In recent years, Google has entered into a growing set of markets that are adjacent to its general search engine, launching new products such as Google Flights, Google Shopping, and Google Local. To leverage its dominance in general search, Google has often tied these products to its general search page, excluding competitor content. In this paper, we explore the strategic tradeoffs platforms face when pursuing a tying strategy to enter complementary markets, empirically investigating Google's decision to tie Google Local (its reviews product) to its search engine. We experimentally vary the content displayed on top of organic search results (called the "Onebox"), to show either exclusively Google reviews (the status quo), or reviews from multiple platforms that are determined to be the best-performing by Google's own organic search algorithm. We find that users prefer the OneBox and are more likely to engage with it when it includes competitor content. This suggests that Google's strategy of excluding competitor content leaves customers with a lower quality product. However, the number of reviews contained in Google Local has increased rapidly in recent years, suggesting that there may be a benefit of excluding competitors as well. Overall, these results shed light on a strategic tradeoff for companies that enter a complementary market using a tying strategy: while companies have successfully used this strategy, it can also come at a cost to consumers in the form of a lower-quality product.

This paper offers an approach for governments to harness the information contained in social media in order to make public inspections and disclosure more efficient.As a case study, we turn to restaurant hygiene inspections -which are done for restaurants throughout the United States and in most of the world and are a frequently cited example of public inspections and disclosure.We present the first empirical study that shows the viability of statistical models that learn the mapping between textual signals in restaurant reviews and the hygiene inspection records from the Department of Public Health.The learned model achieves over 82% accuracy in discriminating severe offenders from places with no violation, and provides insights into salient cues in reviews that are indicative of the restaurant's sanitary conditions.Our study suggests that public disclosure policy can be improved by mining public opinions from social media to target inspections and to provide alternative forms of disclosure to customers.