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<title>Marketing Science current issue</title>
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<prism:eIssn>1526-548X</prism:eIssn>
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<title>Marketing Science</title>
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<link>http://mktsci.journal.informs.org</link>
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<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/403?rss=1">
<title><![CDATA[Editorial--Analytical Transparency]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/403?rss=1</link>
<description><![CDATA[
<p>No abstract available.</p>
]]></description>
<dc:creator><![CDATA[Bradlow, E. T., Coughlan, A. T.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1090.0504</dc:identifier>
<dc:title><![CDATA[Editorial--Analytical Transparency]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>404</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>403</prism:startingPage>
<prism:section>Articles</prism:section>
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<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/405?rss=1">
<title><![CDATA[The Option Value of Returns: Theory and Empirical Evidence]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/405?rss=1</link>
<description><![CDATA[
<p>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.</p>
<p>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.</p>
]]></description>
<dc:creator><![CDATA[Anderson, E. T., Hansen, K., Simester, D.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0430</dc:identifier>
<dc:title><![CDATA[The Option Value of Returns: Theory and Empirical Evidence]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>423</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>405</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/424?rss=1">
<title><![CDATA[Heterogeneous Learning and the Targeting of Marketing Communication for New Products]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/424?rss=1</link>
<description><![CDATA[
<p>New product launches are often accompanied by extensive marketing communication campaigns. Firms' allocation decisions for these marketing communication expenditures have two dimensions&mdash;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.</p>
<p>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.</p>
<p>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&mdash;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.</p>
]]></description>
<dc:creator><![CDATA[Narayanan, S., Manchanda, P.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0410</dc:identifier>
<dc:title><![CDATA[Heterogeneous Learning and the Targeting of Marketing Communication for New Products]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>441</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>424</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/442?rss=1">
<title><![CDATA[Do Innovations Really Pay Off? Total Stock Market Returns to Innovation]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/442?rss=1</link>
<description><![CDATA[
<p>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.</p>
<p>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.</p>
]]></description>
<dc:creator><![CDATA[Sood, A., Tellis, G. J.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0407</dc:identifier>
<dc:title><![CDATA[Do Innovations Really Pay Off? Total Stock Market Returns to Innovation]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>456</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>442</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/457?rss=1">
<title><![CDATA[The Benefits of Downstream Information Acquisition]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/457?rss=1</link>
<description><![CDATA[
<p>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&mdash;the <I>efficiency</I> effect that improves retail pricing decision making in an uncertain environment, and the <I>strategic</I> 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.</p>
]]></description>
<dc:creator><![CDATA[Guo, L.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0408</dc:identifier>
<dc:title><![CDATA[The Benefits of Downstream Information Acquisition]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>471</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>457</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/472?rss=1">
<title><![CDATA[Direct-to-Consumer Advertising of Prescription Drugs: A Strategic Analysis]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/472?rss=1</link>
<description><![CDATA[
<p>Consumers cannot purchase a prescription drug without a prescription from a physician, yet many prescription drugs are promoted to consumers with the help of direct-to-consumer (DTC) advertising. In this paper, we propose and test a competitive model of DTC advertising. We find that the brand specificity of DTC advertising can have an inverted U-shaped relationship with detailing, DTC advertising, and profits. Furthermore, an increase in the cross-price sensitivity between competing prescription drugs is not always detrimental to firm profits. A laboratory test lends qualitative support to some of our model predictions. We also discuss potential implications of DTC advertising for generic drugs and over-the-counter drugs.</p>
]]></description>
<dc:creator><![CDATA[Amaldoss, W., He, C.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0411</dc:identifier>
