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A Data Envelopment Analysis-Based Methodology for Ranking Cities and Prioritizing Urban Criteria
No full textThis paper proposes a methodology for ranking cities and prioritizing the criteria that influence these rankings within a multi-criteria decision-making (MCDM) framework. A composite Data Envelopment Analysis (DEA) model is developed to generate a fully ranked list of cities, ensuring robustness through data-driven and non-arbitrary weight assignments. Additionally, fixed-effects and random-effects models are employed to identify the criteria significantly impacting city rankings over time. The performance of these models is compared using the Hausman, Dickey-Fuller, and Breusch-Pagan tests. By analyzing large U.S. cities at five-year intervals from 2000 to 2020, this study determines city rankings and evaluates the influence of various quality-of-life criteria. The results show that cost of living, education, and income have the most substantial impacts on city rankings. These insights offer valuable guidance for policymakers aiming to improve urban socio-economic and environmental attributes. Furthermore, they provide businesses with critical information for strategic planning, market analysis, human resource management, and sustainable development
Supplier Risk Management Strategies and the Effect on Defense Contractor Operational Performance
Get PDFThe aerospace and defense industry consists of complex supply chain and operating environments that require a diligent focus on risk management. In this industry, supplier and risk management are two topics that have received increased research attention. The main findings in previous studies highlight the importance of close supplier management and its impact on supply chain performance of defense contracting firms. The goal of the present research is to better understand the relationship between supplier management and firm performance, specifically in the context of aerospace and defense sectors. The current study was completed by undergoing an extensive literature review and conducting qualitative interviews with supply chain professionals from defense contracting firms. The results of the interviews yielded emphasis on the importance of supply chain relationships and the impact of continuous measurement of supplier performance on overall defense contracting firm performance. Several differences in effective supplier management practices were identified between previously completed research and present-day practices. The current study aims to further the understanding of current supplier management practices and the relationship to operational performance in the industry
The Renewable Divide: Examining the Impact of Renewable Energy on Pollution Across Development Levels
Get PDFThis paper uses linear regression to analyze the relationship between renewable energy and environmental quality in both developed and developing countries. Developed nations often have stricter regulations and lower pollution levels, while developing nations prioritize economic growth, leading to rising pollution. Using data from the World Bank, World Health Organization, the Organization for Economic Co-operation and Development, and the International Monetary Fund, this research aims to identify how renewable energy consumption in these contrasting contexts impact environmental outcomes. The analysis explores the effectiveness of various environmental conditions, using regression analysis to assess the impact of renewable energy on air pollution. The findings on this thesis will be of great help by understanding how a nation\u27s development stage influences the effectiveness of this, making it easier to design better strategies for a sustainable future
Under Pressure: A Quantitative Approach to Measuring Clutch Performance in the NBA
Get PDFThis research investigates the existence and relevance of clutch performance in the 2023-2024 NBA regular season. Players are analyzed both individually and against league averages to determine their clutch performance levels using an original clutch score formula . This research aims to answer the questions of whether clutch performance is a real phenomenon, how individual player performance is affected in clutch time, and to determine a formula that can effectively predict the winner of the Clutch Player of the Year Award. The findings and formulas developed in this research help to shed light on the complexities of clutch performance, which has largely been considered an immeasurable trait in the past
AI\u27s Impact on the Labor Market: Shaping the Present and Forecasting the Future
Get PDFArtificial Intelligence is one of the fastest growing technologies, providing humans with a tool to assist them in their daily lives. While this is an advantage, there is also the downside that AI has the ability to remove routine and repetitive tasks. This paper takes a closer look at the impacts of Artificial Intelligence on the labor market and analyzes the implications of AI, both positive and negative. It elaborates on both the job opportunities present due to AI and the job displacement that may occur. A detailed survey was distributed to college students to understand their perceptions of AI and the labor market and to gauge their feelings about the increasing use of AI. The data that has been collected via surveys and interviews has been used as the foundation in determining the true effects that AI poses and whether it is a tool that will benefit humans who participate in the labor market. Descriptive statistics have been used to support the results gathered and to come to the appropriate conclusion that college students feel good about the increasing use of AI but are worried about jobs being taken away, although not necessarily their jobs
Evolution of Buyer Representation: Factors Reshaping Real Estate Transactions in the Boston Area
Get PDFThis study investigates the evolving factors influencing real estate buyers\u27 decisions to engage with real estate agents in the Boston area. By focusing on agent characteristics, legal considerations, market trends, and technological advancements, this research aims to understand how these elements are reshaping the role of buyer agents. As factors reshaping buyer’s decisions in real estate transactions remain fluid especially in the wake of the NAR Settlement, this study will research current opinions of both homebuyers and real estate agents. The objective is to provide insights into the shifting standards of buyer representation in the real estate industry and their broader implications for the market\u27s future
Socioeconomic Factors Affecting Gendered Happiness: A Cross-Sectional Study of OECD Countries
Get PDFThis paper explores how socioeconomic factors influence life satisfaction across OECD countries and how these effects vary by gender. Using a cross-sectional dataset, the study runs three separate regressions, total, men’s, and women’s happiness to test whether factors like health, education, safety, and support networks impact life satisfaction differently for men and women. A Random Forest model is also used to validate the robustness of selected predictors. Findings show that health and support matter universally, but men’s well-being is more closely tied to educational attainment, while women’s happiness is more sensitive to feelings of safety
Decarbonization Under Carbon Policy and Pricing Shifts: A Machine Learning-Driven Synthetic Control and Panel Data Analysis
Get PDFThis study evaluates the effectiveness of carbon pricing instruments – Carbon taxes and Emissions Trading Systems (ETS) – in reducing CO2 emissions per capita across 152 countries from 1990 to 2023 using dynamic panel regressions with fixed effects. The analysis estimates both short-run and long-run effects while controlling economic structure, energy mix, and environmental policy stringency (EPS). The results show that ETS policies yield the strongest long-term reduction in emissions at approximately 7.35%, followed by carbon taxes at 5.6%, and EPS regulatory measures at 6.35%. However, when all three instruments are modeled together, the marginal effects of pricing mechanisms weaken, suggesting possible policy interaction or diminishing returns. To reinforce causal identification, the Synthetic Control Method (SCM) is applied to the EU, revealing a growing gap between actual emissions and those of a synthetic counterfactual since the implementation of carbon pricing policies. This machine learning model is used to forecast emissions through 2029, further projecting sustained divergence under the current policies. These findings offer robust evidence that carbon pricing works best when paired with regulatory rigor and institutional capacity. This study contributes a novel empirical approach by integrating econometric modeling, SCM, and predictive analytics to assess the real-world performance of climate policy and instruments, offering insights for policymakers seeking cost-effective paths toward decarbonization
[IN] Transformation President\u27s Impact Report
Get PDFThe 2025 President\u27s Impact Report highlights Bryant University’s continued excellence in higher education, from its top-tier rankings and dynamic campus life to its hands-on learning experiences and strategic partnerships. Strong financial foundations and visionary leadership solidify its position as an innovative and forward-thinking institution. IN the Lead Bryant\u27s international rankings and thought leadership in prestigious publications reinforce its position as a leader in higher education