Business Analytics Commons^™

Decoding Stock Market Movements: The Role Of Unemployment And Volatility, Bipllab Roy, Suparna Bhattacharjee

Northeast Journal of Complex Systems (NEJCS)

This study investigates how unemployment and market volatility interact with stock prices in the Indian context, framing the stock–labour–volatility nexus as a complex adaptive system (CAS) rather than a set of linear, time-invariant relationships. Using verified secondary data on unemployment, India VIX, and NSE stock indices for 2013–2023, we first apply simple and multiple regression as a descriptive baseline. Results show a strong negative association between unemployment and stock prices (R ≈ 0.824, R² ≈ 0.68, p < 0.05), consistent with Keynesian demand-side channels, while the linear VIX–stock relationship is weak and statistically insignificant (R² ≈ 0.07, p > 0.05), consistent with the expectation that volatility operates through non-linear, regime-dependent mechanisms not captured by OLS.

Importantly, we document and transparently disclose critical …

Development Of Artificial Intelligence (Ai) Utilization Scale In Business To Business (B2b) Sales Process And Conceptual Model: Exploratory Study, Michael Rodriguez

Atlantic Marketing Association Proceedings

No abstract provided.

Practical Applications Of Artificial Intelligence For Small Business Marketing: A Literary Review & Llm Approach, Noah C. Kowalski

Honors Capstones

This Honors Capstone Research Paper examines the practical application of artificial intelligence in small business digital and social media marketing. As AI technologies become more accessible, small businesses have new opportunities to improve efficiency, enhance customer engagement, and compete more effectively in digital markets. However, there is a lack of clear guidance on how to implement these tools in a practical and cost-effective way.

This study uses a qualitative approach, combining a literature review with an applied analysis of widely used AI marketing tools including ChatGPT, Canva, Hootsuite, Buffer, Google Analytics 4, and HubSpot. These tools were evaluated based on …

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.

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.

Grantspace Beta: Readiness And Strategic Recommendations, Jason B. Cole

Business Analytics Student Projects and Publications

This paper examines the beta readiness of GrantSpace, an AI-powered grant management platform developed by North Light AI, as it pivots from institutional customers to freelance and independent grant writers. As generative AI tools have commoditized basic writing capabilities, competitive advantage in grant technology increasingly depends on supporting creative flow, reducing professional risk, and enabling policy-compliant workflows. Using market analysis, competitive benchmarking, and UX and data-readiness evaluation, this study assesses whether GrantSpace’s current beta experience aligns with freelance grant writer needs.

Understanding The Incidents On Legacy Airlines With Explainable Artificial Intelligence And Text Mining: Case Study Top 5 Us Airlines, Dean Sutherland, Mehmet Burak Cankaya

Beyond: Undergraduate Research Journal

Aircraft incident data from the Federal Aviation Administration between 1978-2023 was analyzed for the top five airlines in the United States: Delta Air Lines Inc., American Airlines Inc., Alaska Airlines Inc., Southwest Airlines Co., and United Airlines Inc. This analysis aimed to predict conditions with a higher chance of causing injury and determine the best machine-learning model for this prediction. The target variable of "injuries occurred" is processed through machine learning methods such as Naïve Bayes, logistic regression, and XGBoost. This was to predict the injuries and understand and explain the complex fault mechanism with explainable artificial intelligence. The XGBoost …

The Impact Of Ai On Salary Trends And Employment Projections, Anastasiia Semerianova, Annie Chen, Rebecca Mui, Ekaterina Viro, Hui Ting Huang, Thiy Alsaidi

Publications and Research

This project is designed to research the potential future impact of AI implementation on job displacement across key industries such as healthcare, manufacturing, and others. It aims to analyze how automation and AI technologies influence employment trends and workforce demands, as well as the correlation between AI integration and changes in salary structures. The goal is to provide data-driven insights that can inform policymakers, educators, and industry leaders on how to prepare for and adapt to evolving labor market dynamics.

Transforming Accounting With Artificial Intelligence, Aidan M. Morneault

Business Analytics Student Projects and Publications

The accounting field is evolving quickly with the integration of Artificial Intelligence (AI), and BNN is taking on this challenge. This report explores how BNN incorporates AI tools like Microsoft’s CoPilot and Caseware into its operations to streamline audits, enhance efficiency, and ensure compliance. This report will also cover how the industry handles this new technology, but still have a focus on BNN. While AI has brought significant benefits such as reducing costs, speeding up data processing, and moving towards real-time audits, it also presents challenges. These challenges include trust in AI outputs, high implementation costs, and workforce training. To …

Comment Letter On Sec’S Proposed Rule On Conflicts Of Interest Associated With The Use Of Predictive Data Analytics By Broker-Dealers And Investment Advisers, File Number S7-12-23, Sergio Alberto Gramitto Ricci, Christina M. Sautter

Faculty Works

This comment letter responds to the Securities and Exchange Commission’s proposed rule Release Nos. 34-97990; IA-6353; File Number S7-12-23 - Conflicts of Interest Associated with the Use of Predictive Data Analytics by Broker-Dealers and Investment Advisers. Our comments draw on our scholarship relating to laypersons’ participation in securities markets and the corporate sector as well as on the role of technology in corporate governance.

We express concerns that the SEC’s proposed regulation undermines individuals’ ability to access capital markets in an efficient and cost-effective manner. In the era of excessive concentration of equities ownership and power, often with negative societal …

Effects Of Concussion And Visuomotor Metrics On Nhl Performance: An Explainable Ai Approach, Michael T. Moschitto

Master's Theses

Cognitive motor integration (CMI), the simultaneous coordination between cerebral function and motor output, is known to deteriorate following a mild traumatic brain injury (mTBI). This thesis explores the relationship between mTBI, CMI, and the performance of elite athletes in the National Hockey League (NHL). The approach focuses on examining the predictive value of various supervised Machine Learning (ML) models with an emphasis on Explainable Artificial Intelligence (XAI) models. Since the ML solution is intended to complement human scouting decisions, we evaluate the experiments based on both interpretability and accuracy on a limited class imbalanced dataset. The contributions of this research …

Accounting And Financial Statements Auto Analysis System, Zhen Jia

Electronic Theses, Projects, and Dissertations

This project was motivated by the need to revolutionize the generation of financial statements and financial analysis process thus speeding up business decision making. The research questions were: 1) How can machine learning increase the speed of financial statement preparation and automate financial statements analysis? 2) How can businesses balance the benefits of automating financial analysis with potential concerns around privacy, data security, and bias? 3) Can the Java J2EE framework provide a reliable running environment for machine learning?

The findings were: 1) Machine learning can significantly increase the accuracy and speed of financial analysis. Using machine learning algorithms, financial …

Thinking Local With Original Data In Ai And Machine Learning Research, David G. Taylor, Robert Mccloud

WCBT Working Papers

Sacred Heart University spent significant funds to establish an AI lab. Initially there is no ongoing research and no real plan for a research agenda. This paper details how the Jack Welch College of Business and Technology created and implemented an active meaningful research plan. It involves two key elements: thinking local and using business connections to foster active, impactful research. Surrounding communities, business connections, area environment, and other Sacred Heart University departments all played a part. The research plan also identifies a specific issue in working with local and business contact sources: the AI researcher almost never gets data …