Heterogeneous Search Costs Research Articles

Optimal Design of Revenue‐Maximizing Position Auctions with Consumer Search

We examine the impact of consumer search from the perspective of revenue‐maximizing optimal auction design. In this two‐sided market, advertisers are endowed with privately known qualities, and consumers incur heterogeneous search costs when clicking on advertisements displayed by the search engine. Our general approach eliminates ad hoc restrictions and therefore allows us to uncover the salient economic trade‐offs. We adopt the optimal mechanism design approach to examine this two‐sided private information problem. The optimal mechanism design approach gives rise to the truly revenue‐maximizing scheme, and yields managerial implications that are substantially different from the literature. We show that from the revenue maximization perspective, the search engine necessarily displays the advertisers in the descending order of their qualities. The search engine shall insert unnecessary hassles to induce the revenue‐maximizing search behaviors. Thus, each consumer stops searching pre‐maturely compared to the socially optimal search behavior. In addition, the search engine shall implement probabilistic forced termination upon consumers’ clicking on advertisements, and this probability is higher for advertisers with poorer qualities. When each advertiser has a two‐dimensional type on consumer learning and matching, even if consumers’ search costs become negligible, the allocative inefficiency does not vanish. Moreover, no strategic obfuscation is imposed. When allowing for non‐independent qualities, we show that product variety does not constitute a rationale for advertisers’ favoritism.

Optimal Design of Revenue-Maximizing Position Auctions With Consumer Search

We examine the impact of consumer search from the perspective of revenue-maximizing optimal auction design. In this two-sided market, advertisers are endowed with privately known qualities, and consumers incur heterogeneous search costs when clicking on advertisements displayed by the search engine. Our general approach eliminates ad hoc restrictions and therefore allows us to uncover the salient economic trade-offs. We adopt the optimal mechanism design approach to examine this two-sided private information problem. We show that from the revenue maximization perspective, the search engine necessarily displays the advertisers in the descending order of their qualities. The search engine shall insert unnecessary hassles to induce the revenue-maximizing search behaviors. Thus, each consumer stops searching pre-maturely compared to the socially optimal search behavior. Moreover, the obfuscation level is higher for consumers with higher search costs. In addition, the search engine shall implement probabilistic forced termination upon consumers' clicking on advertisements, and this probability is higher for advertisers with poorer qualities. When each advertiser has a two-dimensional type on consumer learning and matching, we show that even if consumers' search costs become negligible, the allocative inefficiency does not vanish. Moreover, no strategic obfuscation is imposed. When allowing for non-independent qualities, we show that product variety does not constitute a rationale for advertisers' favoritism.

Estimation of Sequential Search Models

We propose a new likelihood-based estimation method for the sequential search model. By allowing search costs to be heterogeneous across consumers and products, we can directly compute the joint probability of the search sequence and the purchase decision when consumers are searching for the idiosyncratic preference shocks in their utility functions. Under this procedure, one recursively makes random draws for each dimension that requires numerical integration to simulate the probabilities associated with the purchase decision and the search sequence under the sequential search algorithm. We then present details from an extensive simulation study that compares the proposed approach with existing estimation methods recently used for sequential search model estimation, viz., the kernel-smoothed frequency simulator (KSFS) and the crude frequency simulator (CFS). In the empirical application, we apply the proposed method to the Expedia dataset from Kaggle which has previously been analyzed using the KSFS estimator and the assumption of homogeneous search costs. We demonstrate that the proposed method has a better predictive performance associated with differences in the estimated effects of various drivers of clicks and purchases, and highlight the importance of the heterogeneous search costs assumption even when KSFS is used to estimate the sequential search model. Lastly, from a managerial perspective, we show that sorting products by their expected utilities can enhance consumer welfare and increase the number of transactions.

Choice Overload in Online Platforms

Online platforms have the unique ability of offering virtually unlimited assortments. However, they often assume frictionless conditions in the purchase process which may not always hold in practice. We study the impact of heterogeneous search costs on the formation of consideration sets, and how consumers' purchase behavior responds to changes in the online assortment size. We first build a consider-then-choose framework to study how customers who have different familiarity with the options form their consideration sets and make subsequent purchase decisions. We then leverage a field experiment and detailed clickstream datasets to support our theoretical results. We further conduct counterfactual analyses to emulate customers' decision making process under different assortment reductions.

Prices and heterogeneous search costs

We study price formation in a model of consumer search for differentiated products in which consumers have heterogeneous search costs. We provide conditions under which a pure‐strategy symmetric Nash equilibrium exists and is unique. Search costs affect two margins—the intensive search margin (or search intensity) and the extensive search margin (or the decision to search rather than to not search at all). These two margins affect the elasticity of demand in opposite directions and whether lower search costs result in higher or lower prices depends on the properties of the search cost density.

