Digital Commons Network^™

Unearthing Potential: Impact Investors’ Perspectives On Egypt’S Social Enterprise Market, Yousef Hesham Shoukry

Theses and Dissertations

This thesis examines impact investing in Egypt from the vantage point of the impact investors, revealing that Egypt's constraint is not the availability of capital but its direction, as the absence of legal recognition, coordinated intermediaries, and a shared impact-measurement standard keeps capital out of a market otherwise rich in social enterprise potential. The study employed a constructivist grounded theory approach, drawing on eleven semi-structured interviews with impact fund managers, ecosystem enablers, and public-sector policy advisors operating in or considering Egypt's social enterprise market. Data revealed that practitioners converge on the founding principles of impact investment (combined financial and social …

Bridging The Gap Between Career Expectations Versus Labor Market Realities, Reinette P. Madrid, Grethel T. Ledesma, Ignatius Aryono Putranto, Jyro B. Triviño

Leadership and Strategy Faculty Publications

Most students lack awareness regarding the labor market outcomes for their chosen college majors. This study aims to answer what factors affect the career expectations of graduating students at Quezon City University and how these expectations align with the prevailing labor market situation. It employed descriptive, causal, and explanatory research using a sample of 108 respondents from fourth-year information technology students for the school year 2021 to 2022. Eight of the nine null hypotheses were rejected by employing multinomial logistic and linear regression. Student fixed effects and other labor market outcomes significantly predicted salary, estimated stability, and estimated skills in …

Optimizing Inventory Management, William Hawkins

Agricultural Economics and Agribusiness Undergraduate Honors Theses

Inventory management is extremely important for businesses to maximize their profitability. Many factors go into the decision-making process for how much inventory to hold and when to restock this inventory. Through the process of an internship, I determined that some of the most important factors were the amount of a part that needed to be ordered at a time and what order quantities would allow for high levels of customer satisfaction. In this research, I compared these factors between the different models I studied, and the data I received from Riggs CAT to determine whether or not maximum efficiency and …

Quantifying Customer Sentiment For Automobile Brand Perception Analysis Using Machine Learning On Twitter, Sujith Samuel Mathew, Kadhim Hayawi, Neethu Venugopal, May El Barachi

All Works

Social networking sites provide a platform for individuals to express their opinions publicly. Brand managers actively use these platforms to gain insights into brand perceptions, as users often share their views on products and services. In this study, we use sentiment analysis to assess customer sentiment towards five leading automobile brands, analyzing text content shared on Twitter(or X). The research models the ’Brand Polarity Score’, which indicates whether customers perceive the brand positively or negatively. This score is further weighted based on the tweet’s influence, characterized by the engagement metrics of the tweet and the author’s follower count. We also …

Temporally Rigorous And Traceable Predictive Maintenance Via Joint Labeler-Model Optimization, Maytha Al-Ali, Ahmad Alharbi

All Works

Predictive maintenance (PdM) is a critical enabler of intelligent asset management in Industry 4.0, yet many existing frameworks remain difficult to operationalize due to methodological fragmentation. Common limitations include sacrificing temporal realism and class granularity for computational expediency, decoupling labeling strategy design from model hyperparameter optimization, and insufficient support for reproducibility and deployment traceability; particularly in rare-failure regimes. To address these challenges, we propose a unified, end-to-end, and fully traceable PdM framework that jointly optimizes labeling and model parameters while enforcing strict temporal fidelity. The proposed pipeline co-optimizes the failure lookahead window () and LightGBM hyperparameters within a single Bayesian …

The Role Of Corporate Sustainability Goals In Shaping Organizational Intentions And Adoption Of Green Technologies In Small- And Medium-Sized Enterprises, Syed Zamberi Ahmad, Abdul Rahim Abu Bakar, Imane Belyamani, Manar Fawzi Bani Mfarrej

