Showing papers in "Marketing Science in 2009"

Firm-Created Word-of-Mouth Communication: Evidence from a Field Test

Abstract: In this paper, we investigate the effectiveness of a firm's proactive management of customer-to-customer communication. We are particularly interested in understanding how, if at all, the firm should go about effecting meaningful word-of-mouth (WOM) communications. To tackle this problem, we collect data from two sources: (1) we implement a large-scale field test in which a national firm created word of mouth through two populations: customers and noncustomers, and (2) we collect data from an online experiment. We break our theoretical problem into two subproblems. First, we ask: “What kind of WOM drives sales?” Motivated by previous research, we hypothesize that for a product with a low initial awareness level, WOM that is most effective at driving sales is created by less loyal (not highly loyal) customers and occurs between acquaintances (not friends). We find support for this in the field test as well as in an experimental setting. Hence, we demonstrate the potential usefulness of exogenously created WOM: conversations are created where none would naturally have occured otherwise. Then, we ask: “Which agents are most effective at creating this kind of WOM?” In particular, we are interested in evaluating the effectiveness of the commonly used opinion leader designation. We find that although opinion leadership is useful in identifying potentially effective spreaders of WOM among very loyal customers, it is less useful for the sample of less loyal customers.

Website Morphing

Abstract: Virtual advisors often increase sales for those customers who find such online advice to be convenient and helpful. However, other customers take a more active role in their purchase decisions and prefer more detailed data. In general, we expect that websites are more preferred and increase sales if their characteristics (e.g., more detailed data) match customers' cognitive styles (e.g., more analytic). “Morphing” involves automatically matching the basic “look and feel” of a website, not just the content, to cognitive styles. We infer cognitive styles from clickstream data with Bayesian updating. We then balance exploration (learning how morphing affects purchase probabilities) with exploitation (maximizing short-term sales) by solving a dynamic program (partially observable Markov decision process). The solution is made feasible in real time with expected Gittins indices. We apply the Bayesian updating and dynamic programming to an experimental BT Group (formerly British Telecom) website using data from 835 priming respondents. If we had perfect information on cognitive styles, the optimal “morph” assignments would increase purchase intentions by 21%. When cognitive styles are partially observable, dynamic programming does almost as well---purchase intentions can increase by almost 20%. If implemented system-wide, such increases represent approximately $80 million in additional revenue.

Quantifying the Long-Term Impact of Negative Word of Mouth on Cash Flows and Stock Prices

Abstract: This paper seeks to quantify the long-term financial impact of negative word of mouth (NWOM), an issue that has long challenged extant research. We do so with real-world data on firm security prices. The developed time-series models innovatively uncover (1) short-and long-term effects of NWOM on cash flows, stock returns, and stock volatilities, and (2) NWOM's “wear-in” effects (i.e., it takes a number of months before the stock price impact of NWOM reaches the peak point) and “wear-out” effects (i.e., it takes several months after the peak before the stock price impact of NWOM dies out completely). In addition, the results related to endogeneity and feedback effects from the stock market are also interesting, supporting the idea that historical underperformance in stock prices may breed more harmful future buzz in a “vicious” cycle of NWOM. After controlling for competition, NWOM's long-term financial harm becomes more destructive in magnitude, kicks in more quickly, and haunts investors longer. Overall, these findings offer some unique implications for buzz management, time-series models quantifying the financial impact of word of mouth, and the marketing-finance interface.

The Option Value of Returns: Theory and Empirical Evidence

Abstract: When a firm allows the return of previously purchased merchandise, it provides customers with an option that has measurable value. Whereas the option to return merchandise leads to an increase in gross revenue, it also creates additional costs. Selecting an optimal return policy requires balancing both demand and cost implications. In this paper, we develop a structural model of a consumer's decision to purchase and return an item that nests extant choice models as a special case. The model enables a firm to both measure the value to consumers of the return option and balance the costs and benefits of different return policies. We apply the model to a sample of data provided by a mail-order catalog company. We find considerable variation in the value of returns across customers and categories. When the option value is large, there are large increases in demand. For example, the option to return women's footwear is worth an average of more than $15 per purchase to customers and increases average purchase rates by more than 50%. We illustrate how the model can be used by a retailer to optimize his return policies across categories and customers.

