Methods for a Large Number of Attributes

Vithala R. Rao
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Vithala R. Rao: Cornell University

Chapter Chapter 5 in Applied Conjoint Analysis, 2014, pp 185-223 from Springer

Abstract: Abstract In the previous chapters we discussed various conjoint analysis methods for ratings-based ad choice-based studies. One problem that nags applied researchers is how to deal with the issue of large numbers of attributes (and levels) to be included that arise in any practical problem. This problem may arise particularly for technologically complex products which usually have a large number of attributes. Over the years, researchers have come up with different methods to deal with this problem. While we have mentioned tangentially some of the applicable methods, this chapter will pull together various methods developed. In the next section (Sect. 5.2), we will describe the main problem when a conjoint study has to deal with a large number of attributes and then present an overview of the methods available in the literature. In Sect. 5.3, we will describe each method in some detail (data collection approach and analysis method) along with an application. Section 5.4 compares the methods on a set of relevant criteria. Finally, we will offer several directions for future research on the issue of a large number of attributes in any conjoint study and conjecture possible newer developments. Some newer data collection methods that use auctions also deal with the large number of attributes problem.

Keywords: Attribute Level; Conjoint Analysis; Fractional Factorial Design; Importance Rating; Support Vector Machine Method (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-3-540-87753-0_5

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