Lee G. Cooper

Strategic Marketing Planning for Radically New Products

In this article, the author outlines an approach to marketing planning for radically new products, disruptive or discontinuous innovations that change the dimensionality of the consumer decision. The planning process begins with an extensive situation analysis. The factors identified in the situation analysis are woven into the economic webs surrounding the new product. The webs are mapped into Bayesian networks that can be updated as events unfold and used to simulate the impact that changes in assumptions underlying the web have on the prospects for the new product. The author illustrates this method using a historical case regarding the introduction of videotape recorders by Sony and JVC and a contemporary case of the introduction of electric vehicles. The author provides a complete, numerical example pertaining to a software development project in the Appendix.

Standardizing Variables in Multiplicative Choice Models

To use multiplicative competitive interaction (MCI) models as part of a theory of the evaluative process in choice, we need a method to transform interval scale consumer judgments into positive, ratio scales. We develop a coefficient—zeta-squared—that possesses the needed scale requirements and other theoretically desirable properties, and report four research studies to demonstrate the diversity of applications of multiplicative choice models using zeta-squared. We also discuss the relations of MCI models to Luce choice models to illustrate the potential of zeta-squared for representing the effects of similarity on choice, and consider some of the benefits of standardizing variables in MCI models or multinomial logit models.

A Review of Multidimensional Scaling in Marketing Research

The domain of this review includes the develop ment and application of multidimensional scaling (MDS) in product planning; in decisions concerning pricing and branding; in the study of channels of dis tribution, personal selling, and the effects of advertis ing ; and in research related to the fact finding and analysis mission of marketing research. In research on product planning, specific attention is given to market structure analysis, to the development of a master con figuration of product perceptions, to the role of indi vidual differences, to representing consumer prefer ences, to issues in market segmentation, and to the use of asymmetric MDS to study market structure. Regarding fact finding and analysis, this review deals with issues in data collection such as the response rate, time, and accuracy of judgments; the validity, re liability, and stability of judgments; and the robustness of data collection techniques and MDS algorithms. A separate section on new-product models deals with the determination of relevant product markets, the identifi cation of determinant attributes, the creation of prod uct perceptual spaces, and the modeling of individual or market-segment decision making. Three trends are discussed briefly; (1) a trend toward finer grained in spection of individual and group perceptions, (2) a trend toward merging consumer level measurement and market level measurements, and (3) a trend to ward the study of the creation of new markets, rather than new products in existing markets.

Voting for a Political Candidate Under Conditions of Minimal Information

Until very recently, the major focus of research in the field of consumer behavior has been on the selection of products, brands and decision choices primarily in the sphere of marketing. The purpose of this paper was to modify a model developed to measure market share to account for the variables that enter into the selection of a political candidate and predict voting behavior.

Building market structures from consumer preferences

The authors present a model that maps competitive market structures by identifying the preference structure of each consumer segment. By marrying two different data types—switching probabilities an...

TWO LOGIT MODELS FOR EXTERNAL ANALYSIS OF PREFERENCES

A logit vector model and a logit ideal point model are presented for external analysis of paired comparison preference judgments aggregated over a homogeneous group. The logit vector model is hierarchically nested within the logit ideal point model so that statistical tests are available to distinguish between these two models. Generalized least squares estimation procedures are developed to account for heteroscedastic sampling error variances and specification error variances. Two numerical illustrations deal with judgments concerning employee compensation plans and preferences for salt and sugar in the brine of canned green beans.

A MULTIVARIATE INVESTIGATION OF PREFERENCES

The concept of preference is of primary importance in psychology. It has had an implicit role in almost every psychological theory, but no major efforts have been directed toward the explication of preference as a psychological concept. Why is one object preferred to another? is a question which has remained unan- swered, at least to the extent that the psychological nature of pref- erence has remained subservient to the other purposes of investigators.

Obtaining squared multiple correlations from a correlation matrix which may be singular

A theorem is presented relating the squared multiple correlation of each measure in a battery with the other measures to the unique generalized inverse of the correlation matrix. This theorem is independent of the rank of the correlation matrix and may be utilized for singular correlation matrices. A coefficient is presented which indicates whether the squared multiple correlation is unity or not. Note that not all measures necessarily have unit squared multiple correlations with the other measures when the correlation matrix is singular. Some suggestions for computations are given for simultaneous determination of squared multiple correlations for all measures.

A New Solution to the Additive Constant Problem in Metric Multidimensional Scaling.

A new solution to the additive constant problem in metric multidimensional scaling is developed. This solution determines, for a given dimensionality, the additive constant and the resulting stimulus projections on the dimensions of a Euclidean space which minimize the sum of squares of discrepancies between the formal model for metric multidimensional scaling and the original data. A modification of Fletcher-Powell style functional iteration is used to compute solutions. A scale free index of the goodness of fit is developed to aid in selecting solutions of adequate dimensionality from multiple candidates.

Using genetic algorithms to breed competitive marketing strategies

Genetic algorithms (GAs) have been used for mappings which optimize a repeated procedure. An offshoot of this has been their use in what has been called co-evolution of mappings. This paper reports results from a project in which GAs have been used to: 1) to derive mappings which may explain the behavior of brand managers in an oligopolistic retail market for coffee; and 2) to attempt to improve on the historical profits of these brand managers, pitted in weekly competition with each other, vying for sales and profits with their different brands of ground, sealed coffee on the supermarket shelves. As well as advancing the practice of GAs, with separate populations competing, the work also advances our understanding of modeling players in repeated oligopolistic interactions or games.