Beyond conjoint analysis: Advances in preference measurement

被引：67

作者：

Netzer, Oded ^{[1
]}

Toubia, Olivier ^{[1
]}

Bradlow, Eric T. ^{[2
]}

Dahan, Ely ^{[3
]}

Evgeniou, Theodoros ^{[4
]}

Feinberg, Fred M. ^{[5
]}

Feit, Eleanor M. ^{[5
]}

Hui, Sam K. ^{[6
]}

Johnson, Joseph ^{[7
]}

Liechty, John C. ^{[8
]}

Orlin, James B. ^{[9
]}

Rao, Vithala R. ^{[10
]}

机构：

[1] Columbia Univ, Columbia Business Sch, New York, NY 10027 USA

[2] Univ Penn, Philadelphia, PA 19104 USA

[3] Univ Calif Los Angeles, Anderson Sch, Los Angeles, CA 90095 USA

[4] INSEAD, F-77305 Fontainebleau, France

[5] Univ Michigan, Stephen M Ross Sch Business, Ann Arbor, MI 48109 USA

[6] NYU, Stern Sch Business, New York, NY 10012 USA

[7] Univ Miami, Sch Business Adm, Coral Gables, FL 33146 USA

[8] Penn State Univ, Smeal Coll Business, University Pk, PA 16802 USA

[9] MIT, Alfred P Sloan Sch Management, Cambridge, MA 02139 USA

[10] Cornell Univ, Johnson Grad Sch Management, Ithaca, NY 14853 USA

来源：

MARKETING LETTERS | 2008年 / 19卷 / 3-4期

关键词：

Preference measurement; Conjoint analysis; Marketing research;

D O I：

10.1007/s11002-008-9046-1

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

We identify gaps and propose several directions for future research in preference measurement. We structure our argument around a framework that views preference measurement as comprising three interrelated components: (1) the problem that the study is ultimately intended to address; (2) the design of the preference measurement task and the data collection approach; (3) the specification and estimation of a preference model, and the conversion into action. Conjoint analysis is only one special case within this framework. We summarize cutting edge research and identify fruitful directions for future investigations pertaining to the framework's three components and to their integration.

引用

页码：337 / 354

页数：18

共 50 条

[1] Beyond conjoint analysis: Advances in preference measurement
Oded Netzer
Olivier Toubia
Eric T. Bradlow
Ely Dahan
Theodoros Evgeniou
Fred M. Feinberg
Eleanor M. Feit
Sam K. Hui
Joseph Johnson
John C. Liechty
James B. Orlin
Vithala R. Rao
[J]. Marketing Letters, 2008, 19 : 337 - 354
[2] New Method for Preference Measurement in Ranking-based Conjoint Analysis
Kim, Bu-Yong
[J]. KOREAN JOURNAL OF APPLIED STATISTICS, 2014, 27 (02) : 185 - 195
[3] Measurement of headlight form preference using choice based conjoint analysis
Swamy, Surya
Orsborn, Seth
Michalek, Jeremy
Cagan, Jonathan
[J]. PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE 2007, VOL 6, PTS A AND B, 2008, : 197 - 206
[4] Predicted preference conjoint analysis
Radas, Sonja
Prelec, Drazen
[J]. PLOS ONE, 2021, 16 (08):
[5] CONJOINT-ANALYSIS VS PREFERENCE ANALYSIS - A COMPARISON
SCHORI, TR
MEADOW, HL
[J]. PSYCHOLOGICAL REPORTS, 1987, 60 (03) : 1063 - 1068
[6] Conjoint analysis of consumer preference for bluefin tuna
Ariji, Masahiko
[J]. FISHERIES SCIENCE, 2010, 76 (06) : 1023 - 1028
[7] Conjoint analysis of consumer preference for bluefin tuna
Masahiko Ariji
[J]. Fisheries Science, 2010, 76 : 1023 - 1028
[8] Preference measurement using conjoint methods: An empirical investigation of reliability
Bryan, S
Gold, L
Sheldon, R
Buxton, M
[J]. HEALTH ECONOMICS, 2000, 9 (05) : 385 - 395
[9] CAPTURING CONSUMER PREFERENCE THROUGH EXPERIENTIAL CONJOINT ANALYSIS
Tovares, Noah
Cagan, Jonathan
Boatwright, Peter
[J]. PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, 2013, VOL 5, 2014,
[10] PREFERENCE OF RELEVANT OTHERS AND INDIVIDUAL CHOICE MODELS - APPLICATION OF CONJOINT MEASUREMENT
WIND, Y
[J]. PUBLIC OPINION QUARTERLY, 1974, 38 (03) : 447 - 447

← 1 2 3 4 5 →