuasion, and the cognitive-affective trust framework to examine founder- backer interactions. Using a …

Organizational Metamorphosis: When Artificial Intelligence Transforms Companies Into New Economic Life Forms, Allan M. Glass

All Dissertations

Traditional theories of organizational change fall short in explaining how artificial intelligence (AI) transforms organizations. This grounded theory study, based on interviews with 34 organizational leaders, identifies a novel phenomenon: organizational metamorphosis - the irreversible transformation of organizations into fundamentally new entities through deep integration with AI as a cognitive partner.

The metamorphosis process unfolds in three phases. Individual Awakening occurs when leaders experience powerful interactions with AI, prompting a rapid shift from skepticism to advocacy. Once a critical mass of leaders undergo this shift, it initiates Organizational Restructuring, characterized by reimagined work design, boundary dissolution, and altered temporal rhythms. …

Two Essays In Finance: Can Machines Better Predict Insider Trading? And Csr And Firm Value Following Dividend Cuts: International Evidence, Solmaz Batebi

Theses and Dissertations

This dissertation consists of two essays. In the first paper, I find that machine learning (ML) models predict the likelihood and magnitude of insider trading significantly better than linear models such as OLS and logistic regression. I use ML models, including LASSO, Random Forest, and eXtreme Gradient Boosting, optimizing model parameters through Bayesian hyperparameter tuning to identify the best configuration. Additionally, I apply SHAP values to better understand the determinants of insider trading. I also use Gaussian Thompson Sampling (GTS) to explore the sources of insiders’ market-timing capabilities. I find that ML models can boost the R² for models predicting …

Projectpath: Turn Skills Into Stories, Brady M. Katler, Gregory Lontok

Honors Thesis

In today's job market, even just landing an interview can prove to be quite the challenge. With ProjectPath, we provide applicants the tools to transform a job application into a tailored project. These projects have been proven to help users stand out among all the competition.

Hospital Organizations’ Obligation To Promote Spiritual Well-Being Among Nurses: Development Of A Normative Ethical Argument, Michael Jordan

Electronic Theses and Dissertations

This dissertation presents an innovative strategy to promote the support of nurses' spirituality within hospital organizations. By focusing on the spiritual well-being of nurses by hospital organizations, with a natural extension into nursing schools, the approach aims to enhance nurse’s ability to protect their own spirituality, provide comprehensive spiritual care to patients, and increase nurse moral resilience. By investing in nurses' spirituality and spiritual growth, hospitals can potentially increase job satisfaction among nursing staff, improve patient care outcomes, and create a more holistic healing environment for both nurses and patients. As the nursing shortage continues and the number of nurses …

Analytics & Insights Internship At Market Performance Group, Ava Mccrary

Information Systems Undergraduate Honors Theses

An Honors Thesis discussing the growth of analytics in the corporate world.

Shortage To Surge - Studying The Post-Covid-19 Guitar Retail Market, Jed H. Kim

Data Science Undergraduate Honors Theses

The COVID-19 pandemic was one of the most catalyzing events of the 21st century, leading to supply chain disruptions, lifestyle changes, and a massive shift towards digital technologies. During the COVID-19 lockdown, many people had more free time, and over 16 million individuals learned to play guitar in the first 2 years of the pandemic. According to a study by Fender, 62% of these new guitar learners cited the pandemic as their primary reason for learning the instrument. However, pandemic policies and supply chain disruptions meant that many guitar retailers were unable to satisfy demand, and backorders accumulated. After the …

Challenges The Sporting Industry Faced During Covid-19 On Fan Attendance: The Case Of The National Basketball Association, Marlon Long

Electronic Theses, Projects, and Dissertations

This culminating experience project investigates the challenges the sporting industry faced during the COVID-19 pandemic, with a focused look at the National Basketball Association. The research questions are: (Q1) How did the NBA arena shutdowns impact fan attendance for each team during the COVID-19 pandemic? (Q2) What factors influenced NBA arena attendance before the COVID-19 shutdowns? (Q3) What factors influenced NBA arena attendance after the COVID-19 shutdown? The data collected includes all 30 NBA teams from 2019 through the 2024 seasons. The research questions were analyzed using multilinear regression analysis and comparison of attendance data over 6 seasons including the …