Big data analytics in E-commerce: a systematic review and agenda for future research
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POSITION PAPER
Big data analytics in E-commerce: a systematic review and agenda for future research Shahriar Akter 1 & Samuel Fosso Wamba 2
Received: 1 September 2015 / Accepted: 26 February 2016 # Institute of Applied Informatics at University of Leipzig 2016
Abstract There has been an increasing emphasis on big data analytics (BDA) in e-commerce in recent years. However, it remains poorly-explored as a concept, which obstructs its theoretical and practical development. This position paper explores BDA in e-commerce by drawing on a systematic review of the literature. The paper presents an interpretive framework that explores the definitional aspects, distinctive characteristics, types, business value and challenges of BDA in the e-commerce landscape. The paper also triggers broader discussions regarding future research challenges and opportunities in theory and practice. Overall, the findings of the study synthesize diverse BDA concepts (e.g., definition of big data, types, nature, business value and relevant theories) that provide deeper insights along the cross-cutting analytics applications in e-commerce. Keywords Big data analytics . E-commerce . Business value JEL Classification M15 . M310
Introduction In the past few years, an explosion of interest in big data has occurred from both academia and the e-commerce industry. This explosion is driven by the fact that e-commerce firms that Responsible Editor: Rainer Alt * Shahriar Akter [email protected]
1
University of Wollongong, NSW 2500, Australia
2
NEOMA Business School, Rouen 76825, France
inject big data analytics (BDA) into their value chain experience 5–6 % higher productivity than their competitors (McAfee and Brynjolfsson 2012). A recent study by BSA Software Alliance in the United States (USA) indicates that BDA contributes to 10 % or more of the growth for 56 % of firms (Columbus 2014). Therefore, 91 % of Fortune 1000 companies are investing in BDA projects, an 85 % increase from the previous year (Kiron et al. 2014a). While the use of emerging internet-based technologies provides e-commerce firms with transformative benefits (e.g., real-time customer service, dynamic pricing, personalized offers or improved interaction) (Riggins 1999), BDA can further solidify these impacts by enabling informed decisions based on critical insights (Jao 2013). Specifically, in the e-commerce context, “big data enables merchants to track each user’s behavior and connect the dots to determine the most effective ways to convert onetime customers into repeat buyers” (Jao 2013,p.1). Big data analytics (BDA) enables e-commerce firms to use data more efficiently, drive a higher conversion rate, improve decision making and empower customers (Miller 2013). From the perspective of transaction cost theory in e-commerce (Devaraj et al. 2002; Williamson 1981), BDA can benefit online firms by improving market transaction cost efficiency (e.g., buyerseller interaction online), managerial transaction cost efficiency (e.g., process efficiency- recommendation algorithms by Ama
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