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.
Top online reviewers who reliably gain consumers' attention stand to make significant financial gains and monetize the amount of attention and reputation they have earned. This study explores how online reviewers strategically choose the right product to review and the right rating to post so that they can gain attention and enhance reputation. Using book reviews from Amazon and Barnes & Noble (BN), we find that reviewers on Amazon, where a reviewer ranking system quantifies reviewers' online reputations, are sensitive to the competition among existing reviews and thus tend to avoid crowded review segments. However, on BN, which does not include such a ranking mechanism, reviewers do not respond to the competition effect. In addition, reviewers on Amazon post more differentiated ratings compared with reviewers on BN since the competition for attention on Amazon is more intense than on BN. Overall, reviewers on Amazon behave more strategically than reviewers on BN. This study yields important managerial implications for companies to improve their design of online review systems and enhance their understanding of reviewers' strategic behaviors.
Internet retailers have been making significant investments in Web technologies, such as zoom, alternative photos, and color swatch, that are capable of providing detailed product-oriented information and, thereby, mitigating the lack of “touch and feel,” which, in turn, is expected to lower product returns. However, a clear understanding of the relationship between these technologies and product returns is still lacking. Our study attempts to fill this gap by using several econometric models to explore the said relationship. Our unique and rich data set from a women's clothing company allows us to measure technology usage at the product level for each consumer. The results show that, in this context, zoom usage has a negative coefficient, suggesting that a higher use of the zoom technology is associated with fewer returns. Interestingly, we find that a higher use of alternative photos is associated with more returns and, perhaps more importantly, with lower net sales. Color swatch, on the other hand, does not seem to have any effect on returns. Thus, our findings show that different technologies have different effects on product returns. We provide explanations for these findings based on the extant literature. We also conduct a number of tests to ensure the robustness of the results.
The Internet and related information technologies are transforming the distribution of product sales across products, and these effects are likely to grow in coming years. Both the Long Tail and the Superstar effect are manifestations of these changes, yet researchers lack consistent metrics or models for integrating and extending their insights and predictions. In this paper, we begin with a taxonomy of the technological and nontechnological drivers of both Long Tails and Superstars and then define and compare the key metrics for analyzing these phenomena. The core of the paper describes a large and promising set of questions forming a research agenda. Important opportunities exist for understanding future changes in sales concentration patterns; the impact on supply chains (including cross-channel competition, competition within the Internet channel, implications for the growth of firms, and the balance of power within the supply chain); implications for pricing, promotion, and product design; and, ultimately, the potential effects on society in general. Our approach provides an introduction to some of the relevant research findings and allows us to identify opportunities for cross-pollination of methods and insights from related research topics.
Trust is particularly important in online markets to facilitate the transfer of sensitive consumer information to online retailers. In electronic markets, various proposals have been made to facilitate these information transfers. We develop analytic models of hidden information to analyze the effectiveness of these regimes to build trust and their efficiency in terms of social welfare. We find that firms' ability to influence consumer beliefs about trust depends on whether firms can send unambiguous signals to consumers regarding their intention of protecting privacy. Ambiguous signals can lead to a breakdown of consumer trust, while the clarity and credibility of the signal under industry self-regulation can lead to enhanced trust and improved social welfare. Our results also indicate that although overarching government regulations can enhance consumer trust, regulation may not be socially optimal in all environments because of lower profit margins for firms and higher prices for consumers.