Business Commons^™

Cultural Relativism: Addressing Diversity And Expression Of Culture Through Dress, Robert L. Woods, Maureen Archer-Festa, Rachel Raskin, Alyssa Dana Dana Adomaitis

Publications and Research

As America becomes more diverse, so do postsecondary institutions. While they also reflect the world's political, social, and economic climate, institutions of higher learning continuously seek newer and inventive ways to include better culturally diverse students in their programs and campus life. Multicultural education is a set of educational strategies developed to teach students about diverse groups' histories, cultures, and contributions. Moreover, Multiculturalism has become a way of teaching that promotes inclusion, diversity, and democratic learning. If left unaddressed, however, it can breed biases that isolate students, manifest hate crimes, and increase a school's retention rates (Gruman, 2016). Having received …

Artificial Intelligence And Digital Technologies In Finance: A Comprehensive Review, Soudeh Pazouki, Mohamad Jamshidi, Mirarmia Jalali, Arya Tafreshi

Finance Faculty Publications

This study explores the transformative impact of artificial intelligence (AI) and digital technologies on the financial technology (FinTech) industry, highlighting their role in fostering business growth, operational efficiency, and enhanced customer engagement. AI-driven strategies have unlocked new avenues for streamlining workflows, boosting productivity, and expanding financial inclusion by reaching underrepresented populations. However, these advancements also pose challenges, including navigating complex regulatory frameworks and adapting to the rapidly evolving technological landscape. This paper delves into the macroeconomic effects of AI, examining its influence on labor markets, consumer behavior, and organizational success. Furthermore, the paper discusses blockchain applications and their potential to …

Transformative Impact Of Ai And Digital Technologies On The Fintech Industry: A Comprehensive Review, Soudeh Pazouki, Behdad Jamshidi, Armia Jalali, Arya Tafreshi

Finance Faculty Publications

This paper examines the impact of artificial intelligence (AI) and digital technologies on the financial technology (FinTech) industry and demonstrates how AI- enabled strategies are increasing the ability of businesses not only to grow, but also to better serve their customers through operational efficiencies. But as immersive as the technological advancements may be, they present challenges in connection with increasingly complicated licensing regulations and a constantly evolving technological landscape. We examine the way AI and algorithms are streamlining workflows, enhancing productivity and expanding access to financial resources for traditionally under – served populations. The paper also discusses the macroeconomic implications …

Certain Knowledge Of Administrative Decisions Issued By Artificial Intelligence Systems In The Public Sector: A Comparative Analysis, Nayel Musa Alomran, Odai Mohammad Alheilat

All Works

This paper aims to elucidate the matter of certain knowledge pertaining to administrative decisions, those issued by artificial intelligence. It also clarifies the position of the administrative judiciary with regard to the adoption of this presumption and through a comparative analysis of administrative judicial applications in Jor-dan, Egypt, and Morocco. The text addresses the most significant evidence for achieving certain knowledge of an administrative decision – and thereby initiating the appeal period against the appellant. The question at hand is whether the administrative judiciary applies the traditional theory of certain knowledge to its counterpart issued by artificial intelligence systems, especially …

A Bounded Custom Gpt Structures Operational Knowledge For Small-Industry Decision Support, Ikhwan Arief, Alizar Hasan, Nilda Tri Putri, Hafiz Rahmann

Knowledge Engineering and Data Science

Small manufacturing and craft-based firms increasingly use Generative Artificial Intelligence (GenAI) through public chat interfaces, low-cost tools, and informal experimentation. However, these firms often make operational decisions with incomplete records, tacit owner knowledge, fragmented spreadsheets, and limited managerial capacity. Under such conditions, open-ended chatbots may generate fluent but unsafe recommendations by overlooking missing information, contradictory evidence, feasibility constraints, and implementation constraints. This study presents Asisten Cerdas Industri Kecil as a bounded Custom GPT artifact for operational diagnosis, priority selection, and short-horizon action planning in small industries. Using a Design Science Research approach, the study develops a documented artifact corpus comprising …

Complexity, Polycentricity, And Climate Change: An Embedded, Multi-Level Case Study Of A Climate Meta-Network, Timothy Staub

