Digital Commons Network^™

Antecedents Of The Principal Investigator’S Commercial Success When Funded By Small Business Innovation Research Program, Mohammed Bekkour

Theses and Dissertations from DePaul University

The commercial performance of Small Business Innovation Research (SBIR) projects remains substantially below national expectations despite decades of investment and strong technical output. Prior research suggests that commercialization outcomes depend not only on technological merit but also on the behavioral, cognitive, and managerial competencies of the Principal Investigator (PI), who often serves as both scientific lead and entrepreneurial decision-maker. Yet, systematic examination of PI-level attributes within SBIR contexts remains limited. This study investigates how six key constructs—Iterative Learning Process, Proactiveness, Organizational Risk Orientation, Scope Definition, Management Competence, and Simultaneous Project Engagement—relate to commercialization success among SBIR Phase II awardees. Drawing …

Analyzing The Impact Of Applying Ipsas 42 On Social Benefits In Enhancing Reporting Quality And Promoting Financial Sustainability, Burhan Hussein Khalaf Al-Rawi, Hasan Saleh Yusuf Al-Bajari

Muthanna Journal of Administrative and Economics Sciences

The study aims to explore the impact of applying IPSAS 42 on social benefits in enhancing the efficiency of financial reporting and strengthening the sustainability of financial capabilities within Iraqi government institutions. The study objectives were achieved by examining the nature and objectives of IPSAS 42, assessing the current state of disclosure of social benefits in government financial reports, and measuring the extent to which the social benefits standard contributes to promoting financial sustainability. The study relied on secondary financial data from a set of Iraqi government entities, including current expenditures, capital/investment expenditures, oil revenues, non-oil revenues, fiscal deficit, and …

The Impact Of Green Lean Manufacturing On Sustainability Dimensions: An Analytical Study Of Opinions A Sample Of Employees At The National Home Furniture Manufacturing Company, Rana Salim Mataab

Muthanna Journal of Administrative and Economics Sciences

This study aims to determine the extent of the association and impact of green lean manufacturing practices on the dimensions of sustainability (economic, social, and environmental) from the point of view of individuals working in national companies for the manufacture of home furniture. To achieve this goal, a questionnaire was designed according to a five-point Likert scale. In July 2024, using the cross-sectional studies approach, (213) responses that could be analyzed statistically were collected from the study sample. These data were analyzed using two software packages: (AMOSv24) and (SPSSv26). The results indicate that green lean manufacturing practices are associated with …

Green Value Chain Analysis And Its Role In Improving Resource Allocation Decisions: A Case Study In Diwaniya Dairy Factory, Ail Abdul-Hussein Hani Al-Zameli, Nabaa Duaa Fakher

Muthanna Journal of Administrative and Economics Sciences

The purpose of this study is to justify the role of The green value chain as a modern technique of management accounting in facilitating investment decisions and optimizing the effectiveness in resources utilization at industrial units. The premise underlying the study is that green value serves as a frame of reference for analysing activities, which in turn allows to separate value-adding from non-value adding ones, leading to cost reduction and environmental soundness. Management is also not about finding faults for waste and allocating funds, it's all about tapping new ways of creating value by eliminating non-value adding activities. The deductive …

Enhancing Introductory Cybersecurity Learning: A Design-Based Research Case Study, Manny Niri Dr.

Journal of Cybersecurity Education, Research and Practice

This study employs a design-based research (DBR) framework to examine the impact of a comprehensive curriculum redesign in an introductory Foundations of Security module for undergraduate students in computing and cybersecurity at a UK public university between 2019 and 2025. The redesign aimed to enhance student learning, engagement, and critical thinking through the embodiment of evidence-based pedagogical strategies, including flipped classroom delivery, blended learning, gamified practical exercises, repeated low-stakes mock assessments, and structured problem-solving activities. Student feedback, assessment outcomes, attendance records, and faculty reflections were analysed to evaluate the effectiveness of the redesign. The results indicate substantial improvements in student …

The Use Of Artificial Intelligence For Innovation In The Public Procurement System, Karem Sayed Aboelazm, Khalid Mohamed Dganni, Fady Tawakol, Raghda Raafat

All Works

Public procurement represents a substantial share of national economies and is increasingly shaped by the deployment of artificial intelligence (AI). The research problem addressed in this study concerns how AI can be integrated into public procurement systems without undermining core principles of transparency, accountability, and legality. The purpose of the paper is to examine the transformative potential of AI in public procurement while identifying the legal, institutional, and ethical challenges it generates. Methodologically, the study adopts a comparative analytical approach based on procurement laws, government reports, and peer-reviewed scholarship, focusing on the United Arab Emirates (UAE), Estonia, and South Korea. …

