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The impact of information factors on online recommendation adoption

With the advent of large data age, the recommendation system began to enter people's lives, according to the user's habits, how to recommend will become the future business development trend. In this paper, we used Elaboration Likelihood Model (ELM) to demonstrate the important adoption factors on the recommendation system such as the recommendation persuasiveness, recommendation source credibility, recommendation completeness and recommendation credibility. Finally, we show that only recommendation information completeness is not significant on readers' perception of recommendation credibility, others are best for it. And recommendation source credibility and recommendation credibility are both effective effect on recommendation adoption.