Showing papers in "Marketing Science in 2006"

Brands and Branding: Research Findings and Future Priorities

Abstract: Branding has emerged as a top management priority in the last decade due to the growing realization that brands are one of the most valuable intangible assets that firms have. Driven in part by this intense industry interest, academic researchers have explored a number of different brand-related topics in recent years, generating scores of papers, articles, research reports, and books. This paper identifies some of the influential work in the branding area, highlighting what has been learned from an academic perspective on important topics such as brand positioning, brand integration, brand-equity measurement, brand growth, and brand management. The paper also outlines some gaps that exist in the research of branding and brand equity and formulates a series of related research questions. Choice modeling implications of the branding concept and the challenges of incorporating main and interaction effects of branding as well as the impact of competition are discussed.

Research on Innovation: A Review and Agenda for Marketing Science

Abstract: Innovation is one of the most important issues in business research today. It has been studied in many independent research traditions. Our understanding and study of innovation can benefit from an integrative review of these research traditions. In so doing, we identify 16 topics relevant to marketing science, which we classify under five research fields: Consumer response to innovation, including attempts to measure consumer innovativeness, models of new product growth, and recent ideas on network externalities; Organizations and innovation, which are increasingly important as product development becomes more complex and tools more effective but demanding;. Market entry strategies, which includes recent research on technology revolution, extensive marketing science research on strategies for entry, and issues of portfolio management; Prescriptive techniques for product development processes, which have been transformed through global pressures, increasingly accurate customer input, Web-based communication for dispersed and global product design, and new tools for dealing with complexity over time and across product lines; Defending against market entry and capturing the rewards of innovating, which includes extensive marketing science research on strategies of defense, managing through metrics, and rewards to entrants. For each topic, we summarize key concepts and highlight research challenges. For prescriptive research topics, we also review current thinking and applications. For descriptive topics, we review key findings.

Customer Metrics and Their Impact on Financial Performance

Abstract: The need to understand the relationships among customer metrics and profitability has never been more critical. These relationships are pivotal to tracking and justifying firms' marketing expenditures, which have come under increasing pressure. The objective of this paper is to integrate existing knowledge and research about the impact of customer metrics on firms' financial performance. We investigate both unobservable or perceptual customer metrics (e.g., customer satisfaction) and observable or behavioral metrics (e.g., customer retention and lifetime value). We begin with an overview of unobservable and observable metrics, showing how they have been measured and modeled in research. We next offer nine empirical generalizations about the linkages between perceptual and behavioral metrics and their impact on financial performance. We conclude the paper with future research challenges.

Marketing Models of Service and Relationships

Abstract: Given the growth of the service sector, and advances in information technology and communications that facilitate the management of relationships with customers, models of service and relationships are a fast-growing area of marketing science. This article summarizes existing work in this area and identifies promising topics for future research. Models of service and relationships can help managers manage service more efficiently, customize service more effectively, manage customer satisfaction and relationships, and model the financial impact of those customer relationships. Models for managing service have often emphasized analytical approaches to pricing, but emerging issues such as the trade-off between privacy and customization are attracting increasing attention. The trade-offs between productivity and customization have also been addressed by both analytical and empirical models, but future research in the area of service customization will likely place increased emphasis on e-service and truly personalized interactions. Relationship models will focus less on models of customer expectations and length of relationship, and more on modeling the effects of dynamic marketing interventions with individual customers. The nature of service relationships increasingly leads to financial impact being assessed within customer and across product, rather than the traditional reverse, suggesting the increasing importance of analyzing customer lifetime value (CLV) and managing the firm's customer equity.

The Motion Picture Industry: Critical Issues in Practice, Current Research, and New Research Directions

Abstract: The motion picture industry has provided a fruitful research domain for scholars in marketing and other disciplines. The industry has high economic importance and is appealing to researchers because it offers both rich data that cover the entire product lifecycle for many new products and because it provides many unsolved “puzzles.” Although the amount of scholarly research in this area is rapidly growing, its impact on practice has not been as significant as in other industries (e.g., consumer packaged goods). In this article, we discuss critical practical issues for the motion picture industry, review existing knowledge on those issues, and outline promising research directions. Our review is organized around the three key stages in the value chain for theatrical motion pictures: production, distribution, and exhibition. Focusing on what we believe are critical managerial issues, we propose various conjectures---framed either as research challenges or specific research hypotheses---related to each stage in the value chain and often involved in understanding consumer movie-going behavior.

