Elaboration likelihood model perspective on millenial live streaming buyers' impulsive buying tendency - Luo, Xi (2023)
Accelerated by the COVID-19 pandemic, an increasing number of retailers are shifting away from physical stores to digital shopping. In e-commerce, product presentation has shifted from basic textual or graphical descriptions to the adoption of live streaming (i.e., real-time video). Due to the experiential, engaging, and persuasive nature of live streaming shopping, increasing e-retailers adopted live-streaming as a competitive advantage to boost sales. Nielson’s survey shows that 82% of customers have unplanned purchase experiences in broadcasting rooms with 61% of customers being persuaded by streamers’ recommendations. However, streamers' performances are varied; not all streamers are able to deliver persuasive content and increase sales through live streaming, which exposes important live streaming challenges. Existing literature mainly focused on the customer or platform’s perspective to identify the drivers of impulsive buying tendency, which is not enough to understand customers’ impulsive purchase intention in a persuasive communication context. To address this issue, this research aims to bridge the gap in the existing literature by investigating the various information cues in the environment that influence Chinese Millennial shoppers’ impulsive purchase in live streaming shopping. Firstly, underpinned by the Elaboration Likelihood Model (ELM), the central route is related to customers’ cognitive processing of information conveyed by streamers, while the peripheral route is related to customers’ emotional processing of cues signalled by co- viewers. Thus, streamers’ information quality, interaction quality and credibility were adopted as central route factors, while review consistency and resonant contagion were chosen as peripheral route factors that facilitate customers’ impulsive purchase decisions. Secondly, the Stimulus-Organism-Response (S-O-R) model was applied to explain the mediating role of customer engagement. Lastly, the acquisition-transaction utility theory (ATUT) was used to explain the moderating effect of deal proneness on the relationship between central route elements and customer engagement; the social exchange theory (SET) was used to explain the moderating effect of guanxi orientation on the relationship between peripheral route elements and customer engagement; the social response theory (SRT) was used to explain the moderating effect of frugality on the relationship between customer engagement and impulsive buying tendency. In terms of data collection, an online questionnaire was designed using Wenjuanxing and was distributed to target respondents from June to August 2022. Purposive and quota sampling were used to select the respondents where they must be Millennials (born between 1981 and 2000), have live streaming shopping experience within the last two months, and live in Beijing, Shanghai, or Guangzhou. Finally, a total of 735 valid responses were collected using Structural Equation Modelling Partial Least Squares (SEM-PLS) for data analysis. The findings showed that customers’ processing of three central information (i.e., information quality, interaction quality and streamer credibility) and one peripheral cue (i.e., review consistency) significantly influenced Millennials’ engagement and impulsive buying tendency. Second, customer engagement was identified as a key mediator between ELM elements and impulsive buying tendency. Thirdly, deal-prone customers tended to put more emphasis on central information processing while guanxi- oriented customers were more likely to focus on peripheral route information processing. Moreover, Millennial customers with high frugality were less likely to make unplanned purchases. In essence, this study provides e-retailers with useful insights on the way to strengthen customer dual-route information processing in facilitating their impulsive purchase decisions. Despite these interesting findings, this study also has several limitations, for example, this study only focused on China and did not differentiate streamer types. Thus, future studies may conduct cross-country research and explore the impacts of different types of streamers in triggering customers’ impulsive purchase decisions.