Antioch University Dissertations & Theses

The earth is in crisis, and without urgent, systemic, and collective global action to address the emerging threat of climate change, we will continue to see catastrophic events impacting humanity, threatening our very survival in many regions of the world. Temperatures will rise, ice shelves will melt, seas will rise, crops will fail, water scarcity from drought and new weather patterns will increase and spread, wildfires will accelerate, and food and water insecurity, violence, and the largest human migration in history will ensue. These climate crises will displace over 1.2 billion people by 2050 at a rate currently exceeding 21.5 …

Insights In Adaptation: Examining Self-Reflection Strategies Of Job Seekers With Visual Impairments In India, Akshay Kolgar Nayak, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Significant changes in the digital employment landscape, driven by rapid technological advancements and the COVID-19 pandemic, have introduced new opportunities for blind and visually impaired (BVI) individuals in developing countries like India. However, a significant portion of the BVI population in India remains unemployed despite extensive accessibility advancements and job search interventions. Therefore, we conducted semi-structured interviews with 20 BVI persons who were either pursuing or recently sought employment in the digital industry. Our findings reveal that despite gaining digital literacy and extensive training, BVI individuals struggle to meet industry requirements for fulfilling job openings. While they engage in self-reflection …

Quickque: Enabling Quick Access To Information In User Reviews For Screen Reader Users, Mohan Sunkara, Akshay Kolgar Nayak, Sandeep Kalari, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Efficiently perusing online customer reviews is presently challenging for blind users, who rely on a screen reader that supports predominantly one-dimensional narration of content via keyboard shortcuts. To address this, with restaurant reviews as seminal case study, we developed QuickCue, a browser extension prototype that enables screen reader users to quickly obtain the positives and negatives regarding different aspects of a restaurant (e.g., food quality, hygiene, ambiance), without having to sift through numerous reviews containing redundant information. At its core, QuickCue utilizes a large language model to perform aspect and sentiment-based joint classification of reviews to group them based on …

Adapting Online Customer Reviews For Blind Users: A Case Study Of Restaurant Reviews, Mohan Sunkara, Akshay Kolgar Nayak, Sandeep Kalari, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Online reviews have become an integral aspect of consumer decision-making on e-commerce websites, especially in the restaurant industry. Unlike sighted users who can visually skim through the reviews, perusing reviews remains challenging for blind users, who rely on screen reader assistive technology that supports predominantly one-dimensional narration of content via keyboard shortcuts. In an interview study, we uncovered numerous pain points of blind screen reader users with online restaurant reviews, notably, the listening fatigue and frustration after going through only the first few reviews. To address these issues, we developed QuickCue assistive tool that performs aspect-focused sentiment-driven summarization to reorganize …

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 …

Assessing Environmental Performance Through Environmental Management Initiatives, Green Extrinsic And Intrinsic Motivation, And Resource Commitment In Malaysian Hotels, Ataul K. Patwary, S. Mostafa Rasoolimanesh, Roslizawati C. Aziz, Muhammad U. Ashraf, Md Mahmudul Alam, Shafique U. Rehman

Research outputs 2022 to 2026

The level of dedication that an organization has toward the preservation of the natural environment is reflected in its environmental performance. This study evaluates the role of green extrinsic and intrinsic motivation and resource commitment on Malaysian hotel employees’ environmental performance. It also examines the mediating roles of green extrinsic and intrinsic motivation and resource commitment in the relationship between green management initiatives and hotel environmental performance. Data was collected from the Four- and five-star hotel employees and tested the models and hypotheses of this study by employing partial least squares-structural equation modeling. Green extrinsic and intrinsic motivation significantly influence …

Ensemble Learning Models For Large-Scale Time Series Forecasting In Supply Chain, Minjuan Zhang

Dissertations

Machine learning and AI techniques are transforming supply chain forecasting, driven by the expanding availability of data assets. These advanced methods offer powerful opportunities to optimize management processes, reduce operational costs, and enhance strategic decision-making, which is crucial for enterprise success. However, conventional statistical approaches, such as Autoregressive Integrated Moving Average Models (ARIMA), dynamic regression, and Unobserved Component Models (UCMs)—which have long dominated time series forecasting—often fall short in accuracy and scalability. These traditional models face limitations in batch processing, handling large-scale data, addressing uncertainty-induced disruptions, and synchronizing demand-supply scenarios.