All Works

This study investigates green technology adoption (GTA) among small and medium-sized enterprises (SMEs) in the United Arab Emirates (UAE), focusing on the influence of corporate sustainability goals (CSG) and sustainability motivation (SM). Utilizing institutional theory, the theory of planned behavior (TPB), and resource-based view (RBV), the research highlights how SMEs integrate environmental, social, governance (ESG) and economic considerations into their CSG to enhance GTA. Addressing a gap in prior research that has largely emphasized external drivers of adoption while underexploring internal organizational mechanisms, the study conceptualizes CSG as strategic intent and models SM as a second-order construct . Based on …

Generative Ai Adoption And Solvers' Popularity On Supply-Driven Crowdsourcing Platforms: The Dual Role Of Price Signals, Zimeng Zhu, Carol Hsu, Fiona Fui-Hoon Nah, Na Liu

Research Collection School Of Computing and Information Systems

Purpose – We investigate the effect of solvers’ adoption of Generative AI (GenAI) on their popularity in a supply-driven crowdsourcing platform. We also examine the impact of price signals as well as their heterogeneous impact based on the solvers’ membership duration on the platform. Design/methodology/approach – Our analysis focuses on solvers who adopt GenAI for design-related gigs on the supply-driven crowdsourcing platform. By combining propensity score matching (PSM) with multi-period difference-in-differences (DID), we examine how GenAI adoption impacts solvers’ popularity and how price signals affect this main effect. Findings – Our findings reveal that solvers who adopt GenAI tend to …

How Leaders Build Employee Trust In Artificial Intelligence: Voice Opportunities, Humility, And Trust Transfer, Jack Mcguire, David De Cremer, Devesh Narayanan

Research Collection Lee Kong Chian School Of Business

Artificial intelligence is increasingly central to organizational work, yet employee trust in AI remains fragile. Although prior research has primarily explained trust in AI through technological characteristics such as transparency, reliability, and accuracy, we argue that trust in AI is also shaped by the social context in which employees encounter these systems. Drawing on affect-as-information theory and social information processing theory, we develop and test a model in which leader-provided voice opportunities reduce employees’ negative affect about AI-related work experiences, thereby enhancing perceptions of leader trustworthiness and, in turn, trust in AI. We further propose that this indirect effect depends …

The Effects Of Eps Level And Presentation Format Of Analysts’ Forecast Deviation On Non-Professional Investors’ Investment Judgments, Clarence Goh, Prasart Jongjaroenkamol, Poh-Sun Seow

Research Collection School Of Accountancy

We experimentally investigate how the presentation format of the extent to which a firm's earnings per share (EPS) diverges from analysts' EPS forecasts (i.e. deviation information) and a firm's EPS level affect the investment judgments of non-professional investors (referred to hereafter as “investors”). Our results suggest that investors' investment judgments are more positive when firms with low (high) EPS levels disclose deviation information in percentage (absolute) terms. Furthermore, when the percentage of forecast deviation is held constant, investment judgments are more positive when EPS levels are high versus low if the deviation information is expressed in absolute terms. By contrast, …

Full Posterior Uncertainty Propagation In The Bg/Nbd Framework A Bayesian Foundation For Individual-Level Customer Behavior Modeling, Stuart V. Kerr

UNLV Gaming Research & Review Journal

The Beta-Geometric/Negative Binomial Distribution (BG/NBD) model of Fader et al. (2005) is used to describe repeat-transaction behavior in non-contractual settings: a latent visitation rate, heterogeneous across customers, governs how of- ten a customer transacts while active, and a latent dropout probability, also het- erogeneous, governs when a customer permanently churns. In its classical form, BG/NBD is estimated using maximum likelihood, producing single point estimates of the underlying population parameters and, from these, point estimates of each customer’s individual behavior. This paper develops the model from first princi- ples as a fully Bayesian framework, estimated using Markov Chain Monte Carlo (MCMC), …

Where Shoppers Look First: How Navigation Bar Design Shapes Visual Attention Online, James Coyle, Linh Nguyen, Lee Hillman

