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Articles 1 - 30 of 122
Full-Text Articles in Business Analytics
Determining The De-Dieselisation Priorities Of Distributed Diesel Generators In An Electricity Company, Kresna Nurdianto, Ratih Dyah Kusumastuti
Determining The De-Dieselisation Priorities Of Distributed Diesel Generators In An Electricity Company, Kresna Nurdianto, Ratih Dyah Kusumastuti
Journal of Environmental Science and Sustainable Development
The Indonesian Electricity Company (PLN) is one of the main players in the energy transition in Indonesia, and the company plans to achieve net zero emissions by 2060. One way to do this is by implementing the de-dieselisation program, i.e. reducing the use of diesel power plants (PLTD) with new energy and renewable power plants. The Indonesian electricity supply business plan (RUPTL) 2021-2030 targets the reduction of electricity supply from PLTD by 87% by 2030. The program requires a method to determine the order of priorities of PLTDs to be de-dieselised. This research uses multicriteria decision making, namely, analytical hierarchy …
Racial Disparities In Cesarean Section Rates Between Non-Hispanic Black And Non-Hispanic White Populations In The United States, Yanchao Yang, Margaret Mullen, Guangda Zhang
Racial Disparities In Cesarean Section Rates Between Non-Hispanic Black And Non-Hispanic White Populations In The United States, Yanchao Yang, Margaret Mullen, Guangda Zhang
Business Analytics Faculty Publications
This study uses national natality data from the National Vital Statistics System, provided by the National Center for Health Statistics, covering the years 2011 to 2018 (N = 23,810,031) to investigate racial disparities in cesarean section (C-section) rates between non-Hispanic Black and non-Hispanic White mothers in the United States. This analysis offers a comprehensive perspective on the factors contributing to C-section disparities by considering mothers' demographic characteristics, health conditions, and infant health status. Using multivariable logistic regression, the findings reveal consistently higher C-section rates for non-Hispanic Black mothers compared to non-Hispanic White mothers, with the gap widening over time. …
Trade Openness, Human Capital, And Economic Resilience In Saarc Countries: A Post-Covid-19 Analysis, Sumra Khalid, Khalid Mahmood Mughal, Bushra F. Malik
Trade Openness, Human Capital, And Economic Resilience In Saarc Countries: A Post-Covid-19 Analysis, Sumra Khalid, Khalid Mahmood Mughal, Bushra F. Malik
Accounting, Business Analytics, Economics, and Finance Department Faculty Articles
The present study analyzes the interrelationship between trade openness, labor force participation, human capital, and economic growth in the SAARC countries, with particular attention to the implications of the COVID-19 pandemic on these linkages. In this paper, an attempt has been made to gauge both the short-run and long-run impacts that have resulted in the facilitation of economic growth through trade openness by increased market access, technology transfers, and competitive efficiency. However, the pandemic distorted trade flows and lost labor to more labor-intensive industries, generally hitting the low-income and marginal groups harder while underlining vulnerabilities in the trade-dependent economies. These …
Potential Impact Of Artificial Intelligence On Small And Medium Enterprises Innovation In The Eu: A Perspective From Poland, Malgorzata Wilczynska, Alina Walenia, Artur Dabek, Daniel Salabura, Halina Kot
Potential Impact Of Artificial Intelligence On Small And Medium Enterprises Innovation In The Eu: A Perspective From Poland, Malgorzata Wilczynska, Alina Walenia, Artur Dabek, Daniel Salabura, Halina Kot
Markets, Globalization & Development Review
The development of small and medium-sized enterprises is a complex process that requires the use of all approaches to achieve success. In this regard, finding opportunities to use artificial intelligence in such companies is of great importance. The study aims to assess how this technology affects the innovation and financial performance of small and medium-sized enterprises. To draw the main conclusions, the implementation of artificial intelligence at Polish enterprises, including in the context of their financial performance, namely the level of return on assets and the level of debt, was analysed. The study showed that the introduction of artificial intelligence …
Nemo Equipment: Data Integration And Analytics Transformation, Ashlyn M. Smith
Nemo Equipment: Data Integration And Analytics Transformation, Ashlyn M. Smith
Business Analytics Student Projects and Publications
No abstract provided.
