Business Intelligence Commons^™

Decoding Stock Market Movements: The Role Of Unemployment And Volatility, Bipllab Roy, Suparna Bhattacharjee

Northeast Journal of Complex Systems (NEJCS)

This study investigates how unemployment and market volatility interact with stock prices in the Indian context, framing the stock–labour–volatility nexus as a complex adaptive system (CAS) rather than a set of linear, time-invariant relationships. Using verified secondary data on unemployment, India VIX, and NSE stock indices for 2013–2023, we first apply simple and multiple regression as a descriptive baseline. Results show a strong negative association between unemployment and stock prices (R ≈ 0.824, R² ≈ 0.68, p < 0.05), consistent with Keynesian demand-side channels, while the linear VIX–stock relationship is weak and statistically insignificant (R² ≈ 0.07, p > 0.05), consistent with the expectation that volatility operates through non-linear, regime-dependent mechanisms not captured by OLS.

Importantly, we document and transparently disclose critical …

Ai-Augmented Financial Advisors: Comparing Ai And Human Analyst Investment Recommendations In Agreement, Performance, And Firm Size Effects, Crystal Chen

Honors College Theses

This study examines the level of agreement and performance between artificial intelligence (AI) generated investment recommendations and human analyst recommendations across U.S. publicly traded firms. Using a sample of twelve companies categorized by firm size (large, mid, and small), the study collects buy, hold, or sell recommendations from generative AI systems and human analysts. Agreement between AI-to-AI and AI-to-human recommendations is measured using Cohen’s Kappa agreement. Portfolio performance is evaluated by constructing equal-weighted portfolios for each recommendation source and size category. Risk-adjusted returns are measured using the Sharpe ratio over 1-, 2-, and 3-month periods. Furthermore, the study tests whether …

A Forecasting Framework For Distribution Center Capacity Utilization: An Applied Industry Study, Jordan J. Shortt

Data Science Undergraduate Honors Theses

This project develops and evaluates a predictive modeling framework for forecasting distribution center capacity utilization at Company Y, with monthly forecast horizons up to one year. Motivated by the operational challenges of seasonal demand volatility, promotional cycles, and the absence of a formally defined capacity metric, the study first constructs a historical capacity utilization measure from raw warehouse management system data — reconciling item volumes, location dimensions, and utilization factors across all DCs — which serves as the target variable for all modeling work. Four models are developed and evaluated against a naïve seasonal baseline: SARIMA, LightGBM, LSTM, and a …

Behavioral Biases As Drivers Of Complexity In Stock Markets: An Agent-Based Modeling Approach, David Joseph Dr, Alwin Joseph, Blesson James, Kajal Dass

Northeast Journal of Complex Systems (NEJCS)

By modeling financial systems as Complex Adaptive Systems, this study investigates how behavioral biases influence emergent complexity in stock markets. The study integrates heterogeneous agents, such as rational traders, herding agents, overconfident traders, and anchoring/disposition-driven investors, within a Limit Order Book framework calibrated to both U.S. and Indian market conditions using an Agent-Based Modeling (ABM) approach implemented through the high-fidelity ABIDES simulation environment. Price dynamics, volatility patterns, and liquidity structures were analyzed by Monte Carlo simulation experiments with different behavioral compositions. The results show that behavioral biases cause nonlinear price reactions, produce heavy-tailed return distributions that distort order-book complexity, and …

Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park

Annual Research Symposium

Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …

The Writing On The Wall: The Rise Of Applied Ai And The Life-Or-Death Choice Every Ceo Must Make Now, Gary Sheng, Ron Roberts

Digital Laboratory: Publisher of Internet Journal

Applied AI is putting AI to its highest and best use: running your organization as autonomously as possible so you can deliver value for humanity while maximizing the scale of the value. The economy is splitting. Organizations that adopt applied AI are expanding their capacity, accelerating their impact, and pulling ahead. Those that don't are quietly becoming irrelevant, not because they're doing bad work, but because the gap between what they can do and what the moment requires is widening every day. This is not a technology question. It is a leadership question. This paper is written for organizational leaders, …