Atlantic Marketing Journal

Abstract

Despite the crucial role that a website navigation bar can play in affecting consumer behavior, there has been a lack of theory-driven studies to investigate how to most effectively design navigation bars. Grounded in cognitive fit theory and visual attention theory, this study investigates how the effects of navigation bar design and content can influence visual processing of an unfamiliar online retailer’s website. A total of 40 subjects participated in a controlled experiment in which we gathered eye-tracking data. We find that navigation bar placement strongly affects how quickly participants locate the navigation bar: an unexpected placement more than …

Complementary Global–Local Feature Fusion And Ensemble Refinement For Facial-Expression Recognition On Fer2013, H. M. Shahzad, Hassan A. Ahmed

Business Faculty Publications

Facial-expression recognition (FER) on FER2013 remains challenging because of low-resolution images, class imbalance, and label ambiguity. This study presents a global–local feature-fusion framework that integrates complementary representations with validation-based ensemble refinement. A frozen DINOv2 ViT-Base captures global facial semantics, while EfficientNetB3 extracts complementary local texture features. Their fused representation is used for seven-class facial-expression classification. The classification head is first trained with targeted feature-space SMOTE, and the EfficientNetB3 branch is then partially fine-tuned. Five-view test-time augmentation (TTA) is further incorporated at inference, together with an independently trained ConvNeXt-Tiny branch to provide additional architectural diversity. Ensemble weights are selected using a …

Designing For Who Actually Shows Up: A Signal Framework For Online Adult Learners In Cybersecurity And Information Technology, Chad Whistle, Mayyada Al-Hammoshi

Journal of Cybersecurity Education, Research and Practice

Online adult learners pursuing cybersecurity and information technology credentials represent one of the fastest-growing student populations in American higher education, yet the frameworks institutions use to support their success were not designed for them. This population, disproportionately drawn from the 41.9 million Americans who hold some college credit but no credential, arrives workforce-embedded, time-constrained, and skeptical of institutional systems that previously failed to serve them. Existing persistence models grounded in traditional student integration theory inadequately account for the behavioral patterns, motivational structures, and credential expectations that define this learner. This paper proposes the SIGNAL Framework (Skills-based credential architecture, Integrated AI-informed …

From Innovation To Impact: Evaluation Of The Shape Accelerator Cohort, Iryna V. Lendel, Chloe Wieber

Upjohn Institute Technical Reports

The Solutions Hub for an Alternative Packaging Ecosystem (SHAPE), a Michigan-Ohio partnership operated by the Michigan State University Research Foundation as part of a National Science Foundation Regional Innovation Engine, co-funded a special cohort of the NextCycle Accelerator focused on sustainable packaging and circular economy ventures. This report evaluates how the accelerator contributed to firm-level advancement and ecosystem-level change, drawing on program data and interviews with participating companies, program facilitators, stakeholders, and SHAPE management.  Participants most consistently credited coaching, network connections, and the Pitch Showcase with meaningfully impacting their business trajectory, gaining market traction, advancing technology readiness, and gaining access …

Service Robots With Low Anthropomorphism In Restaurants: Consumer Reactions And Implications, Ferhat Eren, Volkan Genc

Journal of Global Hospitality and Tourism

This study investigates consumer responses to low-anthropomorphic service robots in restaurant front of-house roles using the AIDUA (Artificially Intelligent Device Use Acceptance). Data from 1,268  participants were analysed using PLS-SEM. The results revealed that social impact and  anthropomorphism significantly influenced both performance and effort expectancy, while hedonic  motivation influenced only performance expectancy. Performance expectancy strongly influenced  emotions, which in turn significantly influenced both the willingness to use service robots and objections  to their use. However, effort expectancy did not significantly influence emotions. The findings validate the  AIDUA model in this context and offer practical insights for robot design and implementation.

