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Journal of Business & Retail Management Research
Vol-12, Issue 4, July 2018
ISSN 1751-8202 (Print) ISSN 2056-6271 (Online)

Creating shared value through big-data analytics: a conceptual treatise on sustainability presence
Viput Ongsakul National Institute of Development Administration NIDA Business School, Thailand Salil K. Sen National Institute of Development Administration NIDA Business School, Thailand


Sustainability presence; shared value; big-data analytics; predictability, prescriptivity and scalability

        The objective of this study is to review and create a frame of reference for the creation of shared value through big-data analytics that sets sustainability presence (Hampton et al. 2013, Schwab, 2017). Big Data Analytics has potential to cope with challenges of over consumption, unharnessed growth and waste proliferation (Müller, Junglas, vom Brocke & Debortoli, 2016). Sustainability presence is relevant curated data, predictive, prescriptive and scalable (Hampton, 2013). Businesses and retail services incorporate transformation to endure and cope with challenges (ur Rehman, Chang, Batool & Wah, 2016). This paper posits the concept of sustainability presence through big-data analytics. Sustainability presence is defined as an overarching ambiance that nurtures shift from reactive to proactive analytics to create value-embedded information that is purposeful for creating connect on water, waste and energy realms (Iacovidou, et al., 2017). The role of analytics is to scaffold big-data emanating from large-scale processes, to the tune of water, energy, waste impacting sustainability presence, call for higher elevation level eco-evo-big data analytics. Whereas, near-grassroots measure of predictability, prescriptivity and scalability, require calibrated attentional grain (Bansal, Kim & Wood, 2017). Outcomes of this research is ethics of collection (White & Ariyachandra, 2016), storage and usage (George, Haas & Pentland, 2014). of big data (to root for the creation of sustainability presence from all arms of business to speed up the creation of value real-time, thereby harnessing the power of big-data analytics.

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