Research Article
ANFIS based hybrid approach identifying correlation between decision making and online social networks
@ARTICLE{10.4108/eai.13-7-2018.165669, author={Areeba Rahman and Nageen Saleem and Aysha Shabbir and Maryam Shabbir and Muhammad Rizwan and Shahid Naseem and Fahad Ahmad}, title={ANFIS based hybrid approach identifying correlation between decision making and online social networks}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={8}, number={29}, publisher={EAI}, journal_a={SIS}, year={2020}, month={7}, keywords={Rationality, Decision Making, Online Social Networks, Fuzzy Logic, Impulsive Buying}, doi={10.4108/eai.13-7-2018.165669} }- Areeba Rahman
Nageen Saleem
Aysha Shabbir
Maryam Shabbir
Muhammad Rizwan
Shahid Naseem
Fahad Ahmad
Year: 2020
ANFIS based hybrid approach identifying correlation between decision making and online social networks
SIS
EAI
DOI: 10.4108/eai.13-7-2018.165669
Abstract
The fast-growing use of online social networks (OSNs) has prompted stakeholders to change their market strategies and hence have raised several questions on the users' decision making (DM). OSNs, as being regularly used, have resulted in playing a significant role in supporting consumer’s rational DM. We use a hybrid approach i.e. an online survey and fuzzy model development to indicate how OSNs have resulted in giving an impact on the decision making. The research depicts that OSNs support and empower users in the DM process specifically in Rationality, Design, & Choice and the model predicts the DM strategy of each user according to their present decisions using fuzzy logic. Our results also reveal that different types of users (observers, seekers, and advisers) have significantly different participation styles, which in turn have an impact on the efficacy of the DM process. We discussed the implications for OSN designers and developers based on the findings from the research.
Copyright © 2020 Areeba Rahman et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
