Forecasting Unplanned Purchase Behavior under Buy-One Get-One-Free Promotions Using Functional Near-Infrared...

Area of Science:

• Neuroscience
• Consumer Psychology
• Biomedical Engineering

Background:

• Unplanned purchase behavior (UPB) is a significant consumer issue, but traditional measurement methods are limited by human perception and memory.
• Accurate identification of UPB is crucial for understanding consumer decision-making and developing targeted interventions.

Purpose of the Study:

• To propose and validate a novel methodology for identifying UPB using brain-computer interface (BCI) techniques.
• To investigate the neural correlates of UPB, particularly in response to promotional offers like Buy-One-Get-One-Free (BOGOF).

Main Methods:

• Employed functional near-infrared spectroscopy (fNIRS) to record hemodynamic signals and support vector machine (SVM) for classification.
• Collected data from 33 subjects under two conditions: one with BOGOF offers and one without.
• Utilized 6 time-domain features and 10-cross validation for analysis, with AUC evaluating reliability.

Main Results:

• Achieved an average accuracy greater than 94% in UPB detection, with AUC values above 0.97, indicating high reliability.
• Identified distinct brain activity patterns in the prefrontal cortex associated with UPB, especially under the BOGOF condition.
• Confirmed that self-reported impulsivity correlated with UPB detection, suggesting subjects perceived heightened impulsivity during BOGOF promotions.

Conclusions:

• The proposed BCI-based methodology offers a reliable and objective approach for detecting and understanding UPB.
• Findings highlight the influence of promotional strategies like BOGOF on consumer impulsivity and purchasing behavior.
• This research paves the way for computer-aided detection systems to assess the severity of UPB.