Estimation Of Product Attributes And Their Importances

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.

This mono graph is intended for an advanced undergraduate or graduate course as weIl as for the researchers who want a compilation of developments in this rapidly growing field of operations research. This is a sequel to our previous work entitled "Multiple Objective Decision Making--Methods and Applications: A State-of-the-Art Survey," (No. 164 of the Lecture Notes). The literature on methods and applications of Multiple Attribute Decision Making (MADM) has been reviewed and classified systematically. This study provides readers with a capsule look into the existing methods, their char acteristics, and applicability to analysis of MADM problems. The basic MADM concepts are defined and a standard notation is introduced in Part 11. Also introduced are foundations such as models for MADM, trans formation of attributes, fuzzy decision rules, and methods for assessing weight. A system of classifying seventeen major MADM methods is presented. These methods have been proposed by researchers in diversified disciplines; half of them are classical ones, but the other half have appeared recently. The basic concept, the computational procedure, and the characteristics of each of these methods are presented concisely in Part 111. The computational procedure of each method is illustrated by solving a simple numerical example. Part IV of the survey deals with the applications of these MADM methods.

This book constitutes the refereed proceedings of the 5th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2016, held in Da Nang, Vietnam, in November/December 2016. The IUKM symposia aim to provide a forum for exchanges of research results and ideas, and experience of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.