Achieving the Triple Bottom Line Through Big Data Analytics

Baraah Shdifat (), Dilek Cetindamar Kozanoglu () and Shadi Erfani ()
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Baraah Shdifat: University of Technology Sydney (UTS)
Dilek Cetindamar Kozanoglu: University of Technology Sydney (UTS)
Shadi Erfani: University of Technology Sydney (UTS)

Chapter Chapter 32 in The Palgrave Handbook of Corporate Sustainability in the Digital Era, 2021, pp 631-649 from Springer

Abstract: Abstract Sustaining growth and maximizing profitability over the long term are the main goals for businesses to survive in today’s’ competitive markets. However, the current sustainability agenda is pushing firms to extend their focus beyond traditional economic goals to include environmental and social goals. Achieving sustainability outcomes is based on the ability of a firm to deal with the conflicting relationships between the triple bottom line (TBL) pillars (economic, social, and environmental performance). While the rapid evolution of big data technologies has provided different opportunities for organizations, such as improving economic, social, and environmental performance, there is relatively little research on the managerial and academic understanding of how employing big data analytics could help to establish sustainable development outcomes based on the TBL approach. This book focuses on finding ways of improving corporate sustainability in the digital era. Hence, we hope that this chapter might contribute to this investigation by pointing out how big data analytics could be utilized to achieve all three dimensions of TBL sustainability.

Date: 2021
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DOI: 10.1007/978-3-030-42412-1_32

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