Click Fraud

Abstract: Click fraud is the practice of deceptively clicking on search ads with the intention of either increasing third-party website revenues or exhausting an advertiser's budget. Search advertisers are forced to trust that search engines detect and prevent click fraud even though the engines get paid for every undetected fraudulent click. We find conditions under which it is in a search engine's interest to allow some click fraud. Under full information in a second-price auction, if x% of clicks are fraudulent, advertisers will lower their bids by x%, leaving the auction outcome and search engine revenues unchanged. However, if we allow for uncertainty in the amount of click fraud or change the auction type to include a click-through component, search engine revenues may rise or fall with click fraud. A decrease occurs when the keyword auction is relatively competitive because advertisers lower their budgets to hedge against downside risk. If the keyword auction is less competitive, click fraud may transfer surplus from the winning advertiser to the search engine. Our results suggest that the search advertising industry would benefit from using a neutral third party to audit search engines' click fraud detection algorithms.

Business Models for Media Firms: Does Competition Matter for How They Raise Revenue?

Abstract: The purpose of this article is to analyze how competitive forces may influence the way media firms like TV channels raise revenue. A media firm can either be financed by advertising revenue, by direct payment from the viewers (or the readers, if we consider newspapers), or by both. We show that the scope for raising revenues from consumer payment is constrained by other media firms offering close substitutes. This implies that the less differentiated the media firms' content, the larger is the fraction of their revenue coming from advertising. A media firm's scope for raising revenues from ads, on the other hand, is constrained by how many competitors it faces. We should thus expect that direct payment from the media consumers becomes more important the larger the number of competing media products.

Do Innovations Really Pay Off? Total Stock Market Returns to Innovation

Abstract: Critics often decry an earnings-focused short-term orientation of management that eschews spending on risky, long-term projects such as innovation to boost a firm's stock price. Such critics assume that stock markets react positively to announcements of immediate earnings but negatively to announcements of investments in innovation that have an uncertain long-term pay off. Contrary to this position, we argue that the market's true appreciation of innovation can be estimated by assessing the total market returns to the entire innovation project. We demonstrate this approach via the Fama-French 3-factor model (including Carhart's momentum factor) on 5,481 announcements from 69 firms in five markets and 19 technologies between 1977 and 2006. The total market returns to an innovation project are $643 million, more than 13 times the $49 million from an average innovation event. Returns to negative events are higher in absolute value than those to positive events. Returns to initiation occur 4.7 years ahead of launch. Returns to development activities are the highest and those to commercialization the lowest of all activities. Returns to new product launch are the lowest among all eight events tracked. Returns are higher for smaller firms than larger firms. Returns to the announcing firm are substantially greater than those to competitors across all stages. We discuss the implications of these results.

Movie Advertising and the Stock Market Valuation of Studios: A Case of “Great Expectations?”

Abstract: Product innovation is the key revenue driver in the motion picture industry. Because major studios typically launch fewer than 20 movies per year, the financial performance of a single release can have a major effect on the studio's profitability. In this paper we study how single movie releases impact the investor valuation of the studio. We analyze the change in postlaunch stock price and predict the direction and magnitude of excess returns based on the revenue expectation built up for a movie release. That expectation is set, in part, by media support; i.e., highly advertised movies are expected to draw larger audiences than others. By using an event-study methodology, we isolate the impact of a movie launch on studio stock price and track the determinants of that change. We examine a comprehensive data set comprising over 300 movies released by the largest studios. Our results indicate a clear interaction between the marketing support received by a movie and the direction and magnitude of its excess stock return post launch. Movies with above average prelaunch advertising have lower postlaunch stock returns than films with below average advertising. Our findings also suggest that movies that are hits at the box office may result in a lowering of stock price if they had high media support because of high performance expectations built up prior to launch. Thus prelaunch advertising plays a dual role of informing consumers about a movie's arrival as well as helping investors form expectations about the studio's profit performance.

