International Journal of Computational Intelligence Systems

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Volume 10, Issue 1, 2017, Pages 690 - 710

Analysis of Brand Image Effect on Advertising Awareness Using A Neuro-Fuzzy and A Neural Network Prediction Models

Authors
Ali Fahmi1, fahmi@itu.edu.tr, Kemal Burc Ulengin1, ulenginbur@itu.edu.tr, Cengiz Kahraman2, *, kahramanc@itu.edu.tr
1Management Engineering Department, Istanbul Technical University, Macka 34367, Istanbul, Turkey
2Industrial Engineering Department, Istanbul Technical University, Macka 34367, Istanbul Technical University
* Corresponding author.
Corresponding Author
Cengiz Kahramankahramanc@itu.edu.tr
Received 21 September 2016, Accepted 25 January 2017, Available Online 9 February 2017.
DOI
10.2991/ijcis.2017.10.1.46How to use a DOI?
Keywords
Top of mind (TOM); share of voice (SOV); spontaneous awareness (SA); adaptive neuro-fuzzy inference system (ANFIS); artificial neural network (ANN)
Abstract

Almost all the worldwide and nationwide companies utilize advertising to increase their sales volume and profit. These companies pay millions of dollars to reach consumers and announce their products or services. This forces companies to evaluate advertising effects and check whether ads meet companys strategies. They need to evaluate the ads not only after announcement, but also before advertising, i.e. they can be one step ahead by predicting the future advertising awareness through artificial intelligence tools such as fuzzy systems and neural networks. In this study, we propose to use adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) to analyze advertising decision making. ANFIS creates fuzzy rules and trains the neural network using given input data. This training ability of ANFIS and ANN leads to predicting the advertising awareness outputs. Here, we investigate three advertising awareness outputs, namely, top of mind, share of voice, and spontaneous awareness. In order to achieve the valid predictions, data are randomly divided into training data with 70 percent, validation data with 15 percent, and testing data with remained 15 percent of data. The correlation between actual data and predictions are calculated to check the accuracy of the predicted outputs.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
10 - 1
Pages
690 - 710
Publication Date
2017/02/09
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.2017.10.1.46How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

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TY  - JOUR
AU  - Ali Fahmi
AU  - Kemal Burc Ulengin
AU  - Cengiz Kahraman
PY  - 2017
DA  - 2017/02/09
TI  - Analysis of Brand Image Effect on Advertising Awareness Using A Neuro-Fuzzy and A Neural Network Prediction Models
JO  - International Journal of Computational Intelligence Systems
SP  - 690
EP  - 710
VL  - 10
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2017.10.1.46
DO  - 10.2991/ijcis.2017.10.1.46
ID  - Fahmi2017
ER  -