Business Intelligence Commons^™

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 …

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 …

Comparison Of Communication Interfaces In Ai-Driven Styling Services, Yanbo Zhang, Chuanlan Liu

LSU Fashion and AI x Policy Symposium

No abstract provided.

Ai Agent-Powered Fashion Shopping Services: A Future-Oriented Consumer Adoption Perspective, Yanbo Zhang, Chuanlan Liu

LSU Fashion and AI x Policy Symposium

No abstract provided.

Neuroattnfusenet Dual Branch Attention Fusion For Brain Tumor Mri Classification, Md Sanowar Hossain Sabuj, Farzana Sultana, Md Hasan Or Rashid, Rahul Mudhiraj Mullela

Student Publications

Brain tumor MRI classification remains challenging because tumor appearance varies across cases, class boundaries can be visually subtle, and public 2D MRI datasets may contain redundancy or source-specific biases that inflate reported performance. This study proposes NeuroAttnFuseNet, a dual-path attention-guided fusion network for four-class MRI image classification into glioma, meningioma, pituitary, and no tumor. The model combines a Swin-T branch for hierarchical local morphological representation with a frozen DINOv2 ViT-B/14 branch that provides a 768-dimensional global descriptor from the [CLS] token. The Swin and DINOv2 features are concatenated and passed through a channel-attention gate and fusion MLP before final softmax …

Spec Ops Tools Point Of Sale (Pos) Data Insights, Liam Mcgovern

Business Analytics Student Projects and Publications

No abstract provided.

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 …

Beyond Compliance: Rethinking Ethical Accounting Through Ai And Esg, Rafael L. Portillo

Honors Program Theses and Research Projects

With the increasing adoption of these modern technologies in world markets while maintaining these ethical principles, there is an increasing need for alignment between technology development and ethical responsibility. For instance, in the world of accounting, there is an increasing demand to maintain alignment between technology development and ethics. It is for this reason that these researchers have chosen to explore the link between Artificial Intelligence, ESG, and financial reporting ethics.

The goal of this study is to look at new concerns and moral risks that appear when ESG expectations, AI systems, and accounting practices interact. Earlier research usually studies …

The Impact Of The Covid-19 Pandemic On National Hockey League Fan Attendance, Ramon E. Rivera

Electronic Theses, Projects, and Dissertations

The COVID-19 pandemic struck swiftly around the world, causing several societal functions and normalcies to adapt or shut down completely. This culminating project explores the effects of COVID-19 on arena fan attendance of the National Hockey League (NHL). This project was guided by the following three research questions: Q1 – How did the NHL arena closures affect fan attendance during the COVID-19 pandemic? Q2 – What factors influenced NHL fan arena attendance before the start of the COVID-19 pandemic? Q3 – What factors impacted the NHL arena fan attendance after the conclusion of the COVID-19 pandemic? An empirical model developed …

Investigating The Relationship Between Noun Classes And Plant Folk Taxonomy In Chasu Language Of Kilimanjaro Region In Tanzania, Peter Rabson Mziray

Journal of Humanities and Social Sciences

The current study investigates the relationship between noun classes and plant folk taxonomy in Chasu (G 22). The study focuses on two objectives: the first objective is to describe the plant folk taxonomy in Chasu and the second objective is to determine the relationship between noun classes and plant folk taxonomy in Chasu. Data were collected from rural villages in Same and Mwanga districts by using free listing, field interviews (jungle-walk-and-identify), and written texts containing Chasu plant names. The findings reveal that Chasu folk taxonomy reflects different ethnobotanical categories; including a unique beginner which is mmea/mimea ‘plant(s)’, and three life …

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 …

Skill Evolution In The Age Of Ai-Utilizing Text Analytics For Skill Gap Analysis To Prepare Women For Leadership Roles, Blenda G. Mutuma, Marcelline Ouma, Beth Kanyiri