<dc:title><![CDATA[Direct-to-Consumer Advertising of Prescription Drugs: A Strategic Analysis]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>487</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>472</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/488?rss=1">
<title><![CDATA[Voluntary Quality Disclosure and Market Interaction]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/488?rss=1</link>
<description><![CDATA[
<p>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 <I>U-shaped</I> 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.</p>
]]></description>
<dc:creator><![CDATA[Guo, L., Zhao, Y.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0418</dc:identifier>
<dc:title><![CDATA[Voluntary Quality Disclosure and Market Interaction]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>501</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>488</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/502?rss=1">
<title><![CDATA[Benchmarking Performance in Retail Chains: An Integrated Approach]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/502?rss=1</link>
<description><![CDATA[
<p>Standardizing performance expectations across different outlets within a chain, differing in their individual features, their consumers, and the nature of competition they face, can be an onerous task. We develop an integrated, nonlinear, block group-level market share model of store expectations that draws upon the existing trade area as well as store performance literatures. By incorporating and normalizing a large number of external and internal factors impacting performance, we are able to offer a means for the retailer to determine equitable standards. The model is estimated using a variation of the maximum-likelihood estimation, on a data set fashioned from several sources and aggregated at the block group and store levels. Finally, we propose a set of indices that allows us to evaluate relative performances of stores and regions given the competitive environments they face. We find that a block group-level model offers a better fit, as well as significantly richer implications, than a traditional store-level model. Results show that a significant number of stores operate well below their expected levels, an insight not obvious from the raw numbers used to report store statistics to upper management.</p>
]]></description>
<dc:creator><![CDATA[Gauri, D. K., Pauler, J. G., Trivedi, M.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0421</dc:identifier>
<dc:title><![CDATA[Benchmarking Performance in Retail Chains: An Integrated Approach]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>515</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>502</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/516?rss=1">
<title><![CDATA[Price Competition in Markets with Consumer Variety Seeking]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/516?rss=1</link>
<description><![CDATA[
<p>We investigate price competition between firms in markets characterized by consumer variety seeking. While previous research has addressed the effect of consumer inertia on prices, there exists no research on the effects of variety seeking on price competition. Our study fills this gap in the literature. Using a two-period duopoly framework as in Klemperer's analysis of inertial markets, we show that the noncooperative pricing equilibrium in a market with consumer variety seeking may be the same as the collusive outcome in an otherwise identical market without variety seeking. Specifically, our variety-seeking model implies tacit collusion between firms in <I>both</I> periods, unlike the inertia model of Klemperer that implies tacit collusion between firms only in the <I>second</I> period but implies fierce price competition in the first period. When consumers are assumed to have rational expectations about future prices, the implied first-period prices increase further, which is consistent with what Klemperer finds in an inertial market. To summarize, while our variety-seeking analyses support two key results (pertaining to second-period prices and rational expectations) previously derived for inertial markets by Klemperer, they depart from one key result (pertaining to first-period prices).</p>
]]></description>
<dc:creator><![CDATA[Seetharaman, P. B., Che, H.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0434</dc:identifier>
<dc:title><![CDATA[Price Competition in Markets with Consumer Variety Seeking]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>525</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>516</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/526?rss=1">
<title><![CDATA[Financing as a Marketing Strategy]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/526?rss=1</link>
<description><![CDATA[
<p>This paper investigates the issues concerning a film producer that finances production costs not only by the conventional funding from an institutional investor, but also by "Internet funding," financing through the Internet from so-called netizen investors. In Internet funding, netizen investors engage in word-of-mouth activities. Assuming that information asymmetry exists between the producer and investors, we investigate how the Internet funding size varies with the word-of-mouth effect, the monitoring effect of the institutional investor, and the bargaining power of the producer over investors. When the producer has no bargaining power, the Internet funding size is determined by balancing the word-of-mouth effect with the monitoring effect by the institutional investment. If there is no word-of-mouth effect, there may be no Internet funding, because netizen investors interpret Internet funding as an indicator of a negative profit. When the producer has high bargaining power, full Internet funding is possible if the information asymmetry of the film quality is resolved. We discuss how information asymmetry can be resolved by the monitoring of the film quality, the producer's reputation, or the insurance on investment returns. Our model helps to capture several interesting aspects of Internet funding in the Korean film industry.</p>
