Business Intelligence 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 …

A Forecasting Framework For Distribution Center Capacity Utilization: An Applied Industry Study, Jordan J. Shortt

Data Science Undergraduate Honors Theses

This project develops and evaluates a predictive modeling framework for forecasting distribution center capacity utilization at Company Y, with monthly forecast horizons up to one year. Motivated by the operational challenges of seasonal demand volatility, promotional cycles, and the absence of a formally defined capacity metric, the study first constructs a historical capacity utilization measure from raw warehouse management system data — reconciling item volumes, location dimensions, and utilization factors across all DCs — which serves as the target variable for all modeling work. Four models are developed and evaluated against a naïve seasonal baseline: SARIMA, LightGBM, LSTM, and a …

Developing Tracking Compliance Standards For Inbound Freight: A Data-Driven Industry Application At O’Reilly Automotive, Jackson Endacott

Data Science Undergraduate Honors Theses

Visibility of inbound freight is critical for managing operational efficiency, yet many organizations lack standardized compliance metrics for third-party carriers to uphold, preventing them from utilizing tracking data to make data-driven decisions. During a summer internship with the Transportation Department at O’Reilly Automotive, data inconsistencies were addressed in the Transportation Management System (TMS), and that data was utilized to create tracking compliance standards for third-party carriers. Data populated from various sources within O’Reilly’s TMS was cleaned, validated, and utilized to create a Tracking Scorecard that evaluates message transmission rates, timeliness, and errors. This tool provides actionable insights to improve tracking …

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 …

From Data To Action: An Adaptable Crosstabs Template For Participatory Survey Data Analysis, Natalia Pinzon, Vikram Koundinya, William O'R Dowling, Ryan Galt

Journal of Extension

We present a practical and accessible template for quantitative survey data analysis designed for non-academic researchers in order to facilitate engagement from community collaborators. The template, created in Google Sheets, is mainly for computing cross-tabulations, but it also displays frequency distributions and p-values for determining statistical significance. The template allows collaborators to record their observations and questions, promoting an efficient yet interactive review process and fostering a democratic analysis environment. Based on our own experience using this template for a data party, we highlight its effectiveness in promoting collaborative data interpretation, decision-making, and the actionable use of survey findings.

Recent U.S. Government Policy Literature On Critical And Strategic Minerals, Bert Chapman

Libraries Faculty and Staff Scholarship and Research

Critical and strategic minerals have become increasingly important in U.S. government civilian and military policymaking in recent years. This is demonstrated by the heavy use of such minerals in many critical civilian and military infrastructures. This work will discuss how this subject has been addressed in laws, presidential documents, and works by government agencies along with congressional oversight committees and support agencies. It will stress how the United States is heavily dependent on strategic minerals from adversarial foreign countries such as China and will examine U.S. efforts to increase its ability to produce such materials in the United States by …

Shortage To Surge - Studying The Post-Covid-19 Guitar Retail Market, Jed H. Kim

Data Science Undergraduate Honors Theses

The COVID-19 pandemic was one of the most catalyzing events of the 21st century, leading to supply chain disruptions, lifestyle changes, and a massive shift towards digital technologies. During the COVID-19 lockdown, many people had more free time, and over 16 million individuals learned to play guitar in the first 2 years of the pandemic. According to a study by Fender, 62% of these new guitar learners cited the pandemic as their primary reason for learning the instrument. However, pandemic policies and supply chain disruptions meant that many guitar retailers were unable to satisfy demand, and backorders accumulated. After the …

Ai Meets Economics: Can Deep Learning Surpass Machine Learning And Traditional Statistical Models In Inflation Time Series Forecasting?, Ezekiel N.N. Nortey, Edmund F. Agyemang, Enoch Sakyi-Yeboah, Obu-Amoah Ampomah, Louis Agyekum