2025 San Diego Regional Climate Collaborative Annual Report, San Diego Regional Climate Collaborative

San Diego Regional Climate Collaborative

The San Diego Regional Climate Collaborative is a network for public agencies that serves the San Diego region to share expertise, leverage resources and advance comprehensive solutions to facilitate climate change planning. By partnering with academia, nonprofits, and businesses, the SDRCC also works to leverage the profile of regional leadership. This is the 2025 San Diego Regional Climate Collaborative Annual Report.

Enhancing Cyber Hygiene Among Communities Through Experiential Cyber-Security Awareness Programs, Dr Atul Bamrara, Partha Roy, Vishwanath Gargote, Khandu Thungon

Journal of Cybersecurity Education, Research and Practice

Human error remains the most frequently exploited vulnerability in the cyber-security ecosystem. Despite substantial investments in technical safeguards, cybercriminals increasingly rely on social engineering, misinformation, and emotionally manipulative tactics to compromise users. This study examines behavioral changes among participants who underwent structured cyber-security workshops addressing both conventional cyber hygiene practices and emerging digital threats. The training modules covered digital arrest scams, identity theft, sextortion, fake technical support fraud, fake social media profiles, online gaming related risks, and deep fake manipulation. The workshops were designed using interactive simulations, real world case studies, and hands on problem based exercises, with the explicit …

Educating For Responsible Ai Governance - Building Interdisciplinary Frameworks For The Management Of Artificial Intelligence, Grace Eboh

Southwestern Business Administration Journal

As Artificial Intelligence (AI) becomes increasingly prevalent across industries, there is a critical need for educational programs that teach effective AI governance and management. This article examines how educational institutions can develop comprehensive curricula to prepare professionals for the complex challenges of overseeing AI systems responsibly. It analyzes current gaps in AI governance education, proposes frameworks for curriculum design, and identifies key competencies required for effective AI stewardship. The findings suggest that successful AI governance education must adopt an interdisciplinary approach that integrates technical literacy, policy understanding, ethical reasoning, and organizational management.

Utilizing The Financial Calculator For Graduated Annuities: Compound Rate, Discount Rate, Present Value, And Future Value, Su-Jane Chen

Southwestern Business Administration Journal

This paper lays out a comprehensive, systemic, and conceptual framework for applying a financial calculator to handle graduated (growing) annuities, a practically important topic that has not received its due attention in finance textbooks. It introduces an alternative to the conventional approach in transforming the growth rate and the interest rate into a single rate as I in the calculator. It then shows that both approaches give the same answer and demonstrates how they can be used interchangeably with the illustration of several numerical examples. In short, this article provides a thorough rationale and gives a clear presentation for the …

Una Student Organizations, Student Engagement Center, University Of North Alabama

Documents

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Comparative Study On Ai Talent Cultivation In China And The United States: Strategies And Recommendations, Lexuan Li, Ke Wen, Wenjie Liu, Wei Shen, Zhenguo Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence (AI), as the core driving force of the new industrial revolution, has become a strategic pillar for enhancing national competitiveness, with the cultivation of AI talent being a decisive factor. This study systematically compares the AI talent cultivation systems of China and the United States from three perspectives: strategic planning, formal education, and practical domains. The findings reveal that the U.S. has continuously and systematically advanced AI talent cultivation plans at the national level, granted institutions substantial autonomy in talent cultivation with deep integration of industry-academia-research collaboration, and established a well-developed AI innovation and entrepreneurship environment. Accordingly, the …

Governing Bme Amplification In Large Language Models: A Standards-Aligned Framework For Llm Data Lifecycle Risk Detection And Ethical Ai Governance, Dale A. Rutherford

Theses and Dissertations

Large Language Models (LLMs) now underpin critical systems in education, healthcare, and policy advisory contexts, yet remain susceptible to the recursive amplification of bias, misinformation, and error (BME). These distortions, driven by feedback loops between user interactions, model retraining, and data reuse, accelerate epistemic drift and erode information quality over time. This dissertation advances a comprehensive governance architecture to detect, quantify, and mitigate these risks across the full AI lifecycle. The research introduces the BME Metric Suite, a standards-aligned diagnostic framework comprising five original metrics: Bias Amplification Rate (BAR), Echo Chamber Propagation Index (ECPI), Information Quality Decay (IQD), Pretraining Diversity …

