当前,电子商务与社交媒体的深度融合促成社交化电子商务成为新生热门发展趋势,在此背景下,以当前国内主流社交媒体新浪微博为载体,基于层次分析法–熵值法综合评价模型研究电商平台微博口碑有助于促进产品销售,提升平台的服务质量。文...当前,电子商务与社交媒体的深度融合促成社交化电子商务成为新生热门发展趋势,在此背景下,以当前国内主流社交媒体新浪微博为载体,基于层次分析法–熵值法综合评价模型研究电商平台微博口碑有助于促进产品销售,提升平台的服务质量。文章依据内容传播力、用户认可度、用户互动度3大一级指标分析9个电商平台的微博口碑,研究结果表明,内容传播力权重最大、用户互动度次之、用户认可度权重相对较低,并据此为优化电商平台微博口碑提供思路,促进电子商务的进一步发展。At present, the deep integration of e-commerce and social media has promoted social e-commerce to become a new and popular development trend. In this context, taking the current domestic mainstream social media Sina Weibo as the carrier, based on the analytic hierarchy process-entropy method comprehensive evaluation model, the e-commerce platform Weibo word-of-mouth is helpful in promoting product sales and improving the service quality of the platform. Based on the three first-level indicators of content dissemination, user recognition and user interaction, this paper analyzes the microblog word-of-mouth of nine e-commerce platforms. The research results show that the weight of content dissemination is the largest, followed by user interaction, and the weight of user recognition is relatively low. Based on this, it provides ideas for optimizing the microblog word-of-mouth of e-commerce platforms and promotes the further development of e-commerce.展开更多
文摘当前,电子商务与社交媒体的深度融合促成社交化电子商务成为新生热门发展趋势,在此背景下,以当前国内主流社交媒体新浪微博为载体,基于层次分析法–熵值法综合评价模型研究电商平台微博口碑有助于促进产品销售,提升平台的服务质量。文章依据内容传播力、用户认可度、用户互动度3大一级指标分析9个电商平台的微博口碑,研究结果表明,内容传播力权重最大、用户互动度次之、用户认可度权重相对较低,并据此为优化电商平台微博口碑提供思路,促进电子商务的进一步发展。At present, the deep integration of e-commerce and social media has promoted social e-commerce to become a new and popular development trend. In this context, taking the current domestic mainstream social media Sina Weibo as the carrier, based on the analytic hierarchy process-entropy method comprehensive evaluation model, the e-commerce platform Weibo word-of-mouth is helpful in promoting product sales and improving the service quality of the platform. Based on the three first-level indicators of content dissemination, user recognition and user interaction, this paper analyzes the microblog word-of-mouth of nine e-commerce platforms. The research results show that the weight of content dissemination is the largest, followed by user interaction, and the weight of user recognition is relatively low. Based on this, it provides ideas for optimizing the microblog word-of-mouth of e-commerce platforms and promotes the further development of e-commerce.
