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Title

Big Data Analytics Evaluation, Selection and Adoption: A Developing Country Perspective

Author

Anas Jebreen Atyeh†, Mohammed-Issa Riad Mousa Jaradat†† and Omar Suleiman Arabeyyat†††

Citation

Vol. 17  No. 9  pp. 159-171

Abstract

One of the biggest challenges for organizations especially in a developing country is to select the suitable big data analytics (BDA) platform that can satisfy their requirements. Trade-offs are exist among multiple business requirements fulfilled by different BDA platforms. This paper formulates the selection of BDA platforms as a fuzzy multi-criteria group decision making problem, and presents a fuzzy multi-criteria group decision making framework that helps organizations to evaluate, select, and adopt a suitable BDA platform that best satisfies their requirements. An Intuitionistic Fuzzy Goal Programming (IF_GP) algorithm based on goal programming and intuitionistic fuzzy numbers is developed to facilitate an agreement among a group of decision makers and eliminate the uncertainty to better represent their opinions. The developed algorithm is incorporated within the proposed framework for adequately dealing with the BDA platform performance evaluation and selection problem. A numerical example for BDA platform selection is given to illustrate the application of proposed framework and IF_GP algorithm using a Jordanian case study. The need for this paper is important as the outcomes and conclusions of the analysis could be utilized to improve and hasten the adoption of using big data analytics technology in a developing country.

Keywords

Big data Big data analytics (BDA), BDA platform, Goal programming, Intuitionistic fuzzy numbers Multi- criteria group decision making Adoption Jordan.

URL

http://paper.ijcsns.org/07_book/201709/20170921.pdf