Neural Signature of Buying Decisions in Real-World Online Shopping Scenarios – An Exploratory Electroencephalography Study Series

Abstract

The neural underpinnings of decision-making are critical to understanding and predicting human behavior. However, findings from decision neuroscience are limited in their practical applicability due to the gap between experimental decision-making paradigms and real-world choices. The present manuscript investigates the neural markers of buying decisions in a fully natural purchase setting: participants are asked to use their favorite online shopping applications to buy common goods they are currently in need of. Their electroencephalography (EEG) is recorded while they view the product page for each item. EEG responses to pages for products that are eventually bought are compared to those that are discarded. Study 1 repeats this procedure in three batches with different participants, product types, and time periods. In an explorative analysis, two neural markers for buying compared to no-buying decisions are discovered over all three batches: frontal alpha asymmetry peak and frontal theta power peak. Occipital alpha power at alpha asymmetry peaks differs in only one of the three batches. No further significant markers are found. Study 2 compares the natural product search to a design in which subjects are told which product pages to view. In both settings, the frontal alpha asymmetry peak is increased for buying decisions. Frontal theta peak increase is replicated only when subjects search through product pages by themselves. The present study series represents an attempt to find neural markers of real-world decisions in a fully natural environment and explore how those markers can change due to small adjustments for the sake of experimental control. Limitations and practical applicability of the real-world approach to studying decision-making are discussed.

Motivation in the metaverse: A dual-process approach to consumer choices in a virtual reality supermarket

“…This is in line with our assumption and prior findings and suggests that planned behavior is reflected as a theta-alpha activity ratio even in a virtual shopping environment. As opposed to most of the research in the field of consumer neuroscience, which mainly focus on consumers’ “purchase” and “no purchase” ( Rosenlacher et al, 2018 ; Golnar-Nik et al, 2019 ; Goto et al, 2019 ; Eichhorn et al, 2021 ; Melendrez-Ruiz et al, 2021 ; Horr et al, 2022 ) we have extended this view by looking deeper to the relative contribution of cognitive and emotional response and the dual-process of consumer’s decision-making process. Additionally, one of the important contributions of this study is that, compared to highly controlled lab experiments, it adds a higher ecological validity to the research by using an immersive VR supermarket.…”

Human behavior in free search online shopping scenarios can be predicted from EEG activation using Hjorth parameters

“…All others were labeled as no-buy episodes. The rationale behind combining buy and cart episodes was that both are assumed to represent a positive attitude toward the product and the general willingness to buy it (Horr et al, 2022).…”

“…This led to prediction accuracies below 65% in both the 2-class and the 3-class classification for all algorithms. The above frequency bands were chosen, as they were previously shown to be related to purchase choices in the present online shopping scenario (Horr et al, 2022). Of course, adding additional time-frequency features may still result in a better prediction.…”

“…A range of commonly used machine learning algorithms is employed for predicting these labels. The method of EEG is an obvious choice when working with real-life decision-making, as it allows participants to interact naturally with their environment while providing a signal with high temporal resolution that can, via eye-tracking glasses and screen monitoring, be directly linked to participants' momentary visual input (Horr et al, 2022).…”