Documenting For Success: A Case Study Of A Graduate Writing Retreat, Elliott Rose, Denise Wetzel, Sara C. Kern, Katie O'Hara-Krebs, Laurin Davis, Salah Seoudi, Carmen Cole

Transforming Libraries for Graduate Students

Graduate students often find themselves balancing the demands of research and writing while managing complex academic and personal needs. Writing retreats provide an intentional space for graduate students to focus on their academic goals while supporting community-building, institutional belonging, and a welcoming environment. This proposal outlines a model for academic librarians and staff to plan and implement an effective graduate writing retreat designed to support graduate student academic activities through intentional collaboration and documentation.

Penn State University’s (PSU) Graduate Student Writing Retreat started as an event housed within the University Library’s Science, Technology, Engineering, and Math (STEM) department. The retreat …

Digital Transformation And Esg Performance In China: The Mediating Role Of Green Innovation, Zhou Yanyu

Student Works (2020-2029)

This study explores the relationship between digital transformation and ESG performance in Chinese A-share listed companies, focusing on the mediating role of green innovation. From the view of resource-based theory, the digital transformation is found to the first enhances ESG performance and how green innovation serves as a key transmission mechanism. Using fixed-effects regression analysis based on 6,763 firm-year observations from 2015 to 2023. The empirical results indicate that digital transformation improves ESG performance by fostering green innovation, which in turn partially mediates this effect. These findings provide theoretical insights on how digital capabilities drive corporate sustainability and offer practical …

Everyone Works On The Sustainability Team: Power Structures And Brand Communication In Sustainable Consumption, Sofia Johansson

USF Tampa Graduate Theses and Dissertations

In response to growing concerns about the way in which consumption practices negatively degrade the environment and contribute to climate change, this thesis explores the role in which brands may counteract this. There are two significant issues pertaining to environmental marketing: (1) current efforts to promote green consumerism, through which consumer brands market products as “eco-friendly” with only marginal reductions in climate impact and misleading labels, are insufficient in mitigating climate change. (2) Additionally, this kind of consumption is unjust, whereby it is marked up in price, limiting access to merely individuals in higher income brackets. Given the insufficiencies of …

Predicting House Prices Using Machine Learning, Pejal Rath, Robert Slater

SMU Data Science Review

This study explores the use of Machine Learning methods to predict housing prices, a problem of significant interest in real estate economics, and data science. Traditional hedonic pricing models have long been used to evaluate the impact of housing attributes on property values, but they often lack the flexibility to capture nonlinear relationships and complex feature interactions. Recent advancements in regression based and Machine Learning approaches provide promising alternatives that may improve prediction of accuracy and market insights. This research will investigate how models such as linear regression, random forest, and gradient boosting can be applied to publicly available housing …

Application Of Open-Source Small Large Language Models For Finance Report Analysis, Tue Vu, Mark Austin, Marcel Tuijn

SMU Data Science Review

The rapid integration of generative AI in finance introduces both opportunities and challenges, particularly when analyzing sensitive data such as Securities and Exchange Commission (SEC) filings. This study investigates the use of open-source Small Large Language Models (SLLMs), deployed locally through the Ollama and LangChain frameworks, combined with Retrieval-Augmented Generation (RAG) for extracting financial insights relevant to index performance and reporting quality. Two key objectives guide this work: (1) benchmarking multiple open-source SLLMs for sentiment analysis, multiple-choice reasoning, and financial question answering, and (2) assessing the feasibility of locally deployed SLLMs for domain-specific financial queries. A standardized set of 50 …

Redesigning Online Graduate Orientation To Foster Academic Resilience And Prevent Underperformance, Stella Michael-Makri, David E. Rodriguez

Journal of Academic Underperformance

Graduate students in fully online programs often begin their academic journey without adequate preparation for the emotional, structural, and cultural challenges of graduate-level work. For students who are first-generation, racially marginalized, international, or returning to education after time away, this lack of scaffolding can lead to early disengagement, underperformance, or attrition. Orientation, often treated as a checklist of logistical tasks, represents a missed opportunity for meaningful academic intervention. This manuscript proposes a five-module conceptual model for online graduate orientation designed to proactively support online graduate students in the domains of emotional regulation and academic identity, time management and executive functioning, …