To address these challenges, a novel class of AI-powered ensemble …

Interactive Visualization Workflows For Mitigating Analytical Uncertainty, Kaustav Bhattacharjee

Dissertations

This dissertation takes a process-centric and stakeholder-first perspective for handling analytical uncertainty: the form of uncertainty that confronts data analysts' insight-generation processes in high-consequence decision-making scenarios. The cost of an incorrect decision when data is used for movie recommendations as opposed to when personal data is used to drive insights or when data-driven modeling is used to drive real-time decisions for maintaining the health of a grid are vastly different in terms of consequences. This dissertation looks at analytical uncertainty in two real-world scenarios: i) how sensitive information leakage can be prevented during the open data release process with data …

Shalom In Social Media Marketing Shalom In Social Media Marketing, Jill R. Risner, Thomas Betts

University Faculty Publications and Creative Works

This paper will examine social media and the ways in which it currently does and does not contribute to shalom through an examination of both the platforms themselves as well as the content shared through them. As Christ’s ambassadors in the world and the primary funders of social media, marketers have power and an obligation to consider social media’s impact on shalom in the world and to use it in ways that contribute to shalom. This paper will provide several recommendations of how marketers can do this including posting content that intentionally contributes to shalom, engaging on platforms that support …

Adopting Association Rule Learning For Detecting And Ranking Influential Users On Hashtags, Layal Abu Daher, Islam Elkabani, Rashed Zantout

BAU Journal - Science and Technology

Social Media platforms are networks of relationships in which users are considered as nodes in a graph and relationships between users are considered edges. These graphs symbolize online groups or communities. It has been a challenge for researchers to study the evolution of such communities due to their rapid and dynamic development. The contribution of our work is twofold: (i) studying the effectiveness of a set of Direct and Indirect Influence Measures that identify the factors that urges users to participate in certain communities; (ii) proposing an Association Rule Mining technique to identify influential users on a dataset of a …

Designed For Limb Loss: An Artificial Intelligence-Based Bionic Prosthetic Arm Transition From Simulation To Reality, Amira J. Zaylaa Dr., Imane Haidar, Ziad Doughan, Mohammad Moumnieh, Hamza Mrad, Ali M. Haidar

BAU Journal - Science and Technology

Limb or organ loss of human remains challenging especially in the world of incessant reliance on touch-based screens and tasks. Thereby, patients can barely withstand and cope with the augmenting restrictions that they encounter due to this loss. Modern means and technologies, such as advanced and artificial parts reduced restrictions on patients with disabilities or a lost limb or organ. Hand prostheses, for instance, provided a powerful tool for improving the functional capabilities of human limbs, thereby improving the quality of life of the user. However, patients using prosthetic arms are still encountering numerous problems, such as, suffering from intact …

Digital Twin And Cybersecurity In Additive Manufacturing, Lidong Wang

Journal of Cybersecurity Education, Research and Practice

Additive manufacturing (AM) has been applied to automotive, aerospace, medical sectors, etc., but there are still challenges such as parts’ porosity, cracks, surface roughness, intrinsic anisotropy, and residual stress because of the high level of thermal gradient. It is significant to conduct the modeling and simulation of the AM process and achieve quality products. Digital Twin (DT) can help AM with forecasting defects/errors through simulation and real-time process monitoring. DT is a concept of Industry 4.0, and its digital structure reflects the real-time behaviors of a cyber-physical or physical system. This paper introduces the progress of DT applications in AM, …

Increasing Youth Engagement In Community Heritage And Social Justice Through Implementation Of A Youth Participatory Empowerment Model, Jancarlos Wagner-Romero, Mary Gillis, Lindsay Clemens, Amanda J. Dworak Rowland, Curlinda Mitchell-Blacksheep, Melanie Canaday-Talley

Journal of Multicultural Affairs

Youth in traditionally marginalized communities are often the target of policies and practices without the opportunity to provide input. This article highlights effective strategies to empower youth to become active participants in their communities. Using a Youth Participatory Empowerment Model (YPEM), youth participants from six demographically distinct communities engaged in YPEM-supported activities and strategies to identify and address a need within their community. To gain insight into successful strategies, qualitative data from pre and post implementation focus group interviews and observational field notes informed the conclusions. The participant youth represent tribal, undocumented, rural, suburban, and urban youth from underserved populations. …

