Business Analytics Commons^™

Understanding Film Tax Credits In Nevada And Nationally, Michael J. Brown, David F. Damore, William E. Brown Jr.

Policy Briefs and Reports

This policy primer provides an overview of Nevada’s transferable tax credit program for film and other productions and reviews articles, reports, audits, and studies of film tax credits as a tool for economic development in the United States. This review considers a significant body of work analyzing the use of film tax credits in support of economic development. Studies and state audits often show that because film tax credits do not create the number and quality of full-time jobs necessary to merit their costs and do little to stimulate other related industries, they are a poor financial choice for state …

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, …

Enhancing Sarcasm Detection With Contextual Factors For Improved Model Robustness Based On Bmlrf, Walter O. Yodah, Alice S. Mataruse, Never O. Kangara

Communications of the IIMA

Detecting sarcasm in text remains a critical yet challenging task in natural language processing (NLP). Despite significant advances through deep learning, particularly the use of transformer-based architecture like BERT, sarcasm detection models still face challenges in achieving high accuracy. A major limitation lies in their insufficient incorporation of contextual awareness, including conversational history, social inter- actions, emotional cues, and cultural factors. To address this, this paper proposes the BERT with Meta-Feature Logistic Regression Fusion (BMLRF) model, which in- tegrates sentence-level embeddings from a pre-trained transformer with meta-features capturing social, emotional, and cultural contexts. The model also leverages multi-turn dialogue history …

Time Travel Validation For Time Series Data, Thomas Tiahrt

Mountain Plains Business Conference

Model validation is necessary to evaluate the predictive effectiveness of time series forecasts. The standard validation method is to start at the earliest point in the data, train on two of the minimum meaningful number of periods or cycles of periods (i.e., two or more blocks) then test on the next block. Subsequent models are tested by extending the training period one block at a time and testing on the following block. Alternatively, the last block can be substituted for the following block. Other forward progressions can be used including forms of cross validation. In any case, the forecaster chooses …

When Generative Ai Helps Too Much: Engagement, Learning, And Student Outcomes In Business Statistics, Bruce A. Reinig

Mountain Plains Business Conference

After two decades of teaching business statistics, first in person, then online, and now in the era of generative AI, I have observed substantial shifts in how students approach learning. Many rely on ChatGPT and similar tools to produce assignment answers, sometimes at the expense of genuine understanding, which may lead to lower exam scores. Using LMS analytics, I track students’ engagement with video lectures and find this behavior more predictive of exam success than assignment completion. This presentation reports on an ongoing observational study and seeks feedback to strengthen its design and effectiveness in supporting authentic student learning.

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 …

Passenger Delight In Liminal Spaces: Uncovering The Dynamics Of Airport Airside F&B, Thorsten Merkle, Sushanta Das

ICHRIE Research Reports

The airport airside environment is a unique and highly consequential setting for consumer behavior, where passengers’ food and beverage (F&B) decisions are shaped by time pressure, emotional states, and spatial constraints. This study empirically validates two complementary frameworks - the CX Delightors Framework and the Airport Airside Consumption Model - in the U.S. context to deepen understanding of passenger behavior in this liminal space. Using survey data from 1,374 passengers across three major U.S. hub airports (DEN, PHX, SLC), we conducted principal component analyses to refine the original nine CX Delightors attributes into five robust dimensions: Hospitality & Ambiance, Value …

Does Idiosyncratic Volatility Follow A Random-Walk? Evidence From U.S. Stocks, Zihan Cao, Ossama Elhadary

Publications and Research

In asset pricing literature, idiosyncratic volatility (IVOL) measures the firm-specific risk that is not explained by broader market movements. In this study, I investigate whether the idiosyncratic volatility (IVOL) of individual stocks follows a random-walk. Using monthly residuals from the Fama-French three-factor model (Fama & French, 1993), I estimate IVOL for more than 11,000 U.S. stocks, and apply the Augmented Dickey-Fuller test (Said & Dickey, 1984) to determine whether IVOL behaves like a random-walk. While most stocks display random-walk behavior, the proportion varies across industries, with some sectors showing deviations from random-walk behavior. Stocks with different levels of average return …