Promotional Chat on the Internet

Abstract: Chat rooms, recommendation sites, and customer review sections allow consumers to overcome geographic boundaries and to communicate based on mutual interests. However, marketers also have incentives to supply promotional chat or reviews in order to influence the consumers' evaluation of their products. Moreover, firms can disguise their promotion as consumer recommendations due to the anonymity afforded by online communities. We explore this new setting where advertising and word of mouth become perfect substitutes because they appear indistinguishable to the consumer. Specifically, we investigate here whether word of mouth remains credible and whether firms choose to devote more resources promoting their inferior or superior products. We develop a game theoretic model in which two products are differentiated in their value to the consumer. Unlike the firms, the consumers are uncertain about the products' quality. The consumers read messages online that help them decide on the identity of the superior product. We find a unique equilibrium where online word of mouth is persuasive despite the promotional chat activity by competing firms. In this equilibrium, firms spend more resources promoting inferior products, in striking contrast to existing advertising literature. In addition, we discuss consumer welfare implications and how other marketing strategies might interact with promotional chat.

The Value of Different Customer Satisfaction and Loyalty Metrics in Predicting Business Performance

Abstract: Managers commonly use customer feedback data to set goals and monitor performance on metrics such as “Top 2 Box” customer satisfaction scores and “intention-to-repurchase” loyalty scores. However, analysts have advocated a number of different customer feedback metrics including average customer satisfaction scores and the number of “net promoters” among a firm's customers. We empirically examine which commonly used and widely advocated customer feedback metrics are most valuable in predicting future business performance. Using American Customer Satisfaction Index data, we assess the linkages between six different satisfaction and loyalty metrics and COMPUSTAT and CRSP data-based measures of different dimensions of firms' business performance over the period 1994--2000. Our results indicate that average satisfaction scores have the greatest value in predicting future business performance and that Top 2 Box satisfaction scores also have good predictive value. We also find that while repurchase likelihood and proportion of customers complaining have some predictive value depending on the specific dimension of business performance, metrics based on recommendation intentions (net promoters) and behavior (average number of recommendations) have little or no predictive value. Our results clearly indicate that recent prescriptions to focus customer feedback systems and metrics solely on customers' recommendation intentions and behaviors are misguided.

Idea Generation, Creativity, and Incentives

Abstract: Idea generation (ideation) is critical to the design and marketing of new products, to marketing strategy, and to the creation of effective advertising copy. However, there has been relatively little formal research on the underlying incentives with which to encourage participants to focus their energies on relevant and novel ideas. Several problems have been identified with traditional ideation methods. For example, participants often free ride on other participants' efforts because rewards are typically based on the group-level output of ideation sessions. This paper examines whether carefully tailored ideation incentives can improve creative output. I begin by studying the influence of incentives on idea generation using a formal model of the ideation process. This model illustrates the effect of rewarding participants for their impact on the group and identifies a parameter that mediates this effect. I then develop a practical, web-based asynchronous “ideation game,” which allows the implementation and test of various incentive schemes. Using this system, I run two experiments that demonstrate that incentives do have the capability to improve idea generation, confirm the predictions from the theoretical analysis, and provide additional insight on the mechanisms of ideation.

How Does Objective Quality Affect Perceived Quality? Short-Term Effects, Long-Term Effects, and Asymmetries

Abstract: We examine the relationship between objective and perceived quality for 241 products in 46 product categories over a period of 12 years. On average, we find that the effect of a change in objective quality is not fully reflected in customer perceptions of quality until after about six years. In the first year after a quality change, only about 20% of the total effect over time is realized. These effects are significantly larger and quicker for a decrease in quality relative to an equivalent increase. Interestingly, we also find that brand reputation has a “double” advantage. High-reputation brands are rewarded three years quicker for an increase in quality and punished one year slower for a decrease in quality compared to low-reputation brands. These differences in response time are a meaningful measure of brand equity. Finally, we examine the differences in quality effects across several product- and category-specific variables and discuss the implications of our findings.