Communications of the IIMA

ABSTRACT
The rapid advancement of Artificial Intelligence (AI) is transforming the global workforce, presenting both opportunities and challenges for leadership development, particularly for women. As AI automates routine tasks and redefines skill requirements, there is a growing demand for uniquely human capabilities such as emotional intelligence, creativity, and strategic thinking, qualities that are inherently strong and often highly associated with women. Research indicates that women typically score higher in emotional intelligence, particularly in areas such as empathy and relationship management, which are critical for effective leadership (Goleman, 2020). Furthermore, studies by McKinsey & Company (2022) highlight that gender-diverse leadership teams, …

Sentiment Analysis Of Public Commentary On U.S. Farm Bills, Frank Tenkorang, Fletcher Ziwoya

Mountain Plains Business Conference

This study applies sentiment analysis to public commentary on U.S. farm bills to assess patterns of support and opposition. Using Reddit posts from relevant subreddits, we employed two natural language processing models, VADER and RoBERTa, to evaluate sentiment over time. While both models yielded differing sentiment distributions, they revealed increased public engagement during farm bill years, particularly in 2018. Most sentiments were neutral, but negative opinions outweighed positive ones. Posts with stronger sentiments tended to attract more user interaction, especially controversial ones. These findings highlight the polarized yet active public discourse surrounding agricultural policy and the potential for data-driven policy …

A Monte Carlo Analysis Of Cost Competitiveness Of Chinese And U.S. Fine Chemical Exports To Europe Under Europe’S Energy Crisis, Lin Luo

Dissertations

The European energy crisis, driven by geopolitical conflicts, has created a significant supply-demand gap in Europe’s fine chemical sector, necessitating reliance on imports from the United States and China. This quantitative study examined how energy, labor, and logistics costs interacted to shape the cost competitiveness of U.S. and Chinese fine chemical exports to Europe, using a Monte Carlo simulation parameterized with historical data from 2015-2023, to provide a probabilistic forecast of competitive outcomes. The findings revealed that while China holds a 76.55% probability of being the lower-cost supplier, its advantage is characterized by high volatility primarily due to its logistics …

Projectpath: Turn Skills Into Stories, Brady M. Katler, Gregory Lontok

Honors Thesis

In today's job market, even just landing an interview can prove to be quite the challenge. With ProjectPath, we provide applicants the tools to transform a job application into a tailored project. These projects have been proven to help users stand out among all the competition.

Analytics & Insights Internship At Market Performance Group, Ava Mccrary

Information Systems Undergraduate Honors Theses

An Honors Thesis discussing the growth of analytics in the corporate world.

Shortage To Surge - Studying The Post-Covid-19 Guitar Retail Market, Jed H. Kim

Data Science Undergraduate Honors Theses

The COVID-19 pandemic was one of the most catalyzing events of the 21st century, leading to supply chain disruptions, lifestyle changes, and a massive shift towards digital technologies. During the COVID-19 lockdown, many people had more free time, and over 16 million individuals learned to play guitar in the first 2 years of the pandemic. According to a study by Fender, 62% of these new guitar learners cited the pandemic as their primary reason for learning the instrument. However, pandemic policies and supply chain disruptions meant that many guitar retailers were unable to satisfy demand, and backorders accumulated. After the …

Challenges The Sporting Industry Faced During Covid-19 On Fan Attendance: The Case Of The National Basketball Association, Marlon Long

Electronic Theses, Projects, and Dissertations

This culminating experience project investigates the challenges the sporting industry faced during the COVID-19 pandemic, with a focused look at the National Basketball Association. The research questions are: (Q1) How did the NBA arena shutdowns impact fan attendance for each team during the COVID-19 pandemic? (Q2) What factors influenced NBA arena attendance before the COVID-19 shutdowns? (Q3) What factors influenced NBA arena attendance after the COVID-19 shutdown? The data collected includes all 30 NBA teams from 2019 through the 2024 seasons. The research questions were analyzed using multilinear regression analysis and comparison of attendance data over 6 seasons including the …

