Personalized vs non-personalized recommendations: how recommender systems, recommendation sources and recommendation platforms affect trial of YouTube videos among digital natives in Saudi Arabia

Purpose This study aims to examine the difference between personalized and non-personalized recommendations in influencing YouTube users’ video choices. In addition, whether men and women have a significant difference in using recommendations was compared and the predictors of recommendation video use frequency were explored. Design/methodology/approach A survey of 524 Saudi Arabia college students was conducted using computer-assisted self-administered interviews to collect their video recommendation sources and how likely they follow the recommendation from different sources. Findings Video links posted on social media used by the digital natives were found as the most effective form of recommendation shows that social approval is important in influencing trials. Recommendations can succeed in both personalized and non-personalized ways. Personalized recommendations as in YouTube recommended videos are almost the same as friends and family’s non-personalized posting of video links on social media in convincing people to watch the videos. Contrary to expectations, Saudi men college students are more likely to use recommendations than women students. Research limitations/implications The use of a non-probability sample is a major limitation and self-reported frequency may result in over- or under-estimation of video use. Practical implications Marketers will realize that they may not need the personalized recommendation from the large site. They can use social media recommendations by the consumers’ friends and family. E-mail is the worst platform for a recommendation. Social implications Recommendation is a credible source and can overcome the avoidance of advertising. Its influence on consumers will be increasing in years to come with the algorithmic recommendation and social media use. Originality/value This is the first study to compare the influence of different online recommendation sources and compare personalized and non-personalized recommendations. As recommendation is growing more and more important with algorithm development online, the study results have high reference values to marketers in Islamic countries and beyond.