Sponsored Results in Intelligent Recommenders: Impact on Quality Signaling and Consumer Welfare
نویسندگان
چکیده
Search engines, referrals services, advisors, and other forms of information gatekeepers and recommenders, are omnipresent in today’s information-heavy economy. These services widely employ sponsored recommendations, wherein merchants pay the recommender in return for favorable placement in the recommender’s list. As a form of advertising, sponsored results can serve as a signaling mechanism when consumers are uncertain about merchant quality levels. Notably, such advertising occurs over an intelligent recommender which, with some level of precision, can make its own recommendations on merchant quality. We develop and analyze an economic model of sponsored search that illuminates several aspects of this practice. First, we explain how the recommender’s intelligence impacts the merchants’ allocation of signaling effort between price and advertising. Compared with advertising in traditional media, intelligent recommenders reduce merchants’ need for advertising signals and make it more possible to signal via the cheaper instrument, price. Second, however, an increase in a recommender’s precision may neither increase its sponsorship revenues nor make consumers better off: the crucial determinant of this effect is the recommender’s pricing power in the advertising market. Under low pricing power, improvement in precision decreases the advertising expenditure, causing higher prices and lower consumer surplus. Conversely, with substantial pricing power, higher precision yields a higher advertising fee, lower product prices, and increased consumer surplus. Third, the adoption of sponsored results by the recommender may not always improve consumer surplus. Chasing advertising revenues, recommenders may overuse sponsored results when doing so reduces consumer surplus—the better the recommender, the more likely that adoption of sponsored results harms consumers—creating an interesting challenge for regulatory constraints on this practice.
منابع مشابه
When do Recommender Systems Work the Best?: The Moderating Effects of Product Attributes and Consumer Reviews on Recommender Performance
We investigate the moderating effect of product attributes and consumer reviews on the efficacy of a collaborative filtering recommender system on an e-commerce site. We run a randomized field experiment on a top North American retailer’s website with 184,375 users split into a recommender-treated group and a control group with 37,215 unique products in the dataset. By augmenting the dataset wi...
متن کاملThe impact of rice imports on domestic consumer welfare using the inverse demand system
Rice is the second strategic product after wheat and one of the most widely consumed food products in the country. Population growth, consumption and growing demand, price fluctuations and welfare effects due to changes in the amount and price of rice require the attention and planning and foresight of policymakers and the countrychr('39')s planning system. In this study, in the framework of in...
متن کاملOnline Sponsored Search Advertising as a Quality Signal and its Impact on Consumer Bahvior
The advent of sponsored search advertising raises many interesting questions regarding consumer's behavior, seller's advertising strategy, and the ensuing market dynamics. Online markets are characterized by significant information asymmetries and consumers rely on a number of informational cues or signals to infer the seller's quality. Of the various quality signals, advertising and price have...
متن کاملA Dynamic Model of Sponsored Search Advertising
A Dynamic Model of Sponsored Search Advertising Sponsored search advertising is ascendant Jupiter Research reports expenditures rose 28% in 2007 to $8.9B and will continue to rise at a 26% CAGR, approaching 1/2 the level of television advertising and making it one of the major advertising trends to a¤ect the marketing landscape. Yet little empirical research exists to explore how the interacti...
متن کاملDeveloping Constraint-based Recommenders
Recommender systems provide valuable support for users who are searching for products and services in e-commerce environments. Research in the field long focused on algorithms supporting the recommendation of quality & taste products such as news, books, or movies. Nowadays, the scope of those systems is extended to complex product domains such as financial services or electronic consumer goods...
متن کامل