Voluntary Quality Disclosure and Market Interaction

Abstract: Marketers disclose quality information directly to potential consumers using a variety of communication channels. This study investigates how competition may influence duopoly firms' incentive to voluntarily reveal quality information. We show that firms in competitive markets reveal less information than a monopoly firm. In addition, sequential disclosure leads to asymmetric equilibrium disclosure behavior: the disclosure leader reveals unambiguously less information than in the simultaneous disclosure case, whereas the follower ex ante reveals less (more) private information than that released by the leader or by the firms in the simultaneous case when the disclosure cost is sufficiently low (high). We also examine the equilibrium firm profits and social welfare. We demonstrate that there may be a U-shaped relationship between equilibrium monopoly profits (or social welfare under both monopoly and duopoly) and the disclosure cost. Moreover, in comparison to the simultaneous disclosure case, sequential disclosure can lead to increasingly softened competition, improving both firm profitability and social welfare.

Path Data in Marketing: An Integrative Framework and Prospectus for Model Building

Abstract: Many data sets, from different and seemingly unrelated marketing domains, all involve paths---records of consumers' movements in a spatial configuration. Path data contain valuable information for marketing researchers because they describe how consumers interact with their environment and make dynamic choices. As data collection technologies improve and researchers continue to ask deeper questions about consumers' motivations and behaviors, path data sets will become more common and will play a more central role in marketing research. To guide future research in this area, we review the previous literature, propose a formal definition of a path (in a marketing context), and derive a unifying framework that allows us to classify different kinds of paths. We identify and discuss two primary dimensions (characteristics of the spatial configuration and the agent) as well as six underlying subdimensions. Based on this framework, we cover a range of important operational issues that should be taken into account as researchers begin to build formal models of path-related phenomena. We close with a brief look into the future of path-based models, and a call for researchers to address some of these emerging issues.

Heterogeneous Learning and the Targeting of Marketing Communication for New Products

Abstract: New product launches are often accompanied by extensive marketing communication campaigns. Firms' allocation decisions for these marketing communication expenditures have two dimensions---across consumers and over time. This allocation problem is different relative to the problem of allocation of resources for existing products. In the case of new products, consumers are uncertain about their quality and learn about the products through marketing communication. Furthermore, different consumers may have different rates of learning about product quality; i.e., there may be heterogeneous learning. Thus, consumer responsiveness to marketing communication could vary along two dimensions. For each consumer, this responsiveness would vary over time, as she learns about product quality. Across consumers, there would be differences in responsiveness in each time period. For optimal allocation of marketing communication across both consumers and time, firms would need estimates of how consumer responsiveness varies across consumers and over time. Past studies have typically focused on one of these two dimensions in which responsiveness varies. They have either looked at heterogeneity in responsiveness across agents or the variation in responsiveness over time. In the context of new products, past research has looked at how consumer learning about product quality causes responsiveness to vary over time. In this study, we build a model that allows for heterogeneous learning rates and obtain individual-level learning parameters for each consumer. We use a novel and rich panel data set that allows us to estimate these model parameters. To obtain individual-level estimates of learning, we add a hierarchical Bayesian structure to the Bayesian learning model. We exploit the natural hierarchy in the Bayesian learning process to incorporate it in the hierarchical Bayesian model. We use data augmentation, coupled with the Metropolis-Hastings algorithm, to make inferences about individual-level parameters of learning. We conduct this analysis on a unique panel data set of physicians where we observe prescription decisions and detailing (i.e., sales-force effort) at the individual physician level for a new prescription drug category. Our results show that there is significant heterogeneity across physicians in their rates of learning about the quality of new drugs. We also find that there are asymmetries in the temporal evolution of responsiveness of physicians to detailing---physicians who are more responsive to detailing in early periods are less responsive later on and vice versa. These findings have interesting implications for the targeting of detailing across physicians and over time. We find that firms could increase their revenue if they took these temporal and cross-sectional differences in responsiveness into account while deciding on allocations of detailing.

