Business Analytics Commons^™

Assessing The Readiness And Awareness Of Key Stakeholders In The Egyptian Maritime Industry To Implement Smart Green Port Practices: A Case Study Of Alexandria Port, Mohamed Elhussieny, Ahmed El Kassar, Kareem Tonbol

Blue Economy

This study explores the readiness and preparedness of the major stakeholders within the Egyptian maritime sector towards the adoption of smart green port practices, with particular consideration given to Alexandria Port. With growing environmental threats, the need to support sustainable maritime operations is high. The study evaluates the current state of the ecosystem at Alexandria Port and benchmark it against international standards to highlight the critical gaps that should be covered for the effective execution of smart green port approaches. The results indicate that, although stakeholders have basic knowledge of sustainability issues, large perceived barriers, particularly regarding resource availability, limited …

Kroger Post-Pandemic Customer Segmentation, Mario Mata, Joey Truitt, Renn Spigelmyer, Dhanuja Kasturiratna, Lisa Holden, Nitish Baidya, Hanna Tafari

Posters-at-the-Capitol

The grocery retail industry landscape has changed greatly in the wake of the pandemic. Specifically, delivery and pickup services have become more popular and customer buying habits have evolved. At the same time, improvements in data collection and analysis have allowed grocery marketing strategies to become highly individualized.

We worked with 84.51, an analytics firm, to identify customer segments for the Kroger Company based on data from 2023. Using clustering techniques, we organized customers into groups, or segments, based on similar characteristics. We identified and profiled four distinct groups of customers. Three segments were characterized by high frequency and spending …

Predicting Hazardous Near-Earth Objects Using Machine Learning For Planetary Defense, John Costa (Student), Lily Popova Zhuhadar (Mentor)

Posters-at-the-Capitol

Predicting Hazardous Near-Earth Objects Using Machine Learning for Planetary Defense

This research develops a machine learning model to classify Near-Earth Objects (NEOs) as hazardous or non-hazardous based on their physical and orbital characteristics, leveraging NASA's dataset of certified NEOs. NEOs, including asteroids and comets, often pass within close proximity to Earth, and while most pose no threat, some have the potential for catastrophic impacts. By using predictive models such as decision trees and random forests, this study aims to prioritize resources for monitoring and mitigation of high-risk objects. The model incorporates key features like velocity, diameter, and proximity to Earth …

Predicting College Student Dropout Rates Using Predictive Analytics, Jenna Wells (Student), Lily Popova Zhuhadar (Mentor)

Posters-at-the-Capitol

This research develops a predictive model to forecast college student dropout rates using RapidMiner™, with the goal of identifying at-risk students early to facilitate timely interventions. Using a Kaggle dataset that includes 4,424 student records and 36 academic, demographic, and socioeconomic features, the study applies machine learning techniques to classify students as either graduates, dropouts, or currently enrolled. The model reveals critical factors influencing dropout rates, such as tuition fees, scholarship status, and second-semester grades. The Logistic Regression model, chosen based on accuracy and performance metrics, shows promising results with a precision of 82.64% and recall of 79.55% for predicting …

Midwest Entrepreneurship Case Competition Page In The Pitch Platform, Zoeanna A. Mayhook, Annette H. Bochenek, O'Neill Terence, Ilana Stonebraker

Libraries Faculty and Staff Supplemental Materials

This is an archived version of the competition page for the 2024 Midwest Entrepreneurship Case Competition, a regional, library-led business case competition held from February 10–24, 2024. The page was hosted on Purdue University’s Pitch Platform, an in-house system for managing case competitions. This page was captured on January 7, 2025.

Collecting Financial Data From Online Sources: Enhancing Large Language Models With Real-Time Search, Yang Li

Department of Information Management and Business Analytics Faculty Scholarship and Creative Works

Timely and accurate access to financial data is crucial for empirical research in accounting and finance. However, current data collection processes are often manual, inconsistent, and difficult to scale. This study asks: How can large language models (LLMs) be effectively used to automate financial data collection? Using design science research methodology (DSRM), the author develops a modular architecture that integrates a real-time search API and auxiliary information processing into LLM workflows. The study applies the model to two tasks: extracting ESG report release dates and identifying customer firm tickers from COMPUSTAT. The system achieves 96% and 95% accuracy, respectively, comparable …

2024-2025 Morehead State University Audit Report, Morehead State University. Accounting And Financial Services Office.

Morehead State University Audit Reports

2024-2025 Audit Report for Morehead State University.

