International Journal of Scientific & Technology Research

Home About Us Scope Editorial Board Contact Us

IJSTR >> Volume 8 - Issue 7, July 2019 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Study Of M-Commerce Trends And Big Data Analytics Pros & Cons In M-Commerce

[Full Text]



Dr. Archana Sharma, Ms. Shweta Singh



Big Data, M-Commerce, Data Analytics, Amazon, Flipkart, E-Commerce, chatbota, augmented reality



Big Data refers to tools and methodologies that aim to ce have been expended in retail, telecommunication, information services and finance, services. This research explores the relevance of big data analytics in current trends of M-Commerce and various technologies that make analytics of consumer possible. This research further extends with the case study of Amazon, Flipcart, walmart to provide the insight that how these firms apply big data analytics in their business strategies for better use of M Commerce applications. Further this paper highlights to access, maintain and technical challenges and privacy issues of Big Data in M-Commerce.



[1]. https://www.pwc.in/en_IN/in/assets/pdfs/publications/2015/eco mmerce-in-india-accelerating-growth.pdf/ retrieved on 02 April, 2015.
[2]. “M-Commerce In India Will Grow Manifold By2019”, http://www.cxotoday.com/story/why-M-Commerce-growth-inindia-will-be-unstoppable/“M-
[3]. “MCommerce”,http://searchmobilecomputing.techtarget.com/defin ition / M-Commerce
[4]. Ahmad Ghandour-"Big Data Driven E-Commerce Architecture",International Journal of Economics, Commerce and Management,ISSN 2348 0386 Vol. III, Issue 5, pp:940-947,May 2015.
[5]. Chaudhuri S, Dayal U, Narasayya V. An Overview of Busi¬ness Intelligence Technology. Communications of the ACM. 2011; 54(8):88–98.
[6]. Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, Motoda H, McLachlan GJ, Ng A, Liu B, Yu PS, Zhou ZH, Steinbach M, Hand DJ, Steinberg D. Top 10 Algorithms in Data Mining. Knowledge and Information Systems. 2007; 14(1):1–37.
[7]. Joseph, R. C., & Johnson, N. A. (2013). Big data and transformational government. IT Professional, 15(6), 43–48.
[8]. Bihani, P., & Patil, S. T. (2014). A comparative study of data analysis techniques. International Journal of Emerging Trends & Technology in Computer Science, 3(2), 95–101.
[9]. http://www01.ibm.com/software/in/analytics/solutions /customer-analytics/social-media-analytics/.
[10]. http://www.webopedia.com/TERM/P/predictive_anal ytics.html.
[11]. Mobile analytics at http://www.netbiscuits.com/mobile- analytics/.
[12]. Hunter DR, Handcock MS, Butts CT, Goodreau SM, Morris MM. ergm: A Package to Fit, Simulate and Diagnose Ex¬ponential-Family Models for Network. Journal of Statistical Software. 2008; 24(3):1–29.
[13]. Patterson DA. Technical Perspective: The Data Center Is the Computer. Communications of the ACM. 2008; 51(1):105.