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Australasian Marketing Journal
Article . 2021 . Peer-reviewed
License: SAGE TDM
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Forecasting Advertisement Effectiveness: Neuroscience and Data Envelopment Analysis

Authors: Nicolas Hamelin; Sameh Al-Shihabi; Sara Quach; Park Thaichon;

Forecasting Advertisement Effectiveness: Neuroscience and Data Envelopment Analysis

Abstract

This research used a novel method in which biometric data and data envelopment analysis (DEA) (a statistical tool generally used for multi-criteria decision making) were used to assess advertising effectiveness. Facial detection and eye-tracking analyses were used to measure participants’ reactions to 14 real estate advertisements. Each of the 14 advertisements had been suggested to a real estate company by a creative advertisement company for a real upcoming advertising campaign in Modern Living for Males and Females. A total of 20 females and males, each of whom wanted to purchase a property, participated in this study. The real estate company was not sure which advertisement to select or which advertisement would be more effective in relation to the male and female target markets. The eye-tracking analysis provided useful information in relation to advertisement design efficiency and cue saliency, which can also affect participants’ emotional responses. DEA was employed to process attention, engagement, and joy provoked by the advertisements. The advertising materials were then benchmarked for each gender using the R studio and R Core Team and a robust DEA for the R (rDEA) package. Furthermore, we used an output-oriented model and variable returns-to-scale to identify the advertisement which maximized the positive emotional responses of each gender, revealing significant differences between males and females in relation to ad effectiveness.

Keywords

330, multi-criteria decision making, Commerce, 650, facial expression analysis, Marketing research methodology, Psychology, data envelopment analysis, tourism and services, advertising, advertisement effectiveness, management, advertisement material

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    popularity
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    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
18
Top 10%
Top 10%
Top 10%
Green