An Analysis Of Consumer Behavior In The Brazilian E-Commerce Market: An Investigation Of Customer Loyalty, Seasonality, And Regional Preferences, Hai Doan

Student Publications

This paper investigates key drivers of consumer behavior within Brazil's emerging e-commerce market by analyzing the Olist Public Dataset. As technology increasingly allows for data-driven marketing strategies, understanding the nuanced behaviors of diverse consumer bases, especially in an emerging market like Brazil, is critical for firm success. This study tests three hypotheses regarding the relationship between positive customer reviews and e-loyalty, the fluctuation of seasonal sales during holiday periods, and the influence of geographic urbanization on product preferences. Utilizing regression analyses on 100,000 orders from 2016 to 2018, the results showed no significant relationship between positive review scores and repeat …

Integrating Data Analytics Into Financial Risk Management For Regulatory Decision Support And Financial System Resilience, Md Shehab Hossain, Saddam Nasir Chowdhury, Rakesh Kumar Reddy Aduri

Student Publications

This paper explores how data analytics can be incorporated in financial risk management and thus serve as a basis for effective financial risk management decision support and financial system resilience. Traditional risk assessment methods are less effective in the face of growing volumes, velocity and complexity of data, especially in pinpointing new systemic risks, interconnections, market shocks, and institutional stress. The study examines the use of machine learning, real-time monitoring, stress testing and early-warning systems in the detection, assessment, and mitigation of credit, market, liquidity, operational, and systemic risks through descriptive, predictive and prescriptive analytics. It takes a conceptual and …

Federal Funding In The Mountain West, 2021-2024, Isabelle G. Graham, Olivia K. Cheche, Caitlin J. Saladino, William E. Brown Jr.

Elections & Governance

This fact sheet presents data on the number of federal funding awards granted to the five Mountain West states of Arizona, Colorado, Nevada, New Mexico, and Utah between 2021 and 2024. These awards include investments authorized under major federal legislation such as the Inflation Reduction Act (IRA), CHIPS and Science Act, and Bipartisan Infrastructure Law (BIL), among other programs tracked by Invest.gov. The One Big Beautiful Bill Act (OBBBA) will see funding for these programs sunsetted (terminated as the above legislation expires).

Analisis Dampak Kebijakan Insentif Fiskal Terhadap Tingkat Komponen Dalam Negeri (Tkdn) Industri Manufaktur Di Indonesia, Muhammad Muhammad, Riyanto Riyanto

Jurnal Kebijakan Ekonomi

Over the last decade, the manufacturing sector's contribution to Indonesia's economy has declined. In 2010, it was 29.10% of GDP, but by 2022, it had dropped to 19.14%. Employment in the sector also fell, from 14.91% of the workforce in 2010 to 13.80% in 2022. To reverse this trend, the government introduced a policy to boost the Domestic Component Level (DCL) in manufacturing. By offering fiscal incentives to industries meeting certain DCL targets, the government aims to drive economic growth and job creation. A study using BPS data from 2008-2019 shows that this policy raised DCL by 23.5%.

Applying Detective Analytics For Mitigating Financial Crime In An Organisation, Nontobeko Mlambo, Tiko Iyamu

African Conference on Information Systems and Technology

Despite the growing popularity of detective analytics, it is consistently challenging to understand the factors that influence the adoption. This is increasingly discouraging organisations, even though the tool is important for tracing, tracking, and mitigating financial crime. This study applied concepts of ‘follow the actors’ and shifting negotiation of actor-network theory (ANT) to gain a better understanding of the factors that influence the adoption of detective analytics in a qualitative case study using a South African-based financial organisation. From the analysis, integration of analytics tools, integration of detective analytics with other systems and processes, development of a template for each …

Swift/Kelce Star Power Effect? Engagement Created A 96% Increase In Nfl Discussion Online With 82% Of Social Media Posts Expressing “Joy” About The Couple, Yi Luo, Jin-A Choi, Bond Benton

