Business Commons^™

Digital Infrastructure Development Through Digital Infrastructuring Work: An Institutional Work Perspective, Adrian Yeow, Wee-Kiat Lim, Samer Faraj

CCX Research

Being able to understand and characterize the digital infrastructure development (DID) process has become even more pressing today due to the rapid advent and implementation of new digital infrastructure (DI) in organizations as well as since the COVID-19 crisis. While information systems (IS) research has begun to recognize the institutional nature of such digital infrastructures, there remains a gap in our understanding of how such developments unfold from an institutional perspective. Through our field study of a digital infrastructure development project involving the implementation of an enterprise-wide electronic medical record system at a large US medical facility, we show how …

Why Ai Monitoring Faces Resistance And What Healthcare Organizations Can Do About It: An Emotion-Based Perspective, Karl Werder, Lan Cao, Eun Hee Park, Balasubramaniam Ramesh

Information Technology & Decision Sciences Faculty Publications

Continuous monitoring of patients' health facilitated by artificial intelligence (AI) has enhanced the quality of health care, that is, the ability to access effective care. However, AI monitoring often encounters resistance to adoption by decision makers. Healthcare organizations frequently assume that the resistance stems from patients' rational evaluation of the technology's costs and benefits. Recent research challenges this assumption and suggests that the resistance to AI monitoring is influenced by the emotional experiences of patients and their surrogate decision makers. We develop a framework from an emotional perspective, provide important implications for healthcare organizations, and offer recommendations to help reduce …

Future Of Bse Days 2025: Growing A Regenerative Bse, Derek M. Heeren, Santosh Pitla, Jennifer R. Keshwani, Mark Stone

Department of Agricultural and Biological Systems Engineering: Presentations and White Papers

The Future of BSE Days 2025: Growing a Regenerative BSE brought together over 150 faculty, staff, students, and partners to envision the next quarter-century of the Department of Biological Systems Engineering. The event emphasized regeneration—not only of resources and ecosystems, but also of ideas, learning models, and relationships. Across seven major sessions—three Spark Talks and four Pillar Workshops—participants explored how BSE can thrive amid technological disruption, demographic change, and societal transformation.

Key Outcomes

Redefining Impact: This session challenged participants to evolve from counting outputs to valuing relationships, collaboration, and community well-being.

Adaptive Learning Models: This discussion introduced design studios, micro-credentials, …

Understanding The Challenges And Satisfaction Among The Medical Professional Preceptors, Cornelia Ko

West Chester University Doctoral Projects

This study evaluates the Penn Medicine Family Medicine Clerkship program through a mixed-methods approach, exploring the challenges and factors influencing the satisfaction of medical professional preceptors when precepting students. A quantitative survey with 54 preceptor participants reveals the top challenges preceptors face: workload, conflicts with patient care, and limited clinical space. Despite this, there is strong support for the program, with 89% of preceptors enjoying the role and 85% expressing willingness to continue to precept for the next three years. Finally, data analysis shows no statistical correlation between preceptor motivation with gender, ethnicity, age group, years of serving, or total …

A Two-Phase Learning Approach Integrated With Multi-Source Features For Cloud Service Qos Prediction, Fuzan Chen, Jing Yang, Haiyang Feng, Harris Wu, Minqiang Li

Information Technology & Decision Sciences Faculty Publications

Quality of Service (QoS) is a key factor for users when choosing cloud services. However, QoS values are often unavailable due to insufficient user evaluations or provider data. To address this, we propose a new QoS prediction method, Multi-source Feature Two-phase Learning (MFTL). MFTL incorporates multiple sources of features influencing QoS and uses a two-phase learning framework to make effective use of these features. In the first phase, coarse-grained learning is performed using a neighborhood-integrated matrix factorization model, along with a strategy for selecting high-quality neighbors for target users. In the second phase, reinforcement learning through a deep neural network …

A Spoofing Speech Detection Method Combining Multi-Scale Features And Cross-Layer Identification, Hongyan Yuan, Linjuan Zhang, Baoning Niu, Xianrong Zheng