Diagnosing Influential Observations Via Hybrid Secretary–Osprey Optimization Algorithm (Hsooa) In Gamma Regression Models For Fasting Blood Glucose Data, Luay Adil Abduljabbar, Sabah Manfi Ridha

Journal of Economics and Administrative Sciences

Influence diagnostics are essential for identifying influential observations that may affect the estimation accuracy of regression models. Classical diagnostic measures such as Cook's Distance and DFFITS may become less effective in complex or highly dispersed datasets. In this study, a new Hybrid Secretary–Osprey Optimization Algorithm (HSOOA), based on the integration of the Secretary Bird Optimization Algorithm (SBOA) and the Osprey Optimization Algorithm (OOA), is proposed for influential observation detection in the Gamma Regression Model (GRM). This optimization framework successfully achieves an optimal balance between global exploration and local exploitation. The proposed HSOOA framework was applied to a real medical dataset …

Random Forest Algorithm Vs. Linear Regression For Financial Performance Determinants: Evidence From Iraqi Mixed-Sector Firms, Odaiy Obaid Zeidan, Mustafa Habib Mahdi

Journal of Economics and Administrative Sciences

This paper examines the predictive factors of financial performance among Iraqi mixed-sector firms, comparing the predictive power of traditional Ordinary Least Squares (OLS) regression with the Random Forest (RF) machine learning algorithm. Utilizing annual data from 11 firms over the period 2015–2020, the study measures financial performance using Return on Assets (ROA), Return on Equity (ROE), and Return on Sales (ROS). OLS regression identified the directional relationships and p-values, whereas Random Forest evaluated predictive accuracy and modeled nonlinear relationships. The OLS results indicate that firm size, liquidity, productivity, and cash-to-asset ratio have significant positive effects on financial performance, while the …

Chacahoula 2026, Volume 93, Pawan Khatri, Alayna Pellegrin

Chacahoula

The 2026 issue of Chacahoula, There's No Place Like Home, emphasizes the way in which our university becomes a home to students.  Featuring prize-winning poetry from Allyson Gee, Nick Fredrick, Amaris Kendall and Anmol Subedi, the book includes December 2025 and May 2026 graduating classes, as well as stunning photography of  campus life on the banks of Bayou Desiard. With features covering students, faculty, and staff, this year's time capsule preserves an academic year in the life of the University of Louisiana at Monroe. This edition includes a video message from President Carrie Castille. Download the PDF to your device …

Green Finance’S Role In Bank Risk: Empirical Evidence From The Emerging Economy, Viverita Viverita, Dwi Nastiti Danarsari, Ratih Dyah Kusumastuti, Ruhaini Muda

Journal of Environmental Science and Sustainable Development

Indonesia’s Financial Services Authority (OJK)’s sustainable finance roadmap, phases I and II, primarily aims to facilitate sustainable development by integrating economic, social, and environmental considerations into financial policies. A special objective is to promote the development of green financial products and services. This policy allows banks to mitigate reputational and regulatory challenges. Nevertheless, the prompt implementation of green credit may entail transition risks, such as policy adjustment costs. A limited body of research examines the direct relationship between green finance and bank risk, particularly in the context of sustainability mandates. This study analyzes the influence of green finance on banking …

Regional Creative Economy Resilience Index: An Analysis Of The Creative Industry's Role In Fostering National Economic Resilience According To Asta Cita, Dks Nugraha Nugraha, Ramadhania Mumtaz Keesa

Jurnal Vokasi Indonesia

Indonesia's creative economy has survived worldwide economic shifts, especially the COVID-19 epidemic. This industry now drives innovation, culture, and technology. No systematic technique exists to quantify the creative ecosystem's impact on regional economic resilience. The Regional Creative Economy Resilience Index (IRED) is a conceptual model based on Asta Cita 2024–2029's eight strategic missions. This article uses the Asta Cita framework to describe how the creative industry strengthens national economic resilience and advances the IRED idea as a data-driven research and policy tool. This qualitative-descriptive study synthesizes 20 periodicals (2020–2025), analyzes policy, and maps themes using Asta Cita. Source triangulation …