Transforming Accounting With Artificial Intelligence, Aidan M. Morneault
Transforming Accounting With Artificial Intelligence, Aidan M. Morneault
Business Analytics Student Projects and Publications
The accounting field is evolving quickly with the integration of Artificial Intelligence (AI), and BNN is taking on this challenge. This report explores how BNN incorporates AI tools like Microsoft’s CoPilot and Caseware into its operations to streamline audits, enhance efficiency, and ensure compliance. This report will also cover how the industry handles this new technology, but still have a focus on BNN. While AI has brought significant benefits such as reducing costs, speeding up data processing, and moving towards real-time audits, it also presents challenges. These challenges include trust in AI outputs, high implementation costs, and workforce training. To …
Navigating Workforce Utilization Metric In The Indian It Industry: A Multifaceted Study, Shipra Jha
Navigating Workforce Utilization Metric In The Indian It Industry: A Multifaceted Study, Shipra Jha
Management Dynamics
The measurement of workforce utilization is a critical concern for organizations, especially within the dynamic landscape of the IT industry. This research explores the multifaceted nature of utilization metrics by devising Utilization Insight Elicitation Framework (UIEF), focusing on three major themes: defining utilization and understanding the significance, assessing its impact on employee well-being, and contemplating its future relevance. Examining utilization from cost and revenue perspectives reveals how organizations optimize costs while ensuring project profitability. The study scrutinizes the balance between cost-focused and headcount-centered approaches, considering employees' roles and project demands. Additionally, it discusses factors for inclusion/exclusion in utilization calculations and …
Comparative Analysis Of Outward Foreign Direct Investment: A Case Study Of China And The United States In The United Kingdom, Jing Yang
Applied Economics Theses
This study aims to conduct a comparative analysis of outward foreign direct investment (OFDI) from China and the United States into the United Kingdom, with the intention of uncovering the distinct motivations behind their investment behaviors under different political-economic systems. Given the unique political and cultural backgrounds of China and the US, their approaches to OFDI exhibit varied characteristics in the international market. The United Kingdom, a main investment destination for both China and the US, is selected to reflect the distinctive features of Chinese and US’s OFDI.
The research focuses on how the determinants such as market growth, natural …
Identification Of Distressed Real Estate Properties Using Natural Language Processing/Machine Learning, Pavithra Sirigiri
Identification Of Distressed Real Estate Properties Using Natural Language Processing/Machine Learning, Pavithra Sirigiri
Electronic Theses, Projects, and Dissertations
The Real Estate industry is a great asset class that involves constructing, buying, and selling property. Although technology has made significant progress in buying and selling real estate properties online, via Zillow and Redfin, the ways to find distressed real estate properties as an investment opportunity seem to be lacking. This culminating experience project explored how to use machine learning to classify a property as distressed or non-distressed. The research questions are: Q1. How can Natural Language Processing methods like Latent Dirichlet Allocation (LDA) be leveraged to identify distressed and non-distressed real estate properties? (Tijare & Rani, 2020) and Q2. …
The Practical Adoption And Application Of Blockchain Technology Within The Beverage Industry, Alexander Adams Jr
The Practical Adoption And Application Of Blockchain Technology Within The Beverage Industry, Alexander Adams Jr
Electronic Theses, Projects, and Dissertations
Abstract
The beverage industry is facing heightened scrutiny as the demand for transparency and accountability reaches new heights. In the age of information technology, companies must prioritize enhanced traceability to ensure product safety, comply with government regulations, maintain customer trust, and protect brand integrity. This thesis explores the potential of blockchain technology as a solution to these challenges, focusing on its ability to decentralize data, improve traceability, and expedite response times during safety recalls. The research provides an overview of the evolution of food safety regulations, beginning with the first establishment by Upland Sinclair, and examines current traceability practices and …
Using Ai Tools To Unmask Sarcasm, Sidra Tehniyath Lnu
Using Ai Tools To Unmask Sarcasm, Sidra Tehniyath Lnu
Electronic Theses, Projects, and Dissertations