]]></description>
<dc:creator><![CDATA[Seog, S. H., Hyun, Y. J.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0423</dc:identifier>
<dc:title><![CDATA[Financing as a Marketing Strategy]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>540</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>526</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/541?rss=1">
<title><![CDATA["Counting Your Customers" One by One: A Hierarchical Bayes Extension to the Pareto/NBD Model]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/541?rss=1</link>
<description><![CDATA[
<p>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.</p>
<p>Using three different types of databases&mdash;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.</p>
]]></description>
<dc:creator><![CDATA[Abe, M.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1090.0502</dc:identifier>
<dc:title><![CDATA["Counting Your Customers" One by One: A Hierarchical Bayes Extension to the Pareto/NBD Model]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>553</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>541</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/554?rss=1">
<title><![CDATA[Statement from the Editor Regarding "'Counting Your Customers' One by One: A Hierarchical Bayes Extension to the Pareto/NBD Model"]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/554?rss=1</link>
<description><![CDATA[
<p>No abstract available.</p>
]]></description>
<dc:creator><![CDATA[Bradlow, E. T.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0383</dc:identifier>
<dc:title><![CDATA[Statement from the Editor Regarding "'Counting Your Customers' One by One: A Hierarchical Bayes Extension to the Pareto/NBD Model"]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>554</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>554</prism:startingPage>
<prism:section>Articles</prism:section>
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<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/555?rss=1">
<title><![CDATA[Research Note--How Much Should You Invest in Each Customer Relationship? A Competitive Strategic Approach]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/555?rss=1</link>
<description><![CDATA[
<p>We analyze firms' decisions to invest in customer relationship management (CRM) initiatives such as acquisition and retention in a competitive context, a topic largely ignored in past CRM research. We characterize each customer by her intrinsic preference towards each firm, the contribution margin she generates for each firm, and her responsiveness to each firm's retention and acquisition efforts. We show that a firm should invest most heavily in retaining those customers that exhibit moderate responsiveness to its CRM efforts. Further, a firm should most aggressively seek to attract those customers that exhibit moderate responsiveness to their provider's CRM efforts and those that are moderately profitable for their current provider. Investing more in customers that are more responsive does not always lead to higher firm profits, because stronger competition for such customers tends to erode the effects of higher CRM efforts of an individual firm. When firms develop a customer relationship over time to generate higher contribution margin or customer responsiveness, we show that such developments may not always be desirable, because sometimes these future benefits may lead to more intense competition and hence lower profits for both firms.</p>
]]></description>
<dc:creator><![CDATA[Musalem, A., Joshi, Y. V.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0424</dc:identifier>
<dc:title><![CDATA[Research Note--How Much Should You Invest in Each Customer Relationship? A Competitive Strategic Approach]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>565</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>555</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/566?rss=1">
<title><![CDATA[Research Note--The Traveling Salesman Goes Shopping: The Systematic Deviations of Grocery Paths from TSP Optimality]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/566?rss=1</link>
<description><![CDATA[
<p>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 <I>order deviation</I> (i.e., not following the TSP-order of category purchases), and the additional distance because of <I>travel deviation</I> (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.</p>
]]></description>
<dc:creator><![CDATA[Hui, S. K., Fader, P. S., Bradlow, E. T.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0402</dc:identifier>
<dc:title><![CDATA[Research Note--The Traveling Salesman Goes Shopping: The Systematic Deviations of Grocery Paths from TSP Optimality]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>572</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>566</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/573?rss=1">
<title><![CDATA[Research Note--Wine Journalism--Marketing or Consumers' Guide?]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/573?rss=1</link>
<description><![CDATA[