Information Technology & Decision Sciences Faculty Publications

Pre-trained self-supervised speech models can extract general acoustic features, providing feature inputs for various speech downstream tasks. Spoofing speech detection, which is a pressing issue in the age of generative AI, requires both global information and local features of speech. The multi-layer transformer structure in pre-trained speech models can effectively capture temporal information and global context in speech, but there is still room for improvement in handling local features. To address this issue, a speech spoofing detection method that integrates multi-scale features and cross-layer information is proposed. The method introduces a multi-scale feature adapter (MSFA), which enhances the model’s ability …

Optimal Control Of Queueing Systems With Error-Prone Servers, Junqi Hu, Sigrún Andradóttir, Hayriye Ayhan

Information Technology & Decision Sciences Faculty Publications

Consider a Markovian tandem line with finite intermediate buffers and an equal number of stations and servers. Servers are flexible but noncollaborative, so that a job can be processed by at most one server at any time. When a job is being processed, it can be damaged and wasted depending on the proficiency of the server. We identify the dynamic server assignment policy that maximizes the long-run average throughput of the system with two stations and two servers. We find that the optimal policy is either a single or a double threshold policy on the number of jobs in the …

Investing In The Age Of Generative Ai: A Gpt-Based Sentiment Analysis Approach, Xianrong Zheng

Information Technology & Decision Sciences Faculty Publications

Generative AI, which ushers a new age of AI, comes with huge economic potential. To capitalize the AI boom, investors are interested in trading AI stocks. AI chatbots, which can identify and classify the sentiment from financial news, can be leveraged for investment. So, this paper proposes a GPT-based sentiment analysis approach for trading AI stocks. Also, natural experiments are conducted to evaluate its effectiveness. Initial results show that the approach achieves a good rate of return.

The Influence Of Shopping Context And Anthropocentric Bias On Consumer Preferences For Human And Ai Designers In Fashion, Dooyoung Choi, Ha Kyung Lee, Christina Soyoung Song, Ji Young Lee

Educational Leadership & Workforce Development Faculty Publications

This study explores how shopping contexts (hedonic vs. utilitarian) influence consumer preferences for AI- vs. human-designed fashion products. In Study 1, participants with hedonic motivations preferred human-designed items, while those with utilitarian motivations preferred AI-designed products, supporting the hypothesis that shopping context affects designer preferences. Study 2 further investigates the mediation of competence-warmth traits in designer preferences and the moderation of anthropocentric bias. It finds that hedonic shopping contexts increase the desire for warmth-related traits, leading to a preference for human designers, while utilitarian contexts favor competence-related traits and AI designs. Additionally, individuals with higher anthropocentric biases showed stronger preferences …

Coastal Flooding And Housing Market Liquidity: Policy Implications For Eastern U. S. Communities, Wai Yan Siu, Rex Sitti

ODU Articles

Coastal flooding poses an escalating threat to communities across the U.S East Coast, where rising sea levels and intensifying storms increasingly overwhelm existing infrastructure and natural defenses. These events generate complex economic consequences that extend beyond immediate property damage to affect community stability and long-term development patterns. The real estate industry in particular, faces increasing levels of flood risk. Existing research on climate risk and real estate markets focuses predominantly on price capitalization effects, overlooking the critical dimension of housing market liquidity. This study examines the causal impact of coastal flooding on days-on-market (DOM), a metric of liquidity in the …

Utilizing Artificial Intelligence As A Strategic Risk Management Tool For Public Sector Operations And Auditing Processes, Oğuz Ümit Tamer, Bruce D. Mcdonald Iii, Farouk Hemici, Georgia Kontogeorga

School of Public Service Faculty Publications

Symbolizing a significant turning point in the historical landscape, AI is becoming an effective tool in today's public administration, not only for increasing capacity, quality, and speed in services, but also for strategic risk management. Regulators and algorithmic auditing play a central role in implementing fairness, transparency, and persistent controls against risks in AI systems. Discussing modern applications of AI, such as anomaly-based fraud detection, resource estimation, and continuous auditing, and their respective strengths and weaknesses, this study concludes that AI significantly enhances efficiency and oversight but also poses the risk of enshrining bias, opacity, and accountability gaps. By considering …

