Management Sciences and Quantitative Methods Commons^™

The Structural Limitations Of Mining Output Growth In Nevada, Mckinley Brown, Emma Kitchen

Undergraduate Economics Working Paper Series

This study compares short and long trends in Nevada to the production output within the mining industry. Nevada produces around 70% of the United States gold and about 15% of the world's critical minerals. From its position as one of the most resource rich mining regions globally to its emergence as a growing economic hub, mining played a central role in Nevada's economy. However, despite the industry’s importance, Nevada still faces inefficiencies in production output due to insufficient attention to key inputs such as labor, infrastructure, technology, and energy resources.

Consistency-Based Computing Of Fuzzy Eigenvalues And Fuzzy Eigenvectors: Method And Application, Kamala. R. Aliyeva Prof., Nihad Mehdiyev, Shamil Mehdi

Chemical Technology, Control and Management

The computation of eigenvalues and eigenvectors under uncertainty is a fundamental problem in fuzzy linear algebra and decision analysis. When matrix elements are represented by fuzzy numbers, classical spectral methods cannot be directly applied due to nonlinearity, ambiguity in ordering, and the propagation of uncertainty. Moreover, in many practical applications, particularly those involving pairwise comparison matrices, the reliability of eigenvalue-based results strongly depends on the consistency of the underlying data. This paper proposes a consistency-based framework for computing fuzzy eigenvalues and fuzzy eigenvectors that explicitly integrates consistency analysis into the spectral derivation process. The proposed method preserves the fuzzy structure …

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 …

Hybrid Quantum-Classical Optimization Of The Resource Scheduling Problem, Tyler Christeson, Md Habib Ullah, Ali Arabnya, Amin Khodaei, Rui Fan

Electrical and Computer Engineering: Faculty Scholarship

Resource scheduling is critical in many industries, especially in power systems where the Unit Commitment (UC) problem determines the on/off status and output levels of generators under physical and economic constraints. Traditional exact methods, such as Branch-and-Bound, Branch-and-Cut, dynamic programming and mixed-integer linear programming (MILP), remain the backbone of UC solution techniques, but they often rely on linear approximations or exhaustive search, leading to high computational burdens as system size grows. Metaheuristic approaches, such as genetic algorithms, particle swarm optimization, and other evolutionary methods, have been explored to mitigate this complexity; however, they typically lack optimality guarantees, exhibit sensitivity to …

Early Stem Impressions, Student Engagement, And Readiness For Digitalization, Myron Sheu

Journal of International Technology and Information Management

This study examines how early impressions of science, technology, engineering, and mathematics (STEM) shape business students’ learning behaviors and, ultimately, their readiness for organizational digitalization. Focusing on gender differences, subgroup identities, and perceived obstacles, the analysis uses survey data processed through correlation matrices, regression models, and subgroup heatmaps to trace the relationship between initial attitudes toward STEM and subsequent engagement patterns. The findings reveal consistent links between positive early impressions and active participation in structured STEM activities, along with gender-based distinctions in action preferences. Subgroup analyses further uncover nuanced patterns where stereotypes or perceived barriers correspond with reduced engagement. Collectively, …

Wings Of Perception: Investigating Customer Sentiments In Indian Aviation Sector, Yashodhan Karulkar, Kaiwan Vaghchhipawala, Aditya Trivedi, Anushree Talekar

Journal of International Technology and Information Management

India's aviation sector, a key contributor to the nation's economy, has experienced rapid growth, supporting nearly 7.5 million jobs and contributing approximately $30 billion annually to the GDP (Gross Domestic Product). The growth, driven by increased demand for air travel and government incentives, has resulted in more competition among carriers. In the competitive market, it is necessary to understand customer preferences to enhance the quality of service and maintain a competitive edge. The dissemination of customer opinions on social media and review platforms offers airlines the opportunity to access passenger views. However, extracting useful information from this unstructured data is …

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 …

Does Digital Innovation Matter For Hospital Efficiency? Evidence From U.S. Hospitals, C. Christopher Lee, Shihui Fan, Jung Young Lee, David W. Hwang

Journal of International Technology and Information Management

Purpose – This study examines the impact of digital innovation on hospital performance, providing evidence to guide healthcare administrators and policymakers in making informed decisions regarding digital investment.