Cybersecurity And Business Analytics: Strengthening Financial And Governmental Digital Defenses, Bushra F. Malik, Ravindar Reddy Gopireddy

Accounting, Business Analytics, Economics, and Finance Department Faculty Articles

The rapid digitization of financial services and federal operations has significantly increased cybersecurity risks. Cybercriminals are continuously evolving their attack methodologies, targeting financial institutions and government agencies to exploit vulnerabilities in digital infrastructures. Business analytics has emerged as a powerful tool in combating these threats by leveraging artificial intelligence (AI), machine learning (ML), and big data analytics to detect, analyze, and prevent cyber threats in real time. This paper explores the convergence of cybersecurity and business analytics, emphasizing their combined role in strengthening threat intelligence, fraud detection, incident response, and regulatory compliance. The research provides insights into emerging security trends, …

The Economic And Environmental Impact Of Shinkansen And High-Speed Rail Infrastructure: A Comparative Analysis Of Economic Growth And Carbon Emissions Reduction, Dillan R. Victory

SPARK Symposium Presentations

The development of Japan's high-speed rail system, the Shinkansen, has played a pivotal role in the country's post-war economic resurgence. Introduced in 1964 with the Tokaidō Shinkansen, this transformative infrastructure investment significantly reduced travel times, bolstered economic activity around station hubs, and facilitated regional development by enabling urban decentralization. This paper explores the long-term economic benefits of high-speed rail, including its impact on land value, business expansion, and carbon emissions. The case study of the Linear Chuo Shinkansen, Japan's latest maglev project, underscores both the economic promise and the political resistance to expansion, particularly in regions such as Shizuoka.

Using …

Llm-Guided Multimodal Information Fusion With Hierarchical Spatio-Temporal Graph Network For Sentiment Analysis, Yujie Jin, Yong Wang, Yuzhe Wang, Qiyang Chen, Bin Hu, Yanling Han, Chaoyin Ma, Witold Pedrycz

Department of Information Management and Business Analytics Faculty Scholarship and Creative Works

Multimodal sentiment analysis aims to attain a precise comprehension of emotions by integrating complementary textual, visual, and audio information. However, issues such as sentiment discrepancies between modalities, ineffective integration of multi-modal information, and the intricacy of order dependency significantly constrain the models' efficacy. The authors propose an LLM-guided Hierarchical Spatio-Temporal Graph Network (L-HSTGN). By multimodal large model feature enhancement, bidirectional spatio-temporal joint modeling, and dynamic gate fusion mechanism, they effectively address the aforementioned problems. Firstly, they produce cross-modal emotion pseudo-labels based on the multimodal large model, and the single-modal representation was optimized by combining adversarial regularization. Secondly, they develop a …

Adaptive Pricing Under Information Uncertainty, Charles Chomba Mubari

Beacom School of Business Student Publications

This paper investigates adaptive pricing strategies under conditions of information uncertainty. Using a Bayesian learning framework, we model dynamic pricing decisions and assess performance under varying market conditions. The results demonstrate that adaptive pricing outperforms static pricing in terms of expected revenue and market efficiency.

Affordance-Based Information Technology Sensemaking [Abits], Arvin Mesgari, Chitu Okoli, Ana Ortiz De Guinea

Information Systems and Business Analytics Faculty Works

Information Technology (IT) use gives rise to a wide variety of outcomes. This stems in part from the divergent ways in which individuals understand technology. While the sensemaking literature unveils how meaning is attached to organizational phenomena via cognitive and social processes, it overlooks the discovery dimension of making sense, that is detecting the role of the IT artifact in bringing about outcomes. In other words, there is a need to explain how the IT artifact contributes to technology sensemaking and its outcomes. This paper presents a framework that enables scholars to analyze the IT artifact’s role in technology sensemaking …

The Moderating Role Of Hospital Staffing Levels On The Effectiveness Of Clinical Decision Support Systems In Mitigating Patient Readmission Rates, Youyou Tao, Arindam Brahma, Kevin Baldwin, Rui Sundrup, Dezhi Wu

Information Systems and Business Analytics Faculty Works

Healthcare staffing shortages and high 30-day readmission rates are pressing challenges in today's healthcare systems. While extensive studies have explored the positive impact of Health Information Technology (HIT) on health outcomes, the effect of hospital staffing on HIT effectiveness, particularly Clinical Decision Support Systems (CDSS), is underexplored. Therefore, we examine whether physician and resident staffing levels moderate the impact of CDSS on 30-day readmission rates. After analyzing data from 1,605 hospitals in the United States from 2017 and 2018, we found that the effect of CDSS implementation in reducing 30-day readmission rates is more pronounced in hospitals with lower bed-to-physician …

Sustainability Gaps: The Role Of Esg Disparities In M&A Performance During The Covid-19 Era, Anastasia Nikolaeva

