bluuebunny/crossref_metadata_2025 huggingface dataset:
Generalizing What Is Known About Temporal Aggregation and Advertising Carryover
Authors: Leone Robert P.
Published: October 2008

This paper provides a theoretical explanation for the inconsistent findings from previous econometric analyses of aggregated data concerning the duration of advertising carryover. Using this theoretical explanation and the knowledge of a data interval bias, the paper reviews and summarizes the empirical work in the area of sales response modeling, and then after adjusting for aggregation bias, presents support for an empirical generalization that the average advertising duration interval is of brief duration—typically between six and nine months.
Empirical Generalisations, Theory, and Method
Authors: Ehrenberg A. S. C.
Published: October 2008

Should we judge empirical generalisations as mere regularities, separately from theory? The paper argues that this may bring out the links with theory better and gives illustrative examples. It also notes how in pursuing empirical generalisability more explicitly, we will have to shift how we design and analyse our studies.
Empirical Marketing Generalization Using Meta-Analysis
Authors: Farley John U. , Lehmann Donald R. , Sawyer Alan
Published: October 2008

A decade of work in marketing meta-analysis has produced empirical generalizations concerning parameters in models of advertising, price, diffusion, and consumer behavior. Results from these meta-analyses should replace the now discredited zero null hypotheses of such parameters in future work. Probably more important than nonzero “grand mean” average effects is an approach called Parametric Adjustability, which provides estimated parameter values for specific conditions reflecting markets and research technologies. Systematic application of the methodology can also help guide research along productive routes and away from repetition of work which has little potential to add new knowledge.
Empirical Generalizations and Marketing Science: A Personal View
Authors: Bass Frank M.
Published: October 2008

Marketing has matured to the point where it seems desirable to take stock of where we are, what we have learned, and fruitful directions for extending the knowledge base that has developed. Science is a process involving the interaction between empirical generalizations and theory. An empirical generalization is “a pattern or regularity that repeats over different circumstances and that can be described simply by mathematical, graphic, or symbolic methods.” One of the purposes of the Empirical Generalizations Conference held at Wharton on February 16–18, 1994 was to develop a list of examples of such empirical generalizations in marketing. Empirical generalization can precede a theory to explain it or it can be predicted by a theory. Science is the process of interaction between theory and data that leads to higher level theories. Examples are provided here of empirical generalizations in marketing and their theoretical counterparts. One example is provided of a higher level theory.
A Latent Look at Empirical Generalizations
Authors: Morrison Donald G. , Silva-Risso Jorge
Published: October 2008

All empirical data and the resulting parameters are subject to error. In this paper we explicitly use the standard, but hardly profound, “model” [Formula: see text] as a lens for better viewing empirical studies in search of empirical generalizations in marketing. This lens is especially valuable when the unit of analysis is the individual consumer. However, even when a macro study contrasts price elasticities across cities, this O = T + E framework can be very helpful.
Patterns of Buyer Behavior: Regularities, Models, and Extensions
Authors: Uncles Mark , Ehrenberg Andrew , Hammond Kathy
Published: October 2008

Many empirical regularities in the buying behavior of consumers have been linked together into a comprehensive model, the Dirichlet. In this paper we list some of the well-established regularities, show how they are theoretically intertwined, and illustrate how this approach to modeling can assist the marketing analyst.
Channel Coordination When Retailers Compete
Authors: Ingene Charles A. , Parry Mark E.
Published: October 2008

This paper explores channel coordination by a manufacturer that sells through competing retailers and that treats these retailers equally, as required by the Robinson-Patman Act. The authors show that, in general, there exists no single two-part tariff with a constant per-unit charge that will duplicate the behavioral results (i.e., prices, quantities, and channel profits) that are obtained by a vertically integrated system; that is, the channel cannot be coordinated except in the trivial cases of identical or noncompeting retailers. However, an appropriately specified quantity-discount schedule will enable the channel to earn the same profits generated by a vertically integrated system. Conditions are derived under which a manufacturer will prefer to offer various two-part tariffs with constant per-unit charges instead of the channel-coordinating quantity-discount schedule.