School of Mathematical & Statistical Sciences Faculty Publications

This study examined the forecasting ability of deep learning (DL) and machine learning (ML) models against benchmark traditional statistical models for the monthly inflation rates in the USA. The study compared various DL and ML models like transformers, linear regression, gradient boosting (GB), extreme gradient boosting (XGBoost), and adaptive boosting (AdaBoost) with traditional baseline time-series models like autoregressive integrated moving averages (ARIMA) and exponential smoothing (ETS) with Holt-Winters seasonal method utilizing data sourced from the Federal Reserve Bank of St. Louis. The study consistently showed that all DL and ML models outperformed the traditional approaches. In particular, the Transformer (RMSE …

A Machine-Learning Tool-Supported Methodology For Nonprofit Donor Analysis, Corbin Weiss

Campus Research Month

We developed a machine-learning tool-supported methodology for modeling the nonprofit donor relationship. This approach was demonstrated in the case of a US-based nonprofit. Conclusions were drawn from this example and tool-support provided for use by other nonprofits.

A New Measure Of Non-Parametric Correlation For Variables In The Likert Scale, Shubhabrata Das

Working Papers

We propose a new measure of nonparametric correlation that is especially suited for measuring association between variables measured in the Likert scale where data is ordinal and tied observations are extremely common. The proposed general structure of the measure is based on graded level of concordance and discordance between the pairs of metrics. The general form of the measure has all the desirable properties except the measure is not necessarily zero for independent variables. This limitation is acceptable given only ordinal nature of the metrics. Three versions of the measure are studied. The first is based on simple equi-distant weights. …

Robust Conic Satisficing, Arjun Ramachandra, Napat Rujeerapaiboon, Melvyn Sim

Working Papers

In practical optimization problems, we typically model uncertainty as a random variable though its true probability distribution is unobservable to the decision maker. Historical data provides some information of this distribution that we can use to approximately quantify the risk of an evaluation function that depends on both our decision and the uncertainty. This empirical optimization approach is vulnerable to the issues of overfitting, which could be overcome by several data-driven robust optimization techniques. To tackle overfitting, Long et al. (2022) propose a robust satisficing model, which is specified by a performance target and a penalty function that measures the …

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 …

Striking A Balance: Market Shock & Responses In Automotive Components Manufacturing, Emma Lane Mcgahey

All Theses

This thesis examines the effects of extreme market shocks on supply chain dynamics within the automotive industry. Through an analysis of demand data from an automotive manufacturer to its component suppliers (January 2018 to May 2024), the study investigates the relationship between market shocks and supply chain responses, providing insights into how auto components inventory management handles downstream responses to market shocks. With supporting public data—from FRED, BLS, and the U.S. Census Bureau resources—we explore two primary relationships: the impact of market shocks on the Average Standard Deviation of Demand (SDO) and the effect of demand variability on expedited pricing …

Course-Skill Atlas: A National Longitudinal Dataset Of Skills Taught In U.S. Higher Education Curricula, Alireza Javadian Sabet, Sarah H. Bana, Renzhe Yu, Morgan R. Frank

Economics Faculty Articles and Research

Higher education plays a critical role in driving an innovative economy by equipping students with knowledge and skills demanded by the workforce. While researchers and practitioners have developed data systems to track detailed occupational skills, such as those established by the U.S. Department of Labor (DOL), much less effort has been made to document which of these skills are being developed in higher education at a similar granularity. Here, we fill this gap by presenting Course-Skill Atlas – a longitudinal dataset of skills inferred from over three million course syllabi taught at nearly three thousand U.S. higher education institutions. To …

Who Are You Rooting For? T20 Cricket World Cup 2024, Usa & Wi, Purvesh Desai

Dissertations, Theses, and Capstone Projects

The T20 Cricket World Cup '24 played in USA & WI will bring immense excitement to the cricket lovers around the world and have a question to themselves “Who shall I Root for?” How do people or fans support their favorite teams and on what criteria do they pick these teams will discuss in here.

Patriotism, tradition, and favorite individual players, are the main reasons for the fans to choose their and support the team. Nation is the biggest pride of an individual and many people choose their pride over everything. People celebrate when the home team plays on the …

Experimental Methods In Predicting Market Drift And Other Portfolio Optimization Factors Using Graph Theory, Perry Harrison Zhang

Computer Science Senior Theses

No abstract provided.

