Artificial Intelligence and Robotics Commons^™

Customizing Ai Strategies Across Multiple Generations, Matthew Harrer

Theses

This project investigates how artificial intelligence can help brands and marketers connect more effectively with Generation X, Millennials, and Generation Z. The literature review lays the groundwork that focuses on consumer behaviors and the integration of AI into digital marketing practices for each generation. The second part of the project involves a secondary data analysis of 21 recent marketing surveys and reports that explores topics related to trust, personalization, and social media. By integrating the findings into an insightful guidebook, marketers will be able to maximize these insights into clear actionable strategies.

Exploring The Potential Of Large Language Models (Llms) To Simulate Social Group Dynamics: A Case Study Using The Board Game "Secret Hitler", Kaj Hansteen Izora, Christof Teuscher

Northeast Journal of Complex Systems (NEJCS)

This study explores the capacity of large language model-powered agents to simulate human-like behavior in multi-agent social systems. Using Secret Hitler — a hidden-role board game centered on trust, deception, and strategic communication — we evaluate how LLM agents navigate dynamic group interactions. Our findings show that agents exhibit human-like behaviors, including strategic temporal adaptation, contextual reasoning, and complex social cognition such as theory of mind and implicit coordination. Notably, 85% of agent decisions factored in at least two other players’ mental states, highlighting their capacity for multi-agent mental state inference. However, they struggled with key aspects of human gameplay, …

Alibaba: Building Advanced Intellectual Property Governance For E-Commerce Marketplaces, Liang Chen, Sin Mei Cheah, Can Huang, Guoqiao Liu

Asian Management Insights

How the global e-commerce powerhouse harnessed artificial intelligence (AI) to balance innovation and intellectual property (IP) rights protection.

Thriving In The Age Of Ai: Navigating Ai Identity Threat Through Ai Job Crafting, Yuming He

Theses and Dissertations in Business Administration

As artificial intelligence (AI) technologies like GenAI tools increasingly reshape the workplace, employees increasingly face threats to their work identity. Grounded in the identity threat response model and job crafting theory, this study investigates how AI identity threat influences employee AI job crafting behaviors and how these behaviors, in turn, affect vitality and learning. Using survey data from 521 full-time employees who actively engage with AI tools, the results indicate that AI identity threat stimulates both AI approach job crafting and AI avoidance job crafting. AI approach crafting enhances both vitality and learning, while AI avoidance crafting only supports vitality. …

Predicting Consumers’ Purchase Intention Of Browsed Products: A Study Based On Eye‑Tracking, Feiyan Jia, Choon Ling Sia, Yani Shi, Fiona Fui-Hoon Nah, Keng Siau

Research Collection School Of Computing and Information Systems

Predicting consumers’ purchase intention of browsed products enables sellers to implement nuanced promotion strategies to stimulate purchase. But how can we predict consumers’ purchase intention of browsed products? Our research demonstrates that consumers’ eye movement data collected when they browse products can serve this aim. We train and test the prediction model using logistic regression and random forest algorithms. Using data collected in a laboratory experiment, our empirical results show that both algorithms perform much better than a random guess, and the logistic regression performs slightly better than the random forest. Our findings imply that eye movement data enable sellers …

Who Should Take Responsibility For Artificial Intelligence Actions And Outcomes? Perception Of Auditors As Users Of Ai Systems, Hanh Hoang Le

Doctoral Dissertations

As artificial intelligence (AI) systems become increasingly embedded in auditing processes, questions arise regarding how professional auditors perceive and allocate responsibility for AI-assisted decisions. This study investigates the effects of AI explainability and auditors’ perceived autonomy on perceived responsibility in the context of audit decision-making. Drawing on theories of moral responsibility and professional judgment, the study employs a 2x2 experimental design using hypothetical audit scenarios to manipulate levels of AI explainability and auditors’ autonomy. Hierarchical regression analysis reveals that perceived autonomy statistically significantly increases auditors’ perception of responsibility for AI-assisted decisionmaking, whereas AI explainability is not a significant predictor. Additionally, …

First Annual Advances In Business Education Conference 2025 Proceedings, Kelsey Metz, Joshua Ray

Advances in Business Education (ABE) Conference Proceedings

Conference Overview: The First Annual Advances in Business Education (ABE) Conference was held on May 16, 2025, at Lincoln Memorial University in Harrogate, Tennessee. Hosted by the LMU School of Business, the ABE Conference was established to promote teaching excellence through innovation and collaboration in business education. With a focus on fostering meaningful dialogue among educators, researchers, and students, the conference welcomed participants from across disciplines and institutions. The event was structured around three key tracks:

Pedagogy & Teaching Excellence: Showcasing innovative teaching methods and strategies for enhancing student learning and engagement.