The Financial Markets and Customer Satisfaction: Reexamining Possible Financial Market Mispricing of Customer Satisfaction

Abstract: We investigate the association between information contained in the American Customer Satisfaction Index (ACSI) metric and future stock market performance. Some past research has provided results suggesting that the financial markets misprice customer satisfaction; i.e., firms advantaged in customer satisfaction are posited to earn positive future-period abnormal stock returns. We reexamine this relationship and find that statistically significant evidence of financial market mispricing of customer satisfaction is limited to firms in the computer and Internet sector. The results suggest that the mispricing anomaly reported in past research appears not to stem from a systemic failure of the financial markets to impound the financial implications of customer satisfaction into current stock price, but rather from abnormal returns achieved by a small group of satisfaction leaders in the computer and Internet sector over the period of study. Analyses based on unconditional risk covariates and analyses using conditional risk covariates estimated from short-window, high-frequency data support this finding.

Standard vs. Custom Products: Variety, Lead Time, and Price Competition

Abstract: In this paper, we study the standardization and customization decisions of two firms in a competitive setting, along with variety, lead time, and price decisions. We incorporate consumer heterogeneity both in firm preference (or store convenience) and in product attribute preferences. We find that the equilibrium outcome depends on the cost efficiencies of the production technologies as well as the consumer sensitivity to product fit and lead time. We develop an index that signifies the relative attractiveness of the standardization and customization strategies, and the potential outcomes. We identify the strategic roles of product variety and lead time in the competition. In contrast to the previous literature, we find that increasing the variety will not intensify the price competition if there is sufficient firm differentiation. Rather, it relieves the price pressure for the firm as it satisfies consumer needs better and enables higher price premiums. We also analyze the impact of asymmetric variable costs, fixed costs, and brand reputation on the equilibrium decisions.

Functional Regression: A New Model for Predicting Market Penetration of New Products

Abstract: The Bass model has been a standard for analyzing and predicting the market penetration of new products. We demonstrate the insights to be gained and predictive performance of functional data analysis (FDA), a new class of nonparametric techniques that has shown impressive results within the statistics community, on the market penetration of 760 categories drawn from 21 products and 70 countries. We propose a new model called Functional Regression and compare its performance to several models, including the Classic Bass model, Estimated Means, Last Observation Projection, a Meta-Bass model, and an Augmented Meta-Bass model for predicting eight aspects of market penetration. Results (a) validate the logic of FDA in integrating information across categories, (b) show that Augmented Functional Regression is superior to the above models, and (c) product-specific effects are more important than country-specific effects when predicting penetration of an evolving new product.

Beyond Attention Effects: Modeling the Persuasive and Emotional Effects of Advertising Creativity

Abstract: While creativity in advertising is a growing area of marketing research, relatively little is known about how the effects of creativity are produced. Accordingly, this research explores the basic persuasive i.e., desire to postpone closure and emotional i.e., positive affect mechanisms through which creative ads exert their influence on consumer viewing and purchase intentions. In addition, the model hypothesizes that the level of involvement with the ad moderates the desire to postpone closure effects but not the emotional impact. An overall model of the impact of ad creativity is developed and tested using structural equations analysis. Results from three experiments show the model receives good support.

Content vs. Advertising: The Impact of Competition on Media Firm Strategy

Abstract: Media firms compete in two connected markets. They face rivalry for the sale of content to consumers, and at the same time, they compete for advertisers seeking access to the attention of these consumers. We explore the implications of such two-sided competition on the actions and source of profits of media firms. One main conclusion we reach is that media firms may charge higher content prices in a duopoly than in a monopoly. This happens because competition for advertisers can reduce the return per customer impression from the ad market, making each firm less willing to underprice content to increase demand. Greater competitive intensity may thus increase content profits and decrease ad profits. These findings are in sharp contrast to those in a regular one-sided product market, in which competition typically lowers product prices and profits. We extend the framework to examine competition across different media (e.g., between magazines and cable TV) and show that firms in a duopolistic medium may benefit from more intense competition from a monopolist in another medium. We characterize the conditions for each firm in the duopoly medium to bundle more ads and earn greater total profits than the rival firm in the monopoly medium.

