Lower Search Costs Research Articles

Dynamic Selection and Distributional Bounds on Search Costs in Dynamic Unit-Demand Models

This paper develops a dynamic model of consumer search that, despite placing very little structure on the dynamic problem faced by consumers, allows us to exploit intertemporal variation in within-period price and search cost distributions to estimate the population distribution from which consumers' search costs are initially drawn. We show that static approaches to estimating this distribution generally suffer from a dynamic sample selection bias because forward-looking consumers with unit demand for a good may delay their purchase in a way that depends on their individual search cost. We analyze identification of the population search cost distribution using only price data and develop estimable nonparametric upper and lower bounds on the distribution function and a nonlinear least squares estimator for parametric models. We also consider the additional identifying power of weak assumptions such as monotonicity of purchase probabilities in search costs. We apply our estimators to analyze the online market for two widely used econometrics textbooks. Our results suggest that static estimates of the search cost distribution are biased upwards, in a distributional sense, relative to the true population distribution. In a small-scale simulation study, we show that this is typical in a dynamic setting where consumers with high search costs are more likely to delay purchase than those with lower search costs.

Search for differentiated products: identification and estimation

When consumers search for differentiated products, a given search decision can be explained either by low search cost or by low tastes for the set of products already found. We propose an identification strategy that allows to estimate the search cost distribution in the presence of unobserved tastes. The required data takes the form of conditional search decisions: observations of search actions combined with previously observed product displays. We develop an application using clickstream data from a hotel search platform. Estimates of price elasticity of demand in the search model differ from those in the static model, reflecting the bias due to endogeneity of search‐generated choice sets.

Within-Group Concentration, Between-Group Concentration, and the Winners and Losers of Digital Music Distribution

By lowering search costs, making more products available, and providing access to free content, information technology (IT) has changed patterns of market concentration in media industries such as recorded music. In this paper, I argue that to understand how IT has changed media markets we need to go beyond considering market concentration in terms of the distribution of sales by product, and also consider the distribution of sales by group of products: between-group concentration. With cross-country panel data, I show that IT had different effects on sales that depended strongly on the between-group concentration in each country at the time of the internet shock. I develop and test the hypothesis that the formal industry fared relatively better in markets with more between-group concentration than in markets with less. I conclude with a discussion of lessons and further questions implied by the results.

A Duo-Theme DEMATEL approach for exploring the driving factors of online luxury goods sales: E-retailers’ perceptions

Factors affecting online luxury goods sales are complicated and intertwined. To stimulate online luxury goods sales, understanding of key influencing factors and causal relationships among the intertwined factors is of essential importance. To this end, this study first divides factors affecting online luxury goods sales into two distinct aspects: perceived benefits (PB) and perceived risks (PR), and then introduces a duo-theme Decision Making Trial and Evaluation Laboratory (DEMATEL) approach for the depiction of the driving factors that have the most effects on others in both aspects. An example of online luxury bags sales, from e-retailers’ perceptions, is presented. Results show that “wider selection” is the foremost driving factor, followed by “convenience,” “better price,” and “cost” in the PB aspect; whereas “trust and security” is the most influential driving factor, followed by “uncertainty” in the PR aspect. Accordingly, the luxury bags e-retailers are suggested to offer more information about the choices available, easier for ordering, and lower search and transaction costs through the Internet. In the meantime, they should also provide warranty of security for personal/financial information and product quality.

Second Opinions in Markets for Expert Services: Experimental Evidence

We experimentally investigate the role of second opinions in markets where experts such as physicians both diagnose and provide the services. Physicians may exploit their informational advantage and overtreat their patients by providing a more costly and expensive treatment than necessary. We show that introducing costly second opinions significantly reduces the level of overtreatment. Lowering search costs leads to significantly more second opinions, but the overtreatment level does not decrease. Under low but not under high search costs, market efficiency rises with the introduction of second opinions, as the reduction in treatment costs due to less overtreatment exceeds the increase in incurred search costs.

