Business Intelligence Commons^™

Ai And The Metaverse In Business Strategy, Emma M. Han, Emma Nguyen

Student Scholar Symposium Abstracts and Posters

The Metaverse has quickly become an important part of the future of the business world. Mainstream companies like Walmart, Toyota, Nike, and many others have established a presence with virtual goods (NFTs), virtual spaces for consumers to interact, and employees to collaborate and train. Yet there is little research into Metaverse strategies that are efficient and sustainable over time. With the rise of AI, businesses now have the opportunity to integrate AI and the Metaverse as complementary technologies, reshaping their strategies for innovation and competitive advantage. We researched the top 500 global brands to uncover lessons from entry approaches taken. …

Analytics & Insights Internship At Market Performance Group, Ava Mccrary

Information Systems Undergraduate Honors Theses

An Honors Thesis discussing the growth of analytics in the corporate world.

Perceptions Of Artificial Intelligence In Healthcare: A Qualitative Study Among Physicians And Nurses In Florida, Aaron Miri

MUSC Theses and Dissertations

This investigation will leverage participant focus group interviews with 32 clinicians (16 nurses / 16 physicians) to study what, if anything, is inhibiting AI adoption across the hospital. Specific physicians will be sourced across the key service lines of primary care, oncology, cardiology, behavioral health, and emergency department medicine, as these tend to be patient volume driven and thus have the maximum amount of potential for positive impact leveraging AI. Nurses in these same departments will be assessed to analyze if there is a similarity or difference between the nursing and physician AI adoption barriers.

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 …

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.

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 …

Comparative Assessment Of Machine Learning And Deep Learning Models For Drug Effectiveness Using Sentiment Analysis, Blessing Ogechukwu Nwogu

Electronic Theses, Projects, and Dissertations

In recent years, the proliferation of online patient-generated drug reviews has created a valuable resource for assessing drug effectiveness and patient satisfaction, with sentiment analysis emerging as a powerful tool for extracting insights from this unstructured data.

This culminating research project conducted a comparative analysis of traditional Machine Learning (ML) and Deep Learning (DL) models for assessing drug effectiveness using sentiment analysis of participant reviews. The research aimed to evaluate the performance of Support Vector Machine (SVM), XGBoost, Random Forest, Long Short-Term Memory (LSTM), and Bidirectional Encoder Representations from Transformers (BERT) models in this context. This culminating research project addressed …

Faids: Artificial Intelligence Developmental Systems Framework For Predicting And Preventing Cyberattacks In Supply Chain Networks, Lordt Becklines

Research & Publications

Cyber threats and attacks disrupt and damages supply chain networks (SCNs), which are complex and interlinked. Current methods to predict and prevent cyberattacks are inadequate and ineffective. This research proposes an AI developmental systems framework (FAIDS) to protect SCNs from cyberattacks. The framework has four components: (1) an AI threat intelligence system; (2) an AI risk assessment system; (3) an AI decision support system; and (4) an AI learning and adaptation system. The framework is tested on a simulated retail SCN. The results show that the framework can predict and prevent cyberattacks and improve the network's resilience and security. The …

Experimental Methods In Predicting Market Drift And Other Portfolio Optimization Factors Using Graph Theory, Perry Harrison Zhang

Computer Science Senior Theses

No abstract provided.

Enhancing Customer Support Operations Through Gpt & Q-Learning: A Model Study, Adam Alidra, Bob O'Brien, Dalton Young

SMU Data Science Review

Abstract. “Growth strategies that are purpose-led, customer-centric, experience-driven, data/AI-enabled, and technology-scaled require new mindsets…” (Cornfield, 2021). What can we take from this? Business growth and customer experience are inextricably tied together. Therefore, thriving, as an organization, is dependent on reimagining enterprise operations through modern, scalable data and AI technologies. Our study aims to enhance support operations with emerging AI capabilities, including OpenAI’s LLM models, built on self-attention mechanism transformer architecture, and tailored for business needs through prompt engineering. Our research uses Markov Decision Process and the Q-learning algorithm to evaluate synthetically created support incidents. Through this set of methods, our …

Balancing Perspectives: Assessing The Integration Of Ai In Academic Support Within Higher Education, Sami Ali

2024 Spring Honors Capstone Projects - Archive

The rapid advancement of A The rapid proliferation of Artificial Intelligence (AI) across various sectors highlights its transformative potential, yet its integration into educational settings raises ethical concerns, particularly regarding its misuse by students. This study conducts a detailed sentiment analysis and systematic literature review to examine the diverse perspectives on AI within education, from both academic and non-academic viewpoints. Utilizing advanced data mining tools to analyze sentiments and trends, this research reveals a complex landscape where optimism about AI’s capabilities is tempered by concerns over ethical implications and potential misuse. The findings contribute to the dialogue on leveraging AI …

