Business Intelligence Commons^™

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 …

Toward An Ecosystem Of Non-Fungible Tokens From Mapping Public Opinions On Social Media, Yunfei Xing, Justin Z. Zhang, Yuming He, Yueqi Li

Information Technology & Decision Sciences Faculty Publications

As blockchain technology advances, non-fungible tokens (NFTs) are emerging as unconventional assets in the commercial market. However, it is necessary to establish a comprehensive NFT ecosystem that addresses the prevailing public concerns. This study aimed to bridge this gap by analyzing user-generated content on prominent social media platforms such as Twitter, Weibo, and Reddit. Employing text clustering and topic modeling techniques, such as Latent Dirichlet Allocation, we constructed an analytical framework to delve into the intricacies of the NFT ecosystem. Our investigation revealed seven distinct topics from Twitter and Reddit data and eight topics from Weibo data. Weibo users predominantly …

Provision Cfo: Empowering Strategic Financial Excellence For Small Businesses And Entrepreneurs, Cindra Vang

Doctor of Strategic Leadership (DSL) Capstone Abstracts

Project Overview

ProVision CFO offers strategic financial management solutions tailored to the unique needs of entrepreneurs, small businesses, and rapidly growing organizations. This project aims to equip clients with robust financial strategies and actionable insights necessary for sustainable growth, operational excellence, and long-term success. ProVision CFO provides comprehensive financial guidance including fractional CFO and accounting services.

Project Themes

The ProVision CFO framework encompasses three key components designed to optimize financial performance and organizational effectiveness. Component One—Strategic Clarity: Establishing clear financial goals aligned with organizational vision, mission, and values. Component Two—Financial Optimization: Providing accounting services to streamline financial processes and enhance …

Understanding The Determinants Of Blockchain Adoption: An Empirical Study, Amarpreet Kohli, Nihar Kumthekar, Piyush Shah, Rebecca Jauch

Journal of International Technology and Information Management

Blockchain technology (BT) has the potential to enhance security and robustness of transactions through a distributed ledger bookkeeping process. This study employs technology-organization-environment (TOE) framework and threat-rigidity theory (TRT) to examine whether perceived disruption caused by COVID-19 pandemic significantly impacted the adoption of BT, and inclination to adopt BT in the US. The COVID-19 pandemic provided a unique backdrop, as it affected businesses across all industries, sizes, and geographies. Results show a non-significant effect of perceived pandemic disruption on the current stage of BT adoption and intention to adopt BT. However, disruption readiness positively influences the current stage of BT …

The Federal Reserve’S Fight Against Covid-19: A Study Of The Corporate Bond Intervention, Noah Seilgson

Fordham Journal of Corporate & Financial Law

In response to the COVID-19 pandemic, the Federal Reserve (Fed) embarked on an unprecedented mission to stabilize the U.S. economy as businesses shut down. One emergency Fed facility, the Secondary Market Corporate Credit Facility (SMCCF), was used to purchase corporate bonds and corporate bond exchange-traded funds (ETFs) in the secondary market. This extraordinary measure, which injected liquidity into the corporate bond market, aimed to mitigate economic fallout for large companies. Purchasing corporate bonds marked a departure from previous Federal Reserve interventions, but the statutory authority was the same as had been used in past crises: Section 13(3) of the Federal …

Company Districts, C.J. Suglia

Fordham Journal of Corporate & Financial Law

Special districts that are owned or controlled by private entities and act almost uniformly like a company town can be dubbed a “company district.” These special districts, similar to historical company towns, have autonomy over the districts, control the local government, and only have to answer to the state government. Historical company towns like Pullman, Illinois and Hershey, Pennsylvania had almost canonical command over the land within their boundaries. Company districts operate their business similar to a company town—in a city that the private entity controls, but do not have employees living on-site. Company districts benefit by being immune to …

Algorithms In Finance: Balancing First Amendment Protections And Regulation, Yusraa Tadj

Fordham Journal of Corporate & Financial Law

As algorithms become a function of decision-making in the financial sector, policymakers, the judiciary, and academics grapple with regulatory questions. With the increased reliance on algorithms in finance, the Securities and Exchange Commission (SEC) proposed a rule to mitigate potential conflicts of interest that can arise out of financial firms using algorithms. Algorithm users, including financial firms, are finding novel ways to protect algorithm use, such as by offering them First Amendment protections.

This Note considers to what extent algorithms can be considered protected speech amidst the complexity of algorithms and relationship within the financial sector. The Note argues that …

Consumer Financial Data And Non-Horizontal Mergers, Linda Jeng, Jon Frost, Elisabeth Noble, Chris Brummer

Fordham Journal of Corporate & Financial Law

This Article explores the potential competitive implications of non-horizontal mergers where they involve extensive consumer data, including consumer financial data. As data become increasingly central to firm strategy, mergers between data-rich firms, while potentially leading to positive outcomes, can also create market power in ways not entirely accounted for by traditional antitrust theory. The Article considers some of these implications. It introduces new metrics for valuing data sets held by merging firms that could help competition authorities evaluate market impacts more effectively. The Article then suggests potential tools to mitigate anti-competitive effects of data-rich mergers. It advocates for further research …

Confronting Indecision, Lane Allison Murray

ENGS 15.11: Design and Education

This course aims to increase students' understanding of indecision and how to confront it. The class provides insight into how the fear of the unknown holds people back from making decisions and about understanding one's values as a means to combat indecision. Students and teachers alike explore instances of indecision and evaluate their own impulses & thought processes by reflecting on the deeper reasons for their choices. Students will increase their comfort level of asking themselves and their peers questions about the values that guide them and, in doing so, strengthen their relationships with themselves and others.

