Adaptive Choice-based Conjoint Analysis

Adaptive Choice-Based Conjoint Analysis is a methodological framework within preference elicitation that iteratively personalizes choice tasks based on respondent choices to more efficiently estimate individual utility functions compared to static conjoint designs.

90

Publications

4.2K

Citations

291

Authors

179

Institutions

Publications per year

2017–2026

32

Variants

Acbc

Authors

291

  1. LF
    Liana Fraenkel

    Yale University, United States

    9 publications · 392 citations

    9

    h-index

  2. MD
    M.A. Drake

    North Carolina State University, United States

    6 publications · 288 citations

    6

    h-index

  3. DR
    Dick R. Wittink

    Cornell University, United States

    4 publications · 158 citations

    4

    h-index

  4. DB
    David B. Montgomery

    Stanford University, United States

    4 publications · 177 citations

    4

    h-index

  5. CA
    Catherine A. Ramus

    University of California, Santa Barbara, United States

    4 publications · 177 citations

    4

    h-index

1–5 of 291

Venues

  1. Journal of Marketing Research

    4 publications · 154 citations

    4

    h-index

  2. Medical Decision Making

    MDM · 4 publications · 147 citations

    4

    h-index

  3. Journal of Sensory Studies

    3 publications · 122 citations

    3

    h-index

  4. SSRN Electronic Journal

    Repository · 3 publications · 114 citations

    3

    h-index

  5. Journal of Dairy Science

    JDS · 2 publications · 63 citations

    2

    h-index

1–5