Absorptive Capacity in High-Technology Markets: The Competitive Advantage of the Haves

Abstract: The rapid rate of knowledge obsolescence in many high-technology markets makes it imperative for firms to renew their technological bases constantly. Given its critical importance, excellence in renewal of technological base would serve as a dynamic capability. Drawing on past literature, we identify this dynamic capability associated with acquiring and utilizing external technological know-how with the notion of absorptive capacity (AC). We ask the following questions: (a) What would cause some firms to have a higher AC than others? and, (b) What is the impact of AC on a firm's profitability? We build a conceptual framework suggesting that marketing, R&D, and operations capabilities have a significant positive impact on a firm's AC. We test our framework on a data set of firms in high-technology markets. Using an econometric technique called stochastic frontier estimation, we infer the AC of firms from an observation of the know-how they actually absorb. We find that firm-specific capabilities significantly impact AC. Also, we find that AC has a significant impact on profitability and that this impact is moderated by the pace of technological change: the greater the pace of change, the greater the impact.

Research Note---The Benefits of Personalized Pricing in a Channel

Abstract: In this note, we explore channel interactions in an information-intensive environment where the retailer can implement personalized pricing and the manufacturer can leverage both personalized pricing and entry into a direct distribution channel. We study whether a retailer can benefit from personalized pricing and how upstream personalized pricing or entry into a direct distribution channel affects the allocation of channel profit. We find that the retailer is worse off because of its own or upstream personalized pricing, even when the retailer is a monopoly. However, it may still be optimal for the retailer to embrace personalized pricing in order to reap the strategic benefit of deterring the manufacturer from selling direct and targeting end consumers.

Returns on Business-to-Business Relationship Marketing Investments: Strategies for Leveraging Profits

Abstract: Firms invest heavily in different types of business-to-business relationship marketing activities in the belief that such programs bolster their bottom line. In this study, we develop and test a conceptual model that links customer-specific relationship marketing investments to short-term, customer-specific financial outcomes. Data from a matched set of 313 business customers covered by 143 salespeople of 34 selling firms indicate that investments in social relationship marketing pay off handsomely, financial relationship marketing investments do not, and structural relationship marketing investments are economically viable for customers serviced frequently. We conceptualize relationship marketing in a context involving nested participants (customers, salespeople, selling firms) and employ a hierarchical linear modeling approach to account for observations that are not independent. Across the three hierarchical levels, the impact of the financial, social, and structural components of relationship marketing investments and the potential moderating factors offer valuable insights into contextual factors and managerial strategies for leveraging relationship marketing investments. In an attempt to suggest normative guidelines to managers, we extend our analysis to a simple resource allocation model that describes the optimal mix of relationship marketing resources based on firm strategies.

Understanding Store-Brand Purchase Behavior Across Categories

Abstract: This paper investigates whether the tendency to buy store brand is category specific, or an enduring consumer trait. We develop a multicategory brand-choice model with a factor-analytic structure on the covariance matrix of the coefficients. The methodology allows us to elicit the basic latent tendency for a household to buy store brands, while controlling for other causes such as price sensitivity. The model is applied to a set of ten food and nonfood product categories. We find strong evidence of correlations in household preferences for store brands across categories. Using a two-dimensional factor structure, we find that one of the factors explains a substantial amount of variation in store-brand preference, while the other factor explains price sensitivity---consistently across categories. The presence of these factors in all categories indicates that there are unobservable household-level traits that are non-category specific, i.e., stable across product categories. Using data from five holdout categories, we find that household estimates of these latent factors are very useful in predicting demand for store brands in new categories. Other potential applications for store managers are discussed.

