IDEAS home Printed from https://ideas.repec.org/a/kap/mktlet/v19y2008i3p337-354.html
   My bibliography  Save this article

Beyond conjoint analysis: Advances in preference measurement

Author

Listed:
  • Oded Netzer
  • Olivier Toubia
  • Eric Bradlow
  • Ely Dahan
  • Theodoros Evgeniou
  • Fred Feinberg
  • Eleanor Feit
  • Sam Hui
  • Joseph Johnson
  • John Liechty
  • James Orlin
  • Vithala Rao

Abstract

No abstract is available for this item.

Suggested Citation

  • Oded Netzer & Olivier Toubia & Eric Bradlow & Ely Dahan & Theodoros Evgeniou & Fred Feinberg & Eleanor Feit & Sam Hui & Joseph Johnson & John Liechty & James Orlin & Vithala Rao, 2008. "Beyond conjoint analysis: Advances in preference measurement," Marketing Letters, Springer, vol. 19(3), pages 337-354, December.
  • Handle: RePEc:kap:mktlet:v:19:y:2008:i:3:p:337-354
    DOI: 10.1007/s11002-008-9046-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11002-008-9046-1
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11002-008-9046-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Neeraj Arora & Xavier Dreze & Anindya Ghose & James Hess & Raghuram Iyengar & Bing Jing & Yogesh Joshi & V. Kumar & Nicholas Lurie & Scott Neslin & S. Sajeesh & Meng Su & Niladri Syam & Jacquelyn Thom, 2008. "Putting one-to-one marketing to work: Personalization, customization, and choice," Marketing Letters, Springer, vol. 19(3), pages 305-321, December.
    2. Marshall P. & Bradlow E.T., 2002. "A Unified Approach to Conjoint Analysis Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 674-682, September.
    3. Jin Gyo Kim & Ulrich Menzefricke & Fred M. Feinberg, 2007. "Capturing Flexible Heterogeneous Utility Curves: A Bayesian Spline Approach," Management Science, INFORMS, vol. 53(2), pages 340-354, February.
    4. Timothy J. Gilbride & Greg M. Allenby, 2004. "A Choice Model with Conjunctive, Disjunctive, and Compensatory Screening Rules," Marketing Science, INFORMS, vol. 23(3), pages 391-406, October.
    5. Jerry Wind & Paul E. Green & Douglas Shifflet & Marsha Scarbrough, 1989. "Courtyard by Marriott : Designing a Hotel Facility with Consumer-Based Marketing Models," Interfaces, INFORMS, vol. 19(1), pages 25-47, February.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Blattberg, Robert C & George, Edward I, 1992. "Estimation under Profit-Driven Loss Functions," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 437-444, October.
    8. Toubia, Olivier & Hauser, John & Simester, Duncan, 2003. "Polyhedral Methods for Adaptive Choice-Based Conjoint Analysis," Working papers 4285-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    9. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    10. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    11. Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth & Börsch-Supan, Axel, 2002. "Hybrid Choice Models: Progress and Challenges," Sonderforschungsbereich 504 Publications 02-29, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
    12. Barnett R. Parker & V. Srinivasan, 1976. "A Consumer Preference Approach to the Planning of Rural Primary Health-Care Facilities," Operations Research, INFORMS, vol. 24(5), pages 991-1025, October.
    13. Han Bleichrodt & Jose Luis Pinto, 2000. "A Parameter-Free Elicitation of the Probability Weighting Function in Medical Decision Analysis," Management Science, INFORMS, vol. 46(11), pages 1485-1496, November.
    14. John C. Liechty & Duncan K. H. Fong & Wayne S. DeSarbo, 2005. "Dynamic Models Incorporating Individual Heterogeneity: Utility Evolution in Conjoint Analysis," Marketing Science, INFORMS, vol. 24(2), pages 285-293, November.
    15. Ernst Fehr & Lorenz Goette, 2007. "Do Workers Work More if Wages Are High? Evidence from a Randomized Field Experiment," American Economic Review, American Economic Association, vol. 97(1), pages 298-317, March.
    16. Michael Yee & Ely Dahan & John R. Hauser & James Orlin, 2007. "Greedoid-Based Noncompensatory Inference," Marketing Science, INFORMS, vol. 26(4), pages 532-549, 07-08.
    17. Peter E. Rossi & Greg M. Allenby, 2003. "Bayesian Statistics and Marketing," Marketing Science, INFORMS, vol. 22(3), pages 304-328, July.
    18. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    19. Rinus Haaijer & Michel Wedel & Marco Vriens & Tom Wansbeek, 1998. "Utility Covariances and Context Effects in Conjoint MNP Models," Marketing Science, INFORMS, vol. 17(3), pages 236-252.
