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Articles 1 - 14 of 14
Full-Text Articles in Business Analytics
Ai For Regression Analysis And More, Eli Snir
Ai For Regression Analysis And More, Eli Snir
Generative AI Teaching Activities
Students use Copilot and NotebookLM to create a dataset and develop statistical analyses including regression.
Exploring Determinants Of Value For Money And Bundling Effects On Public–Private Partnership Projects: A Data-Driven Empirical Study, Gaurav Khadka
Exploring Determinants Of Value For Money And Bundling Effects On Public–Private Partnership Projects: A Data-Driven Empirical Study, Gaurav Khadka
Department of Construction Engineering and Management: Dissertations, Theses, and Student Research
Public–private partnerships (P3s) are widely used to deliver public infrastructure, yet current understanding of what drives variation in Value for Money (VfM) and the effectiveness of project delivery strategies such as bundling remains largely conceptual and grounded in perception-based evidence. Consequently, governments lack empirically validated guidance on which project, financial, and macroeconomic conditions meaningfully influence VfM outcomes and whether bundling improves project performance within the P3 context. This study addresses these gaps through an integrated analysis of 180 Canadian P3 infrastructure projects (1992–2020), one of the most comprehensive datasets of realized VfM internationally, incorporating project characteristics, financial arrangements, and macroeconomic …
The Conditional Nature Of The Value Premium: Interaction And Cross-Sectional Evidence Across Market Regimes, Samuel L. Klein
The Conditional Nature Of The Value Premium: Interaction And Cross-Sectional Evidence Across Market Regimes, Samuel L. Klein
Honors Thesis
This thesis examines why value-based investment strategies generate strong returns in some environments yet weaken or collapse in others. Regressions test whether the performance of the book-to-market ratio depends on the investor’s perception of financial health as defined by F-Score and accruals. Across additive regressions, interaction models, cross-sectionals, and heatmap visualizations, a consistent mechanism emerges. The book-to-market effect is strongest when financial information is neither highly reliable nor severely distressed. In these “moderate-quality” environments, investors struggle to fully distinguish the transitory components of earnings from their persistent counterparts. This makes valuation ratios particularly influential. Accrual intensity and financial strength jointly …
A Machine Learning Approach To Revenue Generation Within The Professional Hair Care Industry, Alexander K. Sepenu, Linda Eliasen
A Machine Learning Approach To Revenue Generation Within The Professional Hair Care Industry, Alexander K. Sepenu, Linda Eliasen
SMU Data Science Review
The cosmetic and beauty industry continues to grow and evolve to satisfy its patrons. In the United States, the industry is heavily science-driven, innovative, and fast-paced, suggesting that to remain productive and profitable, companies must seek smart alternatives to their current modus operandi or risk losing out on this multi-billion-dollar industry to fierce competition. In this paper, the authors seek to utilize machine learning models such as clustering and regression to improve the efficiency of current sales and customer segmentation models to help HairCo (pseudonym for confidentiality), a professional hair products manufacturer, strategize their marketing and sales efforts for revenue …
College Majors And Unemployment Rates, Anna M. Gellerman, Harshita Ahuja
College Majors And Unemployment Rates, Anna M. Gellerman, Harshita Ahuja
Publications and Research
College undergraduates often face the question of whether their major and related job force have high unemployment rates. The perceived high unemployment rates of certain majors due to circulating misinformation presents a need for comprehensive research on college majors and their associated unemployment rate. This paper dives into a ten year trend of unemployment rates by college major, and state to state variabilities of majors and their rates.
Stock Trend Prediction Using Candlestick Charting And Ensemble Machine Learning Techniques With A Novelty Feature Engineering Scheme, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu
Stock Trend Prediction Using Candlestick Charting And Ensemble Machine Learning Techniques With A Novelty Feature Engineering Scheme, Yaohu Lin, Shancun Liu, Haijun Yang, Harris Wu
Information Technology & Decision Sciences Faculty Publications
Stock market forecasting is a knotty challenging task due to the highly noisy, nonparametric, complex and chaotic nature of the stock price time series. With a simple eight-trigram feature engineering scheme of the inter-day candlestick patterns, we construct a novel ensemble machine learning framework for daily stock pattern prediction, combining traditional candlestick charting with the latest artificial intelligence methods. Several machine learning techniques, including deep learning methods, are applied to stock data to predict the direction of the closing price. This framework can give a suitable machine learning prediction method for each pattern based on the trained results. The investment …
An In-Depth Analysis Of The Data Analytics Job Market, Dagny Elaine Wilkins
An In-Depth Analysis Of The Data Analytics Job Market, Dagny Elaine Wilkins
Honors Theses and Capstones
No abstract provided.
Get A Bang For Your Puck: Hockey, Statistics, And Betting, Kathleen Capozello
Get A Bang For Your Puck: Hockey, Statistics, And Betting, Kathleen Capozello
Honors Projects
An exploration into the analytics of hockey and the business of sports betting. The goal of this project was to determine whether an equation could be created to predict the number of goals an NHL forward or defenseman will score in a future season based on a previous season’s data. Additionally, this paper explores the potential monetary values of such an equation, as well as the parties that may find it useful.