Ai Meets Economics: Can Deep Learning Surpass Machine Learning And Traditional Statistical Models In Inflation Time Series Forecasting?, Ezekiel N.N. Nortey, Edmund F. Agyemang, Enoch Sakyi-Yeboah, Obu-Amoah Ampomah, Louis Agyekum

School of Mathematical & Statistical Sciences Faculty Publications

This study examined the forecasting ability of deep learning (DL) and machine learning (ML) models against benchmark traditional statistical models for the monthly inflation rates in the USA. The study compared various DL and ML models like transformers, linear regression, gradient boosting (GB), extreme gradient boosting (XGBoost), and adaptive boosting (AdaBoost) with traditional baseline time-series models like autoregressive integrated moving averages (ARIMA) and exponential smoothing (ETS) with Holt-Winters seasonal method utilizing data sourced from the Federal Reserve Bank of St. Louis. The study consistently showed that all DL and ML models outperformed the traditional approaches. In particular, the Transformer (RMSE …

Effect Of Street-Pricing Deregulation In U.S. Airports On Customer Satisfaction, Thorsten Merkle, Satheesh Seenivasan, Sushanta Das

ICHRIE Research Reports

This study investigates the impact of pricing policies and food and beverage (F&B) strategies on traveler satisfaction in the dynamic airport environment, with a focus on Phoenix airport in comparison with two other (undisclosed) major U.S. airports. Using a mixed-methods approach that integrates unstructured observations and social media analytics, the research provides a comprehensive understanding of passenger behavior, satisfaction, and spending patterns in airside F&B outlets.

Key findings reveal that traveler satisfaction is driven by factors such as service quality, timeliness, perceived value, and emotional engagement, with price sensitivity playing a relatively minor role. Phoenix International Airport exemplifies a successful …

Can Kirana Stores Compete In India's E-Commerce Revolution? Rethinking Traditional Retail In The Digital Age, Anshi Jindal, Ashwarya Kapoor

Management Dynamics

E-commerce has reshaped the global retail landscape bringing both disruptions and opportunities specifically in emerging markets like India. This paper explores the evolution of e-commerce in India and its impact on traditional retail particularly unorganized Kirana stores. By analysing market trends, consumer behaviour and policy implications, the study examines how conventional retailers are adapting to digital transformation. Using Reliance Retail’s JioMart initiative as a case study, it provides insights into the integration of digital and physical retail ecosystems. While e-commerce challenges Kirana stores, it also fosters innovation, growth and the emergence of hybrid retail models.

A Machine-Learning Tool-Supported Methodology For Nonprofit Donor Analysis, Corbin Weiss

Campus Research Month

We developed a machine-learning tool-supported methodology for modeling the nonprofit donor relationship. This approach was demonstrated in the case of a US-based nonprofit. Conclusions were drawn from this example and tool-support provided for use by other nonprofits.

Sustainable Leadership In Family-Owned Businesses: The Practice Of Searching Profitability And Evaluating The Business’ Effects On The Environment, Ahmad Mansour, Hind Al-Ahmed, Ahmad Shajrawi, Khaled Alshaketheep, Muhammad Alshurideh, Arafat Deeb

An-Najah University Journal for Research - B (Humanities)

Objective: This research studies family business sustainability leadership adoption obstacles especially regarding their dual need to achieve both profitability and environmental impact targets while examining potential solutions to these problems. Methodology: A research methodology included literary analysis and field studies along with questionnaire distribution for obtaining qualitative and quantitative data. The research survey gathered information about how family businesses handle sustainability measures that focus specifically on their energy consumption as well as energy efficiency and water management plans. Results/Findings: The analysis revealed renewable energy adoption by 80% of the businesses along with energy efficiency implementation in 75% of the …

Does Ai Help Or Harm? Why And How Ai Use Influences Workplace Outcomes And Employee Well-Being, Haille Trimboli, Reka Lassu

