Business Analytics Commons^™

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 …

Reviving The Skies: The Impact Of Government Focus On Aviation Industry Growth In The Post-Covid World, Sumeet Hassan Anwar, Humna Asad

Journal of Aviation Technology and Engineering

Travel restrictions and border closures during the COVID-19 epidemic drastically reduced air traffic that affected the aviation sector. With an eye toward regional variances and public-private alliances, this essay investigates how government policies, financial interventions, and regulatory frameworks assisted recovery attempts. The essay also looks at how network-based resilience models lower vulnerabilities and improve operational connection, thus guaranteeing future disturbance readiness. Autoregressive integrated moving average models, among other forecasting instruments, help to forecast aviation demand and match recovery plans with changing market dynamics. By means of comparative policy analysis and network theory, this study reveals best practices from Asia, Europe, …

Regression With Microdata And Microsoft Excel®, Humberto Barreto

Economics and Management Faculty publications

A free eversion is available at http://ggl.link/regbook with open-access course materials at dub.sh/regcourse.

Bibliometric Analysis Of Research On Women’S Labor Force Participation And Household Economics, Muhamad Dupi, Inayat Ullah Baloch

Jurnal Ekonomi Kependudukan dan Keluarga

Studies of women labor participation (WLFP) and household economics have grown in size in the last two decades and more research and policy focus are given to gender equality, labor markets and household welfare. Nevertheless, the available literature is still in pieces by region, theme, and institutional settings and a complete bibliometric review of this area of study is yet to be done. The objective of the proposed study is to trace the world-wide literature on the topic of women participation in the labor force and household economics through the analysis of the patterns of publications, networks of cooperations, and …

Smartphone And Sleep, Jesenia Ortiz, Melanie Bonilla, Eduard Reyes, Jose Rivera

Open Educational Resources

The case study and Decision: You are a data analyst advising a university-affiliated research and wellness initiative that is evaluating whether late-night smartphone use should be formally discouraged as part of student wellness guidance. Over the past academic year, administrators have raised concerns about declining sleep quality among students and its potential impact on academic performance, health, and decision-making. While smartphones are an essential tool for communication and learning, their use immediately before bedtime has emerged as a possible contributor to sleep disruption. The initiative must decide whether the available evidence is strong enough to justify recommending that students limit …

When The World Hits Play, Eileen Mazariegos, Danjela Halilaj, Yosmairy Guzman, Freddy Cruz Osorno

Open Educational Resources

The case study and Decision: In 2025, Lehman College administrators face a critical decision: how can music be strategically used to improve student engagement, emotional well-being, and campus connection? The decision must be made now, as rising academic stress, digital isolation, and declining campus interaction are affecting student experience. Leadership must determine whether to invest in a data-driven, campus-focused music platform or continue relying on generalized commercial streaming experiences that do not reflect student needs. The outcome of this decision will shape how students connect emotionally, socially, and academically on campus.

Nyc Fire Causes, Alex Rodriguez, Anyely Rojas Romero, Brianna Itwaru, Shahreen Sneha

Open Educational Resources

The case study and Decision: You are a team of newly hired Data analysts who have been chosen to conduct a case study for the Department of New York City. There is an interest in discovering what exactly is causing fires in New York City. Also, how can we prevent them?

Treasury Bills, Di Wu

Open Educational Resources

The Scenario and The Decision: You are a Data Analyst at a mid-sized investment advisory firm that manages portfolios for both individual and corporate clients. Recently, a significant portion of the client base has expressed interest in shifting capital toward U.S. Treasury bills (T-bills) as a low-risk investment strategy. However, the firm faces a dilemma: while T-bills are considered "safe," their prices and yields fluctuate based on economic conditions and investor demand, making market entry timing critical. The firm has formally requested that you provide a comprehensive analysis to guide their future investment decisions.

