Computer and Systems Architecture Commons^™

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 …

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

Journal of International Technology and Information Management

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

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

Journal of International Technology and Information Management

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

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

The Value Of Personal Data Ecosystems: A Flemish Media Sector Case Study, Maarten De Mildt, Melanie Verstraete, Sofie Verbrugge, Didier Colle

Journal of International Technology and Information Management

Personal Data Stores (PDSs) have been proposed as a privacy-preserving approach to data sharing that increases individual control over personal data while enabling new forms of cross-organizational collaboration. This collaboration leads to the emergence of Personal Data Ecosystems (PDEs). Despite growing interest in PDEs, limited research has examined how the organizational and economic barriers identified in prior studies manifest in practice. This paper investigates these challenges through a case study of the Flemish media sector within the Solid4Media project, which explores the use of PDSs to support data sharing and personalization across media organizations. Using a qualitative research design, data …

Responsible People Analytics For Remote-Work Decisions: A Machine-Learning Benchmark For Classifying Perceived Productivity, Ruth Menjivar, Nima Molavi, Narges Mashhadi Nejad

Journal of International Technology and Information Management

This study examines whether employee-perception survey data can support responsible people-analytics decisions about remote-work productivity. Using the public New South Wales (NSW) Remote Working Survey 2021 (N=1,512), the study benchmarks statistical and machine-learning classifiers for self-reported perceived productivity classes (same, less, or more productive when working remotely relative to onsite work), not objective output, under default, class-weighted, and resampling protocols. Main evidence comes from 5×5 repeated stratified cross-validation using macro F1 and balanced accuracy with fixed model specifications. Class-balanced separability is modest. Random Forest, CatBoost, and LightGBM form a leading cluster with overlapping confidence intervals (macro F1 ≈0.51–0.52). Affective/well-being items, …

Towards Developing A Career Technology Fit Framework And Analyzing Its Influence On Work-Related Outcomes Among It Professionals, Gunjan Tomer

Journal of International Technology and Information Management

With growing attrition rate and significant demand for skilled IT professionals, the importance of studying their behaviour has become important for both academia and industry. Despite ample amount of research, there is still a gap between theory and practice. Based on our qualitative study conducted on Indian IT professionals we propose that technology allocation might contribute in understanding the behaviour of IT professionals. We found that IT professionals evaluate the technology allocated to them based on their individual career motives. This evaluation, either positive or negative, influences their job outcomes. Further, we explored the factors that make a technology preferable …

High Technology And The Developing State: The Arrival Of Supercomputers In India, Ramesh Subramanian

Journal of International Technology and Information Management

While India has made vast strides in information technology in the last few decades, its success is mainly attributed to its software, rather than its hardware sector. In fact, India’s attempts at developing computer hardware that can match international standards have largely been unsuccessful. A notable exception is its development of a series of supercomputers that match and exceed many international standards. This paper looks at an interesting period in India’s computing history – namely the 1980s and 1990s – focusing on its development of an indigenous supercomputer. During that period, supercomputers were thought to be the sole privy of …

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. …

Virtual Makeup And Technology Integration, Vishwa Bhatt

Electronic Theses, Projects, and Dissertations

The Virtual Makeup Streamlit application presents an advanced approach to digital cosmetic try-on by allowing users to apply makeup to their facial images in real time. This project uses computer vision and web technologies to create an interactive and user-friendly platform that capitalizes on the increasing popularity of virtual try-on solutions in the cosmetics industry.

At its core, the system uses effective facial detection and semantic segmentation techniques to recognize and separate facial areas such as lips and hair. Techniques such as U-Net and Resnet, and Midepipe are used to create accurate segmentation masks, which are essential for accurate makeup …

Ntier Code Generator, Mohammed Qattan

Electronic Theses, Projects, and Dissertations

This project presents a software tool designed to automate the generation of standardized code for all layers of an n-tier architecture, including the Database Layer, Data Access Layer (DAL), and Business Logic Layer (BLL). By employing object-oriented principles and parsing the database structure, the tool ensures modularity, scalability, and maintainability. It efficiently formats code templates for CRUD operations, enhancing development efficiency and consistency, while streamlining database interactions and enforcing business rules.

This project presents an innovative software tool designed to automate the generation of standardized code for all layers of an n-tier architecture, including the Database Layer, Data Access Layer …

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. …

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 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.

