Abstract

Conjoint analysis has been a widely used method for measuring customer preferences since 1970s. This method is based on the idea that customers' decisions depend on all tangible and intangible product features. One of the fundamental steps in performing conjoint analysis is the construction of experimental designs. These designs are expected to be orthogonal and balanced in an ideal case. In practice, it is hard to construct optimal designs and thus constructing of near optimal and efficient designs is carried out. There are several ways to quantify the relative efficiency of experimental designs. The choice of measure will determine which types of experimental designs are favoured as well as the algorithms for choosing efficient designs. In this paper, we propose a simultaneous algorithm which combines two optimality criteria: standard criterion named by A-efficiency, and nonstandard criterion, P-value. The algorithm was implemented as the procedure in MCON software for traditional conjoint analysis.

Description