Design/Methodology/Approach – Using data from the 2020 American Hospital Association (AHA) U.S. Hospital Survey and the 2019 AHA Information Technology Survey, we empirically analyze the relationship between five dimensions of digital innovation—automation, cybersecurity, telehealth, health information exchange (HIE), and IT spending—and three efficiency indicators: occupancy rate, capacity productivity, and manpower productivity.

Findings – The results show that digital innovation has varying effects on hospital efficiency. Automation is positively associated with capacity 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. …

Business Process Redesign For Reducing Undelivered Product Return Losses In E-Commerce – An Explainable Ai Approach, Venkataraghavan Krishnaswamy, Deepa R, Himanshu Sharma

Journal of International Technology and Information Management

Product returns in e-commerce affect the profitability of the e-tailer. We adopt a two-stage approach to reduce undelivered product returns in an e-commerce firm. First, we develop and compare machine learning techniques—logistic regression, decision trees, Naïve Bayes, random forest, adaptive boosting, gradient boosting, stochastic gradient boosting, and deep neural networks—on their ability to predict undelivered returns. Next, we use explainable methods, such as relative importance and Shapley values, to develop insights from the best-performing machine learning model. Finally, we use these insights and the predictive model to redesign the firm’s order fulfillment and return processes. A Post-implementation evaluation of the …

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 …

The Importance Of Leader-Member Exchange And Psychological Contracts In Highly Qualified Researchers, Robin L. Ingerick Dba

Theses & Dissertations

This study examined the significance of the relationship between leader-member exchange (LMX) and psychological contracts in United States-based research organizations. When the organization-manager-employee relationship deteriorates, psychological contract breaches can occur, negatively affecting employee outcomes and the organization's financial success and stability. Existing knowledge highlights several factors that influence relationships, including reciprocated treatment, work behaviors and reactions, trust, professional respect, affect, mutual interaction, work autonomy, communication, job satisfaction, and fulfillment. The study sought to determine to what extent is there a predictive relationship between LMX and psychological contracts (employee obligations, employer obligations, fulfillment, and contract transitions) of highly qualified United States-based …

On Modeling Of Multiplicative Bias Factor For Multivariate Degradation Data, Bingxin Yan, Qiuzhuang Sun, Zhisheng Ye

Research Collection College of Integrative Studies

Multivariate degradation data are increasingly common due to advances in sensor technology. They provide rich information for reliability analysis and remaining useful life (RUL) prediction. The multivariate measurement typically contains actual degradation of multiple performance characteristics (PCs) and measurement errors. The multiple PCs often have different physical meanings with different orders of magnitude, making the associated measurement errors vary in the orders of magnitude as well. It is highly desirable to have a parsimonious model accounting for the possible correlation in degradation measurements, so that more flexibility can be reserved for modeling the actual multivariate degradation. This study proposes a …

Orchestrating Complexity: The Art Of Virtual Leadership In System Modelling, Vijay Kumar Sonawane, Bipllab Roy, Purnendu Bikash Acharjee, Indu Pv

Northeast Journal of Complex Systems (NEJCS)

This paper explores the dynamics of virtual leadership within global remote work environments, focusing on the application of complex system modelling to understand and enhance leadership efficacy. The application of computational modelling has been a regular feature in economics, science and technology fields, however its application in virtual leadership with linkage to sport leadership appears to be a novel concept. Adopting a multidisciplinary approach, this paper incorporates Game Theory as a conceptual framework to make the leadership model more relevant and applicable that can offer simpler understanding of complex play of leadership drivers. The model incorporates five key leadership dimensional …

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. …

Sustainability In Forex Trading: A Review In Search Of The Sarsa-Fis Hybrid Method As A Novelty, Joni Fat, Parwadi Moengin, Pudji Astuti, Sally Cahyati

Bulletin of Monetary Economics and Banking

This study employs meta-analysis, rich pictures, timeline analysis, and causal loop diagram to explore the sustainability impacts of the SARSA-FIS hybrid method in forex trading robots. It reviews 56 references (2018-2023), using rich pictures to map AI-driven interactions. Timeline analysis traces AI’s evolution in forex, while causal loop diagram clarifies its role in market dynamics. Responsible algorithms and SRI principles mitigate risks, promoting ethical trading. SARSA-FIS enhances strategies, leveraging AI for sustainable forex practices amidst global uncertainties. The research identifies gaps and positions SARSA-FIS as a novel approach, providing a foundation for advancing AI applications in finance, particularly in forex …