Same-Occupation Spouses: Preferences and Search Costs

Married individuals match with spouses who share their occupation more frequently than predicted by chance, suggesting either a preference for same-occupation matches or lower search costs within occupation. To distinguish between these explanations, we use a differences-in-differences strategy that compares the difference in wages between same-occupation husbands and different-occupation husbands across occupations with different percent male workers. Under the preferences mechanism, the difference should be decreasing in percent male. Under the search cost mechanism, the difference should be increasing in percent male. Our results are consistent with the search cost explanation, especially in occupations with greater degree of workplace communication.

Lowering Appropriability Hazards by Raising Infringers’ Costs

Internet intermediary platforms are online services that provide a means for information to be hosted, accessed, shared, indexed, and transmitted between third parties. Such services lower search costs in the Internet economy by making it possible for users to find and evaluate the information, goods, and services they need and facilitating market exchanges by providing forums which establish transactional norms and codes of conduct. However, intermediary services also make it easier for unauthorized infringement of copyright and trademarks to occur online. In this context, their ability to control online information traffic and marketplace activities makes them a potentially valuable resource for intellectual property (IP) holding firms if they can be induced to assist in identifying and preventing instances of infringement. Accordingly, intermediaries are increasingly a target for IP holders who sue them for the actions of third party users. I frame these lawsuits as a multi-stage raising rivals' costs strategy in which IP holders use intermediaries to lower their own transaction costs while simultaneously raising those of infringers. I suggest that different types of property rights lead to heterogeneous selection preferences amongst potential intermediary targets for litigation. I then argue that the systematic importance of intermediary targets influences the magnitude of property enforcement requests, which in turn drives the likelihood of escalated rounds of litigation. I find that these hypotheses are supported and may have important implications for managers in IP industries, providers of intermediary services and policymakers with respect to Internet governance and intellectual property enforcement.

Expert-mediated sequential search

This paper studies markets, such as Internet marketplaces for used cars or mortgages, in which consumers engage in sequential search. In particular, we consider the impact of information-brokers (experts) who can, for a fee, provide better information on true values of opportunities. We characterize the optimal search strategy given a price and the terms of service set by the expert, and show how to use this characterization to solve the monopolist expert’s service pricing problem. Our analysis enables the investigation of three common pricing schemes (pay-per-use, unlimited subscription, and package pricing) that can be used by the expert. We demonstrate that in settings characteristic of electronic marketplaces, namely those with lower search costs for consumers and lower costs of production of expert services, unlimited subscription schemes are favored. Finally, we show that the platform that connects consumer and experts can improve social welfare by subsidizing the purchase of expert services. The optimal level of subsidy forces the buyer to exactly fully internalize the marginal cost of provision of expert services. In electronic markets, this cost is minimal, so it may be worthwhile for the platform to make the expert freely available to consumers.

The Impact of Consumer Attentiveness and Search Costs on Firm Quality Disclosure: A Competitive Analysis

Firms can invest to disclose quality information about their products to consumers, but consumers are not always perfectly attentive to these disclosures. Indeed, technologies such as digital video recorders have increased the ease with which disclosures can be avoided by consumers. Although such inattention may result in a consumer missing information from one or more competing firms, consumers who have missed disclosures might decide to search for quality information to become fully informed before making a purchase decision. In this paper we incorporate consumer attentiveness, as well as the related endogenous search decision, into a model of quality disclosure. Our results suggest that firms should disclose less quality information as the share of partially informed consumers (informed about one firm but not the other) increases, or as consumer search costs increase. We also provide insights into the potential impact of consumer trends toward lower attentiveness and lower search costs. This paper was accepted by J. Miguel Villas-Boas, marketing.

Who Benefits from Improved Search in Platform Markets?