Automatic Speech Recognition For Air Traffic Control Using Convolutional Lstm, Sakshi Nakashe

Electronic Theses, Projects, and Dissertations

The need for automatic speech recognition in air traffic control is critical as it enhances the interaction between the computer and human. Speech recognition helps to automatically transcribe the communication between the pilots and the air traffic controllers, which reduces the time taken for administrative tasks. This project aims to provide improvement to the Automatic Speech Recognition (ASR) system for air traffic control by investigating the impact of convolution LSTM model on ASR as suggested by previous studies. The research questions are: (Q1) Comparing the performance of ConvLSTM with other conventional models, how does ConvLSTM perform with respect to recognizing …

An Exploration Of Synergy Evaluation Application Model To Support Implementation On Merger And Acquisition, Jieping Mei

Electronic Theses, Projects, and Dissertations

ABSTRACT

The project focuses on a comprehensive system’s analysis and design of the front-end of the Synergy Evaluation Application Model (SEAM) system for mergers and acquisitions (M&As). The research questions asked are: Q1. How did the SEAM system incorporate the system requirements and design that incorporated the strategic goals and priorities of both the acquirer and the acquiree? Q2. What data sources will the SEAM system rely on, and how does it overcome data integration, automation, visualization challenges? Q3. How will the model identify build in potential synergies, both quantitative and qualitative? The research questions were analyzed through the SEAM …

Experts-Driven Design: A Framework For Measuring Social Influence In Online Social Networks, Shyamala N. Chalakudi, Dildar Hussain Dr., Gnana Bharathy Dr, Dakshinamurthy Kolluru Dr

AMTP Proceedings 2024

In our interconnected and ever-changing social landscape, influence is pivotal in molding individuals’ decisions, perspectives, and behaviors. Measuring Social Influence (SI) in Online Social Networks (OSNs) faces significant gaps, notably needing more integration with human behaviors. Our literature review has unveiled twelve psychological theories rooted in human behavior that are fundamental for assessing SI in OSNs. We have further elucidated how human behaviors interact in shaping the influence potential of social media users through exploratory interviews with experts from consulting, industry, and academia. Our study culminated in developing a novel framework designed to encompass the intricacies that not only nurture …

Ai-Assisted Stakeholder Management And Organizational Learning: Evidence From The U.S. Intelligent Service Community, Jiyoon An

AMTP Proceedings 2024

Artificial intelligence (AI) has changed business practices, including stakeholder management and organizational learning. Scant research attention has been dedicated to examining methodology to implement for workflow-aware and skillset-savvy, AI-assisted stakeholder management. This paper has conducted natural language processing (bigram) and network analysis to understand AI-assisted stakeholder management practices in the U.S. intelligent service community. Theoretical and managerial implications are discussed.

Nike's Product Recommendation System And Incorporation Of Ai, Quinton Truman Lamers

Undergraduate Theses, Professional Papers, and Capstone Artifacts

No abstract provided.

Enhancing Marketing Education Through Gamification: Learners’ Characteristics And Motivation In Gamification Strategies, Jagannath Kharel

Theses and Dissertations

The study investigates how the personality traits of marketing students influence their engagement with gamification elements and the resulting learning outcomes. Additionally, it explores how gamification, guided by Self-Determination Theory, enhances these outcomes, and motivates university marketing students. One hundred eleven respondents participated, testing eight hypotheses: seven examined the Big Five traits' influence on attitudes and engagement. At the same time, the final used the self-determination framework to analyze motivation in gamification. Respondents with openness and extraversion favored using gamified learning materials, with no gender differences observed. The study found that gamified learning elements, such as rewards, feedback, levels, challenges, …

The Impact Of Social Media On Charitable Giving For Nonprofit Organization, Namchul Shin

Journal of International Technology and Information Management

Research has extensively studied nonprofit organizations’ use of social media for communications and interactions with supporters. However, there has been limited research examining the impact of social media on charitable giving. This research attempts to address the gap by empirically examining the relationship between the use of social media and charitable giving for nonprofit organizations. We employ a data set of the Nonprofit Times’ top 100 nonprofits ranked by total revenue for the empirical analysis. As measures for social media traction, i.e., how extensively nonprofits draw supporters on their social media sites, we use Facebook Likes, Twitter Followers, and Instagram …

Key Issues Of Predictive Analytics Implementation: A Sociotechnical Perspective, Leida Chen, Ravi Nath, Nevina Rocco