Comparing Funders' Altruism Versus Self-Interest: Leveraging The Context Of Crisis, Dan Liu, Guangzhi Shang, Cynthia Fan Yang

Journal of International Technology and Information Management

While reward-based crowdfunding has widespread popularity, the motivations driving funders, balancing self-interest and altruism, have remained puzzling. Prior research has been constrained by examination methods and produced mixed findings regarding the weight of altruism versus self-interest among funders. Our study takes a fresh perspective, delving into funder behavior amid a major crisis—the tumultuous backdrop of the COVID-19 pandemic. Our findings reveal that funders not only display an increased willingness to contribute but also significantly amplify their contributions, particularly to projects in crisis-affected regions, irrespective of external incentives like rewards. This underscores the prevalence of altruistic motives among funders in challenging …

Adaptation For Whom? Understanding The Impacts Of Dyke Policies On Small-Scale Farmers In Ca Mau Province Of Vietnam, Nguyen Minh Quang, Nguyen Van Minh, Nguyen Vo Chau Ngan, Martha B. Lerski

Publications and Research

Low-lying deltas worldwide are extremely vulnerable to sea-level rise. As the risks of climate-induced flooding become increasingly clear, the thirst for infrastructure-driven adaptation increases. This highlights a patent need to understand the impacts of engineering adaptation solutions, especially those targeting built structures such as dykes and sluices, on farmers from a bottom-up, farmer-centred perspective. The study addresses this call by examining cases where dyke policies, while successful in some dimensions, have undermined small-scale farmer livelihoods in Ca Mau ― Vietnam’s southernmost rural province. It identifies areas in need of attention and adds empirical data related to this group of farmers. …

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 …

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 …

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 …

Juegos De Rol En El Desarrollo De Projectpipe: Una Inmersión En El Uso De Metodologías De Diseño, Julieth A. Gómez Hernández, Cristian C. Orozco Ospina, Nicolas Restrepo Henao

Journal of Roleplaying Studies and STEAM

En el entorno digital actual, la evolución del concepto de juegos de rol ha llevado al desarrollo de aplicaciones web interactivas y educativas. En sintonía con este planteamiento, se presenta la siguiente propuesta, que adopta una metodología integrada para aprovechar la versatilidad del método de Bruno Munari y el Diseño Centrado en el Usuario (DCU). La metodología de Munari descompone la gestión macro del proyecto en pasos manejables; mientras que el DCU se enfoca en la creación de una interfaz intuitiva y funcional mediante prototipos iterativos y pruebas continuas de usabilidad. Como complemento a estas estrategias se integra la metodología …

Beyond The Waterfall: A Review Of Project Management Methodologies In Stem, Yessenia Henriquez

Undergraduate Research Symposium Posters

Project management has been exercised from history's early stages to concurrent practices today. It has evolved from the early stages of the Gantt chart and five primary principles to well-renowned project management methodologies such as Waterfall and Agile. This literature review focuses on comprehending four project management methodologies (Waterfall, Agile, Kanban, and Scrum), learning their criteria and frameworks, and their application in a specific STEM environment when applicable. This work reviews the recent research literature about these four methods. An overview of project management certificates and guidelines is covered as well. Waterfall is known to be a traditional method, having …

Exploring The Impact Of Artificial Intelligence On Project Management Across The Manufacturing, Technology, And Construction Industries, Susie Diaz Ferrera

Harrisburg University Dissertations and Theses

This study explores the impact of Artificial Intelligence (AI) on project management across the manufacturing, technology, and construction industries. The research focuses on understanding the benefits, challenges, and long-term implications of AI utilization in these sectors. Key findings indicate that 46% of participants use AI mainly for task automation and enhancing functions like brainstorming and communication, which significantly boosts efficiency and team productivity. Despite these benefits, the research identifies several obstacles, including high initial costs, inadequate training, technical issues, and unclear regulatory guidelines. The study addresses four main questions, revealing that AI not only enhances project management processes but also …

Drivertech Vehicle Monitoring System, Sarah Aldhafeeri, Fillip Cannard, Kaitlyn Ledon, Shea Spellman

Posters - 2024

DriverTech provides critical data to shipping companies about their fleets of vehicles and drivers. This is done through their vehicle monitoring system. Unfortunately, Windows 10 is reaching end of life, and DriverTech is looking for a new software solution.