We present a model of competition between web search algorithms, and study the impact of such competition on user welfare. In our model, search providers compete for customers by strategically selecting which search results to display in response to user queries. Customers, in turn, have private preferences over search results and will tend to use search engines that are more likely to display pages satisfying their demands. Our main question is whether competition between search engines increases the overall welfare of the users (i.e., the likelihood that a user finds a page of interest). When search engines derive utility only from customers to whom they show relevant results, we show that they differentiate their results, and every equilibrium of the resulting game achieves at least half of the welfare that could be obtained by a social planner. This bound also applies whenever the likelihood of selecting a given engine is a convex function of the probability that a user's demand will be satisfied, which includes natural Markovian models of user behavior. On the other hand, when search engines derive utility from all customers (independent of search result relevance) and the customer demand functions are not convex, there are instances in which the (unique) equilibrium involves no differentiation between engines and a high degree of randomness in search results. This can degrade social welfare by a factor of Ω( √ N ) relative to the social optimum, where N is the number of webpages. These bad equilibria persist even when search engines can extract only small (but non-zero) expected revenue from dissatisfied users, and much higher revenue from satisfied ones.
Kempe and Lucier REF prove that if search engines extract utility from satisfied users or the search engine selection rule is convex, then the social welfare of the game is at least half of the optimum social welfare.
User Satisfaction in Competitive Sponsored Search
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Mathematics Computer Science