Market Entry and Consumer Behavior: An Investigation of a Wal-Mart Supercenter

Abstract: This paper provides an empirical study of entry by a Wal-Mart supercenter into a local market. Using a unique frequent-shopper database that records transactions for over 10,000 customers, we study the impact of Wal-Mart's entry on consumer purchase behavior. We develop a joint model of interpurchase time and basket size to study the impact of competitor entry on two key household decisions: store visits and in-store expenditures. The model also allows for consumer heterogeneity due to observed and unobserved factors. Results show that the incumbent supermarket lost 17% volume---amounting to a quarter million dollars in monthly revenue---following Wal-Mart's entry. Decomposing the lost sales into components attributed to store visits and in-store expenditures, we find that the majority of these losses were due to fewer store visits with a much smaller impact attributed to basket size. We also find that Wal-Mart lures some of the incumbent's best customers, and that retention of a small number of households can significantly reduce losses at the focal store. Finally, certain observed household characteristics such as distance to store, shopping behavior, and product purchase behavior are found to be useful in profiling the defectors to Wal-Mart. Implications and strategies for supermarket managers to compete with Wal-Mart are discussed.

An Empirical Study of the Impact of Nonlinear Shipping and Handling Fees on Purchase Incidence and Expenditure Decisions

Abstract: Shipping-fee schedules are an important but underresearched element of the marketing mix for direct marketers. This paper provides an empirical study on the impact of shipping and handling charges on consumer-purchasing behavior. Using a database from an online retailer that has experimented with a wide variety of shipping-fee schedules, we investigate the impact of shipping charges on order incidence and order size. We use an ordered probability model that is generalized to account for the effects of nonlinear and discontinuous shipping fees on purchasing decisions, and to accommodate heterogeneity in response parameters. Results show that consumers are very sensitive to shipping charges and that shipping fees influence order incidence and basket size. Promotions such as free shipping and free shipping for orders that exceed some size threshold are found to be very effective in generating additional sales. However, the lost revenues from shipping and the lack of response by several segments are substantial enough to render such promotions unprofitable to the retailer. Heterogeneity across consumers also suggests interesting opportunities for the retailer to customize the shipping and other marketing-mix promotion offerings.

An Empirical Model of Optimal Dynamic Product Launch and Exit Under Demand Uncertainty

Abstract: This paper considers the decision problem of a firm that is uncertain about the demand, and hence profitability, of a new product. We develop a model of a decision maker who sequentially learns about the true product profitability from observed product sales. Based on the current information, the decision maker decides whether to scrap the product. Central to this decision problem are sequential information gathering, and the option value of scrapping the product at any point in time. The model predicts the optimal demand for information e.g., in the form of test marketing, and it predicts how the launch or exit policy depends on the firm's demand uncertainty. Furthermore, it predicts what fraction of newly developed products should be launched on average, and what fraction of these products will “fail,” i.e., exit. The model is solved using numerical dynamic programming techniques. We present an application of the model to the case of the U.S. ready-to-eat breakfast cereal industry. Simulations show that the value of reducing uncertainty can be large, and that under higher uncertainty firms should strongly increase the fraction of all new product opportunities launched, even if their point estimate of profits is negative. Alternative, simpler decision rules are shown to lead to large profit losses compared to our method. Finally, we find that the high observed exit rate in the U.S. ready-to-eat cereal industry is optimal and to be expected based on our model.

Structural Modeling in Marketing: Review and Assessment

Abstract: The recent marketing literature reflects a growing interest in structural models, stemming from (1) the desire to test a variety of behavioral theories with market data, and (2) recent developments that facilitate estimation of and inference for these models. Whether one should always go through the effort of developing such tightly parameterized models with the associated computational burden of estimating them and whether it pays off to make strict behavioral assumptions in terms of better decisions remain open questions. To shed some light on these issues, we provide examples of structural approaches to consumer choice and demand as well as examples where the goal is to study the nature of competition in the marketplace. From that review comes our discussion of issues in the development and application of structural models, including their estimation, testing, and validation, their applicability in the practice of marketing, and their usefulness for normative as well as descriptive purposes.