Navigating Transdisciplinary Communication: A Graduate Student's Perspective, Sirimuvva Pathikonda, James Lipuma, Cristo Leon

STEM for Success Resources

Discover "Navigating Transdisciplinary Communication: A Graduate Student’s Perspective," a comprehensive exploration of how diverse disciplines converge to tackle complex challenges. This study, presented at WMSCI 2024, employs a Constructivist lens to highlight the co-construction of knowledge, innovative teamwork tools, and practical strategies for research in STEM and beyond. Co-authored by Sirimuvva Pathikonda, MEM, and James Lipuma, Ph.D., the paper underscores the value of Transdisciplinary Communication (TDC) in fostering collaboration, innovation, and holistic problem-solving across fields. Read the full article here: https://doi.org/10.54808/JSCI.22.06.151.

Utilizing Large Language Models To Synthesize Product Desirability Datasets, John D. Hastings, Sherri Weitl-Harms, Joseph Doty, Zachary L. Myers, Warren Thompson

Research & Publications

This research explores the application of large language models (LLMs) to generate synthetic datasets for Product Desirability Toolkit (PDT) testing, a key component in evaluating user sentiment and product experience. Utilizing gpt-4o-mini, a cost-effective alternative to larger commercial LLMs, three methods, Word+Review, Review+Word, and Supply-Word, were each used to synthesize 1000 product reviews. The generated datasets were assessed for sentiment alignment, textual diversity, and data generation cost. Results demonstrated high sentiment alignment across all methods, with Pearson correlations ranging from 0.93 to 0.97. Supply-Word exhibited the highest diversity and coverage of PDT terms, although with increased generation costs. Despite minor …

Flood Risks Surge In Unexpected Places, Leaving Americans Unprepared And Uninsured, Genna Y. Contino

Capstones

As weather patterns become more unpredictable, the amount of uninsured property loss is expected to soar – disproportionately impacting communities of color in the U.S. Hurricane Helene, which devastated the western North Carolina mountains, demonstrates this trend. Experts say boosting insurance literacy and updating floodplain maps will better prepare the country as it navigates a changing climate.

https://docs.google.com/document/d/e/2PACX-1vSApu2Io6-IjMynum2d3IakyOV2AZysgayw8f4ypNID6dF0j06vumogvy6tJ9XPvqhXtC76fs8ZHre9/pub

Mathematics In Amusement Parks, Kacey Laumann

Honors Projects

This project focuses specifically on the Walt Disney World Park, Magic Kingdom. I started by collecting data through the MyDisneyExperience app. By recording the data, I was then able to create polynomial functions to the fifth the degree. Each attraction received a function which allowed me to predict the wait times for that attraction. Then, by graphing the functions and analyzing the graph using calculus the “best time” and “worst time” to go to the attraction were found. After the analysis the information is used to build a unique schedule for a guest. Then the guest receives this schedule after …

Using Llms To Establish Implicit User Sentiment Of Software Desirability, Sherri Weitl-Harms, John D. Hastings, Jonah Lum

Research & Publications

This study explores the use of LLMs for providing quantitative zero-shot sentiment analysis of implicit software desirability, addressing a critical challenge in product evaluation where traditional review scores, though convenient, fail to capture the richness of qualitative user feedback. Innovations include establishing a method that 1) works with qualitative user experience data without the need for explicit review scores, 2) focuses on implicit user satisfaction, and 3) provides scaled numerical sentiment analysis, offering a more nuanced understanding of user sentiment, instead of simply classifying sentiment as positive, neutral, or negative.

