Explore the vast range of titles available.

It is now well understood that social media plays an increasingly important role in consumers’ decision making. However, an overload of social media content in product search engines can hinder consumers from efficiently seeking information. We propose a structural econometric model to understand consumers’ preferences and costs on search engines to improve user experience under unstructured social media. Our model combines an optimal stopping framework with an individual-level random utility choice model and analyzes click behavior in conjunction with purchase choices. Our model accounts for three major constraints in a consumer’s decision-making process: (1) interdependency in decision making for different alternatives, (2) sequential arrival of information revealed by click-throughs, and (3) nonnegligible search cost. Our approach allows us to jointly estimate consumers’ heterogeneous preferences and search costs under the interplay of social media and search engines, and to predict search and purchase behavior for each consumer. We validate the model using an individual session-level data set of approximately seven million observations resulting in room bookings in 2,117 U.S. hotels. Interestingly, our analysis allows us to quantify the trade-off between consumers’ benefits and cognitive costs from using large-scale unstructured social media information during decision making. Our policy experiments show that providing a carefully curated digest of social media content during the earlier stages of consumer search (i.e., on the search results summary page) can lead to a 12.01% increase in the overall search engine revenue. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2991 . This paper was accepted by Anandhi Bharadwaj, information systems.

I provide novel empirical evidence grounded in an original theoretical framework to explain why colocation matters for the rate, direction, and quality of scientific collaboration. To address endogeneity concerns due to selection into colocation and matching, I exploit the constraints imposed on the spatial allocation of labs on the Jussieu campus of Paris by the removal of asbestos from its buildings. Consistent with search costs constituting a major friction to collaboration, colocation increases the likelihood of joint research by 3.5 times, an effect that is mostly driven by lab pairs that face higher search costs ex ante. Furthermore, separation does not negatively affect collaboration between previously colocated labs. However, while colocated labs grow increasingly similar in topics and literature cited, separated ones embark on less correlated research trajectories. Research outcomes, instead, seem to be mostly influenced by how distance affects execution costs: after colocation, labs are more likely to pursue both lower-quality projects (a selection effect) and high-quality projects (an effort effect). Opposite effects on quality are observed after separation. Whereas search costs affect which scientists are likely to collaborate together, execution costs shape the quality of their output. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2798 . This paper was accepted by Ashish Arora, entrepreneurship and innovation.

Consumers search for product information to resolve valuation uncertainties before purchase. We incorporate search cost into consumer choice models and study the two-stage consider-then-choose policy. In the first stage, a consumer forms her consideration set by balancing utility uncertainty and search cost. In the second stage, she evaluates all products in her consideration set and chooses the one with the highest net utility. We show that the revenue-ordered assortment (i.e., the offer set that includes products in the revenue-decreasing order) fails to be optimal, although it can obtain at least half the optimal revenue. We propose a k -quasi-attractiveness-ordered assortment and show that it can be arbitrarily near optimal for the market share maximization problem. The assortment problems with search cost are generally NP-hard, so we develop efficient approximation or relatively fast exact algorithms for a variety of assortment problems under the consider-then-choose models with search cost. For the joint assortment planning and pricing problem with homogeneous consumers, we show that the intrinsic-utility-ordered assortment and the quasi-same-price policy, which charges the same price for all products except at most one, are optimal. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2790 . This paper was accepted by Gad Allon, operations management.

We explore how Internet browsing behavior varies between mobile phones and personal computers. Smaller screen sizes on mobile phones increase the cost to the user of browsing for information. In addition, a wider range of offline locations for mobile Internet usage suggests that local activities are particularly important. Using data on user behavior at a (Twitter-like) microblogging service, we exploit exogenous variation in the ranking mechanism of posts to identify the ranking effects. We show that (1) ranking effects are higher on mobile phones suggesting higher search costs: links that appear at the top of the screen are especially likely to be clicked on mobile phones and (2) the benefit of browsing for geographically close matches is higher on mobile phones: stores located in close proximity to a user's home are much more likely to be clicked on mobile phones. Thus, the mobile Internet is somewhat less “Internet-like”: search costs are higher and distance matters more. We speculate on how these changes may affect the future direction of Internet commerce.

Many markets have historically been dominated by a small number of best-selling products. The Pareto principle, also known as the 80/20 rule, describes this common pattern of sales concentration. However, information technology in general and Internet markets in particular have the potential to substantially increase the collective share of niche products, thereby creating a longer tail in the distribution of sales. This paper investigates the Internet's \"long tail\" phenomenon. By analyzing data collected from a multichannel retailer, it provides empirical evidence that the Internet channel exhibits a significantly less concentrated sales distribution when compared with traditional channels. Previous explanations for this result have focused on differences in product availability between channels. However, we demonstrate that the result survives even when the Internet and traditional channels share exactly the same product availability and prices. Instead, we find that consumers' usage of Internet search and discovery tools, such as recommendation engines, are associated with an increase the share of niche products. We conclude that the Internet's long tail is not solely due to the increase in product selection but may also partly reflect lower search costs on the Internet. If the relationships we uncover persist, the underlying trends in technology portend an ongoing shift in the distribution of product sales. This paper was accepted by Ramayya Krishnan, information systems.