Consumer Preferences and Product-Line Pricing Strategies: An Empirical Analysis

Abstract: Firms often differentiate their product lines vertically to capture consumers differential willingness to pay for quality. Additionally, many firms offer products varying not in quality but in characteristics such as scent, color, or flavor, that relate to horizontal differentiation. For example, in the yogurt category, each manufacturer carries several product lines differing in quality and price, but within each line there is an assortment of flavors that is uniformly priced. To better understand these product-line pricing strategies, we address two key issues. First, how do consumers perceive product-line and flavor attributes? Second, given consumers preferences, is the current strategy of pricing product lines differently, but offering all flavors within a product line at the same price, optimal? We find that consumers value line attributes more than flavor attributes. Our analysis reveals that firms exploit these differences in consumer preferences by using product lines as a price discrimination tool. However, firms profits would not significantly increase if they were to price flavors within a product line differently. Therefore, the current pricing policy of setting different prices for product lines, but uniform prices for all flavors within a line, appears to be on target.

Setting Quality Expectations When Entering a Market: What Should the Promise Be?

Abstract: This paper examines optimal advertised quality, actual quality, and price for a firm entering a market. It develops a two-period model where advertised quality influences expectations, and hence trial and the gap between actual quality and expectations determines satisfaction, which in turn impacts second-period sales. In such situations a company makes a choice between advertising high quality and getting trial, but little repeat; and advertising low quality and getting low trial, but high repeat. Results are derived by numerical methods, as well as analytically for a special case of the model. The model suggests it is optimal to overstate quality when i customers rely relatively less on advertising to form quality expectations, and ii customers' intrinsic satisfaction with a product is high. These results are consistent with deceptive advertising cases at the FTC, which showed more deception for unknown firms and for firms whose customers were more satisfied. They are also consistent with the decisions made by future managers MBAs, except that the respondents would advertise higher versus lower quality when advertising was effective.

On Customized Goods, Standard Goods, and Competition

Abstract: In this study, we examine firms' incentive to offer customized products in addition to their standard products in a competitive environment. We offer several key insights. First, we delineate market conditions in which firms will (will not) offer customized products in addition to their standard products. Surprisingly, we find that when firms offer customized products they are able to not only expand demand, but can also increase the prices of their standard products relative to when they do not. Second, we find that when a firm offers customized products it is a dominant strategy for it to also offer its standard product. This result highlights the role of standard products and the importance of retaining them when firms offer customized products. Third, we identify market conditions under which ex ante symmetric firms will adopt symmetric or asymmetric customization strategies. Fourth, we highlight how the degree of customization offered in equilibrium is affected by market parameters. We find that the degree of customization is lower when both firms offer customized products relative to the case when only one firm offers customized products. Finally, we show that customizing products under competition does not lead to a prisoner's dilemma.

Observed and Unobserved Preference Heterogeneity in Brand-Choice Models

Abstract: This paper extends the scanner-based choice literature by explicitly incorporating individual-level brand-preference data. We illustrate our model using a unique data set that combines survey and scanner data collected from the same individuals. The addition of individual-specific brand-preference information significantly improves fit and prediction. Furthermore, this “observed” heterogeneity better explains choice than does “unobserved” heterogeneity in the standard scanner model's parameters. More importantly, we find that the standard model underestimates the importance of consumers' brand preferences and overestimates both brand loyalties and price sensitivities. Brand loyalty is overestimated because models without preference information confound state dependence, heterogeneity, and preference effects. Price sensitivities are inflated because the “average” preference-based consumer is implicitly assumed to be more willing to switch from his preferred brand than is the “real” preference-based consumer. Further, standard models overestimate the heterogeneity in price and loyalty sensitivities and misidentify both price- and loyalty-sensitive consumers. The managerial implications of our findings and the applicability of our methodology when survey data are collected infrequently and for only a subsample of consumers are pursued. We demonstrate that even under these circumstances better populationwide pricing and promotion decisions are identified and more accurate targeting results.

Estimating Heterogeneous EBA and Economic Screening Rule Choice Models

Abstract: Consumer choice in surveys and in the marketplace reflects a complex process of screening and evaluating choice alternatives. Behavioral and economic models of choice processes are difficult to estimate when using stated and revealed preferences because the underlying process is latent. This paper introduces Bayesian methods for estimating two behavioral models that eliminate alternatives using specific attribute levels. The elimination by aspects theory postulates a sequential elimination of alternatives by attribute levels until a single one, the chosen alternative, remains. In the economic screening rule model, respondents screen out alternatives with certain attribute levels and then choose from the remaining alternatives, using a compensatory function of all the attributes. The economic screening rule model gives an economic justification as to why certain attributes are used to screen alternatives. A commercial conjoint study is used to illustrate the methods and assess their performance. In this data set, the economic screening rule model outperforms the EBA and other standard choice models and provides comparable results to an equivalent conjunctive screening rule model.