Watchdogs Or Lapdogs: How Audit Committees Influence Financial Reporting Quality And Cybersecurity, Yanru Yang

2025

With the increasing complexity of the business environment, the role of corporate governance and oversight is expanding continuously. Grounded in archival research, my dissertation consists of three studies that explore the features of audit committees in monitoring both financial reporting and broader areas, such as cybersecurity.

The first paper, co-authored with Gopal Krishnan and Wei Yu, examines the implications of audit committee (AC) director departure for financial reporting quality and audit risk. We find that the departures in the firms with most concerning AC departures are associated with a higher likelihood of a future “Big R” restatement announcement and auditor …

A Blueprint To Greener Shorelines: Advancing The Effectiveness, Sustainability, And Widespread Adoption Of Coastal Nature-Based Solutions Through Transdisciplinary Research, Taylor M. Sloey, Sierra Hildebrandt, Rebecca L. Morris, Matthew V. Bilskie, Aaron Bland, David Bushek, Gabriella Dipetto, Daniel Elefant, Vincent Encomio, Ramin Familkhalili, Christine Hladik, Danielle Kreeger, Avery B. Paxton, Cindy M. Palinkas, Latina Steele, Andrew Scheld, Daisuke Taira, Jason D. Toft, Armando J. Ubeda, Christine Whitcraft, Donna Marie Bilkovic

Biological Sciences Faculty Publications

Coastal nature-based solutions (NbS) have emerged as powerful tools to enhance sustainable development and ecological restoration goals. As a rapidly growing field spanning across social, political, ecological, economic, and engineering disciplines, it is critical that researchers working in coastal NbS regularly attempt to identify emerging focal areas for scientific inquiry. Following the 27th Biennial meeting of the Coastal and Estuarine Research Federation, we provide a transdisciplinary perspective (including biologists, engineers, oceanographers, geoscientists, economists, and facilitators of workforce training programs) of pertinent research questions that, if answered, will advance the effectiveness, sustainability, and widespread adoption of coastal NbS. These suggestions for …

An Economic And Production Analysis Of Seaweed Farms In California And The Pacific Northwest, Brian Donovan

Cal Poly Humboldt theses and projects

Since the early 2010s, the seaweed aquaculture industry has steadily expanded in the United States, with states like Alaska, Maine, Hawaii, and Connecticut leading the way in the development of this emerging sector. However, information gaps remain concerning certain aspects of the domestic seaweed aquaculture industry. The purpose of this study was to examine the status of the seaweed aquaculture industry along the West Coast of the United States; specifically in the states of California, Oregon, and Washington. Seaweed farmers in these states were invited to voluntarily complete surveys asking important production, economic, and commercial questions regarding their operations. Data …

Effects Of Round-Up On The Environment, Sandra J. Marcu

Journal of Earth and Life Science

Many people around the world have used and still currently use Roundup but are unaware of the effects it has on the environment. Roundup is a spray on application weedkiller that is widely used around the world today both residentially and commercially. It enables its user to grow a garden or a field of crops with a no-tilling approach to eliminate weeds. It is a well-known and popular choice for killing weeds that has been around since the mid 1970’s (Oca, 2017). John Franz, a Monsanto scientist discovered that glyphosate (main ingredient in Roundup) was an herbicide or weedkiller, and …

Integrated Valuation Of The Ecological, Social And Economic Benefits Provided By A Multifunctional Nature-Based Solution, Laura Costadone, Shan Zhang