A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines

Dissertations

Artificial Intelligence (AI) is transforming Supply Chain Management (SCM), yet many organizations struggle to assess their readiness for AI adoption and to understand how AI capabilities develop across maturity stages. This dissertation addresses this gap by developing a Capability Maturity Model (CMM) for AI integration in SCM, grounded in Organizational Information Processing Theory (OIPT), the Resource-Based View, and related capability frameworks. The model provides a structured approach for evaluating an organization's information-processing requirements, resource configurations, and alignment needed for effective AI-enabled supply chain operations.

Using a design science research approach, the AI-SCM CMM and its associated assessment instrument were derived …

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

Journal of International Technology and Information Management

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

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

Journal of International Technology and Information Management

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

Pillpetz: A Smarter Way To Encourage Medication Adherence In Children, John H. Begley

CMC Senior Theses

Medication adherence is usually framed as a problem of patient behavior, but this thesis argues that it is equally a problem of design. Children who take daily medication face barriers that adults often do not: developing executive function, dependence on caregivers, shifting school and home routines, privacy concerns, and stigma around being perceived as different. The standard prescription bottle, by contrast, was designed primarily for dispensing efficiency, safety, and accidental ingestion prevention—not for sustained daily use by a developing child.

This thesis proposes PillPetz, a smart pill case and digital companion that uses routine, play, dose confirmation, and caregiver-connected support …

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 …

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

Journal of International Technology and Information Management

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

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

Journal of International Technology and Information Management

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

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

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

The Crowdfunding Paradox In Crisis: Rising Funder Demand Vs. Declining Entrepreneur Supply, Dan Liu, Guangzhi Shang, Cynthia Fan Yang

Journal of International Technology and Information Management

This study investigates how the crowdfunding marketplace responds to major crises, focusing on behavioral shifts among funders and entrepreneurs. Results show a dual impact on platform dynamics. On the demand side, funders become more engaged, with notable increases in the number of backers, average contributions, and total pledge amounts. This heightened activity suggests stronger altruistic motivations, as individuals view crowdfunding as a way to support others during difficult times. On the supply side, however, entrepreneurs act more cautiously, leading to a decline in new project launches. This drop likely reflects increased risk aversion and uncertainty as creators navigate volatile conditions. …

Fasttree-Guided Genetic Algorithm For Credit Scoring Feature Selection, Rashed Bahlool, Nabil Hewahi Prof., Youssef Harrath Dr.

Research & Publications

Feature selection is pivotal in enhancing the efficiency of credit scoring predictions, where misclassifications are critical because they can result in financial losses for lenders and exclusion of eligible borrowers. While traditional feature selection methods can improve accuracy and class separation, they often struggle to maintain consistent performance aligned with institutional preferences across datasets of varying size and imbalance. This study introduces a FastTree-Guided Genetic Algorithm (FT-GA) that combines gradient-boosted learning with evolutionary optimization to prioritize class separability and minimize falserisk exposure. In contrast to traditional approaches, FT-GA provides fine-grained search guidance by acknowledging that false positives and false negatives …

Warehouse Reconfiguration With Ats Lab, Ed Cantor, Dana Pazhouhesh, Mathew Oshinski, Samantha Sanchez

Senior Design Project For Engineers

The ATS Lab Warehouse Reconfiguration project is a collaborative effort between Kennesaw State University’s Department of Industrial and Systems Engineering and ATS Lab, located in Marietta, GA. The goal of this project is to redesign the current warehouse layout to enhance operational efficiency, reduce travel time, and implement sustainable inventory management practices, including 5S and Kanban. Aaron Roob, ATS Operations Manager, and Franklin Hungerford, Continuous Improvement Manager, led this initiative. Our team, “Sick Sigma’s,” is composed of Ed Cantor, our Project Manager, who is working as an intern at ATS during this process; Dana Pazhouhesh (Process Engineer); Matthew Oshinski (Quality …

