Business Analytics Commons^™

Foreign Pedagogy In Education: Theoretical Foundations, Cross-Cultural Dynamics, And Implications For Global Learning, Chitra Venugopal, Prabhakar Rontala Subramaniam

Journal of Global Management Research

This conceptual paper examines foreign pedagogy as a critical lens for understanding how teaching philosophies, instructional strategies, and educational values travel across cultural and national boundaries. Drawing on comparative education, sociocultural theory, and postcolonial scholarship, the paper investigates the processes by which pedagogical models are borrowed, adapted, or imposed between educational systems. It argues that foreign pedagogy is not a neutral transfer of knowledge but a deeply ideological practice shaped by power, cultural epistemology, and institutional context. The paper identifies five central themes: the philosophical roots of major global pedagogical traditions, the mechanisms of pedagogical transfer and borrowing, the tensions …

Green Corporate Responsibility And Sustainable Human Resource Management (Hrm) Functions, Sundara Boopathi R, Shanmugam Sundararajan

Journal of Global Management Research

In order to encourage employee sustainability behavior and achieve long-term organizational success, Green Corporate Responsibility and Sustainable Human Resource Management (HRM) departments place a strong emphasis on incorporating environmental principles into HR processes. Within the context of Green Corporate Social Responsibility (GCSR), this study investigates how Sustainable Human Resource Management (Green HRM) functions affect Organizational Sustainability through the mediating roles of Pro-environmental Behavior (PEB) and Pro-environmental Psychological Climate (PEPC). based on the Resource-Based View (RBV), Social Exchange Theory (SET), and Ability-Motivation-Opportunity (AMO) theory. By incorporating six essentials Green HRM practices-green hiring and selection, green training and development, green performance evaluation, …

Identifying Skill Gaps And Upskilling Priorities For C-Level Executives Using The Analytic Hierarchy Process (Ahp) Analysis, Mohamed Riyazhkhan, Mohsin Aziz, Krishna Murthy, Abdul Azeez K M, George Anthony Fernando

Journal of Global Management Research

C-level executives, or chief-level executives, play a significant role in corporate development, and their roles and responsibilities are essential for sustaining organizational effectiveness in an increasingly competitive business environment. They also constitute a fundamental component of organizational management systems (Julie & Emory, 2006). In this research, data were collected exclusively from C-level or C-suite executives (CEO, CFO, COO, and CHRO) from leading corporations in Oman and India. This study investigates three representative cases related to managerial functions across various corporate organizations. The first case examines the job descriptions associated with C-level executives, the second case explores the identification of skill …

A Critical Perspective On Artificial Intelligence's Energy Footprint And Future Research Questions For Accounting And Business Research, Dr Mansi Mansi, Rakesh Pandey

Journal of Global Management Research

No abstract provided.

Reinforcement Learning Approaches For Intelligent Budget Management: A Comparison Of Traditional Budget Model With Q-Learning, And Deep Q-Network Models, Danish Yaqub

Create@State

This study explores the application of Reinforcement Learning (RL) techniques to improve personal budget management and financial decision-making. A traditional rule-based budgeting model is first developed as a baseline approach, where income is allocated to expenses, savings, and debt payments using fixed financial ratios and predefined rules. Although this approach provides a structured framework for financial planning, it lacks adaptability and cannot dynamically optimize decisions when financial conditions change.To address these limitations, two reinforcement learning models—Q-Learning and Deep Q-Network (DQN) are implemented and compared with the traditional budgeting model. In the Q-Learning model, an agent interacts with simulated financial states …

The Convergence Of Big Data And Ai, Prasanna Rajbhandari

Create@State

Big data and artificial intelligence are transforming how organizations analyze information and make decisions. Traditional analytics struggle with large, distributed, and unlabeled datasets. Modern AI systems must adapt quickly, preserve privacy, and extract meaningful insights from complex data environments.

Ownership Duration In The U.S. Business Jet Market, Yuchen Hu

SACAD: Scholarly Activities

This study analyzes ownership duration in the U.S. business jet market using FAA registry data as of February 16, 2026 (N=12,359). The analysis reveals a structured distribution with a mean of 5.86 years and a median of 5.00 years. Crucially, retention varies by acquisition status: new aircraft owners exhibit an average hold of 7.36 years, whereas pre-owned aircraft holders show a significantly higher turnover of 5.11 years, with most resales occurring within a 3–7-year window. These findings suggest that ownership behavior is driven by structured asset management and lifecycle planning, providing a predictive framework for identifying aircraft replacement and trade-in …

Developing Strategies For Pce Outreach, Mariah Blankenbaker, Gordon Carlson, Daniel Adesoji, Levi Eck

SACAD: Scholarly Activities

In collaboration with Professional and Continuing Education (PCE), we produced projects to automate their internal tasks, as well as to promote their services. By taking advantage of software techniques, we bridged live-action footage with 2D and 3D computer visuals for promotional material. In addition, we researched the capabilities of creating a custom Generative Pre-trained Transformer (GPT) and trained it to analyze and interact with thousands of industry datapoints.