ODU Articles

Nature-based Solutions (NbS) offer multifunctional approaches to address climate change and environmental challenges, providing a sustainable alternative to traditional gray infrastructure. Despite their promise, widespread adoption remains limited, in part due to an incomplete understanding of their full costs and benefits relative to conventional infrastructure. Traditional benefit–cost analyses often overlook non-monetized benefits and the interconnected ecosystem services provided by NbS. This study introduces a methodological approach to quantify both the physical and monetary value of ecosystem services and co-benefits delivered by an NbS project. We applied an integrated valuation framework to a case study in Virginia Beach, VA, USA, where …

5g-Practical Byzantine Fault Tolerance: An Improved Pbft Consensus Algorithm For The 5g Network, Xin Liu, Xing Fan, Baoning Niu, Xianrong Zheng

Information Technology & Decision Sciences Faculty Publications

The consensus algorithm is the core technology of blockchain systems to maintain data consistency, and its performance directly affects the efficiency and security of the whole system. Practical Byzantine Fault Tolerance (PBFT) plays a crucial role in blockchain consensus algorithms by providing a robust mechanism to achieve fault-tolerant and deterministic consensus in distributed networks. With the development of 5G network technology, its features of high bandwidth, low latency, and high reliability provide a new approach for consensus algorithm optimization. To take advantage of the features of the 5G network, this paper proposes 5G-PBFT, which is an improved practical Byzantine fault-tolerant …

Towards Dynamic Learner State: Orchestrating Ai Agents And Workplace Performance Via The Model Context Protocol, Mohan Yang, Nolan Lovett, Belle Li, Zhen Hou

Educational Leadership & Workforce Development Faculty Publications

Current learning and development approaches often struggle to capture dynamic individual capabilities, particularly the skills they acquire informally every day on the job. This dynamic creates a significant gap between what traditional models think people know and their actual performance, leading to an incomplete and often outdated understanding of how ready the workforce truly is, which can hinder organizational adaptability in rapidly evolving environments. This paper proposes a novel dynamic learner-state ecosystem—an AI-driven solution designed to bridge this gap. Our approach leverages specialized AI agents, orchestrated via the Model Context Protocol (MCP), to continuously track and evolve an individual’s multi-dimensional …

Feel Bad To Discard A Fashion Product: How Ai Designers Influence Individuals' Sustainable Consumption, Ha Kyung Lee, Dooyoung Choi

Educational Leadership & Workforce Development Faculty Publications

This study explores how AI technology in fashion design influences consumers' sustainable consumption behaviors, focusing on emotional attachment to products. By comparing AI-generated and human-designed fashion items, the study examines how designer type impacts negative emotions about discarding products, mediated by emotional attachment. Results from two experimental studies reveal that designer type significantly affects negative emotions toward discarding human-designed items, but emotional attachment was not influenced by designer type in the first study. This lack of difference may be due to personal characteristics that moderate the effect. The second study found that individuals who perceive AI as human-like form stronger …

Exploring The Impact Of Value Co-Creation Through Ai-Driven Chatbbots On Customer Repeat Purchases, Dooyoung Choi, Jaeha Lee

Educational Leadership & Workforce Development Faculty Publications

Drawing on the Stimulus-Organism-Response (S-O-R) framework, this study explores how perceived value co-creation during chatbot interactions influences customer repeat purchase intentions through cognitive, emotional, and social responses to chatbots. A survey of 220 participants revealed that perceived value co-creation significantly affected repeat purchase intentions, with cognitive evaluations, emotional reactions, and social value serving as key mediators. However, the direct effect of value co-creation on purchase intentions was not significant. The findings suggest that while value co-creation enhances consumer engagement, repeat purchases occur only when consumers experience positive cognitive, emotional, and social outcomes. Therefore, it is crucial for retailers to incorporate …

Artificial Intelligence, Society 5.0 And Smart City Adaptation Initiatives For Businesses: An Integrated Approach, Inês A.M. Gil, Fernando A.F. Ferreira, Neuza C.M.Q.F. Ferreira, Florentin Smarandache, Momtaj Khanam, Tugrul Daim