Insights From Ai Tutors In Undergraduate And Graduate Engineering Courses, Billy Kihei, Sheila Hill, Sumit Chakravarty

Proceedings of the Cognitive Innovation Conference (CognoCon)

As large language models become broadly accessible, questions about how to integrate them productively into engineering education have moved from speculative to urgent. This paper presents the design rationale and early deployment experience of 247officehours.com, a faculty-created, faculty-managed platform that grounds AI tutoring in instructor-selected course materials and connects it to assessment, engagement tracking, and targeted instructional intervention. Drawing on deployment across undergraduate and graduate engineering courses, we describe six core platform features, analyze how student interactions map onto Bloom's revised taxonomy, and identify recurring patterns of productive and unproductive AI use. A tutor–tutee inversion activity, in which students must …

Human-Ai Collaboration In Marketing Brainstorming: A Meta-Analytic Investigation Of Implementation Approaches And Creative Outcomes, Michael Michaels

USF Tampa Graduate Theses and Dissertations

Marketing organizations face intensifying pressure to sustain creative output while managing constrained resources and accelerating digital content cycles. The integration of artificial intelligence into marketing brainstorming processes presents a promising response to this challenge; however, prior to this investigation, no comprehensive quantitative synthesis had established the overall effectiveness of human-AI collaboration in marketing creativity contexts or identified optimal implementation strategies.

This dissertation presents a systematic meta-analytic investigation of AI-enhanced brainstorming effectiveness in marketing contexts. Following PRISMA guidelines, 42 independent empirical studies (N = 2,166 participants) published between 2018 and 2025 were identified across four primary academic databases, coded for implementation …

Analysis Of Student Satisfaction With The Ppg Student Registration Process At Universitas Negeri Malang Using The Servqual And Delone & Mclean Models, Dedi Prestiadi, Darmawan Satyananda, Dedi Tiarno

Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan

This study aims to analyze student satisfaction levels with the Teacher Professional Education (PPG) registration system at Universitas Negeri Malang using an integration of the SERVQUAL and DeLone & McLean models, as well as to develop a strategy for Continuous Quality Improvement (CQI) using Plan-Do-Check-Act (PDCA) cycle. This study uses a descriptive quantitative approach with 10,701 student respondents from three registration stages (BGT 1, Kemenag, and BGT 2). The data collection instrument is a 1–5 Likert questionnaire covering three main aspects: requirements, process, and registration application. Data analysis was conducted through validity and reliability tests, multiple linear regression, and Principal …

Deep Learning Approaches For Anti-Money Laundering On Mobile Transactions: Review, Framework, And Directions, Jiani Fan, Lwin Khin Shar, Ruichen Zhang, Ziyao Liu, Wenzhuo Yang, Dusit Niyato, Kwok-Yan Lam

Research Collection School Of Computing and Information Systems

Money laundering is a financial crime that obscures the origin of illicit funds, necessitating the development and enforcement of anti-money laundering (AML) policies by governments and organizations. The proliferation of mobile payment platforms and smart IoT devices has significantly complicated AML investigations. As payment networks become more interconnected, there is an increasing need for efficient real-time detection to process large volumes of transaction data on heterogeneous payment systems by different operators such as digital currencies, cryptocurrencies, and account-based payments. Most of these mobile payment networks are supported by connected devices, many of which are considered loT devices in the FinTech …

Improving Public Transport Through Machine Learning Influence Flow Analysis (Mifa): Southern England Bus Case Study, Benjamin Lee, Wolfgang Garn, Masoud Fakhimi, Nick F. Ryman-Tubb

Research Collection School Of Accountancy

Public transport (PT) is crucial for enhancing the quality of life and enabling sustainable urban development. As part of the UK Transport Investment Strategy, increasing PT usage is critical to achieving efficient and sustainable mobility. This paper introduces Machine Learning Influence Flow Analysis (MIFA), a novel framework for identifying the key influencers of PT usage. Using survey data from bus passengers in Southern England, we evaluate machine learning models. Subsequently, MIFA uncovers that easy payments, e-ticketing, and mobile applications can substantially improve the PT service. MIFA’s implementation demonstrates that strength and importance lead to specific insights into how service characteristics …

A Data-Guided Analytical Framework For Assessing The Value Of Additional Variables In Heart Transplant Decision Making, Ali Dag, Hamidreza Ahady Dolatsara, Abdullah Asilkalkan, Joseph Ekong, Kamil Ciftci, Ugur Kucuk, Ozlem Cosgun