Business Research: Presenting research focused on advancing knowledge …

Deepfakes On Trial: Developing A High-Accuracy, Court-Admissible Ai Pipeline For Deepfake Detection In Corporate Fraud Litigation, Aiden J. Green

Honors College Theses

As deepfake technology advances, cybercriminals are increasingly using AI-generated videos and audios to impersonate executives and carry out sophisticated CEO fraud schemes. These synthetic forgeries target human trust and corporate communication systems, creating an urgent need for forensic tools capable of authenticating digital evidence with legal accuracy. This thesis presents a forensic-grade AI deepfake detection pipeline designed for this purpose, emphasizing courtroom admissibility, reproducibility, and evidentiary integrity. Built entirely with free, opensource tools, the framework combines metadata analysis, AI-powered spectrogram analysis, neural artifact detection, and facial manipulation recognition into a transparent workflow that accurately identifies synthetic media. It was trained …

Computer Vision In Soccer: Yolov11 Analytics Engine For Quantifying Game Strategy, Connor S. Maurer

Data Science Undergraduate Honors Theses

Single-shot object detection capabilities significantly reduce computational overhead for real-time computer vision in sports analytics at 60 FPS. YOLO11’s lightweight CNN gives promising accuracy while meeting the low-latency demand of dynamic soccer matches. As data-driven approaches take over the sport of soccer, efficient player tracking systems become critical for informing coach’s strategies. I prototype the ETL (Extract, Transform, Load) process of data collected from a single- shot detection program and evaluate its viability for estimating player fatigue. YOLO11 detects players, the ball, and other characteristics, with the output transformed by homography to estimate the positions in the real world. These …

Analytics Insights From Text: Machine Learning, Ai, And Sentiment Analysis On Beige Books, Charlie Smith

Graduate Theses and Dissertations (2019 - present)

Business analytics is about drawing actionable insights from data. These distinct but connected essays represent a novel approach to explore how natural language processing (NLP) advances and machine learning can transform unstructured text data into actionable conclusions. Essay 1 provides a broad framework. Essay 2 strengthens the sentiment analysis with the most recent artificial intelligence methodologies for capturing nuanced sentiment in complex texts. Essay 3 applies those insights to forecast recessions using topics that can be readily interpreted and applied.

The research demonstrates how these methodologies can be applied to enhance understanding of the same dataset, Beige Books. Published by …

Autonomous Intelligence In Fashion: A Comprehensive Analysis Of Agentic Ai Across The Fashion Ecosystem, Andrew Burnstine

Faculty and Staff Publications & Presentations

The fashion industry is undergoing a paradigm shift with the emergence of agentic artificial intelligence (AI), a sophisticated class of intelligent systems exhibiting autonomous decision-making, continuous learning, and adaptive action with minimal human intervention. Moving beyond traditional AI applications in fashion focused on predictive analytics, generative tools, and supervised automation, agentic AI introduces a transformative paradigm wherein intelligent agents proactively navigate the complexities inherent in design, manufacturing, supply chain optimization, and consumer personalization. This paper presents a comprehensive exploration of the evolving role of agentic AI across the multifaceted fashion ecosystem, offering an in-depth analysis of its technological underpinnings, operational …

Perceptions Of Employability With Ai Skills, Brandy Whitford, Patrick J. Cooper

Student Publications and Presentations

Artificial intelligence (AI) is making AI proficiency a key factor in hiring and career advancement. By late 2023, 75% of knowledge workers integrated AI into their workflows, with 92% reporting increased productivity and creativity (Kimbrough, 2024). Employers are adapting—66% prefer candidates with AI expertise, and 77% consider AI skills essential for career growth (Microsoft & LinkedIn, 2024). However, hiring biases related to AI-skilled applicants remain underexplored, particularly concerning gender disparities in employability perceptions. This study examines how AI-related skills influence perceived employability and whether these perceptions vary based on applicant gender. Specifically, it explores whether AI-skilled female applicants receive higher …

A Machine-Learning Tool-Supported Methodology For Nonprofit Donor Analysis, Corbin Weiss

Campus Research Month

We developed a machine-learning tool-supported methodology for modeling the nonprofit donor relationship. This approach was demonstrated in the case of a US-based nonprofit. Conclusions were drawn from this example and tool-support provided for use by other nonprofits.