Optimal Data Interval for Estimating Advertising Response

Abstract: The abundance of highly disaggregate data (e.g., at five-second intervals) raises the question of the optimal data interval to estimate advertising carryover. The literature assumes that (1) the optimal data interval is the interpurchase time, (2) too disaggregate data causes a disaggregation bias, and (3) recovery of true parameters requires assumption of the underlying advertising process. In contrast, we show that (1) the optimal data interval is what we call unit exposure time, (2) too disaggregate data does not cause any disaggregation bias, and (3) recovery of true parameters does not require assumption of the advertising process but only data at the unit exposure time. These results hold for any linear dynamic model linking sales with current and past advertising.

How to Compute Optimal Catalog Mailing Decisions

Abstract: We develop, estimate, and test a response model of order timing and order volume decisions of catalog customers and derive a Bayes rule for optimal mailing strategies. The model integrates the when and how much components of the response; incorporates the mailing decision of the firm; and uses a Bayesian framework to determine the optimal mailing rule for each catalog customer. The Bayes rule we propose for optimal mailing strategy allows for a broad set of objectives to be realized across the time horizon, such as profit maximization, customer retention, and utility maximization with or without risk aversion. We find that optimizing the objective function over multiple periods as opposed to a single period leads to higher expected profits and expected utility. Our results indicate that the cataloguer is well advised to send fewer catalogs than its current practice in order to maximize expected profits and utility.

Benefits of Channel Discord in the Sale of Durable Goods

Abstract: Minimizing strife through vertical integration is commonly seen as the holy grail for long-term success in product distribution. In this paper, we take a different slant, showing that sometimes a separated channel that embodies a degree of discord can be helpful, particularly when a long-term view is taken. This result is shown in the context of durable goods manufacturing. The quandary of durable goods production is that once demand for a certain time frame is met, there is a subsequent temptation to flood the market with additional goods. As such, consumers are reluctant to buy immediately, instead opting to wait for discounted prices. This problem can be alleviated by a degree of channel discord: High wholesale prices ensure future sales will slow to a trickle.

Research Note---Incorporating Satisfaction into Customer Value Analysis: Optimal Investment in Lifetime Value

Abstract: We extend the Schmittlein et al model (1987) of customer lifetime value to include satisfaction Customer purchases are modeled as Poisson events, and their rates of occurrence depend on the satisfaction of the most recent purchase encounter Customers purchase at a higher rate when they are satisfied than when they are dissatisfied A closed-form formula is derived for predicting total expected dollar spending from a customer base over a time period (0, T] This formula reveals that approximating the mixture arrival processes by a single aggregate Poisson process can systematically underestimate the total number of purchases and revenue Interestingly, the total revenue is increasing and convex in satisfaction If the cost is sufficiently convex, our model reveals that the aggregate model leads to an overinvestment in customer satisfaction The model is further extended to include three other benefits of customer satisfaction: (1) satisfied customers are likely to spend more per trip on average than dissatisfied customers, (2) satisfied customers are less likely to leave the customer base than dissatisfied customers, and (3) previously satisfied customers can be more (or less) likely to be satisfied in the current visit than previously dissatisfied customers We show that all the main results carry through to these general settings

Effects of Brand Preference, Product Attributes, and Marketing Mix Variables in Technology Product Markets