Sarcasm can be identified in newspaper headlines in digital communication, as it is contextual and has low inter- and intra-observer reliability. This research aims to improve sarcastic comment identification using a natural language processing approach, especially the BI-LSTM. The primary concern is to use fine-tuning methods to enhance the ways that strengthen the sarcasm identification rate, which regards the factors that complicate an automatic identification process. The study explores the impact of techniques such as early stopping, optimal loss function selection, and hyperparameter tuning to enhance the model's performance. The research questions are: Q1) How can fine-tuning techniques for BI-LSTM …
Juegos De Rol En El Desarrollo De Projectpipe: Una Inmersión En El Uso De Metodologías De Diseño, Julieth A. Gómez Hernández, Cristian C. Orozco Ospina, Nicolas Restrepo Henao
Juegos De Rol En El Desarrollo De Projectpipe: Una Inmersión En El Uso De Metodologías De Diseño, Julieth A. Gómez Hernández, Cristian C. Orozco Ospina, Nicolas Restrepo Henao
Journal of Roleplaying Studies and STEAM
En el entorno digital actual, la evolución del concepto de juegos de rol ha llevado al desarrollo de aplicaciones web interactivas y educativas. En sintonía con este planteamiento, se presenta la siguiente propuesta, que adopta una metodología integrada para aprovechar la versatilidad del método de Bruno Munari y el Diseño Centrado en el Usuario (DCU). La metodología de Munari descompone la gestión macro del proyecto en pasos manejables; mientras que el DCU se enfoca en la creación de una interfaz intuitiva y funcional mediante prototipos iterativos y pruebas continuas de usabilidad. Como complemento a estas estrategias se integra la metodología …
Navigating The Landscape: Perceptions, Motivations, And The Journey Of Data Professionals In Implementing Data Processes And Procedures, Willie Rivers
Navigating The Landscape: Perceptions, Motivations, And The Journey Of Data Professionals In Implementing Data Processes And Procedures, Willie Rivers
Dissertations
This explanatory study investigates the motivations behind data professionals' willingness or resistance to implementing data policies and procedures, utilizing the Theory of Planned Behavior and Psychological Ownership as frameworks. Through interviews with 21 data professionals, the research explains how factors such as perceived control, ownership, and attitudes towards data processes influence their motivation. The study tests key propositions, including the impact of perceived time burdens, bureaucratic procedures, and organizational expectations on data governance engagement. The findings underscore the critical role of control and access to information in motivating the adoption of data policies, providing insights for organizations aiming to enhance …
Midwest Entrepreneurship Case Competition (Mecc) Case Prompt - Anonymized, Zoeanna A. Mayhook, Liz Grauel, Annette H. Bochenek, Ilana Stonebraker, Terence O'Neill
Midwest Entrepreneurship Case Competition (Mecc) Case Prompt - Anonymized, Zoeanna A. Mayhook, Liz Grauel, Annette H. Bochenek, Ilana Stonebraker, Terence O'Neill
Libraries Faculty and Staff Supplemental Materials
This case is an anonymized version of a prompt used in the 2024 Midwest Entrepreneurship Case Competition (MECC), a undergraduate regional event organized in collaboration with multiple Midwest libraries. The prompt challenges students to conduct market validation research using SimplyAnalytics and perform keyword research and analysis.
Knowledge Economy And Its Impact On Economic Growth And Per-Capita Income: Evidence From Arab Countries, Ahmad M. Khreisat, Nahil Saqfalhait, Khawlah Spetan, Raad M. Al-Tal
Knowledge Economy And Its Impact On Economic Growth And Per-Capita Income: Evidence From Arab Countries, Ahmad M. Khreisat, Nahil Saqfalhait, Khawlah Spetan, Raad M. Al-Tal
An-Najah University Journal for Research - B (Humanities)
Purpose: This study aims to analyze the development of the Global Knowledge Index (GKI) (published by the United Nations Development Program (UNDP) and Mohammed Bin Rashid Al Maktoum Foundation (MBRF)) for Arab countries according to their income levels and to assess the impact of the level of knowledge on economic growth and per capita GDP in Arab countries during the period (2017-2021). Methodology: The study covers a sample of the following Arab countries: (UAE, Qatar, Bahrain, Saudi Arabia, Kuwait, Oman, Jordan, Algeria, Lebanon, Tunisia, Egypt, and Morocco). Two econometric models were conducted using panel data based on the (GKI) reports: …
On-The-Go Dining In America: Comparing Convenience, Service Quality, And Satisfaction In Qsr Versus Gas Station Food, Shiva Jahani, Mohammed Lefrid, Lorie A. Tuma
On-The-Go Dining In America: Comparing Convenience, Service Quality, And Satisfaction In Qsr Versus Gas Station Food, Shiva Jahani, Mohammed Lefrid, Lorie A. Tuma
Journal of Tourism Insights
Purpose
The objective of this multi-group study is to examine the influence of service quality and convenience on customer satisfaction in quick service restaurants (QSRs) versus gas stations.