A Dynamic Systems Framework For Customer Lifecycle Management: From Latent State Discovery To Robust Control Policy, Ali Nasirzonouzi

Northeast Journal of Complex Systems (NEJCS)

Traditional marketing often relies on static strategies that fail to capture dynamic customer behavior. This paper introduces an integrated framework to model and control the customer lifecycle, bridging the gap between empirical data and computational simulation. Using the Customer Personality Analysis dataset, we implemented a five-stage methodology. We first identified three distinct customer segments (At-Risk, Standard, High-Value) using Gaussian Mixture Models. To address the lack of longitudinal data, we calibrated a normative transition model based on customer inertia principles. Our analysis revealed that marketing effectiveness is highly state-dependent; notably, At-Risk customers exhibited a 33.5% lift when targeted with catalogs. Leveraging …

Generative Artificial Intelligence In Professional Selling Course: The Art (And Science) Of Prompt Engineering, Michael Rodriguez, Kevin Trainor, Michael Rodriguez

Atlantic Marketing Association Proceedings

No abstract provided.

Examining Digital Transformation In Maritime Logistics: A Big Data Perspective, Jiyoon An

Atlantic Marketing Association Proceedings

No abstract provided.

Global Apparel Companies Adjusting Their Supply Chain Strategies To Post-Covid-19, Alan D. Smith

Atlantic Marketing Association Proceedings

No abstract provided.

Geomarketing: Revolutionizing Market Strategies And Enhancing Spatial Decision-Making Through Ai-Driven Insights, Mark J. Sciuchetti Dr., Jianping Huang

Atlantic Marketing Association Proceedings

No abstract provided.

Sustainability And Technology Aspects Of Supplier Performance, Alan D. Smith

Atlantic Marketing Association Proceedings

No abstract provided.

Digital Transformation And Market Microstructure: Analyzing The Impact Of Algorithmic Trading On National Stock Exchange Of India Price Discovery Mechanisms Through Complex Systems Theory., Mukesh Bhaskar Ahirrao, Harshal Anil Salunkhe, Vishal Sunil Rana

Northeast Journal of Complex Systems (NEJCS)

Abstract

This research examines the evolution of market microstructure at the National Stock Exchange of India (NSE) from 2020 to 2024, a period characterized by substantial growth in algorithmic trading from 35% to 44% of total trading volume. Using market microstructure data and analytical techniques grounded in complex systems perspectives, the study documents temporal patterns in price discovery, liquidity, volatility, and market efficiency associated with this digital transformation.

The analysis reveals several notable changes in market characteristics. Transaction costs improved significantly, with bid-ask spreads declining by 23.4% and market depth increasing by 18.1%. Price adjustment half-life decreased by 50%, indicating …

Marketing The Future Of Radiology: How Ai Integration Enhances Diagnostic Precision And Streamlines Clinical Workflows, Monisha Gupta, Jordan -. Watts Ms, Alberto Coustasse Hencke Dr.

Atlantic Marketing Association Proceedings

No abstract provided.

Face Presence In User-Generated Photos And Its Effect On Review Helpfulness, Anh Dang, Bridget Nichols, Mark Nichols

Atlantic Marketing Association Proceedings

No abstract provided.

Design And Implementation Of A Customer Retention And Voice Ai System For El Nopal, Brando Medina

Undergraduate Theses

This Honors Applied Thesis documents the design and implementation of a live Customer Retention and Voice AI System for El Nopal, a full-service restaurant, to improve customer follow-up, routine communication handling, and cross-channel engagement. The project was developed for El Nopal’s Tyler Center location on Taylorsville Road and focused on building a practical artifact rather than primarily evaluating long-term business outcomes. The completed v1 system consists of three modules: a Customer Retention System centered on a QR-based VIP rewards workflow, a Voice AI System for routine phone support, and a Cross-Channel Integration Layer that connects voice interactions to CRM-based SMS …

Behavioral Biases As Drivers Of Complexity In Stock Markets: An Agent-Based Modeling Approach, David Joseph Dr, Alwin Joseph, Blesson James, Kajal Dass

Northeast Journal of Complex Systems (NEJCS)

By modeling financial systems as Complex Adaptive Systems, this study investigates how behavioral biases influence emergent complexity in stock markets. The study integrates heterogeneous agents, such as rational traders, herding agents, overconfident traders, and anchoring/disposition-driven investors, within a Limit Order Book framework calibrated to both U.S. and Indian market conditions using an Agent-Based Modeling (ABM) approach implemented through the high-fidelity ABIDES simulation environment. Price dynamics, volatility patterns, and liquidity structures were analyzed by Monte Carlo simulation experiments with different behavioral compositions. The results show that behavioral biases cause nonlinear price reactions, produce heavy-tailed return distributions that distort order-book complexity, and …

Crime, Consumers, And Clustering: A Geomarketing Analysis Of Retail Behavior Across Urban Markets, Mark J. Sciuchetti Dr., Jianping Huang

Atlantic Marketing Association Proceedings

No abstract provided.