CMC Senior Theses

My thesis investigates the impact of environmental, social, and governance (ESG) score disparities between acquirer and target companies on cumulative abnormal returns (CAR) in mergers and acquisitions (M&A) from 2018 to 2022, particularly in light of the COVID-19 pandemic. Using Bloomberg and Refinitiv Eikon datasets, I explore whether the ESG delta between merging firms influences financial outcomes, hypothesizing that higher ESG alignment enhances CAR (cumulative abnormal return). My preliminary findings indicate that larger ESG disparities positively affect acquirer CAR but may reduce target CAR, suggesting that ESG alignment benefits vary by stakeholder and merger dynamics. These results highlight the evolving …

Just As Advertised: The Perception And Effectiveness Of Artificial Intelligence In Digital Advertising, Brandon Isem Cáceres

CMC Senior Theses

What do you think when you hear “AI in advertising”? Does it spark intrigue, or does it feel like just another tech buzzword? In today’s fast-paced digital marketing landscape, connecting with consumers is a high-stakes challenge, and artificial intelligence is at the forefront of innovation. From automating campaigns to creating hyper-targeted content, AI promises efficiency and precision—but how do audiences perceive this shift? By analyzing key performance indicators (KPIs) like impressions, click-through rates, and cost-per-click in an an original A/B test, this thesis evaluates the perception and effectiveness of AI-driven advertising strategies. Combining historical insights, case studies, and an original …

The Effect Of The Tcja And Cares Act On Charitable Contributions And The Financial Health Of The Nonprofit Sector, Nathanio A. Bright

CMC Senior Theses

This thesis examines the impact of the Tax Cuts and Jobs Act of 2017 and the Coronavirus Aid, Relief, and Economic Security Act of 2020 on charitable contributions and nonprofit financial health. The standard deduction increase introduced by the TCJA disincentivized middle to low-income earners from making contributions. In March 2020, Congress temporarily increased the AGI limit on charitable deductions while simultaneously offering an above-the-line deduction for all U.S. taxpayers. While earlier studies have analyzed the effect of the TCJA in disincentivizing charitable contributions, no study has examined the moderating effect of the TCJA and CARES Act in affecting contributions …

Cybersecurity Disclosures In The Aerospace And Defense Industry: A Comparative Analysis Of Aerovironment And Industry Peers, Lindsey Veno

Undergraduate Theses, Professional Papers, and Capstone Artifacts

Cybersecurity has become one of the most important topics for companies in every industry, but especially for those in aerospace and defense. With these companies dealing with highly sensitive, governmental data, cyberattacks can lead to serious consequences. In 2023, the Securities and Exchange Commission (SEC) changed the rules regarding cybersecurity disclosures for public companies. These changes required public companies to disclose material cybersecurity incidents within four days and provide more details on how they manage and oversee cyber risks. This paper focuses on how these changes impacted the 10-K cybersecurity disclosures within the aerospace and defense industry, specifically comparing AeroVironment …

Cross Country Analysis Of Leveraged Loan Issuance: A Comparative Case Study, Cristina D. Vasquez Boero

Honors Program Theses

This paper aims to examine the dynamics of the global leveraged loan market through a cross-country analysis of 32,635 loan issuances spanning 133 industries across 29 countries between 2005 and 2024. The study analyzes key loan-level variables; including commitment size, maturity time, facility type, pledge status, priority lien, economic sector, use of proceeds, issue year, and amortization schedule to identify cross-country variation in loan issuance patterns and borrower characteristics, comparing a selected sample of international countries with the United States. The results reveal that the market for leveraged loans has grown significantly over time, specifically due to a higher frequency …

The Usefulness Of The Industry Trade Credit Risk Indicator In The Polish Economic Realities In 2013–2023, Robert Dyrcz, Artur Hołda

Studia i Materiały Wydział Zarządzania Uniwersytet Warszawski

Purpose: The aim of this article is to introduce the methodology for creating a synthetic industry indicator of trade credit risk (PICM Risk Index©), which will be useful in forecasting the number of defaults in economic sectors. In particular, the PICM Risk Index© indicator is to be characterized by the smallest possible forecast error and is to be variable in monthly periods.

Methodology: In the construction of the indicator, the economic situation research of the Central Statistical Office was used. The research hypotheses assumed were that the indicator shows a statistically significant relationship with insolvencies in the sectors …

Ict Technologies: Origins, Development, And Applications In Selected Examples From The Economy And Society, Tomasz Parys

Studia i Materiały Wydział Zarządzania Uniwersytet Warszawski

Purpose: The primary purpose of this paper is to present information and communication technologies, collectively referred to as ICT, as a determinant of the development and functioning of the modern world through the prism of tools, models, concepts and platforms that enable their application. This is accomplished in the article by presenting selected technologies along with illustrating the scope and possibilities of their use.

Methodology: The scope of the research included ICT technologies, their development and evolution, as well as their application in various fields. Extensive source material was collected, with a primary focus on academic publications, including …