The Effects of Money on Fake Rating Behavior in E-Commerce: Electrophysiological Time Course Evidence From Consumers

Abstract

Online ratings impose significant effects on the behaviors of potential customers. Thus, online merchants try to adopt strategies that affect this rating behavior, and most of these strategies are connected to money, such as the strategies of returning cash coupons if a consumer gives a five-star rating (RI strategy, an acronym for “returning” and “if”) or returning cash coupons directly with no additional requirements (RN strategy, an acronym for “returning” and “no”). The current study explored whether a certain strategy (RN or RI) was more likely to give rise to false rating behaviors, as assessed by event-related potentials. A two-stimulus paradigm was used in this experiment. The first stimulus (S1) was the picture of a product with four Chinese characters that reflected the product quality (slightly defective vs. seriously defective vs. not defective), and the second stimulus (S2) displayed the coupon strategy (RN or RI). The participants were asked to decide whether or not to give a five-star rating. The behavioral results showed that the RI strategy led to a higher rate of five-star ratings than the RN strategy. For the electrophysiological time courses, the N1, N2, and LPP components were evaluated. The slightly defective products elicited a larger amplitude of the N1 component than the seriously defective and not-defective products, reflecting that perceptual difficulty was associated with the processing of the slightly defective products. The RI strategy evoked a less negative N2 and a more positive LPP than the RN strategy, indicating that the subjects perceived less conflict and experienced stronger incentives when processing the RI strategy. These findings will benefit future studies of fake online comments and provide evidence supporting the policy of forbidding the use of the RI strategy in e-commerce.

Differential Effects of Monetary and Social Rewards on Product Online Rating Decisions in E-Commerce in China

“…First, previous research found that consumer preferences affected their rating choice and social interactions had an effect on the review generation process (Lee et al, 2015), providing empirical evidence enhancing our understanding of how social imitation and learning affect consumer rating generation. Second, recent studies found evidence of fake reviews in many contexts (Lappas et al, 2016;Wang et al, 2018). For example, in the context of hotel reviews, manipulating online reviews had a significant effect on changing product visibility (Lappas et al, 2016).…”

“…Social rewards (e.g., smiles and greeting cards) are important mediums that could have an effect on the product rating generation process. In addition, monetary rewards during the feedback stage can lead to false-positive rating behaviors (Wang et al, 2018). We speculated that monetary rewards during the priming stage might affect the product rating generation.…”

Symbolic Product Superiority in the Neural Salience of Compensatory Consumption Behavior

“…Concerning LPP in the late processing stage, the current study demonstrated both a significant main effect of game result and interaction between variables. An enhanced LPP within a time window of interest indicates a sustained involvement of cognitive resources and high emotional arousal on motivationally salient stimuli (Ma et al, 2018;Wang et al, 2018). Thus, the data from the present study suggested that defeat status (vs. draw) slowed the diminishment of involved attentional resources for displayed products; meanwhile, emotion arousal would be intense, implying a willingness to make purchase decisions on those products.…”

“…The ERP results provided more concise interpretations of information processing in compensatory consumption. At the preliminary stage, N1 showed similar patterns for all product images, suggesting a stable perceptual difficulty in perceptual behavior control (Wang et al, 2018). In other words, regardless of competition outcome and product category, this factor was homogeneous for those products in the participants' evaluation of purchasing disadvantage, including perceptual emergency and purchase conveniences.…”

“…As a critical component during early perceptual processing, N1 peaked approximately 130-150 ms after stimulus onset, reflecting the individual's perceptual difficulty with the stimuli (Wang et al, 2018). The following P2, with a peak latency at 100-200 ms after stimulus onset, is sensitive to attentional resource allocation (e.g., Carretié et al, 2001;Huang and Luo, 2006;Jin et al, 2017).…”