The Benefits of Downstream Information Acquisition

Abstract: This study investigates the effects of turning terabytes of raw retail data into managerial insights (i.e., downstream information acquisition) in a strategic channel setting. Two effects of information acquisition are identified---the efficiency effect that improves retail pricing decision making in an uncertain environment, and the strategic effect whereby the retailer voluntarily discloses the acquired private information to influence the upstream manufacturer's wholesale pricing behavior. It is shown that the efficiency effect benefits the retailer without affecting the manufacturer, while the strategic effect works to the detriment of the retailer but to the advantage of the manufacturer. Nevertheless, unobservable information acquisition can mitigate the retailer's loss and the manufacturer's benefit from the strategic effect of information disclosure. Moreover, an increasing expected information acquisition cost may benefit the retailer, when that cost is low and information acquisition is unobservable to the manufacturer. The implications of this paper can shed light on how firms interact in a channel where the downstream market is data intensive, but information gleaning is costly.

“Counting Your Customers” One by One: A Hierarchical Bayes Extension to the Pareto/NBD Model

Abstract: This research extends a Pareto/NBD model of customer-base analysis using a hierarchical Bayesian (HB) framework to suit today's customized marketing. The proposed HB model presumes three tried and tested assumptions of Pareto/NBD models: (1) a Poisson purchase process, (2) a memoryless dropout process (i.e., constant hazard rate), and (3) heterogeneity across customers, while relaxing the independence assumption of the purchase and dropout rates and incorporating customer characteristics as covariates. The model also provides useful output for CRM, such as a customer-specific lifetime and survival rate, as by-products of the MCMC estimation. Using three different types of databases---music CD for e-commerce, FSP data for a department store and a music CD chain, the HB model is compared against the benchmark Pareto/NBD model. The study demonstrates that recency-frequency data, in conjunction with customer behavior and characteristics, can provide important insights into direct marketing issues, such as the demographic profile of best customers and whether long-life customers spend more.

Retailers' Multichannel and Price Advertising Strategies

Abstract: Online retailing boasts two major advantages: convenience of home shopping and easy access to information. In this paper, I argue that these two features have important implications for retailers' channel and advertising decisions. Two major questions are addressed: When should a conventional bricks-and-mortar retailer adopt a multichannel strategy? When should a multichannel retailer use its website to advertise offline prices? Analysis shows that the answers hinge on the nature of the product, the retailer's costs, and the competitors' strategies as well as the competitiveness of the market. Multichannel retailing is not necessarily the best strategy for all retailers; no adoption, asymmetric adoption, and symmetric adoption of the strategy are all possible equilibria. Advertising the in-store prices online is not always optimal. Price advertising in multichannel retailing has a different effect when compared with conventional single-channel retailing. It helps coordinate the channels by shifting the sales from online to offline, which is particularly useful when margins online are relatively low. The finding that multichannel retailers can benefit from drawing consumers back to physical stores highlights the risk of boosting online sales without considering the adverse effect on the offline channel and indicates a shifting role of the Web in retailers' businesses.

My Mobile Music: An Adaptive Personalization System for Digital Audio Players

Abstract: New information technologies increasingly make it possible for service providers to adaptively personalize their service, fine-tuning the service over time for each individual customer, based on observation of that customer's behavior. We propose an “Adaptive Personalization System” and illustrate its implementation for digital audio players, a product category with rapidly expanding sales. The proposed system automatically downloads personalized playlists of MP3 songs into a consumer's mobile digital audio device and requires little proactive user effort (i.e., no explicit indication of preferences or ratings for songs). The system works in real time and is scalable to the massive data typically encountered in personalization applications. A simulation study shows the Adaptive Personalization System to outperform benchmark approaches. We implemented the Adaptive Personalization System on Palm PDAs and tested its performance with digital audio users. For actual users, the Adaptive Personalization System provides substantial improvements over benchmark approaches both in terms of the number of songs listened to and listening duration.

