Article Gateway
Not a member yet
7100 research outputs found
Sort by
A Tale of Two Managers: Dunning-Kruger and the Impostor
No full textWe have seen them in action. We may have even worked with one, or both contrasting types of managers. The Impostor Manager (IM) is modest and not self-aware of their abilities. Rather, they attribute their success to luck or chance. The Dunning-Kruger (DKM) manager is the opposite. She or he has an over-abundance of confidence in their skills and ability and often assumes the department's success can be attributed to their superior leadership skills. In this paper, the researchers discuss issues surrounding both types of managers and offer recommendations to develop these managers into high-performing leadership team members
Examining the Intersection of Gender and Race in Employee Engagement
No full textThis study examines differences in employee engagement based on the intersection of gender and race. Survey data from over 5,000 employees are analyzed to compare engagement levels and predictors of engagement for White males, White females, males of color, and females of color. Results indicate that males report significantly higher average engagement than females overall, and this gender gap is more pronounced for employees of color. Regression analyses find common engagement predictors across groups, such as feeling one knows what is expected on the job. However, the strength and significance of various engagement drivers differ based on gender and race. For example, having a best friend at work strongly predicts engagement for White females but not for females of color. Adjusted R-squared values from the regression models also show variation in how well the models predict engagement across gender and racial groups. These findings suggest employee engagement is influenced by one's positioning at the intersection of socially constructed categories like gender and race. Researchers and practitioners should approach engagement with an intersectional lens that considers how race and gender combine to shape individuals' experiences in the workplace
Intellectual Capital and Stock Performance of US High-Tech Acquiring Firms
No full textThis paper examines the impact of intellectual capital on the stock performance of US high-tech acquiring firms between 2010 and 2016. Intellectual capital is characterized as the knowledge that assists companies in creating value and enhancing profitability. The study finds that impacts of intellectual capital on stock performance around the announcement date and in the short run depend on the intellectual capital measure and the industry type. When the overall sample is considered, the VAIC measure indicates that intellectual capital is positively related to stock performance for the 3-year window around the announcement date, while the Tobin’s Q measure suggests a negative impact
Integrating Cognitive, Emotional, and Informational Predictors of Pro-Environmental Behavior
No full textThis study aims to identify the factors that determine pro-environmental behavior. The study's sample consisted of 392 volunteer participants. A structural equation model was employed to examine the predictors of pro-environmental behavior. The determinants that we investigated are internet use, environmental knowledge, perceived environmental pollution threats, and environmental sensitivity. The fundamental findings of the current study indicate that environmental sensitivity is the most significant predictor of pro-environmental behavior. Furthermore, the study found that environmental sensitivity plays a significant mediator role not only between perceived environmental pollution threats and pro-environmental behavior but also between environmental knowledge and, pro-environmental behavior
A New Algorithm for the Weighted Tardiness Problem
No full textWe study the single machine weighted tardiness problem. In view of its NP-hard nature, we explore mathematical properties and dominance conditions to develop an algorithm that is powerful yet extremely simple to implement. Our proposed algorithm is then compared with some well-known heuristics that are currently available in machine scheduling literature. These computational results indicate that our proposed algorithm not only does well but also enables manual solutions for small problem sets due to its simplicity. We believe that future studies with an emphasis on exploring more properties and dominance conditions will result in optimal solutions even for large problem sets
Flows Without Faces: Hidden Logistics in Non-Places
No full textBehind the apparent neutrality of non-places lies a highly sophisticated logistical architecture that remains largely overlooked in academic research. Drawing on sociology, anthropology, and logistics management, the article demonstrates how material, human, and informational flows are tightly orchestrated to generate both fluidity and anonymity in international airports, mega-malls, and other transit environments. Two empirical illustrations highlight the underlying engineering that sustains performance while shaping user experience. A four-dimensional model—flow centrality, logistical coordination, adaptability, and experience construction—provides scholars and practitioners with a transferable framework for analyzing diverse non-places. The interdisciplinary perspective advanced here reframes non-places not as passive byproducts of hypermodernity but as intricate circulation systems in which the control of flows emerges as a critical driver of performance
Economic Policy Uncertainty and Banking Stability in the WAEMU Area: Are Bank Size, Capital and Liquidity Relevant?
No full textThe objective of this study is to examine the effect of economic policy uncertainty on bank stability, considering the roles of bank size, capital, and liquidity in the WAEMU zone. To achieve this, we utilized data from WAEMU countries, excluding Guinea-Bissau, due to a lack of data for the period 1997-2020. Using the DOLS (Dynamic Ordinary Least Square) method, the results revealed that economic policy uncertainty appears to strengthen banking stability, reflecting the cautious behavior of banks in the face of uncertainty. Furthermore, bank size, capital, and liquidity mitigate the positive effect of economic policy uncertainty on banking stability. We determined thresholds of 5.21 for size, 10.96 for the capital adequacy ratio and then 13.87 for the liquidity ratio. In terms of economic policy implications, this article emphasizes the importance of balanced regulation and careful supervision in maintaining banking sector stability during uncertain economic environments
UK Property Market Segmentation: Evidence From a Nonlinear Model
No full textWe examine the hypothesis of nonlinear rental price convergence using the relative house price index across nine major regions of the United Kingdom: East, East Midlands, London, North East, North West, South East, South West, West Midlands, and Yorkshire and the Humber. The analysis covers the period from January 1995 to May 2016. Our findings indicate that none of these regions exhibit convergence in house prices toward the national mean, clearly suggesting market segmentation within the UK property market across housing types—detached, semi-detached, terraced houses, and flats in the specified sample time period
Bridging the Gap Between Education and Employment: An AI-Integrated LinkedIn Networking Pedagogy for Business Students
No full textThis study evaluates an AI-supported, LinkedIn-based networking pedagogy in undergraduate business courses at a private university. Using a convergent mixed-methods design (N = 222), we analyzed platform analytics, branding artifacts, and reflections. Post-intervention, the mean number of impressions per post increased from under 200 to 4,925; the audience composition shifted toward industry professionals; and themes of vocational clarity and agency emerged. Findings indicate that AI prompting strengthens message quality, amplifies visibility, and broadens students’ professional networks. The intervention offers a scalable, values-aware model for integrating digital identity, AI literacy, and career readiness within business curricula
AI-Powered Generation of Teaching Materials to Support Autonomous Learning in Higher Education
No full textThis study presents and evaluates an automated system for generating personalized lecture notes through artificial intelligence, designed to foster autonomous learning in higher education. A modular Python-based workflow integrating local large language models (LLMs) processed a bilingual corpus (Spanish– English) to extract, synthesize, and validate content. Five progressively broader queries—ranging from the definition and composition of olive pomace to its production, industrial uses, and environmental challenges—were tested under two conditions: closed mode (local sources) and open mode (including online references). The system produced coherent notes covering around 90% of key concepts, consistently citing references, with external sources enriching content without reducing coherence. Quantitative evaluation showed keyword coverage of 85–95%, strong agreement between automatic validation and experts (κ=0.85), excellent inter-rater reliability (ICC=0.92), and processing times of about 15 seconds. Results highlight the pedagogical potential, efficiency gains, and ethical challenges of integrating generative AI responsibly in higher education