The Lack Of Social Interaction In The Full-Time Remote Work Environment And Career Development, Tiphany Moguel-Young

Doctoral Dissertations and Projects

The purpose of this qualitative single case study was to explore the lack of social interaction in the full-time remote work environment and its influence on career development for remote workers at a U.S.-based financial services organization in Dallas, Texas. The theory that guided this study was social cognitive career theory. The central research question was, “What attributes of social interactions do remote workers perceive as assisting or hindering their career development?” Data collection consisted of semistructured interviews with nonmanagerial remote workers, a focus group with managers, and anonymous open-ended survey responses and reflective journaling from all participants. The data …

Interpretive Flexibility And The Social Construction Of Generative Ai In Education: A Scot Analysis, Elham Mousavidin, Sujin K. Horwitz

Southwestern Business Administration Journal

The rapid rise of generative artificial intelligence (GenAI) tools has intensified discussions about their role in education. This study uses the Social Construction of Technology (SCOT) framework to explore how educational stakeholders interpret GenAI and how these interpretations influence its development and adoption. Through an interpretive literature review of research published between 2021 and 2025, we examine stakeholder perspectives using SCOT constructs, including relevant social groups, interpretive flexibility, technological frames, and controversies. Results identify three main interpretive tensions shaping current debates: transformational force versus transactional tool, cognitive augmentation versus cognitive atrophy, and digital empowerment versus digital enslavement. These tensions show …

Current Research On The Use Of Ai In Higher Education, Jim A. Mccleskey

Southwestern Business Administration Journal

The rapid adoption of artificial intelligence (AI), particularly generative artificial intelligence (GenAI) tools such as ChatGPT, has introduced profound opportunities and challenges for higher education. This paper presents a thematic scholarly review of recent empirical studies, systematic reviews, and conceptual analyses examining AI’s impact on teaching, learning, assessment, and institutional practice. The literature highlights substantial benefits associated with AI use, including increased academic productivity, personalized and adaptive learning pathways, enhanced accessibility for diverse learners, and new opportunities for pedagogical innovation. At the same time, significant risks emerge related to cognitive offloading, erosion of critical thinking, academic integrity, blurred authorship, assessment …

Uae Audiences' Reliance On Social Media As A Source Of Information On Complementary And Alternative Medicine: A Study Of Al Ain City Residents Based On Media System Dependency Theory, Abdul Rahman Al-Toum, Mohammed Al-Kaabi, Najoud Al-Mansouri, Ahmed Bin Ishaq, Amer Khaled Ahmad, Maram Manajrah

Middle East Journal of Communication Studies

This study examined the extent to which UAE audiences rely on social media as a source of information on complementary and alternative medicine (CAM) and the resulting effects of this reliance. Grounded in Media System Dependency Theory, the study employed an audience survey using a questionnaire administered to a sample of (132) Emirati citizens in Al Ain. The findings revealed that the combined medium and high reliance reached (53%). Regarding the effects, cognitive effects recorded the highest arithmetic means, followed by affective and behavioral effects at comparable levels. Hypothesis testing showed no statistically significant differences in the degree of reliance …

When Does Global Search Pay For Itself? A Measured Exploration Cost And Energy Break-Even Analysis Of A Metaheuristic Search Controller In Solar Energy Systems, Mohamed Ali Muammar Ezgour

Communications of the IIMA

Autonomous energy systems increasingly delegate the choice of operating point to embedded search algorithms, trading a fast local optimizer that can settle on a wrong point against a slower global search that guarantees the right one at a measurable cost. This paper reframes maximum power point tracking under partial shading as that decision and measures its economics on a fixed photovoltaic plant in MATLAB/Simulink. A Hippopotamus Optimization global search handed over to incremental conductance is compared with incremental conductance alone across seventeen initial duty cycles and thirty random seeds. The hybrid reached the global peak in all thirty seeds, whereas …