Assessing the External Validity of Analytical Results from National Brand and Store Brand Competition Models

Abstract: This research has three objectives: (i) to compile analytical results on national brand and store brand marketing obtained from mathematical models, (ii) to assess the external validity of those results and thus the applicability of the results to practice, and (iii) to identify avenues for further research on national brand and store brand competition. A total of 44 analytical results (29 related to retailer strategies and 15 related to manufacturer strategies) are compiled from a survey of literature published between 1966 and 2006. Three criteria are then used to assess the external validity of these results---robustness (R), empirical support (E), and credibility (C) (collectively, REC). Each result is quantitatively assessed (scored) using these three criteria. Robustness is measured as the total number of relevant market conditions for which the result has been shown to hold. Empirical support is measured as the number of independent empirical studies in which the findings are consistent with the analytical result. Credibility is measured as the believability of the theoretical result as perceived by experienced brand managers and retail executives. Thus, the REC scoring approach represents a triangulation of perspectives---robustness (modeler perspective), empirical support (empiricist perspective), and credibility (managerial perspective). In particular, this research serves in part as a bridge between scholars and practitioners in the context of national brand and store brand marketing.

Limited Edition Products: When and When Not to Offer Them

Abstract: Many brands today introduce limited edition (LE) products as part of their product line. However, little is known about the conditions under which a brand should introduce an LE product or the competitive implications of doing so. We investigate this issue using a game theoretic model of a market where two brands compete for consumers who desire exclusivity. Our analysis shows that adding an LE product has a positive direct effect on brand profits through the increased willingness of consumers to pay for such a product, but also has a negative strategic effect by increasing price competition between brands. These effects result in different conclusions depending on the nature of brand differentiation. When brands differ in quality, we show that only the high-quality brand may gain in comparison to a scenario where there are no LE products. Although a low-quality brand may offer an LE product as a defensive strategy, its profits are lower than would be in a world without LE products because of the negative strategic effect. When we consider brands that are differentiated on a horizontal attribute such as taste, we find that the negative strategic effects cause lower equilibrium profits if both brands introduce LE products. Yet brands cannot avoid introducing LE products because they face a prisoners' dilemma.

Dynamic Customer Management and the Value of One-to-One Marketing

Abstract: The concept of one-to-one marketing is intuitively appealing, but there is little research that investigates the value of individual-level marketing relative to segment-level or mass marketing. In this paper, we investigate the financial benefits of and computational challenges involved in one-to-one marketing. The analysis uses data from an online grocery and drug retailer. Like many retailers, this firm uses multiple promotional instruments including discount coupons, free shipping offers, and a loyalty program. We investigate the impact of customizing these promotions on the two most important consumer decisions: the decision to buy from the store and expenditure. Our modeling approach accounts for two sources of heterogeneity in consumers' responsiveness to various marketing mix elements: cross-sectional differences across consumers and temporal differences within consumers based on the purchase cycle. The model parameter estimates are fed into a dynamic programming model that determines the optimal number, sequence, and timing of promotions to maximize retailer profits. A series of policy simulations show that customizing promotions leads to a significant increase in profits relative to the firm's current practice of uniform promotions. However, the effectiveness of various promotions varies because of both cross-sectional differences in consumers as well within consumer heterogeneity due to purchase cycle factors. For instance, we find that free shipping tends to be the preferred instrument for re-acquiring lapsed customers, whereas an across-the-board price cut (via a discount coupon) is the most effective tool for managing the segment of most active customers. Interestingly, we find that customizing based on within-customer temporal heterogeneity contributes more to profitability than exploiting variations across consumers. This is important because the computational burden of implementing the dynamic optimization to account for cross-sectional heterogeneity is far greater than accounting for temporal heterogeneity. Furthermore, targeting promotions based only on timing rather than the nature and magnitude of the offers across consumers alleviates the public relations risks of price discrimination. Implications for marketing managers are also discussed.

