This paper provides a search-based information acquisition framework using an urn model with an asymptotic approach. The underlying intuition of the model is simple: when the scope of information search is more limited, marginal search efforts produce less useful information due to redundancy,...

This paper builds a consumer search model where the cost of going back to stores already searched is explicitly taken into account. We show that the optimal search rule under costly recall is very different from the optimal search rule under perfect recall. Under costly recall, the optimal...

This paper builds a consumer search model where the cost of going back to stores already searched is explicitly taken into account. We show that the optimal search rule under costly recall is very different from the optimal search rule under perfect recall. Under costly recall, the optimal...

We analyse consumers' search and purchase decisions on an Internet platform. Using a rich dataset on all adverts posted and transactions made on a major French Internet platform (PriceMinister), we show evidence of substantial price dispersion among adverts for the same product. We also show...

This paper studies an information design problem in a sequential consumer search environment. Consumers, whose valuation of firm's products is uncertain, observe a noisy signal about the valuation upon being matched with a firm. The goal is to characterize those signal structures that maximize...

We analyse consumers' search and purchase decisions on an Internet platform. Using a rich dataset on all adverts posted and transactions made on a major French Internet platform (PriceMinister), we show evidence of substantial price dispersion among adverts for the same product. We also show...

We study sequential search without priors. Our interest lies in decision rules that are close to being optimal under each prior and after each history. We call these rules robust. The search literature employs optimal rules based on cutoff strategies, and these rules are not robust. We derive...

We model fairness within the context of search. To do this, consider sequential search where the searcher is uncertain about the underlying pool of candidates. Fairness is introduced by requiring that candidates cannot be discriminated against by non-merit characteristics or by the order in...