Asian Business Research Journal

Strategic Capital Allocation, Innovation Intensity, and Market Valuation Dynamics: Evidence from Vietnam's Transitional Economy

Nguyen Tuan Minh PHAM — 2025-07-07

This study investigates the intricate relationships between strategic capital allocation decisions, innovation intensity measured through research and development expenditure, and market valuation dynamics within Vietnam's rapidly evolving transitional economy. Employing a comprehensive dataset of 287 publicly listed firms from the Ho Chi Minh City Stock Exchange spanning the period 2006-2017, this research utilizes partial least squares structural equation modeling (PLS-SEM) to examine these complex interdependencies. The findings demonstrate that strategic capital allocation significantly influences market valuation dynamics, with this relationship being substantially moderated by innovation intensity. Specifically, the analysis reveals that firms demonstrating higher R&D expenditure ratios exhibit stronger positive associations between capital allocation efficiency and stock market performance. Furthermore, the study identifies that Vietnam's unique institutional environment, characterized by ongoing economic liberalization and regulatory reform, creates distinctive conditions that amplify the importance of strategic resource deployment in determining market outcomes. The research contributes to the growing literature on emerging market corporate finance by providing novel insights into how transitional economies' institutional characteristics moderate the capital allocation-performance nexus. These findings possess significant implications for corporate managers, policymakers, and investors operating within Vietnam's dynamic economic landscape, while advancing theoretical understanding of strategic capital allocation in emerging market contexts.

Navigating Digital Disruption in Emerging Markets: The Mediating Role of Demand Forecasting Accuracy in Big Data Analytics Capabilities-Supply Chain Performance Relationships within Vietnam's Fashion E-Commerce Ecosystem

Nguyen Tien Minh TRAN — 2025-07-07

This research investigates the complex interplay between big data analytics capabilities, demand forecasting accuracy, and supply chain performance within Vietnam's rapidly expanding fashion e-commerce sector. Drawing upon resource-based view theory and the dynamic capabilities framework, this study examines how demand forecasting accuracy mediates the relationship between big data analytics capabilities and supply chain performance, specifically stockout reduction. Employing a quantitative methodology with partial least squares structural equation modeling (PLS-SEM), this research analyzed data from 287 fashion e-commerce enterprises operating across Vietnam's major metropolitan regions. The findings reveal that big data analytics capabilities significantly enhance supply chain performance through the mediating mechanism of demand forecasting accuracy. Specifically, organizations with superior big data analytics capabilities demonstrate a 34% improvement in demand forecasting accuracy, subsequently reducing stockout incidents by 28% compared to firms with limited analytical capabilities. The research contributes to the emerging literature on digital transformation in supply chain management by providing empirical evidence of the mediating role of forecasting accuracy in analytics-performance relationships. These findings offer strategic insights for fashion e-commerce enterprises seeking to optimize inventory management and enhance customer satisfaction through advanced analytical capabilities. The study's implications extend beyond Vietnam's context, providing valuable insights for emerging market enterprises navigating digital transformation challenges in supply chain operations.

Behavioral Determinants and Cultural Cognition in Investment Decision-Making: Evidence from Vietnamese Retail Investors in an Emerging Digital Financial Ecosystem

Nguyen Phuong Vy LE — 2025-07-07

This research investigates the complex interplay between behavioral determinants and cultural cognition in shaping investment decision-making patterns among Vietnamese retail investors within the rapidly evolving digital financial ecosystem. Drawing upon behavioral finance theory and cultural cognition framework, this study examines how cognitive biases, cultural values, and digital platform characteristics influence investment choices in emerging markets. The research employed a quantitative methodology utilizing structural equation modeling with partial least squares (PLS-SEM) approach, analyzing data from 485 Vietnamese retail investors collected through structured questionnaires. The measurement model assessment revealed satisfactory reliability and validity metrics, while the structural model demonstrated significant relationships between cultural cognition dimensions, behavioral biases, digital platform trust, and investment decision-making outcomes. Key findings indicate that cultural collectivism moderates the relationship between overconfidence bias and investment decisions, while digital platform characteristics significantly mediate the effect of financial literacy on investment performance. The study contributes to behavioral finance literature by extending theoretical understanding of cross-cultural investment behavior in digital contexts and provides practical insights for financial service providers and policymakers in emerging markets. Results suggest that cultural cognition serves as a critical lens through which behavioral biases manifest in investment decisions, particularly within digitally-mediated financial environments.