Utilizing A Virtual Firewall Appliance For Introducing And Reinforcing The Concepts And Implementation Of Devices To Improve Security In A Computing Environment, Stanley Mierzwa, Christopher Eng

Center for Cybersecurity

The educational realm of higher education cybersecurity curriculum continues to evolve to provide more opportunities for experiential hands-on and work role-related practical applications of technology solutions. Gaining greater competencies is quickly becoming a normal requirement for such programs that are designated by the National Security Agency Center of Academic Excellence programs. The work roles of cybersecurity include a variety of knowledge, skills, and abilities, depending on the category of the activity or task. Firewalls have been a staple cybersecurity, network security, and information security device and strategy to protect organization networks and computing environments. This paper will provide details and …

Book Review: Building A God, Carl Lee Tolbert

The Journal of Values-Based Leadership

No abstract provided.

Recent U.S. Government Policy Literature On Critical And Strategic Minerals, Bert Chapman

Libraries Faculty and Staff Scholarship and Research

Critical and strategic minerals have become increasingly important in U.S. government civilian and military policymaking in recent years. This is demonstrated by the heavy use of such minerals in many critical civilian and military infrastructures. This work will discuss how this subject has been addressed in laws, presidential documents, and works by government agencies along with congressional oversight committees and support agencies. It will stress how the United States is heavily dependent on strategic minerals from adversarial foreign countries such as China and will examine U.S. efforts to increase its ability to produce such materials in the United States by …

Decentralized Multi-Hop Federated Reinforcement Learning For Energy-Efficient And Secure Routing In Lorawan-Based Smart City Infrastructure, Harsha Sammangi, Aditya Jagatha, Jun Liu

Research & Publications

This paper proposes a decentralized hybrid framework that integrates Federated Learning (FL) and Reinforcement Learning (RL) to enable energy-efficient and secure multi-hop routing in LoRaWAN-based smart city networks. The method allows local model training at gateways and relay nodes, combining real-time routing decisions with privacy-preserving federated aggregation. Key metrics such as residual energy, link quality, and node trust levels are embedded into the reward function, and lightweight encryption plus differential privacy safeguard routing metadata. Simulation results demonstrate substantial gains in packet-delivery ratio, latency, network lifetime and resilience to adversarial attacks when compared to traditional routing protocols.

Ai, Blockchain, And Autonomous Innovation : Charting The Future Of Intelligent Enterprises, Shubham Gupta

Harrisburg University Other Works

In today’s digital economy, artificial intelligence (AI) and blockchain are twin forces driving transformative change. AI and blockchain each rose to prominence on their own, but together they hold the promise of revolutionizing how businesses operate and create value. AI systems can analyze massive datasets, automate complex decisions, and even mimic human learning and reasoning. Blockchain technology, on the other hand, enables secure and tamper-proof transactions by distributing records across a network, ensuring transparency and trust without relying on a central authority. The convergence of these technologies is ushering in new possibilities for automation, smarter decision-making, and secure digital transactions …

Exploring Generative Artificial Intelligence (Ai) Applications In Fashion: Ethical Concerns In Human-Like Technology, Melissa Kathryn Gonzalez

Faculty Scholarship and Creative Works

No abstract provided.

Predicting Hazardous Near-Earth Objects Using Machine Learning For Planetary Defense, John Costa (Student), Lily Popova Zhuhadar (Mentor)

Posters-at-the-Capitol

Predicting Hazardous Near-Earth Objects Using Machine Learning for Planetary Defense

This research develops a machine learning model to classify Near-Earth Objects (NEOs) as hazardous or non-hazardous based on their physical and orbital characteristics, leveraging NASA's dataset of certified NEOs. NEOs, including asteroids and comets, often pass within close proximity to Earth, and while most pose no threat, some have the potential for catastrophic impacts. By using predictive models such as decision trees and random forests, this study aims to prioritize resources for monitoring and mitigation of high-risk objects. The model incorporates key features like velocity, diameter, and proximity to Earth …

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 …