Management Sciences and Quantitative Methods Commons^™

A Machine Learning And Artificial Intelligence Sentiment Analysis Of Esg Disclosures, John Barnett Davis

Graduate Theses and Dissertations (2019 - present)

This dissertation examines whether environmental, social, and governance (ESG) disclosure sentiment extracted from SEC Form 10-K Item 1A risk disclosures aligns with Bloomberg ESG scores. The study combines SEC textual disclosures, Bloomberg ESG ratings, firm financial data, executive compensation data, and executive gender characteristics. Natural language processing and artificial intelligence methods, including FinBERT, Loughran-McDonald sentiment measures, BART-MNLI zero-shot classification, LLaMA-based ESG scoring, and readability analysis, are used to evaluate ESG-related disclosure signals. Results reveal that SEC 10-K Item 1A risk-factor sentiment and Bloomberg ESG scores represent related but distinct constructs. ESG sentiment in Item 1A is poorly aligned with third-party …

The Anatomy Of Earnings Conference Calls: An Integrative Framework For Management Research, Matthew P. Mount, Gokhan Ertug, Wei Shi, Tengjian Zou

Research Collection Lee Kong Chian School Of Business

Over the last decade, there has been an explosion in the use of diverse data sources by management scholars to observe and capture managerial and organizational constructs that have historically been difficult to access. This surge has been driven by the growing availability of rich, multi-modal data—textual, image, and audio (Luo, Jia, Ouyang, & Fang, 2024)—together with advances in analytical techniques to process and analyze data, such as computer-aided text analysis (Harrison, Thurgood, Boivie, & Pfarrer, 2019), machine learning (Choudhury, Wang, Carlson, & Khanna, 2019; Harrison, Josefy, Kalm, & Krause, 2023), and deep learning (Gouvard, Goldberg, & Srivastava, 2023). These …

Crowding In Private Capital For Climate Adaptation In India, Shreya Bajaj

Master in Public Policy Theses

Reports show that India is highly vulnerable to climate change. Mitigation efforts alone cannot address these risks, and adaptation remains essential. Yet while much of the existing literature documents the adaptation finance gap, it offers less practical guidance on where private capital can realistically be used and what institutional arrangements are needed to make it work. This paper tries to address that gap in the Indian context.

This paper examines three adaptation finance use cases through which private capital could support climate adaptation and resilience in India: parametric disaster risk transfer, pooled municipal finance, and water fund. For each issue, …

The Impatience Of Winning: An Analysis Of Time Discounting, Predictive Modeling, And The Nba Draft, Alec R. Plante

Business and Economics Honors Papers

This paper examines whether NBA draft decisions can be better explained by incorporating non-geometric time discounting into a model of general manager decision making. Using a dataset of 285 NBA draft prospects over a 12-year period, the impact of college statistics on Value Over Replacement Player (VORP) is determined, and these impact values are then used to create a “predicted” VORP for the first 4 seasons of each player’s career: a projection of what a general manager might think of a prospect’s future value given their college statistics. Following this, geometric and hyperbolic time discounting models are applied to estimate …

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 …

Analysis The Influence Of Product Attributes On Purchase Decision In Choosing A Smartphone Apple Or Samsung., Arumadina Islamiq, Indrawati Indrawati

International Conference on Business and Management Research (ICBMR)

Smartphones are currently a very important and necessary means of communication for the public. Two of the most popular smartphone brands are Samsung and Apple. The purpose of this study is to measure respondents' assessments of product attribute variables (quality, features, brand, design style, and support services) in purchase decisions.

This research is descriptive. It uses quantitative methods. This study examines two variables in detail, namely product attributes (X) as the independent variable and Purchase Decision (Y) as the dependent variable. The respondents in this study consisted of all consumers who currently use Samsung or Apple smartphone products, with 400 …

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 …

Data Tracking And Analytics Within Inventory Management: Coffee Shop And Retail Store Optimization, Mateo J. Moyon