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 …

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 …

Project Tracking With Mobile Devices, Mike Son

Electronic Theses, Projects, and Dissertations

This innovative project tracking with mobile devices provides comprehensive access to project information, modernized communication, and effective work management from any device. Through a simple interface, it enables real-time collaboration, work delegation, and progress monitoring, making project management simpler everywhere. A standout feature of this application is its provision of a dedicated API (Web Programming Interface) for mobile devices, enabling seamless integration and synchronization between the web application and mobile platform apps. This guarantees a consistent and integrated user experience across all devices, allowing for quick task updates, and information sharing. The web application emphasizes security, with secure encryption and …

Task Management Application, Dhaval Chaturbhai Hirpara

Electronic Theses, Projects, and Dissertations

The Task Management Application is a web-based platform designed to facilitate efficient task and project management, similar to other Project Management Tools like Jira, Trello, ClickUp, Wrike, Zoho Projects, and Asana. The application features three distinct roles: Administrator, Project Manager, and Employee, each with specific functionalities and permissions to streamline workflow.

Administrator: This role encompasses comprehensive project oversight, including adding, viewing, and managing project managers, supervising ongoing projects, and viewing employee details.

Project Manager: Project Managers can manage employees, assign tasks, and oversee project progress effortlessly.

Employee: Employees have dedicated functionalities to view and manage tasks assigned …

Service Connect, Namrata Bomble

Electronic Theses, Projects, and Dissertations

ServiceConnect is an innovative web-based marketplace platform designed to revolutionize how local services are accessed and managed in the US. By connecting service providers and customers directly, ServiceConnect provides a simple, secure, user-friendly platform for a range of services such as home repairs, tutoring, pet care and more. Featuring convenient booking tools that increase efficiency while simultaneously building trust among both parties involved. ServiceConnect stands out with its comprehensive service range, user-friendly interface, secure payment processing and rigorous verification process for service providers. Leveraging advanced technologies like ReactJS on the frontend, Node.js & Express on the backend and MongoDB for …

Crime Data Prediction Based On Geographical Location Using Machine Learning, Sai Bharath Yarlagadda

Electronic Theses, Projects, and Dissertations

This project employs machine learning methods like K Nearest Neighbors (KNN), Random Forest, Logistic Regression, and Decision Tree algorithms to monitor crime data based on location and pinpoint areas with risks. The project implements and tunes the four models to improve the precision of predicting crime levels. These models collaborate to offer a trustworthy evaluation of crime patterns. K Nearest Neighbors (KNN) categorizes locations by examining the proximity of data points considering coordinates and other factors to identify trends linked to increased crime data. Logistic Regression gauges the likelihood of crime incidents by studying the connection, between factors (like location …

Automatic Speech Recognition For Air Traffic Control Using Convolutional Lstm, Sakshi Nakashe

Electronic Theses, Projects, and Dissertations

The need for automatic speech recognition in air traffic control is critical as it enhances the interaction between the computer and human. Speech recognition helps to automatically transcribe the communication between the pilots and the air traffic controllers, which reduces the time taken for administrative tasks. This project aims to provide improvement to the Automatic Speech Recognition (ASR) system for air traffic control by investigating the impact of convolution LSTM model on ASR as suggested by previous studies. The research questions are: (Q1) Comparing the performance of ConvLSTM with other conventional models, how does ConvLSTM perform with respect to recognizing …

Effectiveness Of Cnn-Lstm Models Used For Apple Stock Forecasting, Ethan White

Electronic Theses, Projects, and Dissertations

This culminating experience project investigates the effectiveness of convolutional neural networks mixed with long short-term memory (CNN-LSTM) models, and an ensemble method, extreme gradient boosting (XGBoost), in predicting closing stock prices. This quantitative analysis utilizes recent AAPL stock data from the NASDAQ index. The chosen research questions (RQs) are: RQ1. What are the optimal hyperparameters for CNN-LSTM models in stock price forecasting? RQ2. What is the best architecture for CNN-LSTM models in this context? RQ3. How can ensemble techniques like XGBoost effectively enhance the predictions of CNN-LSTM models for stock price forecasting?

The research questions were answered through a thorough …

The Impact Of Social Media On Charitable Giving For Nonprofit Organization, Namchul Shin

Journal of International Technology and Information Management

Research has extensively studied nonprofit organizations’ use of social media for communications and interactions with supporters. However, there has been limited research examining the impact of social media on charitable giving. This research attempts to address the gap by empirically examining the relationship between the use of social media and charitable giving for nonprofit organizations. We employ a data set of the Nonprofit Times’ top 100 nonprofits ranked by total revenue for the empirical analysis. As measures for social media traction, i.e., how extensively nonprofits draw supporters on their social media sites, we use Facebook Likes, Twitter Followers, and Instagram …

Key Issues Of Predictive Analytics Implementation: A Sociotechnical Perspective, Leida Chen, Ravi Nath, Nevina Rocco

