دانلود رایگان مقاله انگلیسی تصمیم گیری خرید آنلاین مشتریان و توصیه کالا بر اساس شبکه رسانه اجتماعی - اشپرینگر 2018

Abstract

With the rapid development of Internet and information technology, e-commerce market has shown a rapid development momentum. Online trading environment of the virtual, making the network trust perception of consumer online shopping decision-making very influential. The social media network application platform is undoubtedly the enterprise used to promote the relationship between consumers and enhance the trust of one of the most convenient channels. Therefore, it is of great significance to explore the factors that influence consumers’ online shopping decisions in the social media network. On the basis of predecessors’ research, this paper explores the influence of consumers’ cognitive ability, relationship intensity and interaction on the decision-making of consumers’ online shopping in the social media network from the perspective of network trust. And through the Sina real micro-blog data on the hypothesis of the regression analysis.

6 Conclusions

In order to explore the impact of social media networks on consumer online shopping decisions to enable e-commerce companies to take what kind of marketing to promote consumer online shopping so as to enhance the effectiveness of e-commerce business. This article picks up the real data of Sina Weibo and finds out that consumers have the cognitive ability in the social media network. The strength and interactivity of Internet have an important influence on people’s network trust and online purchase decision. The research hypothesis is validated through the real microblog data, and the consumer’s cognitive ability is obtained. The interaction between the relationship intensity and the negligence has a positive and positive impact on the consumer online shopping decision-making.

The development of e-commerce, the expansion of information network products, users can not accurately find the goods in line with their preferences, personalized recommendation system to better solve this problem. Although collaborative filtering recommendation technology will help consumers make online purchase decisions, they still have some problems such as low recommendation accuracy, cold start and data sparseness. This article made a deep study, got some research results.