The Past, Present, And Future Of Adaptive Selling: Toward An Integrative Framework, Nawar N. Chaker, Rhett T. Epler, Gabriel Moreno, Dana Amiri, Elizabeth G. Mcdougal

Marketing Faculty Publications

Adaptive selling represents a notable and influential concept in the marketing literature. Despite being discussed in scholarly research and managerial practice for over forty years and mixed findings about its impact, a comprehensive understanding of the construct of adaptive selling remains missing. To remedy this critical knowledge gap, we conduct a comprehensive review of 188 articles across twenty-seven journals. We combine three approaches in our survey of the literature, including a systematic review, a main path analysis, and a bibliographic analysis. Together, this three-prong review offers profound insights into the state of adaptive selling research by (1) mapping the key …

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 …

Predicting Crises On The African Frontier Stock Markets With Investor Sentiment Indicators: A Machine Learning Approach, David Korsah, Lord Mensah

Journal of International Technology and Information Management

This study examined the predictive ability of machine learning algorithms in identifying crises within African stock markets. The study employed seven distinct machine-learning models, analyzing historical stock prices from eight stock markets, three major sentiment indicators, and the exchange rates of local currencies against the US dollar, with each data spanning from May 1, 2007, to April 1, 2023. Extreme Gradient Boosting (XGBoost) emerged as the most effective algorithm for predicting crises. Historical stock prices and exchange rates were identified as the most critical features for prediction. On the sentiment side, investors’ perceptions of potential volatility on the S&P 500, …

A Conceptual View Of Data For Decision-Oriented Databases: A Knowledge-Driven Approach, Sung-Kwan Kim, Wenjun Wang, Seunghyun Kim

Journal of International Technology and Information Management

Typical database design goes through three levels of data modeling: conceptual modeling, logical modeling, and physical modeling. In particular, conceptual modeling is important since it captures and documents user data requirements. Conceptual modeling serves as a blueprint for designing a database by defining information content to be included in a database. Presently, decision-oriented databases have no well-accepted conceptual modeling approach to apply. While some use conceptual modeling approaches for transaction-oriented databases such as the ER (Entity-Relationship) model, they are not well-suited for decision-oriented databases. It is hard to map from the ER Model to decision-oriented data models. Others attempt to …

Pedagogy In The Age Of Ai: Exploring Generative Ai For Higher Education, Alison Munsch Phd

Journal of International Technology and Information Management

Generative Artificial Intelligence (AI) presents transformative opportunities for higher education, enabling personalized learning, enhanced student engagement, and efficient pedagogical practices. This tutorial-style article guides educators in integrating generative AI into their classrooms through hands-on activities, practical strategies, and reflective exercises. It explores the capabilities of AI tools such as ChatGPT, their applications across disciplines, and the ethical considerations for their use. By cultivating critical thinking and fostering student readiness for AI-driven futures, this article underscores the transformative potential of generative AI in higher education with an emphasis on the academic areas of business analytics, information systems, and computer science.

Surviving And Thriving In The Hybrid Cloud: A Review Of The Current Cloud Computing Landscape, Peter Munsch, Alison Munsch

Journal of International Technology and Information Management

Background and Purpose

Both academic and industry institutions have increasingly migrated essential services to public cloud providers (e.g., Microsoft, AWS, Google) with mixed outcomes. Some industry leaders attempted to fully replace their on-premises data centers with public cloud services, a move not advised without thorough performance and cost analyses (Potel, 2023). Despite some organizations pulling back from the “Cloud First” strategy, the public cloud services market continued to grow, with revenue increasing by approximately 20% year-over-year since 2020 and surpassing half a trillion dollars in 2022 (IDC Worldwide Semiannual Public Cloud Services Tracker, 2H 2022). Cloud technologists suggested that hybrid …

Predicting Global Healthcare Supply Chain Delays: A Machine Learning Approach Leveraging Country-Level Logistics Metrics, Jeevan Sai Gali, Nima Molavi, Sepideh Alavi

Journal of International Technology and Information Management

In global healthcare logistics, ensuring the timely delivery of medical commodities is critical, particularly in low- and middle-income countries characterized by infrastructural limitations and operational uncertainties. This research introduces an advanced, data-driven predictive framework designed to forecast delivery delays by synthesizing granular, internal shipment-level data from the USAID Global Health Supply Chain Program (GHSC-PSM) with external country-level logistics capabilities indicators derived from the World Bank’s Logistics Performance Index (LPI). Rather than relying on retrospective trend analyses, this study employs machine learning algorithms such as Random Forest, XGBoost, Support Vector Machines (SVM), and Multi-Layer Perceptron (MLP) to detect …