School of Business

Heart transplantation is a life-saving procedure for patients with end-stage heart failure. The United Network for Organ Sharing (UNOS), which administers the US organ allocation system, substantially expanded the number of clinical and demographic variables collected in its database in 2004. This study examines whether these newly added variables improve the ability to predict survival outcomes for patients on the heart transplant waiting list. An information-gain-based feature selection approach, supported by an extensive review of prior studies, was combined with survival analysis and regularized regression to identify the most influential predictors. Using the selected variables, several classification models, including tree-augmented …

Research On The Influence Mechanism Of Digital Transformation On The International Competitiveness Of The Srdi Smes In China, Bo Sun

Dissertations and Theses Collection (Open Access)

With the continuous advancement of digital technologies, the digital economy is increasingly becoming the dominant force in the global economic landscape. Against this backdrop, the digital transformation of China's specialized, refined, distinctive, and innovative (SRDI) small and medium-sized enterprises (SMEs) has transcended beyond mere technological upgrades and evolved into a crucial strategy for these enterprises to build core competitiveness. Despite SRDI SMEs' strong willingness to pursue digital transformation, research is still lacking on how digital transformation efforts translate into international competitiveness Additionally, existing studies on the degree of digitalization have focused on large enterprises or general SMEs, leaving an academic …

Program Management And Building Partner Capacity: A Tangled Thicket, Phil W. Reynolds

Publications

This chapter explores how the U.S. Department of Defense plans and executes Building Partner Capacity projects in lower-middle and low-income partners. U.S. planners and practitioners rarely understand the effective pre-conditions that influence partner security apparatus and infrastructure. Consequently, security capabilities provided to the partner are rarely sustained and provide questionable security to the affected population. The U.S. Department of Defense uses a three-part approach to building security with partners: training and equipping, building institutional capacity, and monitoring and evaluating. U.S. security planners should manage all three parts concurrently to produce a security capability that the partner uses and sustains and …

Enterprise Digital Transformation: An Analysis Of Value Creation From An Operational Perspective, Weiguo Ling

Dissertations and Theses Collection (Open Access)

Digital transformation has become a critical pathway for the manufacturing sector to break through growth bottlenecks and reshape its core competitiveness. However, in practice, a large number of enterprises are trapped in the transformation paradox of a “discrepancy between perceived consensus and actual outcomes”. The core issue lies in the fact that traditional investment evaluation methods struggle to effectively measure the multi-dimensional value created by digitalization. From the perspective of operational management, this study focuses on the mechanisms and evaluation methods of digital value creation in different manufacturing contexts. A four-dimensional Value Evaluation Framework is proposed, comprise of Value Identification, …

Interest Fit Beyond The Riasec: The Comprehensive Assessment Of Basic Interests-O*Net (Cabin-Net), Chu Chu, Kevin A. Hoff, Zihan Liu, Nicholas F. Heimpel, Anthony Greco, Frederick L. Oswald, James Rounds

Research Collection Lee Kong Chian School Of Business

Over the past half-century, Holland’s RIASEC model has dominated vocational interest research. Although the RIASEC categories effectively capture general occupational themes, their breadth obscures meaningful variability across underlying basic interests, which are more refined interest scales. In this research, we adapted the Comprehensive Assessment of Basic Interests (CABIN; Su et ., 2019) to be used alongside O*NET for assessing interest fit, resulting in the 60-item CABIN-NET that measures 20 basic interest scales organized under RIASEC domains. In Study 1, we refined items for the CABIN-NET using a nationally representative adult sample (N = 768). In Studies 2 and 3, we …

Interdependence And Portfolio Analysis Of Property Sector Real Estate Investment Trusts (Reits) In Malaysia During Covid-19, Muhammad Aqhari Azmi, Muhammad Zaim Razak

International Journal of Management, Finance and Accounting

This study examines the benefits of incorporating Malaysian Real Estate Investment Trusts (REITs) into a mixed-asset portfolio, with a focus on the periods preceding, during, and following the COVID-19 pandemic. The study utilises daily data from 1 January, 2018 to 21 October 2024, sourced from the Datastream database. By utilising the Dynamic Conditional Correlation-Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) model, the study examines the volatility of office property REITs and retail property REITs, as well as the linkages between these assets and stocks and bonds. The findings reveal that REITs exhibit unique volatility structures and correlations with other financial assets, which …