Author List: Weber, Thomas A.; Zheng, Zhiqiang (Eric);
Information Systems Research, 2007, Volume 18, Issue 4, Page 414-436.
In this paper we pursue three main objectives: (1) to develop a model of an intermediated search market in which matching between consumers and firms takes place primarily via paid referrals; (2) to address the question of designing a suitable mechanism for selling referrals to firms; and (3) to characterize and analyze the firms' bidding strategies given consumers' equilibrium search behavior. To achieve these objectives we develop a two-stage model of search intermediaries in a vertically differentiated product market. In the first stage an intermediary chooses a search engine design that specifies to which extent a firm's search rank is determined by its bid and to which extent it is determined by the product offering's performance. In the second stage, based on the search engine design, competing firms place their open bids to be paid for each referral by the search engine. We find that the revenue-maximizing search engine design bases rankings on a weighted average of product performance and bid amount. Nonzero pure-strategy equilibria of the underlying discontinuous bidding game generally exist but are not robust with respect to noisy clicks in the system. We determine a unique nondegenerate mixed-strategy Nash equilibrium that is robust to noisy clicks, In this equilibrium firms of low product performance fully dissipate their rents, which are appropriated by the search intermediary and the firm with the better product. The firms' expected bid amounts are generally nonmonotonic in product performance and depend on the search engine design parameter. The intermediary's profit-maximizing design choice, by attributing a positive weight to the firms' bids, tends to obfuscate search results and reduce overall consumer surplus compared to the socially optimal design of fully transparent results ranked purely on product performance.
Keywords: markets and auctions; paid referrals; search intermediary
Algorithm:

List of Topics

#5 0.180 consumer consumers model optimal welfare price market pricing equilibrium surplus different higher results strategy quality cost lower competition firm paper
#217 0.148 search information display engine results engines displays retrieval effectiveness relevant process ranking depth searching economics create functions incorporate low terms
#91 0.095 auctions auction bidding bidders bid combinatorial bids online bidder strategies sequential prices design price using outcomes behavior theoretical computational efficiency
#190 0.093 new licensing license open comparison type affiliation perpetual prior address peer question greater compared explore competing crowdsourcing provide choice place
#168 0.073 firms firm financial services firm's size examine new based result level including results industry important account does suggests characterize limited
#62 0.072 price buyers sellers pricing market prices seller offer goods profits buyer two-sided preferences purchase intermediary traditional marketplace decisions intermediaries selling
#89 0.066 product products quality used characteristics examines role provide goods customization provides offer core sell key potential stronger insights design initial
#64 0.057 advertising search online sponsored keywords sales revenue advertisers ads keyword organic advertisements selection click targeting indirect listing promotional match generates
#107 0.056 app brand mobile apps paid utility facebook use consumption users brands effects activities categories patterns controls extension store positive factor
#270 0.056 design designs science principles research designers supporting forms provide designing improving address case little space criteria methods increasing synthesis designer
#114 0.055 performance firm measures metrics value relationship firms results objective relationships firm's organizational traffic measure market study improve accounting measuring aggregate