Recent Developments and Future Outlook

Vithala R. Rao ()
Additional contact information
Vithala R. Rao: S. C. Johnson Graduate School of Management Cornell University, Deane Malott Professor of Management (Emeritus)

Chapter 13 in Applied Conjoint Analysis, 2026, pp 429-454 from Springer

Abstract: Abstract The previous chapters described several approaches employed for determining partworths of attributes and tradeoffs among them. The chapters dealt with various methods for both of ratings-based and choice-based conjoint methods. In addition, we described several applications of conjoint methodology to different marketing problems such as product design, product positioning, pricing, market segmentation, and several miscellaneous problems. During the last thirty plus years since these methods were introduced to marketing research, researchers have tackled various problems that are encountered in applying these methods in practice. As Hauser and Rao have noted, conjoint analysis is alive and well. In fact there have been several developments in the last 5–10 years that place this methodology as one of the most vibrant techniques in marketing research.

Keywords: Conjoint analysis; Mixed logit model; Attribute importance; Multinomial probit model; Adaptive conjoint analysis (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sptchp:978-3-032-00894-7_13

Ordering information: This item can be ordered from
http://www.springer.com/9783032008947

DOI: 10.1007/978-3-032-00894-7_13

Access Statistics for this chapter

More chapters in Springer Texts in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().