The authors also establish the existence of a menu of two-part tariffs that mimics all results of a vertically integrated system. However, only under stringent conditions will retailers select the appropriate tariff from the menu. When these conditions are not satisfied, the channel is worse off than in the case of a single, second-best tariff. It is also demonstrated that under a wide range of parametric values the manufacturer will prefer to offer the second-best two-part tariff rather than a menu of two-part tariffs that could maximize channel profits.
Signaling Quality with a Money-Back Guarantee: The Role of Transaction Costs
Authors: Moorthy Sridhar , Srinivasan Kannan
Published: October 2008

Direct marketing is witnessing explosive growth. As consumers increasingly purchase products from their homes, their ability to judge the quality of products they buy is significantly reduced. In this paper we study how money-back guarantees can signal product quality in such environments. We interpret product quality broadly to mean both the level of attributes promised as well as the firm's consistency in delivering on those promises. Key aspects of our formulation are the explicit consideration of transaction costs, and alternative signals of product quality. Transaction costs are the costs the seller or buyer faces when redeeming a money-back guarantee. We show that money-back guarantees signal quality by exploiting the higher probability of returns for a lower quality product, and the attendant higher transaction costs. However, if the seller's transaction costs are very large, then there are less costly ways to signal, namely charging a high price. We compare the signaling performance of (1) price, (2) price with uninformative advertising, and (3) price with a money-back guarantee. Whereas uninformative advertising does not work at all in our model, under certain conditions a money-back guarantee is necessary to signal, and under other conditions, a money-back guarantee is a useful supplement to price.
Addendum to “Cross-Validating Regression Models in Marketing Research” Vol. 12, No. 4, Fall 1993, pp. 415–427
Authors: Steckel Joel H. , Vanhonacker Wilfried R.
Published: October 2008

In our paper, “Cross-Validating Regression Models in Marketing Research,” which appeared in the Vol. 12, No. 4, Fall 1993 issue of Marketing Science, pp. 415–427, we develop a formal statistical test for cross-validating regression models under the simple random splitting framework. The original publication neglected to present definitions for two of the parameters used. We present these in this Addendum.
Manufacturer's Return Policies and Retail Competition
Authors: Padmanabhan V. , Png I. P. L.
Published: October 2008

Manufacturers' returns policies are a common feature in the distribution of many products. The obvious rationale for returns policies is insurance. Practitioners, not surprisingly, have a different perspective and view returns as a cost of doing business. In this paper, we study the strategic effect of returns policies on retail competition and highlight its profitability implications for a manufacturer. The setting for our research is the distribution of products with uncertain demand, limited shelf lives, and retail competition. Our objective is to provide a better understanding of when manufacturers should adopt returns policies. The insights are obtained with a model based on the economics of strategy and decision making under uncertainty.

We show that when retailing is competitive and there is no uncertainty in demand, a returns policy subtly induces retailers to compete more intensely. The provision of a returns policy reduces retail prices without affecting wholesale prices, thereby reducing retailer margins and improving manufacturer profitability. The intuition is that with a returns policy, Cournot-like levels of retail stocks cannot be sustained. Each retailer will order stocks so that it will not be constrained by stocks, and so, intensifying retail competition.

When, however, demand is uncertain and there is a single retailer, a returns policy encourages the retailer to over-stock, and so decreases (upstream) manufacturer profits. While the provision of a returns policy leads to lower retail margins, the optimality of returns policy depends on the overall uncertainty and marginal cost. A returns policy reduces the dispersion in retail prices between the high and low states of demand and the range of retail prices in the returns case is contained within the range of retail prices for the no-returns case.

In the general setting, when there are competing retailers and demand is uncertain, there is a trade-off for the manufacturer between the benefits (more intense retail competition) and the costs (excessive stocking) of a returns policy. We find that a manufacturer should accept returns when the marginal production cost is sufficiently low and demand uncertainty is not too great.

To validate the results of our theory, we conduct an empirical test with data from a major U.S. retailer. The tests confirm our prediction that a returns policy intensifies retail competition and reduces retailer margins. Our theory and empirical test should interest practitioners and researchers in distribution, especially those concerned with managing retail competition.
Direct Estimation of Batsell and Polking's Model
Authors: Park Sang-June , Hahn Minhi
Published: October 2008

Batsell and Polking (1985) developed one of the important choice models that address the problem of independence from irrelevant alternatives. In this note, we propose an estimation method that directly estimates Batsell and Polking's model. Compared to the indirect estimation method suggested by Batsell and Polking, the direct method is simpler, making the BP model more accessible to potential users.
Yes, “Bait and Switch” Really Benefits Consumers
Authors: Hess James D. , Gerstner Eitan
Published: October 2008

In our 1990 Marketing Science paper we demonstrated that a law prohibiting bait and switch may have the surprising consequence of hurting the consumers it was designed to protect. Wilkie, Mela, and Gundlach (1998) postulate that this may be false if upselling is equally effective when the bait brand is available and when it is out of stock. We show here that our earlier conclusion is correct in a more general setting: A law prohibiting bait and switch in a competitive market can reduce consumer well-being but never improve it. When bait and switch occurs, it creates welfare gains, and when it would create welfare losses, it does not occur, regardless of a law prohibiting the practice.
Introduction to the Special Issue on Managerial Decision Making
Authors: Staelin Richard
Published: October 2008

