Operational Research Commons^™

Designing Under Pressure: A Comparative Study Of Ai And Manual Interface Development In A Naval Weapon System Scenario, Tsimur Babakhanau, Noah Clark, Colby Keller, Mary Grace Sorenson, Zoe Tiede

Discovery Day - Daytona Beach

This study implements a detailed naval scenario in which participants acted as operators on a Navy destroyer equipped with a Laser Weapon System (LaWS). Their task was to create a dashboard capable of stopping incoming suicide drone swarms while managing critical laser functions such as thermal constraints, threat prioritization, and adapting to attack dynamics. Poor management could leave the ship vulnerable. AI is increasingly integrated into design methods, fundamentally transforming the process of building user interfaces by compressing hours of work into minutes. Although AI design tools are becoming more common, little is known about how well beginners can use …

Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park

Annual Research Symposium

Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …

A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines

Dissertations

Artificial Intelligence (AI) is transforming Supply Chain Management (SCM), yet many organizations struggle to assess their readiness for AI adoption and to understand how AI capabilities develop across maturity stages. This dissertation addresses this gap by developing a Capability Maturity Model (CMM) for AI integration in SCM, grounded in Organizational Information Processing Theory (OIPT), the Resource-Based View, and related capability frameworks. The model provides a structured approach for evaluating an organization's information-processing requirements, resource configurations, and alignment needed for effective AI-enabled supply chain operations.

Using a design science research approach, the AI-SCM CMM and its associated assessment instrument were derived …

Gpu-Accelerated Biased Random-Key Genetic Algorithms: Framework Optimization And Llm-Driven Configuration, Fnu Harishjitu Saseendran

Open Access Master's Theses

This thesis presents two complementary contributions to the field of GPU-accelerated evolutionary metaheuristics for combinatorial optimization, organized in manuscript format.

The first manuscript, “BrkgaCuda 3.0: A Redesigned Multi-GPU Framework for Biased Random-Key Genetic Algorithms,” presents a ground-up architectural redesign of BrkgaCuda 2.0 that enables a true multi-GPU island model for Biased Random-Key Genetic Algorithms (BRKGA). The BRKGA island model evolves multiple semi-independent populations that periodically exchange elite solutions, a structure that maps naturally to multi-GPU parallelism; however, BrkgaCuda 2.0 is confined to a single GPU. BrkgaCuda 3.0 introduces an IslandManager that distributes populations across any number of GPUs, with multiple …

Online Community Dynamics: An Analysis Using Louvain During Major Sporting Events, Anushka Jaint, Yashodhan Karulkar, Kashish Jindal, Sri Sai Harshita Gadavarthi, Sanya Gulati

Journal of International Technology and Information Management

With the power of social media transforming the way people connect and interact with each other, the dynamics of community formation on platforms such as X during major events are of crucial importance. While social media is an increasingly key driver in determining interactions, little is known about the online influence forming and developing fan communities in high-stakes events. This study looks into the development of user communities for datasets drawn from Kaggle on two of the world’s largest sporting events: the FIFA World Cup 2022, or football, and the T20 World Cup 2022, or cricket, with the aim of …

Blockchain As A Digital Coordination Infrastructure For Project Management: A Systematic Review And Integrative Framework, Cherie Bakker Noteboom, Sai Neelima Seru, Aravindh Sekar

Journal of International Technology and Information Management

Blockchain technology has gained increasing attention as a digital infrastructure capable of improving transparency, trust, and coordination in complex, multi-organizational project environments. However, existing research on blockchain-enabled project management remains fragmented and industry-focused, providing limited guidance for organizational adoption and integration. This study addresses this gap through a systematic literature review of 29 peer-reviewed studies, following PRISMA guidelines, to examine how blockchain capabilities are incorporated into project management practices across industries and maturity stages.

Grounded in Resource-Based View and Coordination Theory, the analysis employs a feature-to-process mapping approach to link six core blockchain capabilities—decentralization, transparency, immutability, smart contracts, traceability, and …

The Crowdfunding Paradox In Crisis: Rising Funder Demand Vs. Declining Entrepreneur Supply, Dan Liu, Guangzhi Shang, Cynthia Fan Yang

Journal of International Technology and Information Management

This study investigates how the crowdfunding marketplace responds to major crises, focusing on behavioral shifts among funders and entrepreneurs. Results show a dual impact on platform dynamics. On the demand side, funders become more engaged, with notable increases in the number of backers, average contributions, and total pledge amounts. This heightened activity suggests stronger altruistic motivations, as individuals view crowdfunding as a way to support others during difficult times. On the supply side, however, entrepreneurs act more cautiously, leading to a decline in new project launches. This drop likely reflects increased risk aversion and uncertainty as creators navigate volatile conditions. …

Too Warm To Win Big? Unpacking The Backer Dynamics Behind Female Crowdfunding Success Using A Warmth And Competence Perspective, Dan Liu

Journal of International Technology and Information Management

While crowdfunding is often heralded as a democratized funding avenue that empowers women with higher success rates, this study reveals a more nuanced picture of gender dynamics. The Stereotype Content Model suggests that women are often perceived as warmer but less competent. Using a large dataset from Kickstarter, we find that female-led projects can attract more backers, likely due to warmth-driven appeal, but receive smaller average contributions, potentially due to concerns about risk linked to lower perceived competence. However, the total funding raised by female-led campaigns is comparable to that of male-led ones, showing no clear advantage or disadvantage. This …

Fasttree-Guided Genetic Algorithm For Credit Scoring Feature Selection, Rashed Bahlool, Nabil Hewahi Prof., Youssef Harrath Dr.

