Effects of Interface Design and Live Atmosphere on Consumers’ Impulse-Buying Behaviour from the Perspective of Human–Computer Interaction

Abstract

Since its introduction, live e-commerce has shown rapid growth, especially in regions such as China, where the total market size has exceeded trillions of RMB. However, e-commerce live streaming has also caused widespread consumer impulse-buying behaviour during the development process. Therefore, based on stimulus–organism–response theory, from the perspective of human–computer interaction, this paper develops an impulse-purchase model for live e-commerce consumers, uses partial least squares structural equation modelling to process and analyse 339 valid questionnaires and, finally, validates the proposed hypotheses. The findings show that consumers’ visual appeal, perceived arousal and engagement play a mediating role in the relations among interface design, live atmosphere and impulse purchase. To promote the sustainability of a live-streaming economy, live-streaming platforms need to design attractive live-streaming interfaces, build a pleasant live-streaming atmosphere and enhance consumers’ positive emotions, while preventing their irrational purchasing behaviour. An in-depth analysis of the formation mechanism of this behaviour can help in alleviating the limitations of the lack of rich research results and a single perspective in this field. In addition, it can help stakeholders promote the sustainability of e-commerce live streaming in practice.

Online Impulsive Buying Behavior Using Partial Least Squares Algorithm

“…Additionally, the visual appeal has a favorable influence on OIBB (H3: β = 0.258, T = 4.501), implying that it can prompt consumers' online impulse buying behavior. This outcome is supported by earlier research, such as the studies conducted by Zhao et al [1] and Yang et al [22]. Previous researchers [2,16,21,22], as mentioned earlier, discussed how visual appeal positively influenced perceived enjoyment, perceived usefulness, and OIBB either individually or on two out of three factors.…”

“…This outcome is supported by earlier research, such as the studies conducted by Zhao et al [1] and Yang et al [22]. Previous researchers [2,16,21,22], as mentioned earlier, discussed how visual appeal positively influenced perceived enjoyment, perceived usefulness, and OIBB either individually or on two out of three factors. However, this current study found that visual appeal had a positive impact on all three factors (perceived enjoyment, perceived usefulness, and OIBB).…”

“…Previous studies declared that visual appeal was an antecedent of perceived enjoyment and it will positively impact perceived enjoyment [2,16]. Similarly, former research also demonstrated that visual appeal was a predictor of OIBB and impacted positively on OIBB [1,22]. Based on that, we suggest the hypothesized: H1: There is a positive correlation between visual appeal and perceived enjoyment.…”

Formation mechanism of user stickiness in live e-commerce: the hybrid PLS-SEM and ANN approach

“…Other researchers have studied impulse buying in live e-commerce from perspectives including popularity cues (Lou et al. , 2022), human-computer interaction (Yang et al. , 2022), flow experience and time pressure (Dong et al.…”

“…Some researchers have studied the mechanism underlying the purchase intention of consumers from many perspectives including information technology (IT) affordance (Sun et al, 2019), online celebrity-product, product-livestreaming content matching (Park and Lin, 2020), swift guanxi (Zhang et al, 2020), reducing uncertainty (Lu and Chen, 2021), eye-tracking experiments (Fei et al, 2021), emotional contagion (Meng et al, 2021), emotional intermediary (Zhou and Tong, 2022) and mental imagery quality and customer trust (Wang et al, 2022). Other researchers have studied impulse buying in live e-commerce from perspectives including popularity cues (Lou et al, 2022), human-computer interaction (Yang et al, 2022), flow experience and time pressure (Dong et al, 2023), information transparency (Xu et al, 2022), livestreaming interactions (Liu et al, 2022) and extending the elaboration likelihood model with herd behavior (Yang and Lee, 2023).…”