Design/methodology/approach
Data were collected online from 552 participants in the USA and analyzed using partial least square structure equation modeling (SmartPLS).
Findings
Service quality and convenience are strong predictors of customer satisfaction in both QSR restaurants and gas station food outlets. In addition, this study concluded significant differences between QSRs and gas stations in terms of these relations.
Research limitations/implications
This study makes a significant contribution to the foodservice and consumer behavior …
Future Trends In Halal Food: How Innovative Islamic Business Models Are Redefining The Indonesian Market, Jimmi Qizwini, Diki Gita Purnama
Future Trends In Halal Food: How Innovative Islamic Business Models Are Redefining The Indonesian Market, Jimmi Qizwini, Diki Gita Purnama
Journal of Middle East and Islamic Studies
Indonesia, a leading actor in the global halal food market, is undergoing significant transformations driven by the adoption of innovative Islamic business models. These models, which seamlessly integrate Islamic ethical principles with contemporary market forces, are fundamentally reshaping the structural and operational landscape of Indonesia’s halal food industry. This study aims to systematically investigate emerging trends, evaluate the impact of these pioneering business models, and provide a comprehensive analysis of their influence on consumer preferences and industry practices. Through a descriptive literature review, the research synthesizes insights from academic discourse and case studies to offer a thorough understanding of these …
Marketing Analytics In 2024 Conferences: Ai And Data-Driven Decision-Making, Maria Petrescu, Anjala S. Krishen
Marketing Analytics In 2024 Conferences: Ai And Data-Driven Decision-Making, Maria Petrescu, Anjala S. Krishen
Publications
The field of marketing (and business) analytics has been developing significantly during the last decade, especially with regard to new (generative) AI technologies. A reflection of this rapid evolution can be seen by the strong presence of analytics-related topics in prominent marketing conferences of 2024. Some of the key themes appearing in the 2024 marketing conferences in relation to marketing analytics include AI integration, consumer engagement, data-driven decision-making, and ethical aspects, as reflected in Fig. 1 and discussed below.
Impact Of University Presidents On Enrollment, Thomas Tiahrt, Raleigh M. Tiahrt, Michael Allgrunn
Impact Of University Presidents On Enrollment, Thomas Tiahrt, Raleigh M. Tiahrt, Michael Allgrunn
Mountain Plains Business Conference
Leadership is reflected in organizations and is often considered to be the foremost predictor of how organizations perform, adapt, and progress during the leader’s tenure. In higher education, the president of a university has a pivotal role in determining the outcomes the university achieves. Our research examines how the highest degree of university presidents, as well as their prior positions, determines the success of a university as defined by first-time full-time enrollments.
Zero Textbook Cost Syllabus For Bus 9430 (Business Analytics Projects Management), David Messineo
Zero Textbook Cost Syllabus For Bus 9430 (Business Analytics Projects Management), David Messineo
Open Educational Resources
This course delves deep into the pivotal roles, multifaceted opportunities, and inherent challenges faced by organizations aiming to harness business analytics as a competitive edge.
- Business Analytics Frameworks: We'll tap into various frameworks such as Lean, Six Sigma, Benchmarking, Kaizen, Value Chain, Balanced Scorecard, and Strategy Maps. While prior knowledge of these is not mandatory, a little research will prove invaluable when tackling class assignments.