Senior Theses

This thesis examines the application of inventory management theory in the small and medium-sized business context, with a specific focus on the food and beverage industry. Drawing on the foundational academic literature spanning from Harris’s EOQ formula in 1913 through stochastic inventory theory, ABC analysis, and just-in-time strategy, this paper establishes the mathematical and operational bases for modern inventory management practice. Although there are proven value to these frameworks, research demonstrates that small to medium sized businesses adopt inventory management systems at lower rates citing cost and implementation as barriers. This thesis argues that the emergence of low-cost inventory and …

Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park

Annual Research Symposium

Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …

Expanding Waste Segregation Initiatives To Reduce Regulated Medical Waste: A Multi-Departmental Quality Improvement Project, Emily M. Su, Anuja L. Sarode, Mohammed Sami, David R. Nehring, Erica L. Laipply, Mustafa Culcuoglu

HCA Healthcare Journal of Medicine

Background

Regulated medical waste (RMW) drives up health care costs, largely due to misclassification of general waste, especially in operating rooms (ORs), intensive care units (ICUs), and obstetrics and gynecology (OBGYN) departments. This study aimed to reduce RMW volume and costs at Akron City Hospital (ACH) through department-specific interventions aligning with Occupational Safety and Health Administration (OSHA) and Ohio Environmental Protection Agency guidelines.

Methods

Periodic analyses compared hospital-wide aggregate RMW volume, pick-up frequency, and disposal costs before and after interventions. The ORs initiated interventions in October 2022, expanding to ICUs and OBGYN by February 2024. Strategies included staff education, flyers …

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 …

Business Process Redesign For Reducing Undelivered Product Return Losses In E-Commerce – An Explainable Ai Approach, Venkataraghavan Krishnaswamy, Deepa R, Himanshu Sharma

Journal of International Technology and Information Management

Product returns in e-commerce affect the profitability of the e-tailer. We adopt a two-stage approach to reduce undelivered product returns in an e-commerce firm. First, we develop and compare machine learning techniques—logistic regression, decision trees, Naïve Bayes, random forest, adaptive boosting, gradient boosting, stochastic gradient boosting, and deep neural networks—on their ability to predict undelivered returns. Next, we use explainable methods, such as relative importance and Shapley values, to develop insights from the best-performing machine learning model. Finally, we use these insights and the predictive model to redesign the firm’s order fulfillment and return processes. A Post-implementation evaluation of the …

How Interest Rates Influence Entry Level Employment Growth For Undergraduate Economics Students, Stiles B. Logan, Marc Joseph, Dylan Hilburn, Hayden Baker, Krisha Patel

SPARK Symposium Presentations

The United States job market has become a growing concern for graduating college students over the last decade. With rising unemployment, increased competition, and the rise of generative AI technology over the last five years, more students than ever are genuinely concerned that they will be unable to find long-term employment after graduation. In this paper, we will analyze the correlation between United States interest rates and entry-level employment growth, with the goal of contributing new and actionable information to help graduating college students plan for the future. We will be using data from IPUMS and FRED, spanning January 2009–December …

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 …

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 …

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 …

Investigating The Relationship Between Noun Classes And Plant Folk Taxonomy In Chasu Language Of Kilimanjaro Region In Tanzania, Peter Rabson Mziray

Journal of Humanities and Social Sciences

The current study investigates the relationship between noun classes and plant folk taxonomy in Chasu (G 22). The study focuses on two objectives: the first objective is to describe the plant folk taxonomy in Chasu and the second objective is to determine the relationship between noun classes and plant folk taxonomy in Chasu. Data were collected from rural villages in Same and Mwanga districts by using free listing, field interviews (jungle-walk-and-identify), and written texts containing Chasu plant names. The findings reveal that Chasu folk taxonomy reflects different ethnobotanical categories; including a unique beginner which is mmea/mimea ‘plant(s)’, and three life …

Sentiment Analysis Of Public Commentary On U.S. Farm Bills, Frank Tenkorang, Fletcher Ziwoya

Mountain Plains Business Conference

This study applies sentiment analysis to public commentary on U.S. farm bills to assess patterns of support and opposition. Using Reddit posts from relevant subreddits, we employed two natural language processing models, VADER and RoBERTa, to evaluate sentiment over time. While both models yielded differing sentiment distributions, they revealed increased public engagement during farm bill years, particularly in 2018. Most sentiments were neutral, but negative opinions outweighed positive ones. Posts with stronger sentiments tended to attract more user interaction, especially controversial ones. These findings highlight the polarized yet active public discourse surrounding agricultural policy and the potential for data-driven policy …