This issue is all about managerial decision making, i.e., how managers go about making decisions and how these decisions can be improved via good marketing analyses. As such it differs somewhat from the regular issues of Marketing Science in that it contains no analytic models or papers that focus only on methodology. Yet it still is true to the overall mission of the journal: it addresses areas of inquiry relevant to marketing practitioners and academics.
The Success of Marketing Management Support Systems
Authors: Wierenga Berend , Van Bruggen Gerrit H. , Staelin Richard
Published: October 2008

This paper provides an introduction to this Special Issue by a) providing a framework for evaluating the potential and actual success of marketing management support systems (MMSS), and b) briefly discussing how each paper in this Special Issue addresses the general topic of managerial decision making. The paper concludes by outlining some key questions that still need to be addressed.
Why Analyst Overconfidence About the Functional Form of Demand Models Can Lead to Overpricing
Authors: Montgomery Alan L. , Bradlow Eric T.
Published: October 2008

Generally, profit predictions are made conditional upon a particular functional form. The typical caveat offered is that this is not the “true” demand model, but is instead some reasonable approximation. We show how the notion of an approximation can be explicitly represented using a random coefficient model. Our model nests the usual situation of complete model certainty as a special case. We go on to show how ignoring the uncertainty in functional form induced by approximation will lead to erroneous pricing decisions that may frequently lead to overpricing.

For example, an inelastic, double-log demand model implies infinite optimal prices. This is clearly a nonsensical, analyst recommendation. We propose a more general form of the double-log model that allows for high confidence in the observed price range, but incorporates increased uncertainty about the adequacy of the double-log approximation as prices move beyond the observed range. The optimal pricing solutions for this new model are lower than those for the usual case with complete certainty. In fact, we find well-defined optimal pricing solutions even for inelastic double-log demand models. This is a finding of great practical importance, given that aggregate demand models tend to be inelastic for grocery categories, and that log demand models are frequently used (Hoch et al. 1995). We argue that the lack of recognizing uncertainty in the modeling process may partially account for why there is a seeming disparity between observed retail prices and the optimal prices implied by maximizing total category profits using estimated demand models (Little and Shapiro 1980).

The problems of making optimal pricing decisions using double-log demand models calibrated with store-level scanner data have been recognized. Previous solutions are to constrain the results to achieve reasonable solutions (Reibstein and Gatignon 1984, Montgomery 1997) or to avoid these models altogether in favor of household choice models aggregated to the store-level (Vilcassim and Chintagunta 1995). Our assessment of the problem is that it is not necessarily an issue of model specification, but one of inference. In other words, double-log models fit well, but optimization leads to out-of-range predictions. Our suggestion is that inferences from an estimated demand model need to be approached with some caution. Specifically, uncertainty about predictions will always exist. If this uncertainty is incorporated into models such as the double-log form, then much better inferences can be made. It is our hope that this research will encourage others to think not only about model specification and estimation, but also inference.
Research Note: Overselling with Opportunistic Cancellations
Authors: Biyalogorsky Eyal , Carmon Ziv , Fruchter Gila E. , Gerstner Eitan
Published: October 2008

In many business sectors such as airlines, hotels, trucking, and media advertising, customers' arrivals and willingness to pay are uncertain. Managers must decide whether to quote a price low enough to guarantee early sales, or to quote a higher price and risk that some units remain unsold. In allocating capacity, they face a trade-off between two types of potential losses; (1) Yield loss—selling at a low price, and losing a better price later, and (2) Spoilage loss—waiting in vain to sell at a high price, and losing the opportunity of an earlier low price offer. Yield loss means that consumers who value the product most do not get to use it, and spoilage loss means that valuable products are wasted because no consumers get to use them. Sellers typically hedge against the risk of spoilage loss by selling some units early at low prices, and against the risk of yield loss by blocking some units in hope of selling them later at a high price.

In this paper we show that the use of overselling with opportunistic cancellations can increase expected profits and improve allocation efficiency. Under this strategy, the seller deliberately oversells capacity if high-paying consumers show up, even when capacity is already fully booked. The seller then cancels the sale to some low-paying customers while providing them with appropriate compensation.