Enhancing Metacognitive Competencies Through Human-Centered Ai: The Role Of Custom-Trained Intelligent Agents In Workforce Upskilling, James Hutson

Faculty Scholarship

This editorial examines the integration of human-computer intelligent interaction (HCII), specifically through human-centered artificial intelligence (AI) and custom-trained intelligent agents, to foster metacognitive competencies critical for workforce upskilling. With 59% of the workforce projected to require substantial upskilling by 2030, developing personalized AI models tailored to individual cognitive and learning profiles presents an innovative pathway. These custom-trained agents leverage human-computer interaction (HCI) technologies and machine learning methodologies to enhance understanding of one’s own learning processes-metacognition-thus empowering individuals to optimize their future learning and adaptability. This approach not only enhances the individual’s ability to engage effectively with complex tasks in the …

The Impact Of Ai Usage On Employee Work Outcomes: The Mediating Roles Of Personal Control And Job Insecurity And The Moderating Role Of Ai Trust, Tiantian Wang

Dissertations and Theses Collection (Open Access)

The widespread application of artificial intelligence (AI) technology in the workplace offers significant potential for process optimization andperformance improvement. However, the psychological mechanisms throughwhich AI usage affects employee outcomes remain underexplored. To address this gap, the present study investigated a sample of 170 employees froma media company in China, utilizing a three-wave longitudinal survey design. Specifically, this study examined how AI usage influenced employee creativity and task performance improvement through two mediatingmechanisms: the enhancement of personal control in problem-solving and the elicitation of job insecurity. Furthermore, the moderating role of trust in AI inthe relationship between AI usage and job …

The Impact Of Artificial Intelligence On Fashion And Retail Efficiency: A Strategic Analysis, Andrew Burnstine, Raouf Ghattas

Faculty and Staff Publications & Presentations

No abstract provided.

Artificial Intelligence In Decision-Making: Literature Review, Najm A. Kh. Alhatimi Aleessawi, Leila Djaghrouri

Journal of the Association of Arab Universities for Research in Higher Education مجلة اتحاد الجامعات العربية للبحوث في التعليم العالي

In the fast-changing world of artificial intelligence (AI), the relationship between technology and decision-making has become a central area of study. Over the past five years, numerous papers have been published examining how AI methods are applied to decision-making processes across various industries. This article aims to highlight the key potential of artificial intelligence to enhance decision-making. It does so by systematically reviewing the literature on the role of AI in improving decision-making, particularly studies published between 2020 and 2024. The review consolidates the main findings from articles in renowned databases such as Google Scholar, Scopus, and IEEE Xplore, offering …

The Role Of Artificial Intelligence In Transforming Physical And Online Fashion Retail: Enhancing Experiences, Driving Sustainability, And Fostering Innovation, Andrew Burnstine

Faculty and Staff Publications & Presentations

This study explores the transformative role of artificial intelligence (AI) in revolutionizing the fashion industry, with a focus on enhancing consumer experiences, promoting sustainability, and driving innovation in retail. It examines AI applications in personalized recommendations, virtual try-ons, and supply chain optimization, while also addressing societal implications. Sustainability is a central theme, highlighting how AI minimizes overproduction, enables circular fashion, and encourages conscious consumerism. Case studies, such as Nike’s AI-powered retail stores and Lynn University’s Surreal Fashion Show, demonstrate practical applications and innovations during the COVID-19 pandemic. This research synthesizes insights from reports by The Business of Fashion and McKinsey …

Why Ai’S Role In Advancing Sustainability Is Underestimated, Lipika Bhattacharya

CCX Research

AI has quietly, but powerfully, woven itself into the fabric of our everyday lives. Yet, AI's potential impact on creating a more sustainable world is undervalued. The author examined artificial intelligence's (AI) role in advancing sustainability. She outlined how AI can be applied in various domains such as agriculture, water management, industry, urban planning, and biodiversity conservation for transformative effects.

