The impact of big data analytics capabilities on green supply chain performance: is green supply chain innovation the missing link?

The objective of this paper is to examine the impact of big data analytics capabilities (BDAC) on green radical supply chain innovation (GRSCI), green incremental supply chain innovation (GISCI), and green supply chain performance (GSCP) in the context of a developing country, Jordan. In addition, the mediating effect of GRSCI and GISCI on the relationship between BDAC and GSCP is tested.

Data collection is carried out through a survey with 303 respondents from manufacturing firms located in Jordan. Partial least squares-structural equation modelling approach is applied to analyse the collected data. Resource-based view and natural resource-based view theory form the adopted theoretical lens for this study.

The results reveal that BDAC positively and significantly affects GRSCI, GISCI, and GSCP. In addition, the results demonstrate that GRSCI and GISCI positively and significantly affect GSCP. Further, it is also found that GRSCI and GISCI positively and significantly mediate the relationship between BDAC and GSCP.

This study's author develops a theoretical and empirical model to investigate the relationship among BDAC, GRSCI, GISCI, and GSCP. This study offers new theoretical and managerial contributions that add value to the supply chain management literature by testing the mediation model in manufacturing firms located in Jordan.