Johnson, Richard M.
March 1987
Marketing Science;Spring87, Vol. 6 Issue 2, p204
Academic Journal
This paper is concerned with the intriguing idea of "automatic" methods for determining those characteristics a product should have for greatest market share. The authors compare four interesting algorithms that approach the problem quite differently. Their undertaking was ambitious and well carried out; the computational effort was large and the results are presented clearly and are believable. The basic idea is compelling: each product is assumed to occupy a position in space, as is each respondent's "ideal point." His "liking" for a product is presumed to be related to the nearness of his ideal point to that product. But beyond this generality are important details about which little is known. Two such questions concern the estimation of ideal points and the choice of the function relating distance to preference. If an ideal point and dimensional weights are estimated from preference data. it is common to find negative weights, unless they are constrained to be nonnegative. To accept these is to refute the underlying model. Procedures for estimating ideal points and dimensional weights simultaneously appear vulnerable to colinearity. This suggcsts there may be problems in quality of estimation even in those cases where negatives are not observed.


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