Ai Art Valuation Company: Artmetric, Zhuochen Tu

MA Projects

ArtMetric is a technology company dedicated to revolutionizing the art market. We have developed an AI-driven valuation platform designed to address the inefficiencies, high costs, and subjectivity inherent in traditional art appraisal. Users upload images of artworks through our platform to quickly receive a data-driven, and affordable valuation report. This report integrates AI visual analysis, real-time market data comparison, and optional expert verification, ensuring both speed and accuracy in valuation. Our target clients include collectors, artists, galleries, and insurance companies. We monetize through subscription services, one-time appraisals, and premium B2B solutions. As the art market accelerates its digital transformation, ArtMetric …

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 …

Ai-Driven Risk Forecasting For Strengthening The United States Food Supply Chain Resilience: Case Study: A National Ai-Enabled Food Supply Chain Risk Forecasting Framework And A Data Analytics Approach To Predicting Disruptions, Sarah Onyeche Usoro, Itua Austin Omogiate, Rahab Zhewe Felix, David Azikutenyi Galadima

Student Publications

The United States food supply chain is one of the most complex and interconnected systems in the world, spanning agricultural production, processing, transportation, storage, and retail distribution. While this complexity enables efficiency and scale, it also increases vulnerability to disruptions caused by climate change, labor shortages, geopolitical shocks, transportation failures, cyber threats, and public health crises. Conventional risk management methods, often reactive and siloed, have proven inadequate in predicting and mitigating systemic shocks that have become frequent occurrences in today’s world. This article examines how artificial intelligence (AI) and data analytics can transform risk forecasting in U.S. food supply chains …

Inequality In Education, Lantz Mcclanahan, Madison Tucker

SPARK Symposium Presentations

No abstract provided.

Corporate Disclosure Meets Natural Language Processing: Topic Modeling, Disclosure Strategy, And Audit Implications, Wanxin Yu

2026

Corporate disclosures serve as a critical channel for firms to communicate their financial performance, strategic initiatives, and firm-specific risks. In recent years, rapid advances in natural language processing (NLP) have provided powerful new tools for extracting insights from the growing volume and complexity of corporate disclosures. This dissertation consists of three studies that explore how advanced textual analysis can reveal deeper insights into corporate disclosures, managerial behavior, and auditor practices.

The first paper (co-authored) develops a topic-based approach to measuring the substantive content of risk factor disclosures. Using an embedding-based topic modeling framework, we identify 30 interpretable risk topics and …

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 …

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 …

Comparison Of Communication Interfaces In Ai-Driven Styling Services, Yanbo Zhang, Chuanlan Liu

LSU Fashion and AI x Policy Symposium

No abstract provided.

Ai Agent-Powered Fashion Shopping Services: A Future-Oriented Consumer Adoption Perspective, Yanbo Zhang, Chuanlan Liu

LSU Fashion and AI x Policy Symposium

No abstract provided.

Integrating Social Media And Entrepreneurship: A Study Of Social Media, Creativity, Strategy, And Innovation In Building A Successful Brand Presence In The Digital Era, Lys Ishiari

Undergraduate Honors Theses

Social media has completely changed what it means to start a business. It was once just a place for personal interactions but is currently a powerful channel that drives the growth of multiple industries (Felicia, 2022). Now, anyone can use their personal creativity and hobbies to build a brand, especially on apps like Instagram, YouTube, and TikTok. The purpose of this study is to identify the common themes behind social media entrepreneurs’ success, which allows individuals to become both creators and business owners in the digital age. Furthermore, a key part of writing this paper is personal; it connects to …

Forecasting The Unpredictable: The Bullwhip Effect In The Toy Industry, Mannat Sethi

CMC Senior Theses

This thesis investigates the bullwhip effect, the amplification of demand variability as it moves upstream in a supply chain, with a focus on the toy industry, and comparative analysis with the technology and consumer goods sectors. Using annual data from 1993 to 2024, the study analyzes production and retail growth for Mattel, Hasbro, Intel, and Procter & Gamble to assess how variance between consumer demand and firm output has changed over time. Bullwhip ratios are calculated as the variance of production growth divided by the variance of retail growth across two periods: 1993–2008 and 2009–2024.

The findings show that toy …