Journal of International Technology and Information Management

Developing an effective business analytics function within a company has become a crucial component to an organization’s competitive advantage today. Predictive analytics enables an organization to make proactive, data-driven decisions. While companies are increasing their investments in data and analytics technologies, little research effort has been devoted to understanding how to best convert analytics assets into positive business performance. This issue can be best studied from the socio-technical perspective to gain a holistic understanding of the key factors relevant to implementing predictive analytics. Based upon information from structured interviews with information technology and analytics executives of 11 organizations across the …

Does Personality Traits And Security Habits Influence Security Of Personal Identification Numbers? The Context Of Mobile Money Services In Tanzania., Daniel Ntabagi Koloseni

Journal of International Technology and Information Management

Security is an important ingredient in financial transactions; as such, it is imperative that attention should be paid to enhancing the security habits and user behaviours of mobile payment services. Establishing a link between security habits, personality characteristics, and security behaviours provides a new dimension to studying security behaviours regarding mobile money services. Therefore, this study investigates how personality traits affect security behaviours and habits and how security habits mediate the link between personality traits and PIN security practices. The study found that conscientiousness, openness to experience, extroversion and security habits influence PIN security practices, while conscientiousness, agreeableness, and neuroticism …

Activities Tailoring Within Agile Scrum Roles: A Case Of Nigerian Healthcare Information Systems Development, Yazidu Salihu, Julian Bass, Gloria Iyawa

Journal of International Technology and Information Management

Developing quality agile healthcare information systems requires understanding regulatory compliance and evolving healthcare needs through activities tailored within agile scrum roles. Agile scrum, a widely adopted philosophy, offers significant advantages in managing software development processes. This research explores how activities within the agile scrum roles are tailored to agile healthcare information systems development within the Nigerian context. This study adopted a qualitative case study methodology and interviewed 12 agile practitioners developing healthcare information systems within Nigeria using semi-structured open-ended interview guide questions. The practitioners were selected based on a snowballing process, a sunset of purposive sampling techniques from our network …

What Can We Learn From A Co-Creation Journey For A Quick Scan Digital Transformation Maturity Assessment Tool For Development Ngos?, Anand Sheombar

Journal of International Technology and Information Management

This paper describes the approach and lessons learned from a co-creation process with Dutch development NGOs to create a practical and easy-to-use assessment tool for practitioners to assess the organisation's maturity level of digital transformation. For this study, we applied a design science research methodology, specifically a six-step co-creation approach suitable for developing maturity models. The digital maturity assessment tool (quick scan) created is a domain- specific digital transformation maturity tool for development NGOs rather than a generally applicable tool. This artefact was evaluated using an eight-point Requirements framework for the development of digital maturity assessment tools. By developing a …

Outsourcing Voting To Ai: Can Chatgpt Advise Index Funds On Proxy Voting Decisions?, Chen Wang

Fordham Journal of Corporate & Financial Law

Released in November 2022, Chat Generative Pre-training Transformer (“ChatGPT”), has risen rapidly to prominence, and its versatile capabilities have already been shown in a variety of fields. Due to ChatGPT’s advanced features, such as extensive pre-training on diverse data, strong generalization ability, fine-tuning capabilities, and improved reasoning, the use of AI in the legal industry could experience a significant transformation. Since small passive funds with low-cost business models generally lack the financial resources to make informed proxy voting decisions that align with their shareholders’ interests, this Article considers the use of ChatGPT to assist small investment funds, particularly small passive …

Early-Warning Prediction For Machine Failures In Automated Industries Using Advanced Machine Learning Techniques, Satnam Singh

Electronic Theses, Projects, and Dissertations

This Culminating Experience Project explores the use of machine learning algorithms to detect machine failure. The research questions are: Q1) How does the quality of input data, including issues such as outliers, and noise, impact the accuracy and reliability of machine failure prediction models in industrial settings? Q2) How does the integration of SMOTE with feature engineering techniques influence the overall performance of machine learning models in detecting and preventing machine failures? Q3) What is the performance of different machine learning algorithms in predicting machine failures, and which algorithm is the most effective? The research findings are: Q1) Effective outlier …

Improving Credit Card Fraud Detection Using Transfer Learning And Data Resampling Techniques, Charmaine Eunice Mena Vinarta

Electronic Theses, Projects, and Dissertations

This Culminating Experience Project explores the use of machine learning algorithms to detect credit card fraud. The research questions are: Q1. What cross-domain techniques developed in other domains can be effectively adapted and applied to mitigate or eliminate credit card fraud, and how do these techniques compare in terms of fraud detection accuracy and efficiency? Q2. To what extent do synthetic data generation methods effectively mitigate the challenges posed by imbalanced datasets in credit card fraud detection, and how do these methods impact classification performance? Q3. To what extent can the combination of transfer learning and innovative data resampling techniques …