Author List: Chen, Hailiang; De, Prabuddha; Hu, Yu (Jeffrey);
Information Systems Research, 2015, Volume 26, Issue 3, Page 513-531.
With the emergence of social media and Web 2.0, broadcasting in the online environment has evolved into a new form of marketing due to the much broader reach enabled by information technology. This paper quantifies the effect of artists' broadcasting activities on a well-known social media site for music, MySpace, on music sales. We employ a panel vector autoregression model to investigate the interrelationship between broadcasting promotions in social media and music sales, while controlling for influential factors such as advertising in traditional media channels, album prices, new music releases, user-generated content, and artist popularity. We characterize two types of broadcast messages in the MySpace context, personal and automated . We find that broadcasting in social media has a significant effect on sales even after controlling for the aforementioned factors, and more important, the effect mainly comes from personal messages rather than automated messages. We also show that the timing and content of personal messages play a role in affecting sales. Our findings point to the importance of conducting captivating conversations with customers in social media marketing.
Keywords: broadcasting ; social media marketing ; music sales ; panel vector autoregression
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#131 0.378 media social content user-generated ugc blogs study online traditional popularity suggest different discourse news making anonymity marketing videos choices page
#136 0.253 expectations expectation music disconfirmation sales analysis vector experiences modeling response polynomial surface discuss panel new nonlinear period understand paper dissonance
#173 0.082 effect impact affect results positive effects direct findings influence important positively model data suggest test factors negative affects significant relationship
#37 0.057 intelligence business discovery framework text knowledge new existing visualization based analyzing mining genetic algorithms related techniques large proposed novel artificial