Branch Mathematics and Statistics Faculty and Staff Publications

The unprecedented migration of populations to urban areas has created major challenges for municipalities and service providers. To address these issues, decision-makers must embrace smart city and Society 5.0 paradigms, both of which focus on adaptability and sustainable development. Artificial intelligence (AI) plays a pivotal role by expanding service capacity, enabling automation, and processing vast data to align urban development with the UN’s Sustainable Development Goals (SDGs). This paper develops a multi-criteria analysis system designed to support decision-making in complex socio-technological contexts. Using cognitive mapping and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique within a neutrosophic environment, the study …

Optimizing Port Logistics Through Generative Ai: Revolutionizing Efficiency And Resilience In The Maritime Industry, Minodora Badea, Olga Bucovetchi, Adrian V. Gheorghe, Gabriel Raicu

Engineering Management & Systems Engineering Faculty Publications

The maritime industry faces growing challenges in optimizing port logistics due to increasing trade volumes, environmental regulations, and supply chain disruptions. This comprehensive literature review examines the transformative role of artificial intelligence (AI), with particular focus on generative AI, in enhancing efficiency and resilience in port operations. Through systematic analysis of 23 peer-reviewed studies published between 2021-2025, this review synthesizes advancements in real-time data integration, machine learning, digital twins, IoT, and autonomous systems that collectively improve operational decision-making, risk management, and environmental sustainability. Key findings reveal that machine learning applications achieve 90% effectiveness ratings in operational optimization, while predictive analytics …

A Comparative Analysis Of Preprocessing Filters For Deep Learning-Based Equipment Power Efficiency Classification And Prediction Models, Sang-Ha Sung, Chang-Sung Seo, Michael Pokojovy, Sangjin Kim

Mathematics & Statistics Faculty Publications

The quality of input data is critical to the performance of time-series classification models, particularly in the domain for industrial sensor data where noise and anomalies are frequent. This study investigates how various filtering-based preprocessing techniques impact the accuracy and robustness of a Transformer model that predicts power efficiency states (Normal, Caution, Warning) from minute-level IIoT sensor data. We evaluated five techniques: a baseline, Simple Moving Average, Median filter, Hampel filter, and Kalman filter. For each technique, we conducted systematic experiments across time windows (360 and 720 min) that reflect real-world industrial inspection cycles, along with five prediction offsets (up …

An Analysis Of Coal Ash Pollution In The State Of Georgia, Mick W. Etchison

Theses and Dissertations

This social science paper will explore the factors contributing to the prevalence of coal ash in specific regions of Georgia and its impact on local ecosystems and human health. It provides an analysis of the current environmental and political issues surrounding the containment and spread of coal ash throughout the State. Coal ash is primarily found in the central, southwestern, and northeastern regions where coal-fired power plants and coal ash storage sites are located. The paper will then discuss the political, economic, and legal reasons behind the lack of effective regulation and mitigation of coal ash spread. Coal ash illustrates …

A Plan To Revitalize The Domestic Superconducting Radio-Frequency Industry, G. Ciovati, M. Schuchman, W. Donaldson, A. Murokh, M. Naughton, D. Osha, D. Packard, J. Rathke, A. Todd

Physics Faculty Publications

Superconducting radio-frequency (SRF) cavities are essential building blocks of modern particle accelerators for scientific research, and they offer unique capabilities that could be transformative for commercial applications. Growth of the domestic SRF industry in North America has faced several challenges over the past decades, as most of the international demand for cavities was supplied by European vendors. This contribution provides a brief review of the domestic industrial vendor space, an outlook of the global demand for SRF cavities and an outline of the challenges leading to this supply chain deficiency. One of the main challenges towards establishing a robust domestic …

Cyberattacks On Port Infrastructures: A Decade Of Trends, Incidents, And Mitigation Strategies (2011-2024), Minodora Badea, Olga Bucovetchi, Adrian V. Gheorghe, Gabriel Raicu

Engineering Management & Systems Engineering Faculty Publications

Port infrastructures are critical to global trade, handling over 80% of the world's cargo by volume. However, their increasing reliance on digital technologies has exposed them to a wide range of cyber threats. This paper provides a comprehensive analysis of cyberattacks targeting port infrastructures from 2011 to the present. We examine the types of attacks, geographical distribution, notable incidents, and underlying vulnerabilities. Additionally, we discuss mitigation strategies and future directions for enhancing cybersecurity in the maritime sector. Our findings highlight the urgent need for robust regulatory frameworks, advanced technological solutions, and collaborative efforts to safeguard critical port operations.