Modeling The Effect Of Population Size On Banking Transaction Channels In Nigeria: Grey Box Vs Support Vector Regression, Desmond Bartholomew, Ngozi P. Olewuezi, Chrysogonus C. Nwaigwe, Felix C. Akanno

CBN Journal of Applied Statistics (JAS)

This study investigates the effect of Nigeria’s population on four selected banking transaction channels. The Nigerian projected population (2022-2027) was used as an input variable for forecasting future volumes of transactions for each channel. The results show that the Support Vector Regression (SVR) model best fits the ATM, Online, and USSD channels of transaction while the Grey-box was better for POS. The forecast results show that ATM, online, and USSD channels had their highest volume of transactions in 2023, while for POS, the highest volume was recorded in 2027. Further results indicate that online and POS transactions would dominate payment …

Spatiotemporal Negative Inventory Outlier Decomposition For Supply Chain Applications In Consumer-Packaged Goods (Cpg), Hayden Mcdonald

Data Science Undergraduate Honors Theses

Coca-Cola is a popular soft drink brand with sales occurring in every Walmart store across the world, which generates large quantities of data and requires a robust supply chain system. However, the company does not currently have a sophisticated, automated, and/or prescriptive system for detecting where, when, and why inventory outages occur and applying preventative measures to avoid loss of revenue from the absence of inventory on store shelves. This thesis proposes and applies a novel, prescriptive system for this purpose. An inventory outage can be seen as a ‘negative’ statistical outlier in a time series of inventory for an …

A Comprehensive Study Of Patent Litigation In The Pharmaceutical Sector: Employing Network Theories, Graph Neural Networks, Agent Based Modeling, Bayesian Network Autocorrelation Models, Sreehas Gopinathan

Information Systems & Operations Management Dissertations - Archive

Understanding the dynamics and predictors of patent litigation is crucial in intellectual property management, especially given the competitive edge patents offer companies. Also, patents serve as both legal tools and repositories of innovation. This research delves into the complex world of patent litigation within the pharmaceutical industry, focusing on creating and applying advanced computational models to study litigation propensities. Techniques such as Graph Neural Networks (GNN), Agent-Based Modeling (ABM), and Bayesian Analysis of Network Autocorrelation Models (BANAM) are employed to explore the litigation phenomenon

Outsourcing Voting To Ai: Can Chatgpt Advise Index Funds On Proxy Voting Decisions?, Chen Wang

Fordham Journal of Corporate & Financial Law

Released in November 2022, Chat Generative Pre-training Transformer (“ChatGPT”), has risen rapidly to prominence, and its versatile capabilities have already been shown in a variety of fields. Due to ChatGPT’s advanced features, such as extensive pre-training on diverse data, strong generalization ability, fine-tuning capabilities, and improved reasoning, the use of AI in the legal industry could experience a significant transformation. Since small passive funds with low-cost business models generally lack the financial resources to make informed proxy voting decisions that align with their shareholders’ interests, this Article considers the use of ChatGPT to assist small investment funds, particularly small passive …

Management Of Operations In Projects Including Planning, Organization And Control From The Beginning To The End Of Implementation, Burim Isa Berisha Dr.Sc

International Journal of Business and Technology

The project usually arises as soon as the client’s need is identified, and goes through all the extensive phases and sub-phases to take its true form and put into operation. The project is divided into two main parts that include Planning and Implementation that are separate in these stages: definition, planning, organization, control, completion. Planning involves a detailed calculation of the project. This includes known facts, admissible facts and risk calculation. Activity model used by IKOMs Planning as a process involves the cost that accompanies it. The manager must strike the balance between cost and benefit. Project control uses data …

Project Planning And Control, Burim Isa Berisha Dr.Sc

International Journal of Business and Technology

Operations management is important because it relates to the creation of products and services on which we are all dependent. Operations management is also quite motivating; operations are the center of many changes that affect business - changes in customer preferences, changes in the supply chain caused by technologies based on the businesses where we work, where we want to work and so on.

Operations Management includes the role of operations management, the various characteristics of processes, management activities, the responsibilities of managers, and the timely evolution of Operations Management.

