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.
Schmittlein and Mahajan (Schmittlein, D. C., V. Mahajan. 1982. Maximum likelihood estimation for an innovation diffusion model of new product acceptance. Marketing Sci. 1 (Winter) 57–78.) made an important improvement in the estimation of the Bass (Bass, F. M. 1969. A new product growth model for consumer durables. Management Sci. 15 (January) 215–227.) diffusion model by appropriately aggregating the continuous time model over the time intervals represented by the data. However, by restricting consideration to only sampling errors and ignoring all other errors (such as the effects of excluded marketing variables), their Maximum Likelihood Estimation (MLE) seriously underestimates the standard errors of the estimated parameters. This note uses an additive error term to model sampling and other errors in the Schmittlein and Mahajan formulation. The proposed Nonlinear Least Squares (NLS) approach produces valid standard error estimates. The fit and the predictive validity are roughly comparable for the two approaches. Although the empirical applications reported in this paper are in the context of the Bass diffusion model, the NLS approach is also applicable to other diffusion models for which cumulative adoption can be expressed as an explicit function of time.
Response to the commentary Pringle, L. G. 1984. A Comment. Marketing Sci. 3 125–126 on author's paper Rust, R. T., M. I. Alpert. 1984. An audience flow model of television viewing choice. Marketing Sci. 3 113–124.
Comments and authors' rejoinder to Mahajan, V., E. Muller, S. Sharma. 1984. An empirical comparison of awareness forecasting models of new product introduction. Marketing Sci. 3 179–197.
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.
This paper examines the feasibility, practicality, and predictive ability of the consumer model which was proposed by Hauser and Shugan (Hauser, J. R., S. M. Shugan. 1983. Defensive marketing strategies. Marketing Sci. 2 (4, Fall) 319–360). We report results in two product categories, each representing over $100 million in annual sales. We develop “per dollar” perceptual maps and empirical consumer “taste” distributions. As a first test of the model, we compare the predictive ability of the consumer model in one category to (1) pretest market laboratory measurement models, (2) traditional perceptual mapping procedures, (3) a hybrid model using price as an attribute, and (4) actual market shares in test market cities. In the second product category, we illustrate the application of the quantitative model to augment managerial judgment. Besides developing an empirical version of the “Defender” consumer model, our analyses raise a number of behavioral hypotheses worth further investigation.
The recall and recognition of people for 95 print ads were examined with an aim toward investigating memory structure and decay processes. It was found that recall and recognition do not, by themselves, measure a single underlying memory state. Rather, memory is multidimensional, and recall and recognition capture only a portion of memory, while at the same time reflecting other mental states. When interest in the ads was held constant, however, recall and recognition did measure memory as a unidimensional construct. Further, an examination of memory over three points in time showed considerable stability. The findings are interpreted from the perspective of recent research in cognitive psychology as well as current thinking in consumer behavior and advertising research. Managerial implications are considered as well.
A multinomial logit model of brand choice, calibrated on 32 weeks of purchases of regular ground coffee by 100 households, shows high statistical signficance for the explanatory variables of brand loyalty, size loyalty, presence/absence of store promotion, regular shelf price and promotional price cut. The model is parsimonious in that the coefficients of these variables are modeled to be the same for all coffee brand-sizes. The calibrated model predicts remarkably well the share of purchases by brand-size in a hold-out sample of 100 households over the 32-week calibration period and a subsequent 20-week forecast period. The success of the model is attributed in part to the level of detail and completeness of the household panel data employed, which has been collected through optical scanning of the Universal Product Code in supermarkets. Three short-term market response measures are calculated from the model: regular (depromoted) price elasticity of share, percent increase in share for a promotion with a median price cut, and promotional price cut elasticity of share. Response varies across brand-sizes in a systematic way with large share brand-sizes showing less response in percentage terms but greater in absolute terms. On the basis of the model a quantitative picture emerges of groups of loyal customers who are relatively insensitive to marketing actions and a pool of switchers who are quite sensitive.
Structural transformations of the MCI model are presented which make the model easily estimated using dummy variables with widely available regression packages. The MCI model is empirically shown to provide better predictive power than several other models of similar form, but ones which do not produce logically consistent market share estimates.
This paper reports some further analyses and applications of Morrison's model of the predictive relationship between measures of intentions and subsequent purchasing behavior. A review of published studies bearing on the threats to predictive validity of intention scales represented in Morrison's model is presented. Findings from a test-retest study of intention ratings for concept stimuli are shown to be consistent with the levels of reliability expected under the model's assumptions of beta binomial distributed scores. Evidence of the predictive validity of intention measures is found in a re-analysis of several sets of relevant data but a different form of predictive relationship is shown to hold for generic durable goods as compared to branded packaged goods. Whereas a linear relationship is supported in the case of durable goods, the presence of a threshold phenomenon in the branded packaged goods data suggests the use of a piecewise linear model. There is reason to believe that the nature and sources of systematic error present in intentions ratings are different for these two types of purchases.