Journal of International Technology and Information Management

Developing an effective business analytics function within a company has become a crucial component to an organization’s competitive advantage today. Predictive analytics enables an organization to make proactive, data-driven decisions. While companies are increasing their investments in data and analytics technologies, little research effort has been devoted to understanding how to best convert analytics assets into positive business performance. This issue can be best studied from the socio-technical perspective to gain a holistic understanding of the key factors relevant to implementing predictive analytics. Based upon information from structured interviews with information technology and analytics executives of 11 organizations across the …

Activities Tailoring Within Agile Scrum Roles: A Case Of Nigerian Healthcare Information Systems Development, Yazidu Salihu, Julian Bass, Gloria Iyawa

Journal of International Technology and Information Management

Developing quality agile healthcare information systems requires understanding regulatory compliance and evolving healthcare needs through activities tailored within agile scrum roles. Agile scrum, a widely adopted philosophy, offers significant advantages in managing software development processes. This research explores how activities within the agile scrum roles are tailored to agile healthcare information systems development within the Nigerian context. This study adopted a qualitative case study methodology and interviewed 12 agile practitioners developing healthcare information systems within Nigeria using semi-structured open-ended interview guide questions. The practitioners were selected based on a snowballing process, a sunset of purposive sampling techniques from our network …

What Can We Learn From A Co-Creation Journey For A Quick Scan Digital Transformation Maturity Assessment Tool For Development Ngos?, Anand Sheombar

Journal of International Technology and Information Management

This paper describes the approach and lessons learned from a co-creation process with Dutch development NGOs to create a practical and easy-to-use assessment tool for practitioners to assess the organisation's maturity level of digital transformation. For this study, we applied a design science research methodology, specifically a six-step co-creation approach suitable for developing maturity models. The digital maturity assessment tool (quick scan) created is a domain- specific digital transformation maturity tool for development NGOs rather than a generally applicable tool. This artefact was evaluated using an eight-point Requirements framework for the development of digital maturity assessment tools. By developing a …

Melanoma Detection Based On Deep Learning Networks, Sanjay Devaraneni

Electronic Theses, Projects, and Dissertations

Our main objective is to develop a method for identifying melanoma enabling accurate assessments of patient’s health. Skin cancer, such as melanoma can be extremely dangerous if not detected and treated early. Detecting skin cancer accurately and promptly can greatly increase the chances of survival. To achieve this, it is important to develop a computer-aided diagnostic support system. In this study a research team introduces a sophisticated transfer learning model that utilizes Resnet50 to classify melanoma. Transfer learning is a machine learning technique that takes advantage of trained models, for similar tasks resulting in time saving and enhanced accuracy by …

Improving Credit Card Fraud Detection Using Transfer Learning And Data Resampling Techniques, Charmaine Eunice Mena Vinarta

Electronic Theses, Projects, and Dissertations

This Culminating Experience Project explores the use of machine learning algorithms to detect credit card fraud. The research questions are: Q1. What cross-domain techniques developed in other domains can be effectively adapted and applied to mitigate or eliminate credit card fraud, and how do these techniques compare in terms of fraud detection accuracy and efficiency? Q2. To what extent do synthetic data generation methods effectively mitigate the challenges posed by imbalanced datasets in credit card fraud detection, and how do these methods impact classification performance? Q3. To what extent can the combination of transfer learning and innovative data resampling techniques …

Enhancing Accident Investigation Using Traffic Cctv Footage, Aksharapriya Peddi

Electronic Theses, Projects, and Dissertations

This Culminating Experience Project investigated how the densenet-161 model will perform on accident severity prediction compared to proposed methods. The research questions are: (Q1) What is the impact of usage of augmentation techniques on imbalanced datasets? (Q2) How will the hyper parameter tuning affect the model performance? (Q3) How effective is the proposed model compared to existing work? The findings are: Q1. The effectiveness of our model depends on the implementation of augmentation techniques that pay attention to handling imbalanced datasets. Our dataset poses a challenge due to distribution of classes in terms of accident severity. To address this challenge …

Classification Of Large Scale Fish Dataset By Deep Neural Networks, Priyanka Adapa

Electronic Theses, Projects, and Dissertations

The development of robust and efficient fish classification systems has become essential to preventing the rapid depletion of aquatic resources and building conservation strategies. A deep learning approach is proposed here for the automated classification of fish species from underwater images. The proposed methodology leverages state-of-the-art deep neural networks by applying the compact convolutional transformer (CCT) architecture, which is famous for faster training and lower computational cost. In CCT, data augmentation techniques are employed to enhance the variability of the training data, reducing overfitting and improving generalization. The preliminary outcomes of our proposed method demonstrate a promising accuracy level of …