A consumer's decision to engage in search depends on the beliefs the consumer has about an unknown product characteristic (e.g., price). Because beliefs are rarely observed, researchers typically assume that consumers have rational expectations or update beliefs consistent with Bayesian updating. These assumptions are restrictive and do not enable the researcher or the retailer to price discriminate among consumers on the basis of heterogeneity in beliefs. The authors use Monte Carlo experiments to show how these assumptions affect estimates of search cost. Next, they design an incentive-aligned online study in which participants search over the price of a homogeneous good, and the authors elicit distributions of price beliefs before and after each search. Drawing on data collected from a nationally representative panel, they find substantial heterogeneity in prior price beliefs, such that participants update their beliefs in response to search outcomes but deviate from Bayesian updating in that they underreact to new information. Importantly, the authors show that (1) assuming Bayesian updating does not significantly bias search cost estimates at the aggregate level if the researcher accounts for heterogeneous prior beliefs, (2) eliciting heterogeneity in prior expected prices is much more important than eliciting heterogeneity in prior price uncertainty, and (3) a retailer can increase profits through third-degree price discrimination by recognizing the heterogeneity in prior beliefs.

The Internet has made consumer search easier, with consequences for prices, industry structure, and the kinds of products offered. We provide an industry model with strategic design choices that explores these issues. A polarized market structure results: some firms choose designs aimed at broad-based audiences, while others target narrow niches. We analyze the effect of reduced search costs, finding results consistent with the reported prevalence of niche goods and long-tail and superstar phenomena. In particular, the model suggests that long-tail effects arise when there is a wide range of potential designs, relative to vertical heterogeneity among firms. JEL: D11, D21, D83, L11, L86, M31

Consumers often need to search for product information before making purchase decisions. We consider a tractable (continuous-time) model of gradual learning, in which consumers incur search costs to learn further product information, and update their expected utility of the product at each search occasion. We characterize the optimal stopping rules for either purchase, or no purchase, as a function of search costs and of the importance/informativeness of each attribute. This paper also characterizes how the likelihood of purchase changes with the ex ante expected utility, search costs, and the importance/informativeness of each attribute. We discuss optimal pricing, the impact of consumer search on profits and social welfare, and how the seller chooses its price to strategically affect the extent of the consumers' search behavior. We show that lower search costs can hurt the consumer because the seller may then choose to charge higher prices. Discounting creates asymmetry in the purchase and no-purchase search thresholds, and may lead to lower prices if search occurs in equilibrium, or higher prices if there is no search in equilibrium. This paper also considers searching for signals of the value of the product, heterogeneous importance of attributes, endogenous intensity of search, and social learning. This paper was accepted by Pradeep Chintagunta, marketing.

We study the bidding strategies of vertically differentiated firms that bid for sponsored search advertisement positions for a keyword at a search engine. We explicitly model how consumers navigate and click on sponsored links based on their knowledge and beliefs about firm qualities. Our model yields several interesting insights; a main counterintuitive result we focus on is the \"position paradox.\" The paradox is that a superior firm may bid lower than an inferior firm and obtain a position below it, yet it still obtains more clicks than the inferior firm. Under a pay-per-impression mechanism, the inferior firm wants to be at the top where more consumers click on its link, whereas the superior firm is better off by placing its link at a lower position because it pays a smaller advertising fee, but some consumers will still reach it in search of the higher-quality firm. Under a pay-per-click mechanism, the inferior firm has an even stronger incentive to be at the top because now it only has to pay for the consumers who do not know the firms' reputations and, therefore, can bid more aggressively. Interestingly, as the quality premium for the superior firm increases, and/or if more consumers know the identity of the superior firm, the incentive for the inferior firm to be at the top may increase. Contrary to conventional belief, we find that the search engine may have the incentive to overweight the inferior firm's bid and strategically create the position paradox to increase overall clicks by consumers. To validate our model, we analyze a data set from a popular Korean search engine firm and find that (i) a large proportion of auction outcomes in the data show the position paradox, and (ii) sharp predictions from our model are validated in the data.

We study the price-setting behavior in a competitive market for used cars and provide empirical evidence for coarse information processing. Based on detailed field data from one of Europe’s largest online marketplaces for automotive vehicles, we document systematic and sizable price discontinuities at salient car-age and mileage thresholds. The price difference between two otherwise identical cars across registration years (where one was first registered in January and the other in December of the previous year) is up to five times larger than that between two cars first registered in any two subsequent months within a registration year. A similar pattern can be observed in the mileage dimension at 10,000-km odometer marks, which is in line with earlier findings in the literature. Being able to study discontinuities along two dimensions of the same good allows us to further our understanding toward a more general notion of inattentive behavior. While our results are compatible with a behavioral model of limited attention, we also provide evidence for a more traditional explanation based on search frictions. Data and the online appendix are available at https://doi.org/10.1287/mnsc.2016.2714 . This paper was accepted by Uri Gneezy, behavioral economics.