Operations Management is a constant change, fostering creativity which allows …

Long-Term Auditor-Client Relationship And Its Effects On The Audit Quality, Burim Isa Berisha Dr.Sc

International Journal of Business and Technology

Apart from this, the long-term Auditor client relationship has been the center of attention in most of the discussions and debates as well. Numerous studies have been conducted by the academic researchers, financial and professional analysts, regulatory authorities and governing bodies, and in some cases by the Auditors and the firms as well regarding the effects of long-term Auditor-client relationship on audit quality, equity risk premium, financial reports quality, audit pricing etc. These studies provide us with different results, both with the positive and negative associations and effects of long-term Auditor-client relationship on the basis of different factors and contexts. …

Management Of Small Enterprises And Family Businesses In The Republic Of Kosovo, Burim Isa Berisha Dr.Sc, Burim Berisha B.B

International Journal of Business and Technology

Small businesses represent the driving force of an economy. They are the key that enables the production and marketing of thousands of products and services thus becoming the basis for a sound economic development. Consequently, small businesses are of vital importance to the economy.

Small business is a generator of innovation and a source of new jobs. The trend shows that small businesses are the backbone of all developments and movements in the economic system.

The small business scope is present in almost every pore of social and economic life.

According to the Statistical Register for Businesses, there are 9,358 …

The Process Of Adapting Innovations In Banking Services By Businesses In Kosovo, Burim Isa Berisha Dr.Sc, Burim Berisha B.B

International Journal of Business and Technology

This dissertation addresses the importance of a business model from businesses in Kosovo, which is able to adapt innovations from the banking sector such as digital services, and through which become part of a global market where such developments occur step by step. very fast At the beginning of this paper will be given definitions related to the main concepts that are addressed such as business model, innovations in banking services - digitalization of services and the role and importance of linking a business model with banking services of the time. After the theoretical part, from which the main concepts …

The Process Of Adapting Innovations In Banking Services By Businesses In Kosovo, Burim Isa Berisha Dr.Sc, Burim Berisha B.B

International Journal of Business and Technology

This dissertation addresses the importance of a business model from businesses in Kosovo, which is able to adapt innovations from the banking sector such as digital services, and through which become part of a global market where such developments occur step by step. very fast At the beginning of this paper will be given definitions related to the main concepts that are addressed such as business model, innovations in banking services - digitalization of services and the role and importance of linking a business model with banking services of the time. After the theoretical part, from which the main concepts …

Phantom Shootings, Allan Ambris

Dissertations, Theses, and Capstone Projects

This capstone is a website designed to critique NYC Open Data reporting with respect to shootings through a series of visualizations and discoveries. The NYPD Shooting Incidents datasets (Historic and Year to Date) introduce themselves to the user by claiming to be a “list of every shooting incident that occurred in NYC.” The supplied documentation reveals that this is not the case.

After understanding the supporting materials, there are still undisclosed truths. My exploration of the data revealed that a single victim may be represented across multiple entries. Additionally, multiple victims may be represented by a single entry. It is …

"Church On My Couch": Predicting The Future Impact Of Online Ministry Based On The Impact During Covid-19, Samukeliso Mabarani, Sikhumbuzo Dube

Adventist Human-Subject Researchers Association

With “everything from home” as the new norm, “how does the use of digital platforms impact Adventist education, community engagement, and spiritual outreach?” Using a quantitative approach, we draw insights from online ministry during Covid-19 and use the insights to predict the future impact of online ministry statistically.

Tourism, Mapping, Retail And Recreational Trails: A Case Study Of Connectivity Between Trails And Adjacent Downtowns In Anniston, Alabama, Usa, Jennifer Green

Theses

This study examines the estimated increase in economic impact on a geography’s local economy by creating cross-marketing efforts between expanding an established outdoor recreation trail to a closely located city downtown commerce district. This research will analyze the resulting potential rise in sales/lodging tax revenues for that city by mapping the trail and downtown district, and cross-marketing the other to users of both or either venue. Potential increase in economic impact will be estimated utilizing IMPLAN methodology by assessing the economic impact on the local economy that a percentage range of increased spending resulting from this cross-marketing effort could generate.

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …