The Impact of Big-data Analytics on Environmental Performance: The Mediating Roles of Lean Six Sigma and Green Production

Abstract

Big-data analytics has emerged as a significant tool for companies dealing with sustainability challenges due to its potential to improve the industrial sector's environmental performance. Despite this, there is no actual research on this topic to be found in the literature. The role of big-data analytics in improving Lean Six Sigma, green production, and environmental performance is investigated in this study. In addition, the role of Lean Six Sigma and green production as a mediator between big-data analytics and environmental performance is examined. 

To acquire primary data, a survey method was used, with a sample of 302 replies from Jordanian industrial enterprises. Smart PLS 3.0 was used to evaluate the study hypotheses.

The study findings illustrated that big-data analytics is favorably linked with Lean Six Sigma, green production, and environmental performance. Furthermore, green production and Lean Six Sigma have positive relationships with environmental performance. Additionally, the connection between big-data analytics and environmental performance is mediated via Lean Six Sigma and green production. This study adds to the body of knowledge by introducing potential mediators in the link between big-data analytics and environmental performance. Jordan's manufacturing industry must establish adequate methods to address sustainability concerns and increase big-data analytics usage.

The study, which is the first to be carried out in the Jordanian setting, takes an empirical look into the relationship between big-data analytics and environmental performance in light of Lean Six Sigma and green production.