A Multivariate Analysis of Structural Linkages in Cross-Border E-Commerce: An Application of PLS-MGA

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DOI: https://doi.org/10.28924/2291-8639-24-2026-290
Published: Sep 21, 2026
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Tran Thanh Trung, Vo Xuan Vinh, Tran Thi Ngoc Lan, A Multivariate Analysis of Structural Linkages in Cross-Border E-Commerce: An Application of PLS-MGA, Int. J. Anal. Appl., 24 (2026), 290.

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Tran Thanh Trung, Vo Xuan Vinh, Tran Thi Ngoc Lan

Abstract

This study presents a comprehensive multivariate analysis of cross-border e-commerce dynamics by developing and testing a complex structural equation model. Quantifying multifaceted socio-psychological and system-related variables requires robust analytical frameworks. Utilizing Partial Least Squares Multi-Group Analysis (PLS-MGA), this research analyzes multidimensional datasets representing two major supply markets (the United States and China). The conceptual model evaluates structural pathways between consumer affinity, ethnocentrism, e-service parameters, and terminal purchasing behaviors. The multivariate analysis rigorously establishes measurement invariance and validates the measurement model before unearthing significant direct, indirect, and heterogeneous structural linkages across the groups. Statistical findings demonstrate that trust and product judgments serve as critical mediating variables, with distinct structural variations identified between the examined cohorts. By empirically validating these complex interrelations through PLS-MGA, the study advances the application of advanced multivariate analytical methods in behavioral modeling.

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