The impact of Big Data and Predictive Analytics on Triple Bottom Line Sustainability

The rapid development and interest in triple bottom line (TBL) practices in business is having an intense impact on supply chain management and operations. Big Data and Predictive Analytics (BDPA), a multidimensional concept is highly regarded in social science research and business as a tool for extracting business value and achieving high firm performance. However, there is limited research on the impact of big data and predictive analytics on triple bottom line performance in supply chains and operations. Environmental volatility has also become central to many strategic studies. This study investigates the impact of BDPA on environmental performance, social performance and economic performance drawing on Resource Based View, Dynamic Capability View, Contingency Theory and environmental volatility theoretical lens. Focus is emphasised on performance effects of BDPA on the TBL approach to simultaneously account for economic, environmental and social performance of sustainability. The analysis adopts a multi-method design that involves Partial Least Squares – Structural Equation Modelling (PLS-SEM) that is complimented by an Artificial Neural Network (ANN). A BDPA model is constructed and applied using PLS-SEM repeated approach. The investigation into the effects of BDPA on TBL was grounded on data collected from 304 IT professionals located in BRICS (Brazil, Russia, India, China and South Africa) based firms. The findings suggest that BDPA has a significant influence on all three dimensions of TBL, supporting all six hypotheses. This includes finding support for hypothesis for the moderating effect of Environmental Volatility (EV) on the relationship between BDPA and TBL dimensions. There is also evidence for positive relationships between Tangible Resources (TR), Intangible Resources (IR), Human Related Skills (HRS) and BDPA. Further, the findings show the relative importance of the resources that make up the BDPA construct. This research is the first BDPA and sustainability study to show how a PLS-SEM -ANN model can aide in ranking resources in order of importance within organisations.