We derive a new rule to optimally allocate capacity to consumers when overselling is used, and show that overselling helps limit the potential yield and spoilage losses. Yield loss is reduced because the seller can capture more high-paying customers by compensating low-paying customers who give up their right to the product. Spoilage loss is reduced because the compensation decreases the price spread perceived by the seller, and as a result, the seller is less anxious to speculate and “block” units. Overselling with opportunistic cancellations assures that the product will be sold to consumers who value it most. This means that “everybody wins”, and resources are allocated more efficiently than in conventional selling.
Assessing the Reliability of Psychographic Analyses
Authors: Fenwick Ian , Schellinck D. A. , Kendall K. W.
Published: October 2008

Psychographic, or life-style, analysis has proved useful in a wide variety of applications. However users have voiced concern about the reliability of the analysis and the reality of the segmentations it produces. As life-style items tend to be specific to individual applications and often have little theoretical support, there is particular need for a method of evaluating the stability of results. This paper reviews marketing studies which have tested life-style reliability and stability, and presents a method of assessing reliability using the jackknife. This method is particularly useful as it can handle small sample sizes, is not dependent on the number of items in the scale or the type of factor model used, and can provide detailed assessments of factor reliability. An empirical application of the method is presented.
Minimum Market Share
Authors: Karnani Aneel
Published: October 2008

This paper analyzes a specific model of oligopolistic competition involving product differentiation, marketing activities, and economies of scale in production. This model is consistent with sales response models which have been justified on theoretical and empirical bases. It is shown that at a Nash equilibrium each firm must have market share equal to zero or greater than a threshold value. This result has implications for determination of minimum firm size, the effectiveness of a low market share strategy, entry barriers, and the likelihood of concentration in an industry. The paper explores these implications and relates them to various theories and hypotheses in industrial organization and strategic planning.
Estimating the Confidence Interval for the Optimal Marketing Mix: An Application to Lead Generation
Authors: Morey Richard C. , McCann John M.
Published: October 2008

The Dorfman-Steiner Theorem has provided the marketing community with a powerful result for allocating resources between competing marketing mix variables. It is well known that the optimal allocation of resources is in direct proportion to their demand elasticities. To implement this result, the marketing manager must know the elasticities of the various marketing elements under his/her control. Since the precise values of these elasticities is rarely, if ever, known, the manager must use estimates of the elasticities in allocating the resources. Point estimates of the elasticities can be obtained from laboratory or field experiments and from econometric models. In both cases, these estimates are known with uncertainty. This paper discusses the appropriate method for incorporating uncertainties in the point estimates of the elasticities to yield rigorous confidence intervals applicable to the ratio of the elasticities. An empirical example is used to illustrate the methodology.
A Nonuniform Influence Innovation Diffusion Model of New Product Acceptance
Authors: Easingwood Christopher J. , Mahajan Vijay , Muller Eitan
Published: October 2008

A nonuniform influence (NUI) innovation diffusion model for forecasting first adoptions of a new product is proposed. An extension of the Bass model, the proposed model overcomes three limitations of the existing single-adoption diffusion models. First, the current models generally assume that the word-of-mouth effect remains constant over the entire diffusion span. However, for most innovations, the word-of-mouth effect is likely to increase, decrease or remain constant over time. Second, the existing models assume that an innovation must attain its maximum penetration rate before capturing a prespecified level of potential market, for example, 50%. That is, they restrict the location of the inflection point for the diffusion curves. Third, the current models assume that the adoption patterns after and before the location of maximum penetration rate are mirror images of each other. That is, the diffusion curve is symmetric. By allowing the word-of-mouth effect to systematically vary over time, the proposed model allows the diffusion curve to be symmetrical as well as nonsymmetrical, with the point of inflection responding to the diffusion process. Data from five consumer durables are analyzed to illustrate the generality of the model.
Defensive Marketing Strategies
Authors: Hauser John R. , Shugan Steven M.
Published: October 2008

This paper analyzes how a firm should adjust its marketing expenditures and its price to defend its position in an existing market from attack by a competitive new product. Our focus is to provide usable managerial recommendations on the strategy of response. In particular we show that if products can be represented by their position in a multiattribute space, consumers are heterogeneous and maximize utility, and awareness advertising and distribution can be summarized by response functions, then for the profit maximizing firm: it is optimal to decrease awareness advertising, it is optimal to decrease the distribution budget unless the new product can be kept out of the market, a price increase may be optimal, and even under the optimal strategy, profits decrease as a result of the competitive new product. Furthermore, if the consumer tastes are uniformly distributed across the spectrum a price decrease increases defensive profits, it is optimal (at the margin) to improve product quality in the direction of the defending product's strength and it is optimal (at the margin) to reposition by advertising in the same direction.

In addition we provide practical procedures to estimate (1) the distribution of consumer tastes and (2) the position of the new product in perceptual space from sales data and knowledge of the percent of consumers who are aware of the new product and find it available. Competitive diagnostics, such as the angle of attack, are introduced to help the defending manager.
Optimal Price Subsidy Policy for Accelerating the Diffusion Of Innovation
Authors: Kalish Shlomo , Lilien Gary L.
Published: October 2008

Due to the risk inherent in dependence on foreign oil, there is a social benefit in aiding the introduction of alternative energy sources into the market place. The Federal government has initiated a number of programs, including price subsidies, to help accelerate the market diffusion of new, alternative energy systems.