College of Communication and Media Scholarship and Creative Works

On August 27, 2025, Grammy winning singer Taylor Swift and football champion Travis Kelce announced their engagement. Celebrity couples inspire popular reactions with commercial implications. A research study from the Joetta Di Bella and Fred C. Sautter III Center for Strategic Communication in the College of Communication and Media at Montclair State University analyzed online reaction in the period immediately after the power couple’s engagement was announced. Results suggest overwhelming interest, positivity, and potential benefits to major brands, such as the National Football League. Findings include a 96% increase in brand references for the NFL and Kansas Chiefs on social …

Birth Outcomes In The Hispanic Population In The United States: Trends, Variation, And Determinants (2011–2021), Yanchao Yang

Business Analytics Faculty Publications

Background: Cesarean section (C-section) is the most common surgical procedure in the United States, yet its use varies widely across regions and institutions. Although clinical risk factors are central to delivery decisions, geographic context, health system capacity, and local practice patterns may also influence C-section use. Understanding both the determinants and predictability of C-section delivery is important for improving obstetric quality and equity.

Objective: This study aims to document geographic variation in C-section use across the United States, identify maternal and county-level factors associated with C-section delivery, and evaluate the predictive performance of machine learning models across clinically defined risk …

Exploring The Mediating Role Of Individual Performance In The Relationship Between Work-Life Balance And Attrition, Grace O. Leasure

Research Psychology Theses

Extensive research has established a relationship between work-life balance and employee attrition. However, limited attention has been given to the potential mediating role of individual performance within this dynamic. The present study aims to address this gap by examining whether individual performance mediates the relationship between work-life balance and attrition. It is hypothesized that higher work-life balance will be associated with lower attrition rates, partially explained by improved individual performance. Data will be collected via employee surveys and analyzed using mediation analysis. Anticipated results may provide organizations with a quantifiable, performance-based justification for investing in work-life balance initiatives.

An Empirical Analysis Of The Pitch Clock On Major League Baseball, David Langton Jr

All Theses

The pitch clock was instituted in baseball to speed up the pace of play and make the game more watchable. While it has achieved this effect, it may have affected other areas of the sport, like the balance between offense and defense and pitching injuries. This analysis explores the results of a difference-in-difference regression comparing MLB and AAA 2015-2024 seasons. Overall, it finds that pitching statistics were not significantly affected, including elbow injuries. This includes games, ERA, and times a batter is hit by a pitch. In fact, the number of home runs and walks both went down significantly by …

Exploring The Effects Of Remote Work On Leadership Pipelines: With A Focus On Professional Women And Minorities, Mark S. Andrekovich

All Dissertations

I analyzed data from five U.S.-based companies to understand how remote work models affect leadership advancement. Using Role Congruity, Status Characteristics, and Intersectionality theories, I analyzed five hypotheses about the impact of remote work on leadership pipelines. Two of the five hypotheses were supported, revealing bias patterns rather than issues related to remote work. For instance, white employees had greater access to remote work opportunities than non-white employees, who had fewer promotions despite similar performance scores. Contrary to expectations, I found that remote work does not inherently affect promotional advancements. Via a post hoc analysis, I found that hybrid professionals …

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 …

Unified Hybrid Censoring Samples From Power Pratibha Distribution And Its Applications, Mahmoud Mansour, Hebatalla H. Mohammad Dr, Khalaf S. Sultan Prof.

Basic Science Engineering

This paper suggests an extensive inferential method for the Power Pratibha Distribution (PPD) under Unified Hybrid Censoring Schemes (UHCSs), since there is a growing interest in flexible models in both reliability and service operations. This work studies the PPD model using standard Maximum Likelihood Estimation methods and modern Bayesian approaches too. Using a complex architecture, UHCS simulates tests more closely to what is done in practice than by using more basic censoring schemes. Using analysis, the probability and statistical ranges are carefully calculated for the parameters. Tests demonstrate that Bayesian estimation gives better results than many other methods for estimation, …