Research & Publications

Feature selection is pivotal in enhancing the efficiency of credit scoring predictions, where misclassifications are critical because they can result in financial losses for lenders and exclusion of eligible borrowers. While traditional feature selection methods can improve accuracy and class separation, they often struggle to maintain consistent performance aligned with institutional preferences across datasets of varying size and imbalance. This study introduces a FastTree-Guided Genetic Algorithm (FT-GA) that combines gradient-boosted learning with evolutionary optimization to prioritize class separability and minimize falserisk exposure. In contrast to traditional approaches, FT-GA provides fine-grained search guidance by acknowledging that false positives and false negatives …

Detecting Electrical Submersible Pump (Esp) Failures And Estimating Run Life Using Artificial Neural Networks, Mostafa Ahmed Sobhy

Theses and Dissertations

Electric Submersible Pumps (ESPs) are one of the important artificial lift methods for sustaining production in mature and high-water-cut wells; but may suffer frequent failures due to mechanical, electrical, hydraulic, chemical, and operational failures. These failures can yield substantial deferred production and intervention costs. Plenty of ESP installations are fitted with downhole sensors. Yet, it is observed that the current industry practice underutilizes the wealth of available sensor and operational data and lacks standardized, explainable failure-type identification and classification.

In this thesis, a comprehensive Machine Learning (ML) and Deep Learning (DL) framework was introduced for ESPs that simultaneously estimates remaining …

On The Provenance Of Software Systems: Automating Software Traceability With Knowledge Graph And Large Language Model Synergy, Tyler Procko

Doctoral Dissertations and Master's Theses

The present dissertation delineates a system that enables those engaged in software development to automatically generate and maintain project life cycle provenance. All projects are implemented and made manifest with the development of artifacts, e.g., papers, code files, etc. Tools exist to accelerate artifact creation, but little focus is paid to the processes that produce them. In terms of Ontology, or, from Ancient Greek, the study of being, the two most basic entities in reality are Continuant and Occurrent, or, roughly, “Artifact” and “Process”. This dissertation posits that for any created artifact, its process of creation, i.e., its life …

Are Emojis The New Words? A Sentiment Analysis Of Social Media Brand Conversations, Yashodhan Karulkar, Dev T. Vora, Siddharth Vaddepalli, Yash Thakur

Journal of International Technology and Information Management

Emojis have become an increasingly important aspect of consumer-brand interactions in the Indian subcontinent. However, the impact of emoji use on brand image and mental health remains underexplored, particularly in emerging economies like India, where structured research on this topic is limited. To address this gap, the present study analyzes over 4,600 consumer tweets related to 19 prominent brands across eleven industries. Using VADER sentiment analysis, the research develops a metric to assess consumer sentiment and brand engagement in relation to emoji usage. The findings indicate that effective integration of emojis contributes to positive consumer sentiment and enhanced brand engagement. …

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, …

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.

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 …

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 …

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 …

Authenticated Diagnosing Of Covid-19 Using Deep Learning-Based Ct Image Encryption Approach, Mohamed Attia Abdelgwad, Amira Hassan Abed, Mahmoud Bahloul

Future Computing and Informatics Journal

Researchers are motivated to use artificial intelligence in biometrics, medical imaging encryption, as well as cybersecurity due to its rapid progress. An encryption method for CT scans—which are used to diagnose COVID-19 disease—is proposed in this study. The suggested encryption method creates a connection among an individual's face picture and CT image to increase confidentiality. The simple CT picture is first enhanced with a host image. An encryption key is multiplied by the final result. This key is produced by applying a Convolutional Neural Network (CNN) to recognize characteristics from people's face photographs. Additionally, a straightforward CNN with three convolutional …

Analyzing The Impact Of Socioeconomic Factors On Cancer Clinical Trials Accessibility In The U.S. Using Machine Learning, Krysta L. Ray, Hiromi Honda

ATU Scholars Symposium

While cancer impacts all segments of the United States population, specific groups experience a disproportionate burden of the disease due to social, environmental, and economic disadvantages. This research examines the correlation between socioeconomic factors and the accessibility of cancer clinical trials across U.S. counties, employing a comprehensive dataset, County-Level Socioeconomic and Cancer Clinical Trial Data from Noah Ripper, and advanced machine-learning techniques. Our findings, derived from regression analysis and machine learning models like gradient boosting, highlight significant disparities in trial availability linked to socioeconomic indicators, including poverty rates, population estimates, median income, incidence rates, and mortality rates. Many regression models …

