Author: Ahmet Sekreter1
1Department of Business and management,Faculty of Administration Sciences And Economics, Ishik University, Erbil, Iraq
Abstract: An age of network has been living for the last decades. The information technologies have been used by hundreds of millions of users. These technologies are enabling to connect businesses and economic activities. One of the characteristics of the networked economy is the amount of data that produced due to the interlinking of firms, individuals, processes by businesses, and economic activities. Another issue with the networked economy is the complexity of the data. Extraction of the knowledge from the networked economy has challenges by the traditional approach since data is large scale, second decentralized, and third they connect many heterogeneous agents. The challenges can be overcome by the new optimization methods including human element or the social interactions with technological infrastructure.
Keywords: Networked Economy, Big Data, Optimization
Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 98- 115.
Kaisler, S., Armour, F., Espinosa, J. A., & Money, W. (2013). Big data: Issues and challenges moving forward. In System Sciences (HICSS), 2013 46th Hawaii International Conference on (pp. 995- 1004). IEEE.
Kelly, K. (1998). New Rules for the New Economy: 10 Radical Strategies for a Connected World. New York: Penguin Group.
Lu, L., & Wang, G. (2008). A study on multi-agent supply chain framework based on network economy. Computers & Industrial Engineering, 54(2), 288-300.
Richtárik, P., & Takáč, M. (2016). Parallel coordinate descent methods for big data optimization. Mathematical Programming, 156(1-2), 433-484.
Shapiro, C. & Varian, H. (1999). Information Rules: A Strategic Guide to the Network Economy. Boston: Harvard Business School Press.
Shy, O. (2001). The Economics of Network Industries. Cambridge: Cambridge University Press. Slavakis, K., Giannakis, G. B., & Mateos, G. (2014). Modeling and optimization for big data
analytics:(statistical) learning tools for our era of data deluge. IEEE Signal Processing Magazine, 31(5), 18-31.
Tole, A. A. (2013). Big data challenges. Database Systems Journal, 4(3), 31-40.
Villars, R. L., Olofson, C. W., & Eastwood, M. (2011). Big data: What it is and why you should care. White Paper, IDC, 14.
International Journal of Social Sciences & Educational Studies
ISSN 2520-0968 (Online), ISSN 2409-1294 (Print), September 2017, Vol.4, No.1