We develop a model to investigate analytically the effects of a price subsidy over time on the rate of market diffusion. The model considers word-of-mouth effects and learning curve cost declines. Under a set of conditions that a new technology should be expected to meet before commercialization, the optimal subsidy level is shown to be nonincreasing in time. The related market price is shown to be closely related to the diffusion effect. If there is no such effect, the price to the customer is constant. If there is positive diffusion effect, price increases in time, while if market saturation causes demand to decline over time price decreases in time.
Variety Seeking Through Brand Switching
Authors: Givon Moshe
Published: October 2008

A concept of variety seeking behavior is modeled as a stochastic brand choice model. The model yields a measure of variety seeking for each individual consumer. Panel data for 28 products are analyzed for each household and the possibility of market segmentation by variety seeking behavior is explored.
An MDI Model and an Algorithm for Composite Hypotheses Testing and Estimation in Marketing
Authors: Charnes A. , Cooper W. W. , Learner D. B. , Phillips F. Y.
Published: October 2008

This paper indicates how an information theoretic approach via the MDI (minimum discrimination information) statistic can be used to help provide a uniform approach to both statistical testing and estimation in various kinds of marketing analyses. Extensions to constrained versions of the MDI statistic also make it possible to test the consistency of market information with management plans or policies that can be represented in “external” constraints, i.e., constraints formulated without reference to the data base, and to estimate their impact on the market. Composite hypotheses, which are difficult to deal with by the more customary methods used in market research, can be dealt with naturally and easily via these MDI approaches. Basically MDI is more efficient than classical approaches because distribution estimation and hyopthesis testing are done simultaneously and the resulting estimates obtain regardless of the conclusion of the test. Numerical illustrations are supplied and discussed. Recent developments in mathematical programming (duality) theory and methods, which are also pertinent, are briefly examined for their bearing on still further possibilities for constrained MDI modeling.
Technical Note—Factors Influencing the Selection of Preference Model Form for Continuous Utility Functions in Conjoint Analysis
Authors: Cattin Philippe , Punj Girish
Published: October 2008

In conjoint analysis, a consumer's utility function for a continuous attribute is usually estimated using a part worth function. However, one may also use continuous functions. The purpose of the paper is to investigate through simulation the combined influence of the number of degrees of freedom, the nature of the “true” utility function and the amount of error in the data on the selection of a utility function. The focus is on functions that are known or expected to be monotone within the range of attribute levels of interest. One can then choose among linear, quadratic and part worth functions. The results show (a) that estimation procedures with monotonicity constraints should be used, and (b) that it is best to use quadratic or part worth functions rather than linear functions to minimize potential losses in predictive validity.
A Comment
Authors: Pringle Lewis G.
Published: October 2008

“An Audience Flow Model of Television Viewing Choice” by Rust and Alpert (this issue, pp. 113–124) does indeed represent a contribution to the marketing literature. Furthermore, it represents an important step in the process of developing a better understanding of a significant and practical marketing issue: the selection—in advance—of specific advertising vehicles.
An Empirical Comparison of Awareness Forecasting Models of New Product Introduction
Authors: Mahajan Vijay , Muller Eitan , Sharma Subhash
Published: October 2008

Five awareness forecasting models embedded in their respective new product introduction models are compared. Conditions which govern the differences in the awareness estimates provided by the various models are delineated. Managerial implications of the results are discussed.
Assessing the Influence of Campaign Expenditures on Voting Behavior with a Comprehensive Electoral Market Model
Authors: Chapman Randall G. , Palda Kristian S.
Published: October 2008

This paper extends previous single equation econometric modeling efforts of the “sales-advertising” relationship in elections. Operating within the perspective of the general demand context of voting behavior, it develops a comprehensive electoral market model that takes account of potential simultaneous relationships among votes cast, campaign expenditures, and voting participation (turnout). The model is estimated using 3SLS techniques with aggregate electoral district data from each of eight Canadian provincial elections. The model appears to yield consistent and therefore generalizable empirical results across the eight election events. Chief among the empirical results is the expected relationship between campaign efforts and voting behavior: “own” communications efforts (as proxied by campaign expenditures) have a positive impact on votes received, while competitive communications efforts draw votes away from a candidate.
A Normative Model of Consumer Information Processing
Authors: Hagerty Michael R. , Aaker David A.
Published: October 2008

