
Abstract The recent growth of consumer-generated media (CGM), also known as “new” media, has changed the interaction between consumers and firms from being unidirectional to being bidirectional. However, CGM are almost always accompanied by traditional media (such as TV advertising). This research addresses the critical question of whether new and traditional media reinforce or damage one another's effectiveness. This question is important because traditional media, in which a manufacturer creates and delivers content to consumers, consume a firm's resources. In contrast to these paid media, new media (in which consumers create content and this content is exchanged between other consumers and potentially between manufacturers) are primarily available for free. This question becomes even more salient when new product launches are involved, as firms typically allocate approximately half of their marketing budgets to support new products. One of the most prevalent forms of new media is blogging. Therefore, we assemble a unique data set from Japan that contains market outcomes (sales) for new products, new media (blogs) and traditional media (TV advertising) in the movie category. We specify a simultaneous equation log-linear system for market outcomes and the volume of blogs. Our results suggest that new and traditional media act synergistically, that pre-launch TV advertising spurs blogging activity but becomes less effective during the post-launch period and that market outcomes have an effect on blogging quantity. We find detailed support for some of these results via a unique and novel text-mining analysis and replicate our findings for a second product category, cellular phone service. We also discuss the managerial implications of our findings.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 147 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