Online platforms invest large sums in their search technology. Motivated by this observation, we investigate how lowering search costs affects the welfare of market participants, in a model where buyers with horizontally differentiated tastes search and then compete for differentiated goods in an auction. We identify a effect, whereby lower search costs lead to better matches; and a effect whereby lower search costs endogenously shift market participation in favor of some goods and against others. We prove that there is a unique equilibrium, and demonstrate that the decentralized market achieves the social planner's solution. Decreasing search costs thus improves joint welfare; and yet surprisingly it is possible for segmentation effects to dominate matching effects, and joint seller revenue to fall.

Research on the Adaptive-absorption Search Strategy on Scale-free Networks

The search strategy of Brownian particles based on the adaptive-absorption mechanism is proposed. In this strategy, the queue length of each node can be self-adjusted by using the self-adaptive accepting rate function to the incoming particles, and the additional Brownian particles in the networks are absorbed on an absorption path. Scale-free networks are generated for testing the strategy. The experiment results indicate that the strategy has higher network capacity and lower search cost than the existing methods especially for large networks.

Price, Place, People, and Local Experience

With property characteristics unobserved or difficult to measure, there are returns to evaluation, due diligence, and performance. Buyers can invest in observable human capital signals including location and experience that lower search costs. Buyers with local experience have lower search costs, a higher probability of closing and can earn a purchase discount from the acquisition of human capital developed from repeatedly transacting in a specific real estate market. For 1,793 apartment transactions in Atlanta over the 1995 to 2007 period, a very small focused group of local, experienced buyers receives acquisition discounts. The comparison is with non-locals and locals with two or fewer purchases. Inexperienced locals receive no or little discount and match non-local results. Non-locals do not pay a premium when compared to the typical buyer.

Management Insights

Management Insights

Consumer Desired Price Modeling – Case Study on the RCBS Market

This paper is focused on the information asymmetry problem. When the consumer has a market overview then the optimal product can be chosen more or less easily. We model more realistic situation where the consumer does not have a market overview and so the process of search has to be performed. The harder the search is the higher information asymmetry is. The aim of the paper is to find if the information asymmetry prevents the consumer to find optimal product and if yes then to model what price rational consumer will choose. For this purpose we reworked Stigler's model into the model more suitable for the small market needs. We used this model on the retail core banking services to individuals in the Czech Republic. On this market the information asymmetry was found within the European Union research as well as within our own research. We find that information asymmetry prevents even low search cost user the optimal price choice, we are abstracting from the influence of scattered knowledge, advertisement etc. However for more than half of the products on this market it is rational to search fo r the better price and so to generate positive savings. Also we state that information asymmetry is mostl y caused by variable costs on search that express the task of a final price determination.

Price Negotiation in Differentiated Product Markets: Evidence from the Canadian Mortgage Market

This paper develops and estimates a search and bargaining model designed to measure the welfare loss associated with frictions in oligopoly markets with negotiated prices. We use the model to quantify the consumer surplus loss induced by the presence of search frictions in the Canadian mortgage market, and evaluate the relative importance of market power, inefficient allocation, and direct search costs in explaining the loss. Our results suggest that search frictions reduce consumer surplus by almost $20 per month on a $100,000 loan, and that 17% of this reduction can be associated with discrimination, 30% with inefficient matching, and the remainder with the search cost. In addition, we find that product differentiation attenuates the effect of search frictions by reducing the cost of gathering quotes and improving efficiency, while posted prices do so through the ability of the first-mover to price discriminate. In contrast, competition amplifies the welfare effect of search frictions. Despite this, the overall effect of competition is to increase aggregate consumer surplus and drive prices down, but these effects are not spread equally across consumers: those with low search costs benefit more from competition.

