ERP evidence for consumer evaluation of copycat brands

Abstract

Copycat brands mimic brand leaders to free ride on the latter's equity. However, little is known regarding if and how consumers confuse copycat as leading brand in purchasing. In this study, we applied a word-pair evaluation paradigm in which the first word was a brand name (copycat vs. normal brand both similar with a leading brand in category), followed by a product name (near vs. far from the leading brand’s category). Behavioral results showed that, when the product is near the leader’s category, the copycat strategy (CN) was more preferred compared to the normal brand (NN) but not different in the far product condition (CF and NF). Event-related potential (ERP) data provided further insight into the mechanism. The N400 amplitude elicited by the CN condition was significantly smaller than NN. However, when products are far from the leader’s category, there was no significant difference in N400 amplitudes. For the late positive component (LPC), the CN gave rise to a larger amplitude than the CF. The N400 amplitude was suggested to reflect the categorization process, and the LPC demonstrated the recollection process in long-term memory. These findings imply that the copycat brand strategy is generally only effective when products are within the category of the leading brand, which offers important implications for marketing practices.

The effects of review’s mobile phone price on consumers’ purchase intention: An event-related potential study.

“…Based on the grand average waveforms (Figure 3, panel A), the scalp topography (Figure 3 panel B), as well as previous research on decision-making (Chen et al, 2010b; Gunter et al, 1994; Wang et al, 2016), two ERP components, N400, and LPP, were analyzed in this study. Six electrodes (F3, FZ, F4, FC3, FCZ, and FC4) distributed from the frontal to frontal-central regions were selected for N400 analysis (Gunter et al, 1994; Wang et al, 2016), and nine electrodes (C3, CZ, C4, CP3, CPZ, CP4, P3, PZ, and P4) distributed from the central to parietal regions were selected for LPP analysis (Fu et al, 2019; Shang et al, 2018). The mean amplitude of N400 in the time window of 380–480 ms was submitted to a 2 (review’s mobile phone price: high price and low price) × 6 (electrodes: F3, FZ, F4, FC3, FCZ, and FC4) repeated-measure ANOVA.…”

“…The N400 is a negative deflection that typically peaks around 400 ms poststimulus presentation (Chen et al, 2010a; Gunter et al, 1994). N400 is usually distributed from the frontal to the parietal scalp regions and its amplitude was larger in the frontal and frontal-central area (Barber et al, 2013; Shang et al, 2018; Wang et al, 2012). Previous research has revealed that the amplitude of N400 is closely associated with semantic and nonsemantic conflictions (Gunter et al, 1994; Steffensen et al, 2008).…”

A systematic review of the prediction of consumer preference using EEG measures and machine-learning in neuromarketing research

“…These components are most commonly used in neuromarketing research to measure consumer familiarity with brands and products and the conflict between price and expected value. In the reviewed literature, fourteen studies using brand-extension paradigms reported modulations in N200/N400 amplitude [ 42 , 76 , 80 , 125 , 175 , 177 , 179 , 180 , 246 , 248 , 286 , 295 , 299 , 312 ], nine studies reporting N200/N400 modulations used conflict tasks such as oddball tasks [ 79 , 81 , 97 , 100 , 107 , 126 , 129 , 205 , 259 , 311 ], and nine used other tasks, such as auction tasks or advertising stimuli [ 91 , 92 , 105 , 106 , 124 , 128 , 137 , 279 , 279 , 282 , 282 , 284 , 284 , 285 , 285 , 310 ].…”

“…Twelve out of the 15 studies which investigated brand extension in the reviewed literature found significant effects in N200 or N400 amplitude [ 76 , 80 , 125 , 177 , 179 , 180 , 246 , 248 , 286 , 297 , 299 , 312 ], while one used machine-learning and therefore did not investigate modulations in ERP amplitude directly [ 178 ]. Within the 11 studies that reported significant N200/N400 effects, nine reported significant effects of N400 amplitude [ 42 , 80 , 125 , 177 , 180 , 246 , 286 , 295 , 299 ], two reported significant N200 effects [ 76 , 179 ], while only two studies found significant effects in both N400 and N200 amplitude [ 80 , 299 ]. Further, two studies reported non-significant N2 amplitude modulations [ 297 , 299 ].…”

“Sound” Decisions: The Combined Role of Ambient Noise and Cognitive Regulation on the Neurophysiology of Food Cravings

“…One approach to assess this is through EEG. In addition to the measurement of electrophysiological activity response to a specific single time-locked stimulus or event as in ERP research ( Shang et al, 2018 ), longer-lasting and continuous functional indices of neural activity are also possible via EEG ( Fernandez Rojas et al, 2020 ; Firestone et al, 2020 ; Diao et al, 2021 ). Here, the EEG signal can be decomposed into various frequency spectra representing the oscillatory dynamics in the brain and correlated with certain mental processes ( Barlaam et al, 2011 ; Diao et al, 2017 ; Aoh et al, 2019 ).…”