A Theory of Combative Advertising

Abstract: In mature markets with competing firms, a common role for advertising is to shift consumer preferences towards the advertiser in a tug-of-war, with no effect on category demand. In this paper, we analyze the effect of such “combative” advertising on market power. We show that, depending on the nature of consumer response, combative advertising can reduce price competition to benefit competing firms. However, it can also lead to a procompetitive outcome where individual firms advertise to increase their own profitability, but collectively become worse off. This is because combative advertising can intensify price competition such that an “advertising war” leads to a “price war.” Similar to price competition, advertising competition can result in a prisoner's dilemma where all competing firms make less profit even when the effect of each firm's advertising is to enhance consumer preferences in its favor. Given such procompetitive effects, we further show that cost of combative advertising could be a blessing in disguise---higher unit cost of advertising resulting in lower equilibrium levels of advertising, leading to higher prices and profits. We conduct a laboratory experiment to investigate how combative advertising by competing brands influences consumer preferences. Our experimental analysis offers strong support for our conclusions.

Research Note---The Traveling Salesman Goes Shopping: The Systematic Deviations of Grocery Paths from TSP Optimality

Abstract: We examine grocery shopping paths using the traveling salesman problem (TSP) as a normative frame of reference. We define the TSP-path for each shopper as the shortest path that connects all of his purchases. We then decompose the length of each observed path into three components: the length of the TSP-path, the additional distance because of order deviation (i.e., not following the TSP-order of category purchases), and the additional distance because of travel deviation (i.e., not following the shortest point-to-point route). We explore the relationship between these deviations and different aspects of in-store shopping/purchase behavior. Among other things, our results suggest that (1) a large proportion of trip length is because of travel deviation; (2) paths that deviate substantially from the TSP solution are associated with larger shopping baskets; (3) order deviation is strongly associated with purchase behavior, while travel deviation is not; and (4) shoppers with paths closer to the TSP solution tend to buy more from frequently purchased product categories.

Strategic Assortment Reduction by a Dominant Retailer

Abstract: In certain product categories, large discount retailers are known to offer shallower assortments than traditional retailers. In this paper, we investigate the competitive incentives for such assortment decisions and the implications for manufacturers' distribution strategies. Our results show that if one retailer has the channel power to determine its assortment first, then it can strategically reduce its assortment by carrying only the popular variety while simultaneously inducing the rival retailer to carry both the specialty and popular varieties. The rival retailer then bears higher assortment costs, which leads to relaxed price competition for the commonly carried popular variety. We also show that when the manufacturer has relative channel power, it chooses alternatively to distribute both product varieties through both retailers. Our analysis suggests, therefore, that when a retailer becomes dominant in the distribution channel, it facilitates retail segmentation into discount shops, carrying limited product lines, and specialty shops carrying wider assortments. We also illustrate how retailer power leading to strategic assortment reduction can lead to lower consumer surplus.

Understanding the Role of Trade-Ins in Durable Goods Markets: Theory and Evidence