Managerial implications from Indian case studies on e‐reverse auctions

PurposeThe purpose of this paper is to investigate e‐reverse auctions (eRA) implementation experiences across a diverse group of firms and sectors in the Indian context, to derive useful insights for theory and practice.Design/methodology/approachThe paper takes the form of a qualitative multiple case study following direct observation of object reality. The data analysed include written documentation, archival records, physical artifacts and unstructured interviews with key eRA personnel.FindingseRA work best in a competitive, high capacity marketplace and are the dominant strategy when the focus is on low search cost per supplier, when the percent reduction over time in the price offered by the current supplier is low and when the product is standardized. The optimum number of bidders is five to ten. Most of the findings are in line with literature but some of them differ too. These will add to academic discourse.Research limitations/implicationsThe small sample size and case method approach limits the ability to generalize the findings. The firms were selected as a convenience sample and so may not be truly cross‐sectional. Only analytical generalisation is claimed rather than any statistical generalisation.Practical implicationseRA improve effectiveness of the sourcing process and facilitate access to new suppliers. They also lead to standardization of sourcing procedures, reduced order cycle, reduced prices and generally higher service levels. This paper will help firms in India and other countries to develop policies, strategies and procedures while implementing eRA.Originality/valueThe paper is perhaps the first on eRA practices in India. The author describes the practices in detail and based on this develops a framework for eRA process and provides detailed and concise guidelines for managers.

Inflation, price dispersion and market integration through the lens of a monetary search model

Monetary search theory implies that the real effects of inflation via its impact on price dispersion depend on the level of search costs and, thus, on the level of market integration. For less integrated markets, the inflation–price dispersion nexus is predicted to be asymmetrically V-shaped which results in an optimal inflation rate above zero. For highly integrated markets with low search costs, however, the impact of inflation on price dispersion should only be small. Using price data of the European Union member states, this paper tests and confirms these predictions of monetary search theory.

Inflation, price dispersion and market integration through the lens of a monetary search model

Monetary search theory implies that the real effects of inflation via its impact on price dispersion depend on the level of search costs and, thus, on the level of market integration. For less integrated markets, the inflation-price dispersion nexus is predicted to be asymmetrically V-shaped which results in an optimal inflation rate above zero. For highly integrated markets with low search costs, however, the impact of inflation on price dispersion should only be small. Using price data of the European Union member states, this paper is the first that tests and confirms these predictions of monetary search theory.

Determinants of the Optimal Network Configuration and the Implications forCoordination

This paper develops a simulation model to compare the performance of two stylized manufacturing networks: the lead factory network (LFN) and the archetype network (AN). The model identifies the optimal network configuration and its implications for coordination mechanisms. Using an NK simulation model to diffierentiate between exogenous factors (configuration) and endogenous factors (coordination), we find low complexity of the production process, low transfer costs and high search costs, as well as a larger number of manufacturing plants benefit LFN compared to AN. Optimally coordinating the chosen network configuration of LFN might require to fully transfer knowledge in the short run but to transfer nothing in the long run. Moreover, a late knowledge transfer from the lead factory to the plants increases the pre-transfer performance of LFN but results in a larger performance drop, yielding a lower short-run but a higher long-run performance of LFN.

A Semantic Searching Scheme in Heterogeneous Unstructured P2P Networks

Semantic-based searching in peer-to-peer (P2P) networks has drawn significant attention recently. A number of semantic searching schemes, such as GES proposed by Zhu Y et al., employ search models in Information Retrieval (IR). All these IR-based schemes use one vector to summarize semantic contents of all documents on a single node. For example, GES derives a node vector based on the IR model: VSM (Vector Space Model). A topology adaptation algorithm and a search protocol are then designed according to the similarity between node vectors of different nodes. Although the single semantic vector is suitable when the distribution of documents in each node is uniform, it may not be efficient when the distribution is diverse. When there are many categories of documents at each node, the node vector representation may be inaccurate. We extend the idea of GES and present a new class-based semantic searching scheme (CSS) specifically designed for unstructured P2P networks with heterogeneous single-node document collection. It makes use of a state-of-the-art data clustering algorithm, online spherical k-means clustering (OSKM), to cluster all documents on a node into several classes. Each class can be viewed as a virtual node. Virtual nodes are connected through virtual links. As a result, the class vector replaces the node vector and plays an important role in the class-based topology adaptation and search process. This makes CSS very efficient. Our simulation using the IR benchmark TREC collection demonstrates that CSS outperforms GES in terms of higher recall, higher precision, and lower search cost.