The Impact of E-commerce Live Streaming Servicescape on Consumers' Impulsive Purchase Intention
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Abstract
This article aimed 1) to study the impact of e-commerce live streaming servicescape and flow experience effect on consumers' impulse purchase intention, 2) to establish a model of the impact of e-commerce live streaming servicescape on consumers' impulsive purchase intention, and 3) to put forward more targeted and effective e-commerce live streaming marketing suggestions for e-commerce enterprises, consumers and live-streamers. This paper adopts the research methods of quantitative research and qualitative research. In quantitative research, the sample was 402 users with live e-commerce viewing experience or shopping experience. They were selected by a simple method. In qualitative research, the main interviewees are:
2 college students, 2 precious mothers, 2 employees of e-commerce live streaming companies, 2 department directors of e-commerce live streaming companies, and 2 ordinary employees in other industries. The instruments for collecting data were 2 types: questionnaires for quantitative research and in-depth interviews for Qualitative research. Analysis of data by Descriptive statistics and Content Analysis. The research results were found as follows;
1. Social clues include live-streamer credibility, live-streamer interaction, and live-streamer professionalism. It will have a positive and significant effect on consumers' impulsive purchase intention. Physical clues, including atmosphere clues and design clues, will positively affect consumers' impulsive purchase intention.
2. Based on the S-O-R model, the social cues of the servicescape and physical cues of the servicescape are taken as independent variables and flow experience is introduced as the intermediary variable. The model with consumers' impulsive purchase intention as the dependent variable is constructed and tested.
3. As for marketing countermeasures to enhance consumers' impulsive purchase intention in the context of e-commerce live broadcasting, targeted countermeasures, and suggestions are proposed based on e-commerce live broadcasting platforms, e-commerce live broadcasting enterprises, e-commerce live broadcasting live-streamers and consumers who watch e-commerce live broadcasting.
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