Determinants of green accounting practices in Vietnam’s leather and footwear sector: A PLS SEM and ANN approach

Abstract

This study aims to investigate the key factors influencing green accounting practices in Vietnamese leather and footwear manufacturing firms, utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) and Artificial Neural Networks (ANN). A total of 645 respondents from 105 manufacturing firms in Vietnam were surveyed. After data screening, 523 valid responses were retained for analysis. The PLS-SEM results suggest that leadership, regulation, firm size, accounting staff competence, and strategy use practice positively impact green accounting. Conversely, implementation costs have a negative influence on green accounting practices. The ANN analysis further disaggregates these effects across four green accounting measurement items. For the first variable, leadership is the most influential factor, followed by regulation, accounting staff competence, strategy use practice, implementation costs, and firm size. For the second variable, all factors exert a moderate influence, ranging from 27.3% to 52.75%, with leadership being the strongest. The third variable shows modest impact differences, with implementation costs being the most dominant. For the fourth variable, implementation costs (62.80%) and strategy use practice (54.78%) are the most influential. This study plays an important role in designing a research model related to factors affecting green accounting in manufacturing firms, thereby enhancing green accounting practices. It also employs two advanced methods (i.e., PLS-SEM, ANN) to improve the accuracy of expected results. Consequently, this research contributes to green accounting literature in manufacturing firms by highlighting the significant role of advanced empirical research methods.