Nonsequential search equilibrium with search cost heterogeneity

We generalize the model of Burdett and Judd (1983) to the case where an arbitrary finite number of firms sells a homogeneous good to buyers who have heterogeneous search costs. We show that a price dispersed symmetric Nash equilibrium always exists. Numerical results show that the behavior of prices and consumer surplus with respect to the number of firms hinges upon the nature of search cost dispersion: when search costs are relatively concentrated, entry of firms leads to lower average prices and greater consumer surplus; however, for relatively dispersed search costs, the mean price goes up and consumer surplus may decrease with the number of firms.

Prices, Product Differentiation, and Heterogeneous Search Costs

We study price formation in the standard model of consumer search for differentiated products but allow for search cost heterogeneity. In doing so, we dispense with the usual assumption that all consumers search at least once in equilibrium. This allows us to analyze the manner in which prices affect the decision to search rather than to not search at all, which is an important but often neglected aspect of the price mechanism. Recognizing the role the equilibrium price plays in consumers' participation decisions turns out to be critical for understanding how search costs affect market power. This is because the two margins that determine prices - the intensive search margin, or search intensity, and the extensive search margin, or search participation - may be affected in opposing directions by a change in search costs. When search costs go up, fewer consumers decide to search, which modifies the search composition of demand such that demand can become more elastic. At the same time, the consumers who choose to search reduce their search intensity, which makes demand less elastic. Whether the effect on the extensive or the intensive search margin dominates depends on the range and shape of the search cost density. We identify conditions for higher search costs to result in higher, constant, or lower prices. Similar results are obtained when the marginal gains from search vary across consumers.

“A” Business by Any Other Name: Firm Name Choice as a Signal of Firm Quality

This paper considers when a firm’s deliberately chosen name can signal meaningful information. The average plumbing firm whose name begins with A or a number receives five times more service complaints than other firms and also charges higher prices. Relatedly, plumbers with A names advertise more in the Yellow Pages and on Google, and doing so is positively correlated with receiving complaints. As the use of A names is more prevalent in larger markets, I reconcile these findings with a simple model in which firms have different qualities and consumers have heterogeneous search costs.

Prices, Product Differentiation, and Heterogeneous Search Costs

Prices, Product Differentiation, and Heterogeneous Search Costs

Prices, Product Differentiation, and Heterogeneous Search Costs

We study price formation in the standard model of consumer search for differentiated products (Wolinsky, 1986) but allow for search cost heterogeneity. In doing so, we dispense with the usual assumption that all consumers search at least once in equilibrium. This allows us to analyze the manner in which prices affect the decision to search rather than to not search at all, which is an important but often neglected aspect of the price mechanism. Recognizing the role the equilibrium price plays in consumers' participation decisions turns out to be critical for understanding how search costs affect market power. This is because the two margins that determine prices---the intensive search margin, or search intensity, and the extensive search margin, or search participation---may be affected in opposing directions by a change in search costs. When search costs go up, fewer consumers decide to search, which modifies the search composition of demand such that demand can become more elastic. At the same time, the consumers who choose to search reduce their search intensity, which makes demand less elastic. Whether the effect on the extensive or the intensive search margin dominates depends on the range and shape of the search cost density. We identify conditions for higher search costs to result in higher, constant, or lower prices. Similar results are obtained when the marginal gains from search vary across consumers.

Nonsequential Search Equilibrium with Search Cost Heterogeneity

We generalize the model of Burdett and Judd (1983) to the case where an arbitrary finite number of firms sells a homogeneous good to buyers who have heterogeneous search costs. We show that a price dispersed symmetric Nash equilibrium always exists. Numerical results show that the behavior of prices with respect to the number of firms hinges upon the shape of the search cost distribution: when search costs are relatively concentrated (dispersed), entry of firms leads to higher (lower) average prices.

Oligopolistic pricing with heterogeneous consumer search

A finite number of identical stores sell a homogeneous good to consumers with heterogeneous search costs who search sequentially with perfect recall and without replacement. Consumers' search rules are optimal with respect to the stores' pricing strategies, and consumers must visit a store to obtain information about its actual price. A symmetric Nash equilibrium (SNE) always exists. The model exhibits a variety of equilibrium behaviors between monopoly pricing and marginal-cost pricing. The competitiveness of a market depends crucially on the shape of the search cost distribution, moreso than on the number of competing firms.

Inferring an Investment Return Series for Real Estate from Observations on Sales

Accurate measurement of the returns to real estate investment are essential to sound analysis. This paper improves upon the traditionally employed method—collecting comparable sales data. A dynamic model of real estate appraisal is developed in which agents have incomplete information, heterogeneous search costs, and varying expectations. Various types of simulation analysis of the model indicate it performs best in the sense that the return estimate converges to the true value faster than other simpler rules.