Business Analytics Commons^™

The Impact Of Big Data Analytics Powered By Artificial Intelligence On Supply Chain Resilience And Corporate Social Responsibility, John Dickens, Hasan Uvet, Antonina Bauman, Sally Hiott

Atlantic Marketing Association Proceedings

No abstract provided.

Deploying Root-Cause Analysis (Rca) Agents: An Implementation Blueprint For Ai-Augmented Marketing Analytics, Seojoon Oh

AMTP Proceedings 2026

Artificial intelligence is widely adopted in marketing, yet many organizations struggle to translate analytical outputs into timely action. This paper presents a practitioner-oriented blueprint for deploying root-cause analysis (RCA) agents within AI-augmented marketing analytics systems. We propose a three-layer reference architecture—semantic data layer, autonomous RCA agent, and action layer—that enables continuous anomaly detection, causal diagnosis, explanation generation, and recommendation delivery. Through simulated e-commerce use cases, we demonstrate how RCA agents identify performance disruptions such as email engagement declines and checkout failures, and translate diagnostic findings into actionable guidance. Beyond system design, we outline organizational workflows, trust-building validation loops, scalability pathways …

Analyzing Big Data-Ai's Impact On Product Innovation And Customer Engagement, Omar Itani, Samer Elhajjar, Ashish Kalra Dr, Manal Yunis Dr.

AMTP Proceedings 2026

In contemporary business landscapes, an organization's capacity to deliver groundbreaking innovative products and foster deep, meaningful engagement with its customers stands as the paramount objective of modern strategic practices. This dual focus not only drives sustainable growth but also fortifies competitive positioning in hyper-competitive markets. Yet, despite the extensive empirical evidence highlighting the transformative benefits of innovation—such as enhanced market share and profitability—and customer engagement—evidenced by loyalty, advocacy, and repeat business—the pivotal role of big data-artificial intelligence (BD-AI) technologies remains strikingly underexplored. In particular, scant attention has been paid to how BD-AI training equips firms to harness these tools effectively …

Social Media Engagement And Financial Performance In Apparel Retail, Emily M. Burke

Student Publications

As companies increasingly rely on social media to engage with consumers, questions remain about whether social media metrics translate into measurable financial outcomes.This study investigated whether changes in Instagram engagement metrics predicted financial performance among publicly traded apparel and lifestyle retail companies. Social media data, including the number of posts and average likes, were collected manually for February 2025 and February 2026. Financial data, including adjusted stock prices and year-over-year quarterly revenue growth, were collected from Yahoo Finance. The final sample included 28 companies after removing outliers and cases with missing data. Multiple linear regression analyses showed that percent change …

Business Analytics (Assignment), Li Lu Ph.D.

School of Business

This assignment was developed by SUNY Geneseo Professor Li Lu during the spring 2026 semester.

Learning Objectives

• Gain Practical Proficiency: Use a generative AI tool to analyze a business scenario, generate insights, and formulate action plans.
• Critically Evaluate AI Output: Identify and critique the limitations, biases, and assumptions embedded in AI-generated content.
• Apply Ethical Reasoning: Assess business decisions through an ethical lens, identifying potential harms and ensuring recommendations are fair, transparent, and responsible.
• Synthesize and Communicate: Create a professional, evidence-based recommendation memo that integrates AI-generated insights with independent critical analysis and ethical considerations.

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 …

Bba405-Management Decision Making Syllabus, Di Wu

Open Educational Resources

Syllabus for BBA405 Management Decision Making course.

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 …

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 …

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 …

Daniels Distinction Portfolio By Maeve Hoffert, Maeve Hoffert

Business Information and Analytics: Undergraduate Distinction Portfolios

A Daniels Distinction Portfolio of experiential education by Maeve Hoffert.

Predicting House Prices Using Machine Learning, Pejal Rath, Robert Slater

SMU Data Science Review

This study explores the use of Machine Learning methods to predict housing prices, a problem of significant interest in real estate economics, and data science. Traditional hedonic pricing models have long been used to evaluate the impact of housing attributes on property values, but they often lack the flexibility to capture nonlinear relationships and complex feature interactions. Recent advancements in regression based and Machine Learning approaches provide promising alternatives that may improve prediction of accuracy and market insights. This research will investigate how models such as linear regression, random forest, and gradient boosting can be applied to publicly available housing …

Application Of Open-Source Small Large Language Models For Finance Report Analysis, Tue Vu, Mark Austin, Marcel Tuijn

SMU Data Science Review

The rapid integration of generative AI in finance introduces both opportunities and challenges, particularly when analyzing sensitive data such as Securities and Exchange Commission (SEC) filings. This study investigates the use of open-source Small Large Language Models (SLLMs), deployed locally through the Ollama and LangChain frameworks, combined with Retrieval-Augmented Generation (RAG) for extracting financial insights relevant to index performance and reporting quality. Two key objectives guide this work: (1) benchmarking multiple open-source SLLMs for sentiment analysis, multiple-choice reasoning, and financial question answering, and (2) assessing the feasibility of locally deployed SLLMs for domain-specific financial queries. A standardized set of 50 …

Financial Leverage And Firm Performance: An Empirical Review And Analysis, Iqbal Md. M Islam

Journal of Global Business Insights

This paper examines the dual impact of financial leverage on corporate performance by analyzing empirical data across developed and developing nations, industries, and different periods. Leverage can enhance profitability through tax benefits and improved efficiency, but it also maximizes financial risk, making its effects highly context dependent. Theoretical frameworks such as the Trade-off Theory, Modigliani-Miller Theorem, Agency Theory, and Pecking Order Theory offer diverse perspectives on how debt influences firm outcomes. Empirical findings reveal mixed results; moderate leverage may lower capital costs and boost performance, whereas unnecessary debt can lead to financial distress. Disparities emerge between developed and developing economies. …

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 …