A Comprehensive Academic And Industrial Survey Of Blockchain Technology For The Energy Sector Using Fuzzy Einstein Decision-Making, Umit Cali, Annabelle Lee, Barry Hayes, Claudio Lima, D. Jonathan Sebastian-Cardenas, David Flynn, Emre Kantar, Farrokh Rahimi, Kaung Si Thu, Marco Pasetti, Marthe Fogstad Dynge, Merlinda Andoni, Muhammet Deveci, Murat Kuzlu, Raquel Alanso, Kim-Kwang Raymond Choo, Sambeet Mishra, Shammya Shananda Saha, Sonam Norbu, Srinikhil Gourisetti, Ugur Halden, Vahid Hosseinezhad, Valentin Robu

Engineering Technology Faculty Publications

The global energy sector is undergoing a significant transformation driven by decarbonization and digitalization, leading to the emergence of Distributed Ledger Technology (DLT) — particularly blockchain — as a promising tool for enhancing transparency, security, and efficiency in modern power systems. This study aims to provide a comprehensive academic and industrial survey of blockchain applications in the energy sector and develop a robust decision-making framework to identify and prioritize the most promising real-world use cases based on multidisciplinary criteria. A three-stage methodology was adopted: (i) a literature and market review encompassing over 300 academic publications and commercial blockchain initiatives in …

Forecasting Equity Betas Using Option-Implied Moments, Ivan Kolesnikov

CMC Senior Theses

Traditional beta estimates are constructed from historical stock‑and‑market returns and therefore adjust only as fast as realized data accrue. This thesis investigates whether the forward‑looking information embedded in equity‑option prices can enhance beta forecasts. Using near‑end‑of‑day quotes for 236 S&P 500 firms between 2007 and 2024, I extract risk‑neutral variance and skewness, construct five alternative beta estimators (historical, option‑implied, and three hybrids), and evaluate them against realized betas over six‑, twelve‑, and twenty‑four‑month windows. Rolling‑OLS beta remains the most accurate benchmark at short horizons, yet option‑implied moments add economically and statistically significant value when systematic exposure is expected to change …

Natural Capital Credit Risk Assessment In Agricultural Lending: An Approach Based On The Natural Capital Protocol, Francisco Ascui, Theodor Florian Cojoianu

Research Collection College of Integrative Studies

It is increasingly recognised that financial institutions have significant impacts and dependencies on natural capital – defined as the stock of the world’s renewable and non-renewable natural resources and ecosystems that yield flows of environmental goods and services, which directly and indirectly underpin the global economy and human wellbeing. Historically, many of these impacts and dependencies have been overlooked. The value of goods and services that nature provides ‘for free’ has often been ignored, and resources have typically been priced at their cost of extraction, rather than the cost of their replacement or substitution, which would promote more sustainable long-term …

Risk Spillover Effect Of China-Asean Supply Chains: Insights Of Industrial Transfer, Zeyang Bian, Yuning Zhang, Keng Siau, Yaqian Zhang, Jianjia He

Research Collection School Of Computing and Information Systems

As labour costs in China increase, labour-intensive industries are migrating to ASEAN countries, attracted by lower labour costs and market potential. This shift not only affects the economies of China and ASEAN but also reshapes the global manufacturing landscape. This paper investigates the correlation and spillover of supply chain risks using production exposure indicators derived from inter-country input-output data and the R-Vine Copula model. We assess the risk spillover of each country within the global supply chain. Our findings indicate that industrial relocation can significantly alter supply chain structures, thereby affecting the concentration and direction of risks. While China's role …