Abstract: We develop a demand model for technology products that captures the effect of changes in the portfolio of models offered by a brand as well as the influence of the dynamics in its intrinsic preference on that brand's performance. To account for the potential correlation in the preferences of models offered by a particular brand, we use a nested logit model with the brand (e.g., Sony) at the upper level and its various models (e.g., Mavica, FD, DSC, etc.) at the lower level of the nest. Relative model preferences are captured via their attributes and prices. We allow for heterogeneity across consumers in their preferences for these attributes and in their price sensitivities in addition to heterogeneity in consumers' intrinsic brand preferences. Together with the nested logit assumption, this allows for a flexible substitution pattern across models at the aggregate level. The attractiveness of a brand's product line changes over time with entry and exit of new models and with changes in attribute and price levels. To allow for time-varying intrinsic brand preferences, we use a state-space model based on the Kalman filter, which captures the influence of marketing actions such as brand-level advertising on the dynamics of intrinsic brand preferences. Hence, the proposed model accounts for the effects of brand preferences, model attributes and marketing mix variables on consumer choice. First, we carry out a simulation study to ensure that our estimation procedure is able to recover the true parameters generating the data. Then, we estimate our model parameters on data for the U.S. digital camera market. Overall, we find that the effect of dynamics in the intrinsic brand preference is greater than the corresponding effect of the dynamics in the brand's product line attractiveness. Assuming plausible profit margins, we evaluate the effect of increasing the advertising expenditures for the largest and the smallest brands in this category and find that these brands can increase their profitability by increasing their advertising expenditures. We also analyze the impact of modifying a camera model's attributes on its profits. Such an analysis could potentially be used to evaluate if product development efforts would be profitable.

Editorial: Save Research---Abandon the Case Method of Teaching

Abstract: The case method of teaching and the corresponding Socratic Method predate the discovery of the scientific method for advancing knowledge and problem solving. The case method applies known principles e.g., laws to specific situations while the scientific method focuses on discovering principles. Although the case method might be effective at teaching leadership and persuasion skills, it can lack the spirit of inquiry and the worship of the truth associated with the scientific method. Moreover, unlike legal cases, business cases lack precedent i.e., stare decisis, the foundation of written law, and rigorous adjudication. More importantly, the traditional case method of teaching often ignores important research findings. Consequently, it helps destroy the link between academic research and classroom learning. Students lose the benefit of important research findings while leaving the classroom with false confidence about what they know. Researchers lose an incentive to do research relevant to their students. Eventually, there is less research worth teaching, and fewer students value the knowledge learned through painstaking research. Although we might covet the skill of persuasion, time might gradually elevate previously less persuasive managers who have better skills with analysis and collecting relevant information. Great teaching requires great content, in addition to active learning.

An Integrated Choice Model Incorporating Alternative Mechanisms for Consumers' Reactions to In-Store Display and Feature Advertising

Abstract: The marketing literature has suggested two prominent decision mechanisms through which in-store display and feature advertising can affect brand choice, which I call the price-cut proxy effect and the consideration set formation effect. The primary objective of this study is to propose an integrated brand choice model that incorporates these two possible behavioral mechanisms, which have been shown to work by previous research. The model allows consumers to use various combinations of the decision mechanisms with different probabilities and thus enables one to jointly assess the extent to which each effect might occur in actual purchase data and to investigate how consumers might differ in their tendencies to engage in these decision processes. By incorporating these likely behavioral mechanisms, the proposed model alleviates the problems caused by multicollinearity and produces sensible parameter estimates for the joint effects of promotion vehicles in-store display, feature ad, and price discount, which contributes to better managerial decision making.

Estimating the Interdependence of Television Program Viewership Between Spouses: A Bayesian Simultaneous Equation Model

Abstract: When making product choices, consumers are influenced by the preferences of other consumers, such as family members, friends, neighbors, and colleagues. Preference interdependence among family members is likely to be significant because of cohabitation and strong emotional ties. To estimate the preference interdependence, we specify a simultaneous equation model and propose a Bayesian estimation approach. Unlike existing models that use a spatial autoregressive structure to capture the interdependence of consumer preferences, we are able to estimate the potential asymmetry in the preference interdependence among family members in a more flexible way. In a simulation study, we show that models that ignore interdependence of preferences yield biased estimates of consumers' sensitivity to observed attribute preferences. In an empirical application, we estimate the interdependence of the viewership of television programs between husbands and wives in 481 households. We find that wives' viewing behavior depends more strongly on their husbands' viewing behavior than husbands' viewing behavior depends on their wives' viewing behavior. There exist significant differences in parameter estimates of dependence across categories of television programs. Differences in levels of spousal interdependence across households are partially explained by the age and the education level of the spouses.