- Project Lifecycle Management: The course draws upon CRISP-DM, Design Thinking, Story-Telling, Systems Thinking, TQM, and Agile/Kanban Methods to instill and enhance a culture of data-driven, evidence-based decision-making in an enterprise.
Prior exposure to these methodologies …
Midwest Entrepreneurship Case Competition Website (2023-2024), Zoeanna A. Mayhook, Terence O'Neill, Annette H. Bochenek, Ilana Stonebraker
Midwest Entrepreneurship Case Competition Website (2023-2024), Zoeanna A. Mayhook, Terence O'Neill, Annette H. Bochenek, Ilana Stonebraker
Libraries Faculty and Staff Supplemental Materials
Archived Midwest Entrepreneurship Case Competition Website (November 2023 - October 2024)
Research On The Construction Of Multi-Layer Vocation-Skill Network For Industrial Talent Demand Identification, Zhanlei Yao, Jinxuan Li, Xin Xu
Research On The Construction Of Multi-Layer Vocation-Skill Network For Industrial Talent Demand Identification, Zhanlei Yao, Jinxuan Li, Xin Xu
Journal of Scientific Information Research
[Purpose/ signficance]As an important tool for labor market observation,the relative robustness and other characteristics inherent in the traditional occupational classification system make it difficult to reflect changes in industrial talent demand in a timely manner. To solve this problem,this paper focuses on how to use digital means to map the relationship between occupations and skill requirements,and how to construct a multi-layer vocation-skill network and how to realize it. [Method/process]Firstly,design a set of cross-job descriptors,a common language for describing different jobs in Chinese context,in order to establish a vocation description framework for recruitment data development and utilization. Secondly,the Key technology of …
Shelf Space Strategy In Alcoholic Beverage Retail: Analyzing The Impact Of Shelf Facings On Sales Performance And Consumer Behavior, Jesse Core
Dissertations
The alcoholic beverage industry faces intense competition and regulatory constraints, making strategic shelf space management critical. This study investigates the impact of shelf facings on sales performance in the alcoholic beverage sector, focusing on how brand size moderates this relationship.
The study collected data from a regional supermarket chain in Arkansas using a quantitative pretest-posttest control group design. It found that increasing shelf facings for smaller brands significantly enhances overall modular sales, with small brand sales persisting even after reverting to their original facings. Moreover, the analysis reveals that brand size significantly moderates the impact of shelf facings on brand …
The Impact Of Rising Interest Rates, Bank Deposit Betas, And Credit Risk, Abby Craig, Jarrett Grose, Justin Tersoglio, Noah Vanhoy, Brooke Vivenzio
The Impact Of Rising Interest Rates, Bank Deposit Betas, And Credit Risk, Abby Craig, Jarrett Grose, Justin Tersoglio, Noah Vanhoy, Brooke Vivenzio
James Madison Undergraduate Research Journal (JMURJ)
Inflation of the U.S. dollar drove the Federal Reserve Board to enact four interest rate hikes of 0.75% and additional smaller hikes between March 2022 and April 2023. This paper examines how interest rate hikes affect bank deposit betas and credit risk for community banks, hot money banks, and alternative lending institutions based on data from March 2022 to April 2023. After analyzing data from the Federal Reserve Economic Database, this research found that bank deposit betas increase as interest rates rise, that community banks’ betas increase at a slower rate than hot money banks’ betas, and that the level …
Pooling And Winsorizing Machine Learning Forecasts To Predict Stock Returns With High-Dimensional Data, Erik Mekelburg, Jack Strauss
Pooling And Winsorizing Machine Learning Forecasts To Predict Stock Returns With High-Dimensional Data, Erik Mekelburg, Jack Strauss
Finance: Faculty Scholarship
We evaluate US market return predictability using a novel data set of several hundred ag- gregated firm-level characteristics. We apply LASSO, Elastic Net, Random Forest, Neural Net, Extreme Gradient Boosting, and Light Gradient Boosting Machine methods and find these models experience large prediction errors that lead to forecast failures. However, winsorizing and pooling machine learning model forecasts provides consistent out-of-sample predictability. To assess robustness, we apply machine learning methods to high-dimensional data for Canada, China, Germany and the UK as well as the Goyal-Welch data. All machine learning models we consider, except for the ensemble pooled methods, fail to significantly …
The Piranhas: Endgame Of Banking In Indonesia, F. Mario Andaru, Bambang Hadinugroho
