Business Analytics Commons^™

The Convergence Of Big Data And Ai, Prasanna Rajbhandari

Create@State

Big data and artificial intelligence are transforming how organizations analyze information and make decisions. Traditional analytics struggle with large, distributed, and unlabeled datasets. Modern AI systems must adapt quickly, preserve privacy, and extract meaningful insights from complex data environments.

Ownership Duration In The U.S. Business Jet Market, Yuchen Hu

SACAD: Scholarly Activities

This study analyzes ownership duration in the U.S. business jet market using FAA registry data as of February 16, 2026 (N=12,359). The analysis reveals a structured distribution with a mean of 5.86 years and a median of 5.00 years. Crucially, retention varies by acquisition status: new aircraft owners exhibit an average hold of 7.36 years, whereas pre-owned aircraft holders show a significantly higher turnover of 5.11 years, with most resales occurring within a 3–7-year window. These findings suggest that ownership behavior is driven by structured asset management and lifecycle planning, providing a predictive framework for identifying aircraft replacement and trade-in …

Developing Strategies For Pce Outreach, Mariah Blankenbaker, Gordon Carlson, Daniel Adesoji, Levi Eck

SACAD: Scholarly Activities

In collaboration with Professional and Continuing Education (PCE), we produced projects to automate their internal tasks, as well as to promote their services. By taking advantage of software techniques, we bridged live-action footage with 2D and 3D computer visuals for promotional material. In addition, we researched the capabilities of creating a custom Generative Pre-trained Transformer (GPT) and trained it to analyze and interact with thousands of industry datapoints.

A Dynamic Systems Framework For Customer Lifecycle Management: From Latent State Discovery To Robust Control Policy, Ali Nasirzonouzi

Northeast Journal of Complex Systems (NEJCS)

Traditional marketing often relies on static strategies that fail to capture dynamic customer behavior. This paper introduces an integrated framework to model and control the customer lifecycle, bridging the gap between empirical data and computational simulation. Using the Customer Personality Analysis dataset, we implemented a five-stage methodology. We first identified three distinct customer segments (At-Risk, Standard, High-Value) using Gaussian Mixture Models. To address the lack of longitudinal data, we calibrated a normative transition model based on customer inertia principles. Our analysis revealed that marketing effectiveness is highly state-dependent; notably, At-Risk customers exhibited a 33.5% lift when targeted with catalogs. Leveraging …

Generative Artificial Intelligence In Professional Selling Course: The Art (And Science) Of Prompt Engineering, Michael Rodriguez, Kevin Trainor, Michael Rodriguez

Atlantic Marketing Association Proceedings

No abstract provided.

Examining Digital Transformation In Maritime Logistics: A Big Data Perspective, Jiyoon An

Atlantic Marketing Association Proceedings

No abstract provided.

Global Apparel Companies Adjusting Their Supply Chain Strategies To Post-Covid-19, Alan D. Smith

Atlantic Marketing Association Proceedings

No abstract provided.

Geomarketing: Revolutionizing Market Strategies And Enhancing Spatial Decision-Making Through Ai-Driven Insights, Mark J. Sciuchetti Dr., Jianping Huang

Atlantic Marketing Association Proceedings

No abstract provided.

Sustainability And Technology Aspects Of Supplier Performance, Alan D. Smith

Atlantic Marketing Association Proceedings

No abstract provided.

Digital Transformation And Market Microstructure: Analyzing The Impact Of Algorithmic Trading On National Stock Exchange Of India Price Discovery Mechanisms Through Complex Systems Theory., Mukesh Bhaskar Ahirrao, Harshal Anil Salunkhe, Vishal Sunil Rana

Northeast Journal of Complex Systems (NEJCS)

Abstract

This research examines the evolution of market microstructure at the National Stock Exchange of India (NSE) from 2020 to 2024, a period characterized by substantial growth in algorithmic trading from 35% to 44% of total trading volume. Using market microstructure data and analytical techniques grounded in complex systems perspectives, the study documents temporal patterns in price discovery, liquidity, volatility, and market efficiency associated with this digital transformation.

The analysis reveals several notable changes in market characteristics. Transaction costs improved significantly, with bid-ask spreads declining by 23.4% and market depth increasing by 18.1%. Price adjustment half-life decreased by 50%, indicating …

Marketing The Future Of Radiology: How Ai Integration Enhances Diagnostic Precision And Streamlines Clinical Workflows, Monisha Gupta, Jordan -. Watts Ms, Alberto Coustasse Hencke Dr.

Atlantic Marketing Association Proceedings

No abstract provided.

Face Presence In User-Generated Photos And Its Effect On Review Helpfulness, Anh Dang, Bridget Nichols, Mark Nichols

Atlantic Marketing Association Proceedings

No abstract provided.

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 …

Behavioral Biases As Drivers Of Complexity In Stock Markets: An Agent-Based Modeling Approach, David Joseph Dr, Alwin Joseph, Blesson James, Kajal Dass

Northeast Journal of Complex Systems (NEJCS)

By modeling financial systems as Complex Adaptive Systems, this study investigates how behavioral biases influence emergent complexity in stock markets. The study integrates heterogeneous agents, such as rational traders, herding agents, overconfident traders, and anchoring/disposition-driven investors, within a Limit Order Book framework calibrated to both U.S. and Indian market conditions using an Agent-Based Modeling (ABM) approach implemented through the high-fidelity ABIDES simulation environment. Price dynamics, volatility patterns, and liquidity structures were analyzed by Monte Carlo simulation experiments with different behavioral compositions. The results show that behavioral biases cause nonlinear price reactions, produce heavy-tailed return distributions that distort order-book complexity, and …

Crime, Consumers, And Clustering: A Geomarketing Analysis Of Retail Behavior Across Urban Markets, Mark J. Sciuchetti Dr., Jianping Huang

Atlantic Marketing Association Proceedings

No abstract provided.

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.

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.

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 …

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 …

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 …

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 …

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 …

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 …