Education Division Scholarship

Although the recent surge in excitement surrounding artificial intelligence (AI) might suggest it is a new development, AI has been applied in organizations for over forty years (Fanti et al., 2022; Markelius et al., 2024). Indeed, the term "artificial intelligence" itself emerged in the 1950s during a research project at Dartmouth College, where it was used to describe "machines able to simulate human intelligence" (Haenlein & Kaplan, 2019, p. 3). Most recently, in 2022, the landscape of AI use for laypeople greatly changed when OpenAI introduced ChatGPT, a generative AI tool, to the public; ChatGPT is an advanced AI language …

Perceptions Of Artificial Intelligence In Healthcare: A Qualitative Study Among Physicians And Nurses In Florida, Aaron Miri

MUSC Theses and Dissertations

This investigation will leverage participant focus group interviews with 32 clinicians (16 nurses / 16 physicians) to study what, if anything, is inhibiting AI adoption across the hospital. Specific physicians will be sourced across the key service lines of primary care, oncology, cardiology, behavioral health, and emergency department medicine, as these tend to be patient volume driven and thus have the maximum amount of potential for positive impact leveraging AI. Nurses in these same departments will be assessed to analyze if there is a similarity or difference between the nursing and physician AI adoption barriers.

Employee Engagement In Corporate Sustainability Initiatives: An Empirical Comparison Of Conventional And Modern Working Environment Practices, Ahmad Mansour, Hind Al-Ahmed, Ahmad Shajrawi, Khaled Alshaketheep, Muhammad Alshurideh, Arafat Deeb

An-Najah University Journal for Research - B (Humanities)

Objective: The study targets the investigation of Employee Engagement differences across Traditional and New work forms in Corporate Social Initiatives together with workplace practices that boost Sustainable Project Engagement. Methodology: The authors used a mixed-methods design approach in their research. A survey with 300 sustainable project personnel either working full-time or part-time collected quantitative data for analysis. Thirty semi-structured interviews comprised both employee and managerial personnel to collect qualitative data. The evaluation of workplace practices like flexibility and autonomy and communication & leadership on employee engagement was conducted through regression analysis. Researchers employed thematic analysis on interview data for the …

A New Measure Of Non-Parametric Correlation For Variables In The Likert Scale, Shubhabrata Das

Working Papers

We propose a new measure of nonparametric correlation that is especially suited for measuring association between variables measured in the Likert scale where data is ordinal and tied observations are extremely common. The proposed general structure of the measure is based on graded level of concordance and discordance between the pairs of metrics. The general form of the measure has all the desirable properties except the measure is not necessarily zero for independent variables. This limitation is acceptable given only ordinal nature of the metrics. Three versions of the measure are studied. The first is based on simple equi-distant weights. …

De-Dollarization And South Asia: Challenges And Opportunities For Nepal In A Multipolar Currency World, Keshav Bhattarai, Ambika P. Adhikari

Himalayan Research Papers Archive

The United States dollar’s dominance as the global reserve currency, established under the 1944 Bretton Woods system, persists despite the 1971 decoupling of the gold backing to the dollar. Its liquidity, stability, and full support by the US government confer a solid financial security and advantage to the currency, including a universal acceptance of the dollar and a relatively low borrowing cost. Because of these reasons, the US dollar has been able to dominate the global financial markets for the past eight decades. However, the rapidly emerging global political and economic power shifts are challenging the status of the US …

Robust Conic Satisficing, Arjun Ramachandra, Napat Rujeerapaiboon, Melvyn Sim

Working Papers

In practical optimization problems, we typically model uncertainty as a random variable though its true probability distribution is unobservable to the decision maker. Historical data provides some information of this distribution that we can use to approximately quantify the risk of an evaluation function that depends on both our decision and the uncertainty. This empirical optimization approach is vulnerable to the issues of overfitting, which could be overcome by several data-driven robust optimization techniques. To tackle overfitting, Long et al. (2022) propose a robust satisficing model, which is specified by a performance target and a penalty function that measures the …

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 …