Bitseat: Reimagining The Financing For Airliners Using Nonfungible Tokens (Blockchain Technology), Edwin S. Ongola

Journal of Aviation Technology and Engineering

This essay describes how blockchain technology, particularly nonfungible tokens, can be used to raise funding for airliners. The essay begins with a brief overview on the costs, categories, and acquisition methods of airliners. After that, the essay introduces concepts on blockchain technology, tokens, and smart contracts. The essay then touches on how nonfungible tokens can be used to facilitate fractional ownership of airliners. From there, the essay discusses Bitseat, a conceptual nonfungible token for fractional ownership of airliners, covering its overall design, appeal, marketplace alternatives, and challenges. Finally, in the discussion, the essay summarizes the overall concept and outlines its …

People Orientation And Thing Orientation In Business Majors: Implications For Assessing The Impacts Of Cross-Functional Business Program Curricula, Todd J. Hostager, David A. Christopher, Kristy J. Lauver, Christopher Knowles

International Journal for Business Education

Background/Introduction/Purpose:  Prior research documented significant differences in people orientation and thing orientation (PTO) based on type of major and sex.  This study examines a set of measures for helping business programs to assess whether they are producing graduates equipped to consider both people and things when making decisions, regardless of their major or sex.

Methods/Design:  Students in a strategic management capstone course spent a single 75-minute session responding to a brief new venture pitch by identifying what types of additional information they would need to decide whether to invest in the business.  Three Likert-scaled options gauged the extent to participant …

The Role Of Generative Ai In Secondary School Business Education: Insights From Teachers’ Perceptions, Leonard Busuttil, Emanuel Mizzi

International Journal for Business Education

Background/Introduction/Purpose: Generative artificial intelligence (GenAI) has entered classrooms more quickly than the evidence base needed to guide its use, and that evidence base remains concentrated in higher education. Comparatively little is known about secondary school business education, a curricular area that brings together accounting, business studies, economics, financial literacy, marketing, and retail, and in which teachers move between subjects whose epistemological and procedural demands differ considerably. Existing studies also tend to treat business education as a single homogeneous domain, or to examine one of its subjects in isolation. This study addresses that gap by examining how secondary school business education …

Developing A Deep Learning-Based Artificial Intelligence System For Detecting Scientific Misinformation On Digital Platforms, Shorouq Al-Awawdeh, Ayah Al- Jafari

Middle East Journal of Communication Studies

Objectives: This study develops and evaluates an Arabic scientific misinformation detection system by fine-tuning AraBERT-base-v2. It examines the effects of early stopping and input sequence length on model performance, interprets selected linguistic characteristics associated with misleading content, and discusses the limitations of using machine-translated data.

Methodology: The study adopted a mixed-methods design, employing a systematic integration of quantitative and qualitative approaches, supported by an interpretive qualitative reading. The initial database consisted of 23,546 records, including 123 Arabic articles collected from the Akeed, Sheek, and Taqeen platforms, and 23,423 foreign-language records drawn from the GossipCop and PolitiFact collections within FakeNewsNet. After …

From Data To Decision-Making: The Role Of Local Digital Twins In Cross-Domain Management Within Municipalities – A Research-In-Progress Study In Veenendaal, Diana M.E. Boekman, Koen Smit, Guido Ongena, Rob Peters

Communications of the IIMA

Municipalities are facing increasingly complex, interconnected challenges in areas like housing, climate adaptation, mobility, and social policy. Local Digital Twins (LDTs) are seen as a promising tool to make this complexity more understandable and support decision-making. At the same time, both literature and practice show that few initiatives get past the pilot phase, even though getting through that phase is essential for successful long-term adoption.

This paper presents a research-in-progress study on the development and application of an implementation method for LDT technology within the municipality of Veenendaal, based on human values rather than driven by technological possibilities. Based on …