Environmental Governance, Big Data Analytics, and SDG Performance: A PLS-SEM Analysis of SMEs in ASEAN Economies

Abstract

This study examines the relationship between the performance of Sustainable Development Goals (SDGs) in Small and Medium Enterprises (SMEs) in ASEAN economies and Big Data Analytics Capability (BDAC), Environmental Governance Pressure (EGP), and Green Innovation (GI). It continues to explore the mediating role of Data-Driven Decision-Making (DDDM) and the moderating role of Regulatory Pressure (RP). A cross-sectional, quantitative approach was adopted; utilizing survey data collected from SMEs across various ASEAN countries. The direct, indirect and moderating effects of the constructions were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings confirm that BDAC, EGP, and GI play essential roles in enhancing SDG performance, both directly and indirectly through DDDM. DDDM plays a pivotal mediating role in transforming digital and governance capabilities into sustainable outcomes. Moreover, RP has a positive direct effect on SDG performance; its moderating impact on the EGP–SP relationship is marginally significant. According to the study, SMEs need to develop analytics capabilities and integrate data-driven cultures to achieve their sustainability objectives. Policy makers should reinforce regulatory structures and bolster SMEs through incentives and institutional guidance to encourage green innovation and alignment with the SDGs. This study proposes an integrated model linking digital capabilities, environmental governance, innovation, and decision-making to sustainable performance in the SME context, with empirical evidence from emerging ASEAN economies.