<p>This article explores some aspects of wine journalism in Norwegian newspapers. Two issues are discussed: First, are wine sales influenced by wine journalists' reviews? Second, do experts agree on what makes a good wine buy? The results show that wine sales are indeed significantly influenced by the judgements of wine critics; a 10% rise in newspapers' scores in Norway was accompanied by an average increase of 16%&ndash;18% in sales figures for table wines. The effect of wine reviews varied somewhat from newspaper to newspaper. It proved difficult to establish criteria for a good wine buy that are objective and independent of the person making the judgement. The journalists gave no unanimous recommendation of good wine buys to the consumers; the same wine could get good reviews in some papers and might well receive run-of-the-mill reviews in others. However, a majority of the reviewers seemed to agree in the ranking of most of the wines, even if the absolute value of the scores differed.</p>
]]></description>
<dc:creator><![CDATA[Horverak, O.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1090.0489</dc:identifier>
<dc:title><![CDATA[Research Note--Wine Journalism--Marketing or Consumers' Guide?]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>579</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>573</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/580?rss=1">
<title><![CDATA[Research Note--Price-Matching Guarantees, Retail Competition, and Product-Line Assortment]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/580?rss=1</link>
<description><![CDATA[
<p>Price-matching guarantees (PMGs) are offers to match a competitor's price on a specific item. Such guarantees are extremely common in U.S. retail practice, and their impact has been studied in several published papers. The existing analytic literature models each retailer as a single-product seller; most work assumes that each retailer's product is identical with (or completely substitutable for) the competitor's product. In reality, competing retailers often sell multiple products, and these products do not always overlap, or may overlap partially but not totally. Furthermore, retailers that offer PMGs routinely exclude certain offerings from PMG coverage. This raises the interesting question of how product variety and product-stocking factors affect retailer decisions about offering PMGs.</p>
<p>In this paper, we simultaneously consider three factors of retailing importance that imply results consistent with PMG use and nonuse: the ability to choose to stock the same product as, or a product differentiated from, a competitor's offering; the possibility of shelf-space limitations on the ability to stock complete variety; and the category-demand-enhancing effect of variety. These are sensible and realistic descriptive factors shaping retailers' product and pricing decisions, and because they have not been considered jointly in the prior literature on PMGs, their joint consideration helps to expand our understanding of the drivers of PMG implementation and impact. In the presence of these three factors, we examine retailers' decisions about whether to offer a PMG, what product(s) to stock, and how to price the product(s) stocked.</p>
<p>Our results show that shelf-space limitations have an important influence on PMG provision: in particular, when retailers are shelf-space constrained, and product substitutability in the category is sufficiently large, choosing to use PMGs (which by definition also requires stocking identical products) is strictly less profitable than enduring Bertrand (price) competition but enjoying retail product differentiation. The result that PMGs can be profit-reducing relative to head-to-head retail competition is a novel one, driven in our model by the opportunity costs of stocking identical products, i.e., the inability to benefit from the demand-enhancing effects of variety and the differential (small or large) between Bertrand pricing and PMG pricing levels. We further show that under asymmetric shelf-space availability, either product variety will be severely limited or retailers will offer a different array of products. Weak substitution between products leads to the latter, with pricing between the differentiated products Bertrand and monopoly levels; strong substitution leads to the former, with pricing at the monopoly level. Our results also show that with unlimited shelf space, both competing retailers offer PMGs, stock the entire available product line, and enjoy monopoly pricing. Given our focus on product variety issues, we also relate our results to the literature on branded variants.</p>
<p>Our results demonstrate that the nature of product variety, the availability of retail shelf space, and the category-demand-enhancing effect of variety are key market characteristics that jointly and strongly affect the optimality of PMGs and the resulting pricing and profitability characteristics of the market.</p>
]]></description>
<dc:creator><![CDATA[Coughlan, A. T., Shaffer, G.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0404</dc:identifier>
<dc:title><![CDATA[Research Note--Price-Matching Guarantees, Retail Competition, and Product-Line Assortment]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>588</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>580</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/589?rss=1">
<title><![CDATA[Research Note--The Researcher as a Consumer of Scientific Publications: How Do Name-Ordering Conventions Affect Inferences About Contribution Credits?]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/589?rss=1</link>
