A Brief Contextualization of Big Data in the International Business environment: evidence from the Alibaba Group's transition

Matheus Felipe Pereira De Souza


The present work seeks to understand the impacts of Big Data and its adjacent technologies in the international business environment, with a focus on the financial sector, bringing the recent transition of Alibaba Group as a case study. In this effort, the work, in the first moment, brings a conceptualization of Big Data from the perspective of different authors, in different areas of science. In the second moment, an analysis of the applications of Big Data in the governmental scope, providing an understanding of how the technology can be applied from the perspective of the States and, at the same time, a differentiation is made with respect to the use of the Big Data in the business world, with a special focus on the financial sector of international business. In the last instance, an analysis of the Alibaba Group transition, the transition from an e-commerce company to a company that focuses on the dynamics of data is brought by this work, demonstrating how dynamics based on Big Data technologies can lead to strategic changes in companies, but they can also provoke a dynamism in the international business sector as a whole.


Big Data, International Business, E-commerce.

Full Text:



Aley, A. B., Halima, M. B. & Alimi, M. (2015, May). Big Data Analytics for Logistics and Transportation. In Curran Associates. Paper presented at the Proceedings of the 4th IEEE International Conference on Advanced logistics and Transport (France), Valenciennes, pp 301. Valenciennes: Institute of Electrical and Electronics Engineers.

Alizila - News From Alibaba Group (2016). Five Reasons Why Alibaba is a Data (Not E-commerce) Company. Available at: .

Ballou, R. H. (1997). Business Logistics - Importance and Some Research Opportunities. Gestão e Produção 4(2), p. 117-129.

Boyd, D & Crawford, K. (2012) Critical Questions for Big Data. Information, Communication & Society. 15(5), p. 662-679

Buckley, P. J. (2009). Business History and International Business. Business History 51(3), p. 307-333.

Bassiur, M. (2016). How Alibaba deployed Big Data to combat China IPR pirates and counterfeiters. Recode. Available at: . Access: 05 july, 2017.

China Daily (2015). Ant Financial launches big data stock market index. Available at: . Access: 01 June, 2017.

Chui M, Loffler M, Robert R. (2010). The internet of things. Mckinsey Quarterly No. 2.

DHL. (2013). Big Data in Logistics: A DHL perspective on how to move beyond the hype. 31p.

Groenfeldt, T. (2013) Banks Use Big Data to Understand Customers Across Channels. Forbes.

Gutierrez, D. D. (2014). InsideBIGDATA Guide to Big Data for Finance. Dell & Intel.

Hamill, A. (2016). How Alibaba uses big data to understand China’s shoppers. Warc Exclusive.

Hyek, F. A. (1967). Studies on Philosophy, Politics and Economics. Chicago: University of Chicago Press.

Internet Live Stats (2017). Twitter Usage Statistics - Tweets Growth Rate. Available at: < http://www.internetlivestats.com/twitter-statistics/>. Access: 02 June, 2017.

Internet Society (2016). Global Internet Report 2016. Available at: < https://www.internetsociety.org/globalinternetreport/2016/wp-content/uploads/2016/11/ISOC_GIR_2016-v1.pdf>. Access: 02 july, 2017.

Kim, G., Chung J. & Trimi S. (2014) Big-Data Applications in the Government Sector. Communications of the ACM, 57(3), p. 78-85.

Lee, J., Lapira, E., Bagheri, B. & Kao, H. Recent advances and trends in predictive manufacturing systems in big data environment. Manufacturing Letters, 1(1), 2013, p. 38-41.

Lohr, S. (2012). The Age of Big Data. The New York Times, New York, February 11. Available at: .

Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburhh, C. & Byers, A. H. (2011). Big Data: The next frontier for innovation, competition and productivity. McKinsey Global Institute. Available at: < https://bigdatawg.nist.gov/pdf/MGI_big_data_full_report.pdf>.

McAfee, A. & Brynjolfsson, E. (2012). Big Data: The Management Revolution. Harvard Business Review, 90(10), p. 60-68.

Moore, G. E. (1965). Cramming more components onto integrated circuits. Electronics, 38(8). Oracle. Improving Manufacturing Performance with Big Data. Oracle Enterprise architecture white paper, 2015. Available at: .

Salicr, M., Civit, S. (2014). Data analysis and design optimization in industrial product development: how to bring real-life into the classroom. Procedia: Social Behavior Sciences. 41 (1), p. 347–351.

Silva, L. (2011). Logística no comércio exterior. 2. ed. São Paulo: Aduaneiras.

Talluri, S., Narasimhan, R. (2004). A methodology for strategic sourcing. Eur. J. Oper. Res. 1(154), p. 236–250.

Toma, C. & Hancock, J. (2013). Self-Affirmation Underlies Facebook Use. Personality and Social Psychology Bulletin, 39(3), p. 321-331.

Winter, R. (2011). Big Data: Business Opportunities, Requirements and Oracle’s Approach. Winter Corporation: Cambridge, 8 p. Available at:.

Zwitter, A. (2015). Big Data and International Relations. Ethics & International Affairs, 29(4), p. 377-389.


  • There are currently no refbacks.