Estimation of Product Attributes and Their Importances e-bog
436,85 DKK
(inkl. moms 546,06 DKK)
At this point in time, there is no generally accepted methodology for explaining and predicting human behavior given a product choice situation. This is true despite the critical importance of such meth- odology to marketing, transportation and urban planning. While the social sciences provide numerous theories to be tested and the mathe- matical and statistical procedures exist in general to d...
E-bog
436,85 DKK
Forlag
Springer
Udgivet
6 december 2012
Genrer
Econometrics and economic statistics
Sprog
English
Format
pdf
Beskyttelse
LCP
ISBN
9783642657535
At this point in time, there is no generally accepted methodology for explaining and predicting human behavior given a product choice situation. This is true despite the critical importance of such meth- odology to marketing, transportation and urban planning. While the social sciences provide numerous theories to be tested and the mathe- matical and statistical procedures exist in general to do so, at this point, no single unified theory has emerged. It is generally accepted that to explain product choice behav- ior,products must be described in terms of attributes. Using anyone of a number of procedures, it is possible to obtain measurements on the attributes of the products under consideration. However, there is no generally accepted methodology. Given the attribute profiles of two products, in order to explain and predict preference, it is necessary to determine the relative importance of each of the product attributes. Once again, there is no generally accepted methodology. There are two basic approaches: The first, called the attitudinal approach, obtains importance measure- ments directly from respondents using one of many scaling techniques; the second, termed the inferential method endeavors to infer impor- tances from product preference and attribute data. Since it is gen- erally felt that respondents are unwilling and/or unable to provide meaningful importance measurements, the inferential method is most widely accepted.