Understanding The Impact Of Emergent Conflict On Communication And Team Cognition: A Multilevel Study In Engineering Teams, Francisco Cima

Engineering Management & Systems Engineering Theses & Dissertations

The development of team cognition is crucial for fostering high-performing teams. In cognitive-intensive fields like engineering, effective communication serves as a primary precursor to team knowledge development, enabling group members to effectively retrieve and utilize each other's expertise. Despite the critical role of communication, there is a lack of empirical research examining how conflict situations, which are critical emerging factors inherent to teamwork, interact with communication processes to constrain team knowledge development and utilization. This study, rooted in information processing theory, investigates how emerging conflict shapes multilevel team knowledge structures by interacting with communication processes in engineering project teams. Prior …

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 …

Algorithms For Coordinating Multiple Autonomous Vehicles Under Various Constraints With Emphasis On Workload Balancing, Abhishek Patil

Dissertations, Master's Theses and Master's Reports

This dissertation focuses on developing algorithms to solve the problem of coordinating multiple autonomous vehicles under various constraints, aiming to produce practical solutions for real-world applications. Built upon three journal publications addressing two coordination-related problems in different domains, this research document tackles the challenges of heterogeneity constraints and cable entanglement issues encountered by autonomous vehicle systems.

The first problem tackles task allocation and path planning for heterogeneous ground mobile vehicles operating in a 2D environment with asymmetric travel costs. By enhancing previous Primal-Dual approximation heuristic methods, novel techniques are introduced to manipulate dual variables and achieve balanced workload distribution, ultimately …

How Does Digitalisation Transform Business Models In Ropax Ports? A Multi-Site Study Of Port Authorities, Yiran Chen, Anastasia Tsvetkova, Kristel Edelman, Irina Wahlström, Marikka Heikkila, Magnus Hellström

Journal of International Technology and Information Management

This article investigates the relationship between digitalisation and business model changes in RoPax ports. The study is based on six RoPax ports in Northern Europe, examining their digitalisation efforts and the resulting changes in their business models, leading to further digital transformation. The paper offers insights by reviewing relevant literature on digitalisation’s role in business model innovation and its application in ports. The findings reveal that digitalisation supports relevant business model changes concerning port operation integration within logistics chains, communication, documentation flow, and cargo flow optimisation. However, exploring digitalisation’s potential for diversifying value propositions is still limited. Most digitalisation efforts …

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 …

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 …

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 …

Efficient Connectivity Management And Path Planning For Iot And Uav Networks, Amirahmad Chapnevis

Theses and Dissertations

This dissertation explores how to better manage resources in mobile networks, especially for enhancing the performance of Unmanned Aerial Vehicles (UAV)-supported IoT networks. We explored ways to set up a flexible communication architecture that can handle large IoT deployments by making good use of mobile core network resources like bearers and data paths. We developed strategies that meet the needs of IoT networks and enhance network performance. We also developed and tested a system that combines traffic from several mobile devices that use the same user identity and network resources within the core mobile network. We used everyday smartphones, SIM …

An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif

Future Computing and Informatics Journal

This study aims to enhance Adaptive Learning Systems (ALS) in Petroleum Sector in Egypt by using the Microservice Architecture and measure the impact of enhancing ALS by participating ALS users through a statistical study and questionnaire directed to them if they accept to apply the Cloud Computing Service “Microservices” to enhance the ALS performance, quality and cost value or not. The study also aims to confirm that there is a statistically significant relationship between ALS and Cloud Computing Service “Microservices” and prove the impact of enhancing the ALS by using Microservices in the cloud in Adaptive Learning in the Egyptian …

Visual Question Answering: A Survey, Gehad Assem El-Naggar

Future Computing and Informatics Journal

Visual Question Answering (VQA) has been an emerging field in computer vision and natural language processing that aims to enable machines to understand the content of images and answer natural language questions about them. Recently, there has been increasing interest in integrating Semantic Web technologies into VQA systems to enhance their performance and scalability. In this context, knowledge graphs, which represent structured knowledge in the form of entities and their relationships, have shown great potential in providing rich semantic information for VQA. This paper provides an abstract overview of the state-of-the-art research on VQA using Semantic Web technologies, including knowledge …

The Need For International Ai Activities Monitoring, Parviz Partow-Navid, Ludwig Slusky

Journal of International Technology and Information Management

This paper focuses primarily on the need to monitor the risks arising from the dual-use of Artificial Intelligence (AI). Dual-use AI technology capability makes it applicable for defense systems and consequently may pose significant security risks, both intentional and unintentional, with the national and international scope of effects. While domestic use of AI remains the prerogative of individual countries, the unregulated and nonmonitored use of AI with international implications presents a specific concern. An international organization tasked with monitoring potential threats of AI activities could help defuse AI-associated risks and promote global cooperation in developing and deploying AI technology. The …