<description><![CDATA[
<p>When researchers from different fields with different norms collaborate, the question arises of how name-ordering conventions are chosen and how they affect contribution credits. In this paper, we answer these questions by studying two disciplines that exemplify the two cornerstones of name-ordering conventions: lexicographical ordering (i.e., alphabetical ordering, endorsed in economics) and nonlexicographical ordering (i.e., ordering according to individual contributions, endorsed in psychology). Inferences about credits are unambiguous in the latter arrangement but imperfect in the former, because alphabetical listing can reflect ordering according to individual contributions by chance.</p>
<p>We contrast the fields of economics and psychology with marketing, a discipline heavily influenced by both. Based on archival data, consisting of more than 38,000 journal articles, we show that the three fields have different ordering practices. In two empirical studies with 351 faculty and graduate student participants from all three disciplines, as well as in a computer simulation, we show that ordering practices systematically affect and shape the allocation of perceived contributions and credit. Whereas strong disciplinary norms in economics and psychology govern the allocation of contribution credits, a more heterogeneous picture emerges for marketing. This lack of strong norms has detrimental effects in terms of assigned contribution credits.</p>
]]></description>
<dc:creator><![CDATA[Maciejovsky, B., Budescu, D. V., Ariely, D.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0406</dc:identifier>
<dc:title><![CDATA[Research Note--The Researcher as a Consumer of Scientific Publications: How Do Name-Ordering Conventions Affect Inferences About Contribution Credits?]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>598</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>589</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/599?rss=1">
<title><![CDATA[Research Note--Should Captive Sardines Be Compensated? Serving Customers in a Confined Zone]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/599?rss=1</link>
<description><![CDATA[
<p>Many services are delivered to a (large) number of customers simultaneously within a confined zone (e.g., restaurants, resorts, trains, and airplanes). Under unexpected high demand, customers experience discomfort from two major sources: (a) the <I>sardine effect</I> that arises when too many customers (i.e., sardines) compete for space and service resources, and (b) the <I>captivity effect</I> that results from an exit cost incurred by customers who self-select to "escape" the unpleasant service. This paper investigates the optimal compensation and pricing policies under these two effects. We find that offering compensation to sardines can improve profit and social welfare. However, consumers do <I>not</I> benefit when compensated for the discomfort from crowding. This paper also provides insights by exploring the impact of changes in the two effects on price and profit.</p>
]]></description>
<dc:creator><![CDATA[Chen, R. R., Gerstner, E., Yang, Y.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1080.0428</dc:identifier>
<dc:title><![CDATA[Research Note--Should Captive Sardines Be Compensated? Serving Customers in a Confined Zone]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>608</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>599</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/609?rss=1">
<title><![CDATA[Focus on Authors]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/609?rss=1</link>
<description><![CDATA[
<p>No abstract available.</p>
]]></description>
<dc:creator><![CDATA[]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1090.0510</dc:identifier>
<dc:title><![CDATA[Focus on Authors]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>613</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>609</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/614?rss=1">
<title><![CDATA[Call for Submissions--The 2009 ISMS-MSI Practice Prize Competition]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/614?rss=1</link>
<description><![CDATA[
<p>No abstract available.</p>
]]></description>
<dc:creator><![CDATA[]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1090.0501</dc:identifier>
<dc:title><![CDATA[Call for Submissions--The 2009 ISMS-MSI Practice Prize Competition]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>614</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>614</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

<item rdf:about="http://mktsci.journal.informs.org/cgi/content/short/28/3/615?rss=1">
<title><![CDATA[Call for Papers--Special Issue of Marketing Science on User-Generated Content (UGC): Deadline: January 15, 2010]]></title>
<link>http://mktsci.journal.informs.org/cgi/content/short/28/3/615?rss=1</link>
<description><![CDATA[
<p>No abstract available.</p>
]]></description>
<dc:creator><![CDATA[Fader, P. S., Winer, R. S.]]></dc:creator>
<dc:date>2009-06-10</dc:date>
<dc:identifier>info:doi/10.1287/mksc.1090.0503</dc:identifier>
<dc:title><![CDATA[Call for Papers--Special Issue of Marketing Science on User-Generated Content (UGC): Deadline: January 15, 2010]]></dc:title>
<dc:publisher>INFORMS</dc:publisher>
<prism:number>3</prism:number>
<prism:volume>28</prism:volume>
<prism:endingPage>615</prism:endingPage>
<prism:publicationDate>2009-05-01</prism:publicationDate>
<prism:startingPage>615</prism:startingPage>
<prism:section>Articles</prism:section>
</item>

</rdf:RDF>