The Piranhas: Endgame Of Banking In Indonesia, F. Mario Andaru, Bambang Hadinugroho
Journal of Global Business Insights
Neobank is a form of financial technology innovation that offers banking services without a branch office. This is a form of disruption in the banking industry. Therefore, this paper aims to look at the phenomenon regarding the shift in the banking industry due to the presence of neobanks and, at the same time, question whether this is the beginning of the extinction of conventional banking. Based on an analysis of the literature on fintech and digital banking from research, case studies, and news media in both English and Indonesian, this study discusses research related to neobank trends disrupting the conventional …
Advancing Sustainable Investing: A Deep Learning Model For Multi-Source Stock Prediction, Hongxuan Yu, Tingting Zhang, Murat Kizildag
Advancing Sustainable Investing: A Deep Learning Model For Multi-Source Stock Prediction, Hongxuan Yu, Tingting Zhang, Murat Kizildag
Journal of Global Business Insights
The burgeoning role of the stock market within the national economy elevates the importance of precise stock price analysis and prediction, a field that has garnered substantial interest in academic research. Stock price fluctuations, influenced by many factors, including company fundamentals, market sentiment, capital flows, industry news, and macroeconomic policies, present a highly dynamic and complex challenge for predictive modeling. Addressing this challenge, our study introduces an innovative method that capitalizes on the synthesis of news text and stock price data for forecasting market movements. We employ GloVe embeddings to capture semantic nuances from news text and integrate them with …
Adapting Agile Principles For Digital Media Startups, Chukwudi Ukonne
Adapting Agile Principles For Digital Media Startups, Chukwudi Ukonne
Harrisburg University Dissertations and Theses
This paper explores the adaptation of Agile Project Management principles to address the unique challenges faced by media startups and digital news ventures. Operating in fast-paced and dynamic environments, these entities require flexible project management approaches to respond to evolving landscapes and rapidly changing audience demands. Drawing on existing literature and empirical studies, the paper critically analyzes the application of Agile methodologies in media contexts, examining factors influencing successful Agile transformation and the implications for project outcomes. Additionally, the paper provides a review of theories such as Agile Manifesto and Scrum, providing insights into their origins, main arguments, and applications …
Unveiling Key Features: A Comparative Study Of Machine Learning Models For Alzheimer's Detection, Cailean Bushnell
Unveiling Key Features: A Comparative Study Of Machine Learning Models For Alzheimer's Detection, Cailean Bushnell
All Graduate Reports and Creative Projects, Fall 2023 to Present
This thesis rigorously evaluates the application of an array of natural language processing (NLP) techniques and machine learning models to identify linguistic signatures indicative of dementia, as sourced from the DementiaBank Pitt corpus. Utilizing a binary classification paradigm, this study meticulously integrates sophisticated embedding methods—including Doc2Vec, Word2Vec, GloVe, and BERT—with traditional machine learning algorithms such as Random Forest, Multinomial Naïve Bayes, ADA boost, KNN classifier, and Logistic Regression, alongside deep learning architectures like LSTM, Bi-LSTM, and CNN-LSTM. The efficacy of these methodologies is evaluated based on their capacity to differentiate between transcribed speech impacted by dementia and that from control …
How Variations In Health Status Influence Retirement Decisions?, Elham Parvizi Cherri
How Variations In Health Status Influence Retirement Decisions?, Elham Parvizi Cherri
All Theses
Retirement date decisions are crucial for seniors. It is influenced by financial situation, health status, family conditions, planning for the rest of the life, etc. While some literature emphasizes economic well-being as a critical determinant, recent research suggests that health status is a more significant factor in retirement decisions. This thesis explores how variations in health status influence retirement decisions using panel data from the Health and Retirement Study (HRS). Building on the extensive use of HRS data in previous studies, this research expands their approaches and methodologies. Both subjective and objective health variables are utilized to address the potential …