Does Racial Discrimination Exist In The Nba?, Logan Kendall
Does Racial Discrimination Exist In The Nba?, Logan Kendall
Williams Honors College, Honors Research Projects
This paper aims to examines the affect of race on compensation for NBA players. Based on prior research, I pose the hypothesis that racial discrimination does exist in the NBA with there being a premium for white players. A second hypothesis I present based on the previous research is that the premium for white players exist for only some groups of players and for other groups there with not exist discrimination based on player race. By using career data from every player who played in the 2019-2020 NBA season and their 2019-2020 salaries, a few different models where ran. The …
Price Prediction In The Sharing Economy: A Case Study With Airbnb Data, Brandon Mcneil
Price Prediction In The Sharing Economy: A Case Study With Airbnb Data, Brandon Mcneil
Honors Theses and Capstones
Many sharing-economy companies like Airbnb have their profits rely on the dynamic pricing market that they participate in. Airbnb hosts can set their own price based on what they deem the market will buy. Recent research argues that almost all hosts fail to maximize their potential profit due to poorly pricing their listing (Gibbs et al., 2018). While previous studies have looked at how specific variables effect the price of an Airbnb listing, this study aims to be the first to group variables separately into two distinct categories based on the host’s ability to control that variable. Looking at two …
Yelp’S Review Filtering Algorithm, Yao Yao, Ivelin Angelov, Jack Rasmus-Vorrath, Mooyoung Lee, Daniel W. Engels
Yelp’S Review Filtering Algorithm, Yao Yao, Ivelin Angelov, Jack Rasmus-Vorrath, Mooyoung Lee, Daniel W. Engels
SMU Data Science Review
In this paper, we present an analysis of features influencing Yelp's proprietary review filtering algorithm. Classifying or misclassifying reviews as recommended or non-recommended affects average ratings, consumer decisions, and ultimately, business revenue. Our analysis involves systematically sampling and scraping Yelp restaurant reviews. Features are extracted from review metadata and engineered from metrics and scores generated using text classifiers and sentiment analysis. The coefficients of a multivariate logistic regression model were interpreted as quantifications of the relative importance of features in classifying reviews as recommended or non-recommended. The model classified review recommendations with an accuracy of 78%. We found that reviews …
Analyzing Operating And Support Costs For Air Force Aircraft, Scott C. Hewitson, Jonathan D. Ritschel, Edward D. White, Gregory Brown
Analyzing Operating And Support Costs For Air Force Aircraft, Scott C. Hewitson, Jonathan D. Ritschel, Edward D. White, Gregory Brown
Faculty Publications
Purpose: Recent legislation resulted in an elevation of operating and support (O&S) costs’ relative importance for decision-making in Department of Defense programs. However, a lack of research in O&S hinders a cost analyst’s abilities to provide accurate sustainment estimates. Thus, the purpose of this paper is to investigate when Air Force aircraft O&S costs stabilize and to what degree. Next, a parametric O&S model is developed to predict median O&S costs for use as a new tool for cost analyst practitioners.
Design/Methodology/Approach: Utilizing the Air Force total ownership cost database, 44 programs consisting of 765 observations from 1996 to 2016 …
Splitting The Bill: Estimating Personal Consumption In Case Of Wrongful Death, Kathleen Ellis, David I. Rosenbaum
Splitting The Bill: Estimating Personal Consumption In Case Of Wrongful Death, Kathleen Ellis, David I. Rosenbaum
UCARE: Research Products
In cases of wrongful death, the decedent’s survivors may sue alleged responsible parties for lost financial support. Forensic experts estimate a deceased individual’s personal consumption rate in order to separate the portion of the decedent’s income spent on him- or herself from the amount available as financial support for dependents. This paper enhances the prevailing estimation process by regressing consumption rates over individual households surveyed by the United States Bureau of Labor Statistics in its annual Consumer Expenditure Survey. We contend that this method improves the precision of estimates by accounting for the inherent heterogeneity in consumption among households with …
Forecasting Us Army Enlistment Contract Production In Complex Geographical Marketing Areas, Joshua L. Mcdonald, Edward D. White, Raymond R. Hill, Christian Pardo
Forecasting Us Army Enlistment Contract Production In Complex Geographical Marketing Areas, Joshua L. Mcdonald, Edward D. White, Raymond R. Hill, Christian Pardo
Faculty Publications
Purpose: The purpose of this paper is to demonstrate an improved method for forecasting the US Army recruiting. Design/methodology/approach: Time series methods, regression modeling, principle components and marketing research are included in this paper. Findings: This paper found the unique ability of multiple statistical methods applied to a forecasting context to consider the effects of inputs that are controlled to some degree by a decision maker. Research limitations/implications: This work will successfully inform the US Army recruiting leadership on how this improved methodology will improve their recruitment process.
Practical implications: Improved US Army analytical technique for forecasting recruiting goals.