Data is collected using the Microsoft Product Desirability Toolkit (PDT), …

Safeguarding Virtual Healthcare: A Novel Attacker-Centric Model For Data Security And Privacy, Suvineetha Herath, Haywood Gelman, John Hastings, Yong Wang

Research & Publications

The rapid growth of remote healthcare delivery has introduced significant security and privacy risks to protected health information (PHI). Analysis of a comprehensive healthcare security breach dataset covering 2009-2023 reveals their significant prevalence and impact. This study investigates the root causes of such security incidents and introduces the Attacker-Centric Approach (ACA), a novel threat model tailored to protect PHI. ACA addresses limitations in existing threat models and regulatory frameworks by adopting a holistic attacker-focused perspective, examining threats from the viewpoint of cyber adversaries, their motivations, tactics, and potential attack vectors. Leveraging established risk management frameworks, ACA provides a multi-layered approach …

Everyone Brings Something To The Table: A Culturally Sustaining Analysis Of Teacher Candidates’ Mixed Reality Teaching Simulations, Erin Scott

Faculty Publications

Discussions of HBCU students’ content knowledge have centered around developing high impact, asset-based approaches to learning (Williams et al, 2022). So, HBCU teacher preparation providers (TPPs) can also focus efforts on culturally sustaining approaches to developing candidates’ content knowledge and researching how high impact practices, like teaching simulations, can help prepare candidates for classrooms. This exploratory case study uses critical cases (n=2); findings suggest candidates have a developing understanding of content, which forms a solid basis for increasing their knowledge. MRTSs are addressed as a potential high impact, culturally sustaining practice for building candidates’ content knowledge. Further, HBCU TPPs can …

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 …

From Concept To Creation: The Role Of Generative Artificial Intelligence In The New Age Of Digital Marketing, Andrew Smith, James Hutson

Faculty Scholarship

Artificial intelligence (AI) has been extensively used in digital marketing. Still, the recent advances in generative AI (GAI) have revolutionized social media marketing and content creation, lowering barriers that once restricted high-quality design to professionals well versed in expensive and complex software like Adobe Suite. GAI tools enable anyone, from students to marketers, to generate logos, branding, and multimedia content without extensive training. This shift has empowered more people to engage in creative expression, expanding the pool of ideas and creativity. However, the abundance of AI-generated content raises questions about the evolving definition of “art” and the emergence of a …

Generative Artificial Intelligence In Business Higher Education: A Focus Group Study, Xuenan Huo, Keng Siau

Research Collection School Of Computing and Information Systems

This research investigates the opportunities and challenges of integrating generative artificial intelligence (GenAI) into business higher education, drawing insights from an asynchronous focus group research study with doctoral students who serve dual roles as both learners and educators. Key opportunities identified through thematic analysis include knowledge acquisition, intelligent co-ideation, supportive augmentation, and personalized learning. Challenges identified include AI trustworthiness, cognitive dependency, human value, policy and instruction, assessment integrity, and identity management. This study clarifies GenAI’s specific role in business education and provides practical insights for effectively integrating GenAI to enhance learning outcomes and address emerging challenges. An analysis theory on …

Meta-Entrepreneurship: An Analysis Theory On Integrating Generative Ai, Agentic Ai, And Metaverse For Entrepreneurship, Yingying Zhang, Keng Siau

Research Collection School Of Computing and Information Systems

Metaverse entrepreneurship has emerged as an innovative topic alongside the development of generative AI, agentic AI and metaverse. This study conceptualizes meta-entrepreneurship as a novel form of entrepreneurial activity that enables value creation within virtual and physical realms and proposes an analytical theoretical framework based on a systematic literature review, observations, and focus group study. Our framework is structured around three layers (infrastructure, content, and experience) and two domains (metaverse-based operational domain and AI-based production domain), aims to conceptualize “what is meta-entrepreneurship” and identify new possibilities. The research highlights the multifaceted impact of meta-entrepreneurship on individuals, corporations, industries, societies, and …

A Full-History Network Dataset For Btc Asset Decentralization Profiling, Ling Cheng, Qian Shao, Fengzhu Zeng, Feida Zhu

Research Collection School Of Computing and Information Systems

Since its advent in 2009, Bitcoin (BTC) has garnered increasing attention from both academia and industry. However, due to the massive transaction volume, no systematic study has quantitatively measured the asset decentralization degree specifically from a network perspective.In this paper, by conducting a thorough analysis of the BTC transaction network, we first address the significant gap in the availability of full-history BTC graph and network property dataset, which spans over 15 years from the genesis block (1st March, 2009) to the 845651-th block (29, May 2024). We then present the first systematic investigation to profile BTC's asset decentralization and design …