Fostering green innovation: the roles of big data analytics capabilities and green supply chain integration

Purpose The purpose of this study is to investigate the impact of big data (BD) analytics capabilities (BDACs) on green supply chain integration (GSCI) and green innovation (GI) in the context of a developing country, Jordan. In addition, the mediating effect of GSCI on the relationship between BDAC and GI is investigated. Design/methodology/approach Data collection was carried out through a survey with 300 respondents from food and beverages manufacturing firms located in Jordan. Partial least squares-structural equation modeling (PLS-SEM) technique was applied to analyze the collected data. Natural resource-based view (NRBV) theory was the adopted theoretical lens for this study. Findings The results revealed that BDAC positively and significantly affects both GSCI and GI. In addition, the results demonstrated that GSCI positively and significantly affects GI. Further, it is also found that GSCI positively and significantly mediates the relationship between BDAC and GI. Originality/value This study developed a theoretical and empirical model to investigate the relationship between BDAC, GSCI and GI. This study offers new theoretical and managerial contributions that add value to the supply chain (SC) management literature by testing the mediation model in food and beverages manufacturing firms located in Jordan.