A model of information search is proposed which assumes that a consumer chooses the next piece of information so as to maximize his expected value of sample information. The cost of processing, the perceived correlation between attributes, and the perceived importance of attributes would all affect information choice. Three sets of propositions are derived. The model is also estimated and tested for subjects performing an information display board task.
An Investigation into the Order of the Brand Choice Process
Authors: Bass Frank M. , Givon Moshe M. , Kalwani Manohar U. , Reibstein David , Wright Gordon P.
Published: October 2008

This paper investigates the order of the brand choice process at the individual family level using a variety of tests: t, likelihood ratio, binomial runs, and multinomial runs tests. The test of stationarity developed permits separate analyses for stationary and nonstationary purchase sequences. Our analyses indicate that the purchase sequences of a majority of stationary consumers are consistent with the zero-order assumption. This result is observed for all the nine frequently-bought packaged goods studied with the use of panel data and for a product category (soft drinks) using experimental data.
Prediction of Individual Buying Behavior: A Poisson-Bernoulli Model with Arbitrary Heterogeneity
Authors: Dalal S. R. , Lee J. C. , Sabavala D. J.
Published: October 2008

Patterns of customer purchases are often modeled as discrete behavioral events following some probability law. These stochastic models have been applied separately to the phenomena of product class purchase incidence and brand choice (conditional on the products being purchased). Most of these models are probability mixture models where the parameters of an individual customer model vary across the population according to some distribution. This paper proposes a simple model of purchase behavior at the individual level, Poisson (λ) product purchases and Bernoulli (p) brand choices, so that λ and p characterise each customer. However, λ and p may vary jointly across the population in an arbitrary fashion. Therefore, purchase incidence and brand choice are treated together making no assumptions about the dependence between them. This generality is obtained at the cost of efficiency but enables us to focus on the individual behavior. Estimators (with known asymptotic properties) are developed for predicting future purchasing behavior of individuals conditional on their past purchasing behavior.

These predictions of future purchases, at brand and product levels, are of interest to marketing managers. For example, what is the expected number of brand (or product) purchases in period 2 for the group of customers that made x brand and n product purchases in period 1? Apart from the basic insights provided by such predictions, they are particularly useful in evaluating the impact of marketing efforts.

The model and the estimation results are applied to a frequently purchased product and compared with other stochastic approaches. While this paper focuses on buying behavior, the model is applicable to accidents, direct mail purchases and other random events.
Models and Heuristics for Product Line Selection
Authors: Green Paul E. , Krieger Abba M.
Published: October 2008

Recently, a number of articles have appeared in the marketing literature dealing with (single) product design optimization. The present paper represents a start toward extending this research to product line decisions. We first formulate two versions of the problem and describe their various characteristics. Since finding the optimum solution is computationally prohibitive, even for modest size problems, various heuristic approaches are presented and evaluated. Applications involving synthetic and real data are discussed. The paper concludes with comments on related problems and future application areas.
Competition and Cooperation in Marketing Channel Choice: Theory and Application
Authors: Coughlan Anne T.
Published: October 2008

This paper discusses the problem of choosing a vertical marketing channel in a product-differentiated duopolistic market. Firms choose product price and the form of the marketing channel to maximize profits. It is shown that integration of the marketing function results in greater price competition and lower prices than does the use of independent marketing middlemen. The profitability of reducing price competition by using such middlemen is investigated. Two hypotheses—that integration is negatively associated with the products' substitutability and that symmetric channel structures are stable—are tested in a preliminary way and supported with survey data from the international semiconductor industry.
Optimal Pricing and Return Policies for Perishable Commodities
Authors: Pasternack Barry Alan
Published: October 2008

This paper considers the pricing decision faced by a producer of a commodity with a short shelf or demand life. A hierarchical model is developed, and the results of the single period inventory model are used to examine possible pricing and return policies. The paper shows that several such policies currently in effect are suboptimal. These include those where the manufacturer offers retailers full credit for all unsold goods or where no returns of unsold goods are permitted. The paper also demonstrates that a policy whereby a manufacturer offers retailers full credit for a partial return of goods may achieve channel coordination, but that the optimal return allowance will be a function of retailer demand. Therefore, such a policy cannot be optimal in a multi-retailer environment. It is proven, however, that a pricing and return policy in which a manufacturer offers retailers a partial credit for all unsold goods can achieve channel coordination in a multi-retailer environment.
Measuring Simple Preferences: An Approach to Blind, Forced Choice Product Testing
Authors: Buchanan Bruce S. , Morrison Donald G.
Published: October 2008

