Business Intelligence Commons^™

Development Of A Personal Health Recommendation System Based On Data And Machine Learning To Improve User Wellbeing, Eliyah Acantha Manapa Sampetoding, Andi Alisha Faiqihah, Yulita Sirinti Pongtambing

Jurnal Administrasi Bisnis Terapan

The development of personal health recommendation systems has become a significant focus of research, along with the increasing need to improve user well-being. This research critically examines options in data and data mining and Machine Learning to support the establishment of systems to recommend better and improved healthcare services. Drawing on the results of a systematic review of past literature, the study shows that the application of Machine Learning algorithms in disease opinion learning, health condition classification, and demographics is emerging as a prospect for driving clinical decisions. Various models, from Deep Learning to traditional machine learning models such as …

Employee Engagement In Corporate Sustainability Initiatives: An Empirical Comparison Of Conventional And Modern Working Environment Practices, Ahmad Mansour, Hind Al-Ahmed, Ahmad Shajrawi, Khaled Alshaketheep, Muhammad Alshurideh, Arafat Deeb

An-Najah University Journal for Research - B (Humanities)

Objective: The study targets the investigation of Employee Engagement differences across Traditional and New work forms in Corporate Social Initiatives together with workplace practices that boost Sustainable Project Engagement. Methodology: The authors used a mixed-methods design approach in their research. A survey with 300 sustainable project personnel either working full-time or part-time collected quantitative data for analysis. Thirty semi-structured interviews comprised both employee and managerial personnel to collect qualitative data. The evaluation of workplace practices like flexibility and autonomy and communication & leadership on employee engagement was conducted through regression analysis. Researchers employed thematic analysis on interview data for the …

The Media Report: Media & Entertainment Data In America 2019 To 2025, Nelson Granados, Amy Zwagerman, Dejuan Oliver

Graziadio Working Paper Series

No abstract provided.

Manage External And Internal Threats To Commercial Spaces, Alan Saquella

Publications

Securing commercial buildings is a multifaceted challenge that demands a comprehensive and proactive approach. From office complexes and retail hubs to industrial facilities and healthcare institutions, these spaces serve as critical pillars of commerce, administration, and service delivery. Protecting them requires a blend of physical safeguards, advanced technologies and well-defined operational protocols.

A Bibliometric Analysis Of The Pygmalion Effect In Organization Studies, Perihan Senel Tekin, Fevziye Bekar, Duysal Askun Celik

Journal of Global Business Insights

This research aims to examine the literature on the Pygmalion effect, which is expressed as a self-fulfilling prophecy in the context of management organization from a bibliometric perspective. In this context, all relevant publications in the Web of Science database were scanned between 01-06.06.2024. In the first and second searches with the words Pygmalion, Pygmalion effect, Pygmalionism, management, and organization, a total of 27 research articles were subjected to content analysis within the scope of a systematic review. As a result of the content analysis, it was seen that although the Pygmalion effect has been found in …

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. …

Chief Executive Officers, Accountability And Hidden Violations, Alan Saquella

Publications

Corporate governance demands transparency, ethical leadership and accountability from Chief Executive Officers (CEOs). However, numerous cases suggest that CEOs often wield significant influence over what is reported to their boards of directors, particularly when it comes to internal misconduct, regulatory violations, and criminal activity. This lack of transparency raises serious concerns about ethical and legal obligations, as well as the effectiveness of board oversight.

De-Dollarization And South Asia: Challenges And Opportunities For Nepal In A Multipolar Currency World, Keshav Bhattarai, Ambika P. Adhikari

Himalayan Research Papers Archive

The United States dollar’s dominance as the global reserve currency, established under the 1944 Bretton Woods system, persists despite the 1971 decoupling of the gold backing to the dollar. Its liquidity, stability, and full support by the US government confer a solid financial security and advantage to the currency, including a universal acceptance of the dollar and a relatively low borrowing cost. Because of these reasons, the US dollar has been able to dominate the global financial markets for the past eight decades. However, the rapidly emerging global political and economic power shifts are challenging the status of the US …

Exploring Generative Artificial Intelligence (Ai) Applications In Fashion: Ethical Concerns In Human-Like Technology, Melissa Kathryn Gonzalez

Faculty Scholarship and Creative Works

No abstract provided.

Insider Risks And The Evolving Role Of Executive Protection Professionals In Cybersecurity, Alan Saquella

Publications

Insider risks have long been a critical concern in corporate security, traditionally encompassing threats from employees, contractors, or third-party vendors with access to sensitive information. However, as digital transformation accelerates, the convergence of physical and cyber threats has created new vulnerabilities. Executive protection (EP) professionals, historically tasked with safeguarding high-profile individuals from physical threats, now find themselves on the frontlines of combating cyber-criminal attacks. Expanding their skill sets to include cybersecurity awareness is no longer optional—it is a necessity.

This article explores insider risks, the growing need for executive protection professionals to adapt, and practical ways they can enhance their …

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 …

A Critical Challenge: Understanding And Addressing Insider Threats, Alan Saquella

Publications

In today’s hyper-connected world, insider threats have become one of the most pressing challenges for organizations. While external attacks like ransomware and hacking often dominate the headlines, insider threats posed by employees, contractors, or others with internal access are equally, if not more, dangerous. Whether arising from malice, negligence or coercion, insiders have unparalleled access to sensitive systems and data, making their actions potentially catastrophic. The critical insider security issues organizations face and the actionable strategies for mitigation are actions that organizations must take.

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 …

Volume 7 (2024) Artificial Intelligence And Responsibility, Arwa Alnajashi, Danielle Derise, Philip L. Frana, David Mcgraw, Amanda Sawyer, Tatjana Titareva, Raafat Zaini, Allie Zombron

International Journal on Responsibility

The seventh volume of the International Journal on Responsibility (IJR) arrives at a crucial moment in the evolution of artificial intelligence and its integration into our academic and social fabric. As we witness the rapid advancement and deployment of AI systems across various domains, this special issue examines the multifaceted dimensions of responsibility surrounding AI technology, with a particular focus on its role in higher education and broader societal implications.

The articles in this volume contribute to our understanding of responsibility through diverse lenses, from classroom implementation to ethical design considerations. Together, they fulfill IJR’s central mission of exploring “Who …

Role Of Emotional Intelligence In Leadership, Sabrena Craft

M.S. in Leadership

No abstract provided.