Can big data and predictive analytics improve social and environmental sustainability?

Rameshwar Dubey, Angappa Gunasekaran, Stephen J. Childe, Thanos Papadopoulos, Zongwei Luo, Samuel Fosso Wamba () and David Roubaud ()

Technological Forecasting and Social Change, 2019, vol. 144, issue C, 534-545

Abstract: Although literature indicates that big data and predictive analytics (BDPA) convey a distinct organisational capability, little is known about their performance effects in particular contextual conditions (inter alia, national context and culture, and firm size). Grounding our investigation in the dynamic capability views and organisational culture and based on a sample of 205 Indian manufacturing organisations, we empirically investigate the effects of BDPA on social performance (SP) and environmental performance (EP) using variance based structural equation modelling (i.e. PLS). We find that BDPA has significant impact on SP/EP. However, we did not find evidence for moderating role of flexible orientation and control orientation in the links between BDPA and SP/EP. Our findings offer a more nuanced understanding of the performance implications of BDPA, thereby addressing the crucial questions of how and when BDPA can enhance social/environmental sustainability in supply chains.

Keywords: Big data; Predictive analytics; Dynamic capability view; Supply chains; Social sustainability; Environmental sustainability (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (59)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:144:y:2019:i:c:p:534-545

DOI: 10.1016/j.techfore.2017.06.020

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