When comparing alternate product formulations, or evaluating competitors' formulations, researchers often conduct blind, forced choice product tests. In this study, the authors present an approach to designing these tests and evaluating their results. Two types of tests are considered: repeat paired comparisons formats, and formats consisting of several triangle tests and a single paired comparison. The approach consists of psychophysical assumptions, discrimination and preference constructs, and a set of analytical techniques. Using this approach, a researcher can compare product test formats to see which one most efficiently estimates a given construct of interest. The approach can also be used to gauge sample size requirements for a particular product test format and to estimate confidence intervals for an observed product test result. To illustrate the approach the authors compare two popular product test formats—the Four Paired Comparisons, and the Double Triangle Single Preference.
Nonisomorphism, Shadow Features and Imputed Preferences
Authors: Holbrook Morris B. , Moore William L. , Dodgen Gary N. , Havlena William J.
Published: October 2008

Problems arise in generalizing research results based on artificial objects to the case of real products. The few previous investigations of this issue may have obtained inflated assessments of predictive validity by focusing unrealistically on stimuli with isomorphic features and perceptions. Such isomorphism occurs when each feature is matched with a uniquely appropriate perceptual response. To handle the case of nonisomorphism, where features and perceptions do not show a one-to-one correspondence, we propose a method to assess the convergent validity between preference structures for artificial objects and real products via the use of shadow features and imputed preferences. In this approach, shadow features (analogous to the economist's “shadow prices”) are weighted by utilities estimated via conjoint analysis on artificial objects to derive imputed preferences toward real products. The correlation of imputed with actual preferences gauges the convergent validity between artificial and real preference structures. This estimate of convergent validity suggests the maximum predictive validity that one can reasonably expect in generalizing results based on artificial objects to the case of real products (for similar samples of subjects and sets of stimuli). We illustrate the proposed method in a study that collected data on perceptual and affective responses to real and artificial recordings of performances by male pop singers. This illustrative application suggests that, even with satisfactory results in separate analyses for artificial objects (R̄AF = 0.81) and real products (R̄AS = 0.82), one may find only moderate convergent validity (r̄AA = 0.52) and disappointing predictive validity (r15 = 0.40) in applying utilities estimated on artificial objects to the prediction of preferences toward real products.
Technical Note—Why Does the NBD Model Work? Robustness in Representing Product Purchases, Brand Purchases and Imperfectly Recorded Purchases
Authors: Schmittlein David C. , Bemmaor Albert C. , Morrison Donald G.
Published: October 2008

One of the most managerially useful constructs that emerge from the stochastic modelling of brand choice is that of conditional expectations. In this paper the conditional expectations are derived for a generalization of the NBD model, called the beta binomial/negative binomial distribution (BB/NBD) model, first described by Jeuland, Bass and Wright. The model, developed to jointly represent the product class purchase and brand selection processes, is also particularly appropriate for analyzing panel data when not every purchase occasion is recorded. The conditional expectations for the NBD model increase linearly with the number of previous purchases made by an individual. Therefore the degree of nonlinearity of the conditional expectations in our more complicated model allows us to assess the robustness of NBD results when in fact the basic assumptions are not true. This paper gives the simple conditions when the NBD will exactly or approximately represent the BB/NBD; and describes the qualitative deviations between these two models when they are not identical.
Salesforce Compensation Plans: An Agency Theoretic Perspective
Authors: Basu Amiya K. , Lal Rajiv , Srinivasan V. , Staelin Richard
Published: October 2008

A theory of salesforce compensation plans is presented where the sales of a product depend not only on the salesperson's effort but also on the uncertainty in the selling environment. The firm chooses a compensation plan to maximize its profit taking into account the salesperson's likely effort levels under alternative compensation plans and his or her alternative job opportunities. The salesperson (agent) chooses an effort level considering both the disutility from effort and the expected utility from earnings under the compensation plan.

The Agency Theory framework provides an explanation for the differences across firms in the types of compensation plans used such as straight salary, straight commissions, or a combination of salary and commissions. It is shown that the optimal compensation plan is a convex (concave) increasing function of sales if the risk tolerance of the salesperson increases “rapidly” (stays constant) with income.

We identify several structural parameters that affect the compensation plan and show that the implication of changes in some of these parameters is consistent with those mentioned in the sales management literature. For example, we show that the proportion of salary to total compensation would increase with an increase in one or more of the following parameters: (i) uncertainty, (ii) marginal cost of production, and (iii) attractiveness of alternative job opportunities for the salesperson. We conclude with a discussion of the implications of the theory for managing salesforce compensation plans.
A Probabilistic Model For Testing Hypothesized Hierarchical Market Structures
Authors: Grover Rajiv , Dillon William R.
Published: October 2008