Abstract: The act of trading in a used car as partial payment for a new car resonates with practically all consumers. Such transactions are prevalent in many other durable goods markets, ranging from golf clubs to CT scanners. What roles do trade-ins play in these markets? What motivates the seller to set up a channel to facilitate trade-ins? Intuitively, accepting a trade-in would appear to stimulate demand for the producer's product, but facilitating the resale of these used goods that substitute for new goods might also increase cannibalization. Although such transactions involve billions of dollars, we know relatively little about this practice from the extant research literature. This paper develops an analytical model that incorporates key features of real-world durable goods markets: (i) coexistence of new and used goods markets, (ii) consumer heterogeneity with respect to quality sensitivity, (iii) firms that anticipate the cannibalization problem arising from the coexistence of new and used goods, and (iv) lemon problems in resale markets, whereby sellers of used goods are better informed than buyers about the quality of their particular item. In our analysis, a trade-in policy amounts to an intervention by the firm in the used goods market, which reduces inefficiencies arising from the lemon problem. It motivates owners to purchase new goods and reduces their proclivity to hold on to purchased goods because of the low price the latter would fetch in a lemon market. We also show that trade-in programs are more valuable for less reliable products, as well as for products that deteriorate more slowly. Our analysis shows that producers in durable goods markets should consider trade-in programs as a matter of routine. Despite cannibalization concerns arising from a more active resale market, a producer's profits will inevitably rise from introducing trade-ins, given pervasive lemon problems. We test the key predictions of the model about price and volume of trade by assembling a data set of transactions of U.S. automobile consumers and find broad support for our model.

Estimating the Value of Brand Alliances in Professional Team Sports

Abstract: Brands often form alliances to enhance their brand equities. In this paper, we examine the alliances between professional athletes (athlete brands) and sports teams (team brands) in the National Basketball Association (NBA). Athletes and teams match to maximize the total added value created by the brand alliance. To understand this total value, we estimate a structural two-sided matching model using a maximum score method. Using data on the free-agency contracts signed in the NBA during the four-year period from 1994 to 1997, we find that both older players and players with higher performance are more likely to match with teams with more wins. However, controlling for performance, we find that brand alliances between high brand equity players (defined as receiving enough votes to be an all-star starter) and medium brand equity teams (defined by stadium and broadcast revenues) generate the highest value. This suggests that top brands are not necessarily best off matching with other top brands. We also provide suggestive evidence that the maximum salary policy implemented in 1998 influenced matches based on brand equity spillovers more than matches based on performance complementarities.

Optimal Product Line Design When Consumers Exhibit Choice Set-Dependent Preferences

Abstract: In a market of consumers with varying willingness to pay, using product line as a discrimination tool may extract higher profits than serving all consumers with a single product. Local context effects, however, point to yet another consideration in designing product lines: how the appeal of a product changes with the context provided by other products in the choice set. I present a model of product line design that incorporates both discrimination and context management goals and offers recommendations for the variety and positioning of products. To this end, the model makes use of a framework that allows preferences to be choice set dependent. Given this framework, I study how the firm manages externalities between products created by such dependencies. The firm creates distortions above and beyond those resulting from discrimination motives alone. For example, in a vertically differentiated market for quality, quality distortions exist even for the consumers with the highest valuations. The range of quality provisions, given the number of products, is compressed as the relative importance of unfavorable comparisons among products increases. Surprisingly, this compression may even lead the firm to forego discrimination among consumers regardless of the cost of offering distinct products.

Cross-National Logo Evaluation Analysis: An Individual-Level Approach

Abstract: The universality of design perception and response is tested using data collected from 10 countries: Argentina, Australia, China, Germany, Great Britain, India, The Netherlands, Russia, Singapore, and the United States. A Bayesian, finite-mixture, structural equation model is developed that identifies latent logo clusters while accounting for heterogeneity in evaluations. The concomitant variable approach allows cluster probabilities to be country specific. Rather than a priori defined clusters, our procedure provides a posteriori cross-national logo clusters based on consumer response similarity. Our model reduces the 10 countries to three cross-national clusters that respond differently to logo design dimensions: the West, Asia, and Russia. The dimensions underlying design are found to be similar across countries, suggesting that elaborateness, naturalness, and harmony are universal design dimensions. Responses affect, shared meaning, subjective familiarity, and true and false recognition to logo design dimensions elaborateness, naturalness, and harmony and elements repetition, proportion, and parallelism are also relatively consistent, although we find minor differences across clusters. Our results suggest that managers can implement a global logo strategy, but they also can optimize logos for specific countries if desired.