Exploring Intelligent Manufacturing: How Artificial Intelligence Affects Productivity And Labor Demand At The Enterprise Level, Jie Gu

Dissertations and Theses Collection (Open Access)

Manufacturing is a cornerstone of national economic health and social stability, yet it faces challenges such as declining profits, rising labor costs, and an aging workforce. In China, the manufacturing sector is undergoing a critical transformation, driven by technological advancements like artificial intelligence (AI) and the push for intelligent manufacturing. This study explores how AI revitalizes the manufacturing sector by enhancing enterprise productivity and reshaping labor demand, with a focus on quality inspection processes. Using a leading bearing factory as a case study, the research employs econometric models, A/B testing, and interviews to quantify AI’s impact on production efficiency, costs, …

Ai Culture ‘Profiling’ And Anti-Money Laundering: Efficacy Vs Ethics, John W. Goodell, Cal B. Muckley, Parvati Neelakantan, Darragh Ryan

University Research

Using extensive transaction and money laundering detection data, at a globally important financial institution, we investigate the efficacy of including facets of national culture in formulating anti-money laundering predictions. For corporate and individual accounts, Hofstede individualism scores of the country in which a customer is resident, or from which a wire is sent/received, are of first-order importance in the detection of money laundering. When combined with account and transaction data; as well as even a proprietary institutional algorithm, individualism scores continue to determine the models’ predictive performances. The efficacy of cultural profiling in money laundering detection underscores the need for …

A Review Of Artificial Intelligence, Algorithms, And Robots Through The Lens Of Stakeholder Theory, Michael J. Matthews, Su Runkun, Lindsey Yonish, Shawn Mcclean, Joel Koopman, Kai Chi Yam

Management Faculty Publications

With the arrival of the Fourth Industrial Revolution, intelligent machines are affecting the daily lives of multiple organizational stakeholders. However, despite the continued expansion of intelligent machines in society, management scholarship has generally lagged, and current frameworks are under-equipped to offer meaningful guidance regarding the intersection of intelligent machines and organizations. We address this issue via a multidisciplinary review and a novel framework of intelligent machines and value creation. First, we discuss the characteristics of intelligent machines (i.e., autonomy, learning, inscrutability, and materiality) and how variation in these characteristics impacts their affordances and, subsequently, the value offered to stakeholders. We …

The Impacts Of Artificial Intelligence In Radiology, Misty Farmer, Wendy Trzyna

Theses, Dissertations and Capstones

Introduction: There has been significant growth in the use of Artificial Intelligence (AI) in the healthcare industry, especially in Medical Imaging. Radiology has been the clear frontrunner in the adoption of AI in medicine, due in part to the massive amount of digital data available for use in Deep Learning (DL) AI integration has the potential to solve multiple challenges in radiology, address workload issues and transform the field.

Purpose of the Study: The purpose of the research was to evaluate the impact of implementing Artificial Intelligence in radiology to determine if these technologies have had an impact …

Successfully Navigating The Disruption Ai Will Bring To Survey Research, David M. Rothschild, Trent D. Buskirk, Stephanie Eckman, D. Sunshine Hillygus, Frauke Kreuter, David Lazer

Information Technology & Decision Sciences Faculty Publications

Surveys are a core methodological tool in government, industry, and academia, providing essential data for theory development and evidence-based decision-making. As artificial intelligence continues its rapid advancement, it stands to fundamentally transform the entire survey lifecycle - from design and administration to analytics and reporting. Previous transitions to new technologies, such as telephone, internet, and non-probability surveys, led to divisions within the survey research community with real consequences for both the trajectory of research and trust in the industry. We believe the survey community should take proactive steps now to avoid similar challenges with AI integration. Specifically, our paper examines …

The Influence Of Generative Artificial Intelligence On Leadership: An Exploration Of Technology Professionals' Perceptions Regarding Leadership, Adaptation, And Organizational Culture In The Digital Age, Paul Thomas Herdman