Research On Credit Card Transaction Risk Prediction Model Based On Multi-Source Data Fusion And Its Application, Ziang Qi

Harrisburg University Other Works

In this paper, the credit card risk control and early warning model is constructed to predict and control the credit card risk by fusing multi-source data through data mining technology. After analyzing the theoretical application of XGBoost algorithm on credit card transaction risk, its model parameters are optimized by particle swarm algorithm to construct PSO-XGBoost credit card transaction risk prediction model. The credit card transaction risk prediction performance of the PSO-XGBoost model is verified and applied to the abnormal transaction risk assessment of Bank A. The AUC value, accuracy, F1 value, precision rate, and recall rate of the PSO-XGBoost model …

Orchestrating Complexity: The Art Of Virtual Leadership In System Modelling, Vijay Kumar Sonawane, Bipllab Roy, Purnendu Bikash Acharjee, Indu Pv

Northeast Journal of Complex Systems (NEJCS)

This paper explores the dynamics of virtual leadership within global remote work environments, focusing on the application of complex system modelling to understand and enhance leadership efficacy. The application of computational modelling has been a regular feature in economics, science and technology fields, however its application in virtual leadership with linkage to sport leadership appears to be a novel concept. Adopting a multidisciplinary approach, this paper incorporates Game Theory as a conceptual framework to make the leadership model more relevant and applicable that can offer simpler understanding of complex play of leadership drivers. The model incorporates five key leadership dimensional …

Colaboración Interdisciplinaria: Tablero De Control Para Una Institución Politécnica R01 En Los Ee. Uu. [Libro], Cristo Leon Ph.D., Victor Hugo Guzmán Zarate Ph.D.

STEM for Success Showcase

Introducción
En el ámbito académico, la colaboración interdisciplinaria emerge como un imperativo estratégico y un desafío multifacético. Este estudio tiene un enfoque eminentemente práctico y busca diseñar y aplicar una herramienta específica —un tablero de control interactivo— para facilitar y mejorar la colaboración interdisciplinaria en un entorno académico real. La complejidad inherente a este desafío se refleja tanto en el dinamismo del ambiente investigativo como en la falta de definiciones operacionales cohesivas que faciliten la evaluación y visualización de la colaboración interdisciplinaria. Para abordar estos desafíos, el presente estudio se llevó a cabo en la Facultad de Ciencias y Artes …

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 …

Understanding Household Financial Stability: Examining The Effects Of Inflation And Income, Cyndy E. Gutierrez-Fierros

Electronic Theses, Projects, and Dissertations

This study aims to investigate the impact of inflation on US household financial stability from 2013 to 2023. As inflation rises, individuals’ purchasing power erodes leading to influence economic behaviors. Behaviors such as spending, saving, and borrowing should be a priority concern in the US economy. Results of this study reveal that inflation does not affect financial well-being and its direct impact on household stability is statistically weak. Regression testing shows that income emerges as the most significant factor. Most noticeably income influences savings and debt management in a positive way. As per these results, economic policies should be focused …

Strategic Audit: Hilton Worldwide Holdings, Inc., Jenna Derowitsch, Tram Ngo, Tenley Katt, Makenna Henning, Lexi Soukup

Honors Program: Senior Projects (Public)

This comprehensive strategic audit analyzes the internal and external environment in which Hilton Worldwide Holdings Inc. operates, in addition to auditing the strategic drivers that have drove the iconic hospitality firm to success. Hilton Worldwide Holdings, Inc. (Hilton) is a valued hotel chain that has been operating as a global leader in the hospitality industry for more than 100 years. The firm sets an industry standard to provide high-quality hotel services and a reliable stay for more than 200 million guests annually and continues to develop its portfolio of destinations. Technological advancements and shifting customer preferences challenge Hilton to remain …

Market Structure Evolution In The U.S. Automobile Industry: A Review Of Diversity And Concentration Metrics, P.V. (Sundar) Balakrishnan