In this paper a methodology for hierarchical market structure analysis is derived and illustrated. A probabilistic model is developed which provides a general, flexible framework which can be used to test hypothesized hierarchical market structures. Because the general probabilistic model can be translated in terms of a restricted latent class model it can be easily implemented. Among its other benefits, the proposed methodology, utilizing panel data, tracks households over a number of switches, furnishes explicit statistical tests for alternative hypothesized tree structures, as well as individual parameters, and can potentially identify clusters of households who structure the market in similar ways.
The Navy Enlistment Marketing Experiment
Authors: Carroll Vincent P. , Rao Ambar G. , Lee Hau L. , Shapiro Arthur , Bayus Barry L.
Published: October 2008

This paper presents research initiated in 1978 to examine the marketing effectiveness of the U.S. Navy recruiting program and to quantify the relationship between marketing efforts and enlistment achievements. The major component of the research was a one-year, controlled experiment in which levels of Navy recruiters and advertising were systematically varied and a detailed and comprehensive data base assembled. This paper describes the experiment and presents analyses of the experimental data. These analyses led to a number of conclusions regarding the impact of various factors on enlistment numbers and quality: The number of recruiters had a significant impact. Effectiveness of recruiters depended on recruiter tenure with clearly discernable learning and delearning effects. Advertising expenditures of certain types were effective, while others were not. There was a wide variation in the impact of the effective media. Socioeconomic factors such as unemployment and urbanization had major impacts. Navy marketing efforts led to an expansion of the total market for enlistments in addition to their impact on Navy enlistments. The study was carried out in a highly collaborative mode, with frequent meetings and briefings with all levels of Command. This not only facilitated control and direction of the research, but also led to a number of adaptive initiatives undertaken by policy makers. These included reallocation of the advertising budget, development of a tenure-based recruiter incentive system and a change in emphasis from recruit accessions (deliveries) to contracts (sales).
Comments
Authors: Zielske Hugh A.
Published: October 2008

I am flattered to see that the data from our 1959 experiment are still being analyzed. And I am impressed with the mathematical elegance of Mahajan and Muller's (Mahajan, V., E. Muller. 1986. Advertising pulsing policies for generating awareness for new products. Marketing Sci. 5 89–106.) analysis. It would be presumptuous of me to comment on the technical aspects of the paper. However, some comments on our more recent work in this area may be of interest.
Reply—Reflections on Advertising Pulsing Policies for Generating Awareness for New Products
Authors: Mahajan Vijay , Muller Eitan
Published: October 2008

We are indebted to John Little (Little, J. D. C. 1986. Comments. Marketing Sci. 5 107–108.) and Hugh Zielske (Zielske, H. A. 1986. Comments. Marketing Sci. 5 109.) for their valuable comments on our paper. Some of the comments merit further clarification and our response to these comments is provided below.
A Nested Logit Model of Space and Water Heat System Choice
Authors: Dubin Jeffrey A.
Published: October 2008

This paper estimates a nested logit model for space heat and water heat choice using data from the 1980 Pacific Northwest Energy Survey (PNW). The estimated structure involves six alternative space heat systems and three alternative water heat fuel types. Operating and capital costs are predicted for each residence using an energy thermal model.

To relax the Independence of Irrelevant Alternatives assumption we employ a family of nested logit models. We illustrate the two-step estimation method and use a Lagrange multiplier test for nested logit structure. Finally, we use the estimated models to forecast the market shares of alternative space heat systems under an assumed scenario for the course of relative fuel prices.
Estimating Continuous Time Advertising-Sales Models
Authors: Rao Ram C.
Published: October 2008

This paper develops the advertising-sales model in continuous time with a view to studying the consequences of temporal aggregation for estimation. Difficulties arising from temporal aggregation are shown to correspond to the problem of unobservables. Two previously suggested ways of treating these unobservables due to Blattberg and Jeuland and Bass and Leone are studied in detail focusing on the nature of errors due to each approximation and the aggregation of underlying continuous time stochastic processes. The latter determine the properties of the disturbance terms in the estimating equations. Analytical results are presented and these are examined in light of an empirical application.
Technical Note—Delegating Pricing Responsibility to the Salesforce
Authors: Lal Rajiv
Published: October 2008

In this paper, we use an agency theory framework to address the issue of delegating pricing responsibility to the salesperson. In this analysis, it is shown that delegating the pricing responsibility to the salesperson is as profitable as centralization when the salesperson and the sales manager have identical information about the selling environment; but delegation may be more profitable when the saleperson's information is superior to that of the sales manager's. It is also argued that this characteristic is typical of market conditions where we observe delegation of such responsibility in cases identified by Weinberg (Weinberg, C. B. 1975. An optimal commission plan for salesman's control over price. Management Sci. 21 (8, April) 937–943.) and Stephenson, Cron and Frazier (Stephenson, P. R., W. L. Cron, G. Frazier. 1979. Delegating pricing authority to the salesforce: The effects on sales and profit performance. J. Marketing 43 (April) 21–28.).