Theses, Dissertations and Capstones

The emergence of generative artificial intelligence (GenAI) has introduced new complexities for organizational leadership, requiring technology professionals to adapt in real time to evolving digital tools, strategic demands, and cultural dynamics. Although prior research has examined AI’s broad influence on business processes, few studies have explored how technology leaders experience and interpret the leadership challenges and opportunities arising from GenAI. This qualitative dissertation addressed that gap by investigating the perceptions of senior technology professionals regarding GenAI’s influence on leadership roles, competencies, decision making, and organizational culture. Using Lanigan’s (1977) phenomenological method of human science, this study explored the lived experiences …

The Integration Of Big Data In Fintech: Review Of Enhancing Financial Services Through Advanced Technologies, Soudeh Pazouki, Mohammad B. Jamshidi, Mirarmia Jalali, Arya Tafreshi

Management Faculty Publications

Big data analytics is revolutionizing the FinTech industry, offering new opportunities for real-time decision-making, personalized financial services, and improved risk management. By leveraging advanced technologies like machine learning and artificial intelligence, financial institutions can efficiently detect fraud, predict market trends, and create innovative solutions tailored to customer needs. Big data also plays a critical role in promoting financial inclusion through alternative credit scoring models, providing access to credit for underserved populations and fostering broader participation in the financial system.

However, the integration of big data into FinTech is not without its challenges. Issues such as data privacy concerns, regulatory complexities, …

Ally With Ai: An Icebreaker To Unlock Career Aspirations For Online Or Hybrid Organizational Behavior Cohorts, Jyro B. Triviño

Leadership and Strategy Faculty Publications

Modern organizational behavior classroom, which are increasing in size, diversity, and complexity, are shifting to online and hybrid learning environments, challenging the use of traditional icebreaker activities. This paper introduces a 15-minute icebreaker designed to address these issues while integrating the principles of Kolb's experiential learning theory and fostering social capital through peerr engagement in an online setting. By leveraging the availability of generative AI, students prompt a template code to unlock their career aspirations and stimulate social connections among their classmates. This provides an innovative teaching model for meeting the foundational icebreaker goal while serving a suitable tool for …

Artificial Intelligence In Radiology, Olivia Sweeney

Theses, Dissertations and Capstones

Introduction: Artificial intelligence (AI) has increasingly transformed radiologic practice by improving diagnostic accuracy, streamlining workflows, and reducing interpretation errors. As AI integration has expanded across imaging modalities, questions have emerged regarding its effectiveness compared to traditional radiologist-only interpretation.

Purpose of Study: The purpose of this study has been to evaluate the impact of AI-assisted radiology on diagnostic accuracy, efficiency, and error reduction, while also assessing clinician perceptions of AI as a collaborative tool in imaging analysis.

Methodology: This qualitative study has used a systematic review of peer-reviewed literature published between 2015 and 2025, following PRISMA guidelines, combined with an interview …

Fares On Fairness: Using A Total Error Framework To Examine The Role Of Measurement And Representation In Training Data On Model Fairness And Bias, Patrick Oliver Schenk, Christoph Kern, Trent D. Buskirk

Information Technology & Decision Sciences Faculty Publications

Data-driven decisions, often based on predictions from machine learning (ML) models are becoming ubiquitous. For these decisions to be just, the underlying ML models must be fair, i.e., work equally well for all parts of the population such as groups defined by gender or age. What are the logical next steps if, however, a trained model is accurate but not fair? How can we guide the whole data pipeline such that we avoid training unfair models based on inadequate data, recognizing possible sources of unfairness early on? How can the concepts of data-based sources of unfairness that exist in the …

Artificial Intelligence And Environmental Sustainability: Review And Research Directions, Troy Strader, Yu-Hsiang (John) Huang, Yu-Ju Tu

Journal of International Technology and Information Management

Environmental sustainability is one of the most important and complex issues currently facing our global society. One solution to some aspects of this problem could come from artificially intelligent systems and data analytics methods. The objective for this study is to identify the range of recently published research that addresses issues involving the convergence of artificial intelligence (AI) and environmental sustainability. A systematic literature review produced a sample of 62 journal articles from 2018-2024 that were each categorized into one of six research themes that included studies of AI and the ways in which it impacted natural resources, energy and …