AMTP Proceedings 2025

I examine the evolution of market structure in the U.S. automobile industry from 1937 to the present, focusing on the application of both traditional and novel diversity and concentration metrics. I use the Herfindahl-Hirschman Index (HHI), Comprehensive Concentration Index (CCI), and newer metrics from fields such as ecology and genetics to uncover insights into the shifting dynamics of market power, firm turnover, and industry stability. The U.S. automobile industry, characterized by consolidation and technological advancement, provides a unique case study for analyzing long-term market evolution. I contribute to the literature by synthesizing a broad range of diversity metrics and offering …

1 – 1 > 0: Growing The Pie By Reallocating Shelf Space To Small Brands, Jesse Core, Ho Kim

AMTP Proceedings 2025

We examine whether reallocating shelf space to smaller brands enhances total category sales. During a three-month field experiment involving 20 supermarket stores in Arkansas (10 treatment and 10 control stores), we increased shelf facings for smaller brands in treatment stores and reduced facings for larger brands, while maintaining the total shelf space constant. A difference-in-differences analysis reveals that increasing facings for smaller brands significantly boosts total category sales, with an average increase of 960 ounces per week during the intervention. Notably, sales remained elevated by 786 ounces per week after shelf facings reverted to the original level, indicating a persistent …

Enhancing Interoperability In Geospatial Analytics Systems: Navigating Diverse Standards For Optimal Data Integrity, Justin W. Bennett

Dissertations

In this study, we explore the domain of geospatial analytics, focusing on how different geographic information systems (GIS) and technology solutions can better communicate and maximize interoperability. Central to our study is the impact of this interoperability on data integrity, which is critical for accurate decision-making in domains like urban planning, environmental management, and national security. Accurate decision-making requires modeling ecosystems that are easy to comprehend and are often intricate due to their physical or artificial nature and the diversity of geospatial parameters; therefore, it is essential to gather a comprehensive array of spatial and temporal measurements. We examine the …

Uncertainty In Pricing And Risk Measurement Of Survivor Contracts, Kendrick Raymond So, Stephanie Claire Cruz, Elias Antonio Marcela, Jeric C. Briones, Len Patrick Dominic Garces

Mathematics Faculty Publications

As life expectancy increases, pension plans face growing longevity risk. Standardized longevity-linked securities such as survivor contracts allow pension plans to transfer this risk to capital markets. However, more consensus is needed on the appropriate mortality model and premium principle to price these contracts. This paper investigates the impact of the mortality model and premium principle choice on the pricing, risk measurement, and modeling of survivor contracts. We present a framework for evaluating risk measures associated with survivor contracts, specifically survivor forwards (S-forward) and survivor swaps (S-swaps). We analyze how the mortality model and premium principle assumptions affect pricing and …

Surviving And Thriving In The Hybrid Cloud: A Review Of The Current Cloud Computing Landscape, Peter Munsch, Alison Munsch

Journal of International Technology and Information Management

Background and Purpose

Both academic and industry institutions have increasingly migrated essential services to public cloud providers (e.g., Microsoft, AWS, Google) with mixed outcomes. Some industry leaders attempted to fully replace their on-premises data centers with public cloud services, a move not advised without thorough performance and cost analyses (Potel, 2023). Despite some organizations pulling back from the “Cloud First” strategy, the public cloud services market continued to grow, with revenue increasing by approximately 20% year-over-year since 2020 and surpassing half a trillion dollars in 2022 (IDC Worldwide Semiannual Public Cloud Services Tracker, 2H 2022). Cloud technologists suggested that hybrid …

Safeguard Cyberspace In Ransomware Era: Risk Analysis & Cyber Insurance, Li Huang

Electronic Theses & Dissertations (2024 - present)

The increasing frequency and severity of ransomware attacks pose significant challenges for organizational cybersecurity. Fragmentation across disciplines in cyber defense has created practical gaps in the development of the necessary capabilities needed to address rapidly evolving cyber threats. This study explores the impact of ransomware attacks and the evolving role of cyber insurance as a proactive cybersecurity partner. Bridging the gap between actuarial science and cyber risk management, it proposes an interdisciplinary framework that quantifies the impact of ransomware and integrates cyber insurance into cybersecurity strategies.

The primary contribution of this study is methodology. We present a framework that remains …