Big data analytics and brand reputation: Catalysts for circular economy and sustainable performance

The circular economy concept is popular because it encourages resource efficiency, sustainable production, a shift in economic thinking, and the creation of higher-skilled jobs. We are unavoidably used to the traditional linear economy cradle-to-cradle model of production and consumption in our contemporary life. This study aims to determine the elements that support and impede Malaysian manufacturing enterprises’ adoption of the big data analytics and circular economy business model, given the discrepancy in developing countries in Southeast Asia. The circular economy business model is used to analyze the impacts of sustainable performance. Using the lenses of dynamic capability theory (DCT) and covariance-based structural equation modeling (CB-SEM), this study assesses the responses of 241 respondents from various sectors of the manufacturing sector having environmental management systems (EMS) within Malaysia. Therefore, survey-based primary data was gathered to understand the effect of big data analytics on sustainable performance via moderate mediation of circular economy practices, brand reputation, and environmental dynamics. Findings of distal mediation revealed that big data analytics have a significant positive effect on the sustainable performance of manufacturing firms. Furthermore, it is revealed that environment dynamics at each level of mediation moderate the relationship significantly; hence, it is important for the firms to understand the dynamics of the environment, either internal or external, where the firms are operating to effectively implement the big data analytics (BDA), circular economy practices (CEP) to achieve sustainable performance.