    20. Rao, Vithala R & Steckel, Joel H, 1991. "A Polarization Model for Describing Group Preferences," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(1), pages 108-118, June.
    21. Kim, Jin Gyo & Menzefricke, Ulrich & Feinberg, Fred M., 2005. "Modeling Parametric Evolution in a Random Utility Framework," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 282-294, July.
    22. Wiktor Adamowicz & David Bunch & Trudy Cameron & Benedict Dellaert & Michael Hanneman & Michael Keane & Jordan Louviere & Robert Meyer & Thomas Steenburgh & Joffre Swait, 2008. "Behavioral frontiers in choice modeling," Marketing Letters, Springer, vol. 19(3), pages 215-228, December.
    23. Wilfred Amaldoss & Teck-Hua Ho & Aradhna Krishna & Kay-Yut Chen & Preyas Desai & Ganesh Iyer & Sanjay Jain & Noah Lim & John Morgan & Ryan Oprea & Joydeep Srivasatava, 2008. "Experiments on strategic choices and markets," Marketing Letters, Springer, vol. 19(3), pages 417-429, December.
    24. Dan Horsky & Sanjog Misra & Paul Nelson, 2006. "Observed and Unobserved Preference Heterogeneity in Brand-Choice Models," Marketing Science, INFORMS, vol. 25(4), pages 322-335, 07-08.
    25. John Liechty & Rik Pieters & Michel Wedel, 2003. "Global and local covert visual attention: Evidence from a bayesian hidden markov model," Psychometrika, Springer;The Psychometric Society, vol. 68(4), pages 519-541, December.
    26. V. Srinivasan & Allan Shocker, 1973. "Estimating the weights for multiple attributes in a composite criterion using pairwise judgments," Psychometrika, Springer;The Psychometric Society, vol. 38(4), pages 473-493, December.
    27. Rajeev Kohli & R. Sukumar, 1990. "Heuristics for Product-Line Design Using Conjoint Analysis," Management Science, INFORMS, vol. 36(12), pages 1464-1478, December.
    28. Mohamed Lachaab & Asim Ansari & Kamel Jedidi & Abdelwahed Trabelsi, 2006. "Modeling preference evolution in discrete choice models: A Bayesian state-space approach," Quantitative Marketing and Economics (QME), Springer, vol. 4(1), pages 57-81, March.
    29. Joseph Johnson & Gerard J. Tellis & Deborah J. Macinnis, 2005. "Losers, Winners, and Biased Trades," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(2), pages 324-329, September.
    30. Olivier Toubia & John Hauser & Rosanna Garcia, 2007. "Probabilistic Polyhedral Methods for Adaptive Choice-Based Conjoint Analysis: Theory and Application," Marketing Science, INFORMS, vol. 26(5), pages 596-610, 09-10.
    31. Min Ding & Rajdeep Grewal & John Liechty, 2005. "Incentive-aligned conjoint analysis," Framed Field Experiments 00139, The Field Experiments Website.
    32. Olivier Toubia & John R. Hauser, 2007. "—On Managerially Efficient Experimental Designs," Marketing Science, INFORMS, vol. 26(6), pages 851-858, 11-12.
    33. Tomomi Tanaka & Colin F. Camerer & Quang Nguyen, 2010. "Risk and Time Preferences: Linking Experimental and Household Survey Data from Vietnam," American Economic Review, American Economic Association, vol. 100(1), pages 557-571, March.
    34. Paul E. Green & Abba M. Krieger, 1985. "Models and Heuristics for Product Line Selection," Marketing Science, INFORMS, vol. 4(1), pages 1-19.
    35. Rajeev Kohli & Kamel Jedidi, 2007. "Representation and Inference of Lexicographic Preference Models and Their Variants," Marketing Science, INFORMS, vol. 26(3), pages 380-399, 05-06.
    36. Garrett Sonnier & Andrew Ainslie & Thomas Otter, 2007. "Heterogeneity distributions of willingness-to-pay in choice models," Quantitative Marketing and Economics (QME), Springer, vol. 5(3), pages 313-331, September.
    37. Peter J. Lenk & Wayne S. DeSarbo & Paul E. Green & Martin R. Young, 1996. "Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs," Marketing Science, INFORMS, vol. 15(2), pages 173-191.
    38. Tülin Erdem & Michael Keane & T. Öncü & Judi Strebel, 2005. "Learning About Computers: An Analysis of Information Search and Technology Choice," Quantitative Marketing and Economics (QME), Springer, vol. 3(3), pages 207-247, September.
    39. Chong Ju Choi & Carla C. J. M. Millar & Caroline Y. L. Wong, 2005. "Knowledge and the State," Palgrave Macmillan Books, in: Knowledge Entanglements, chapter 0, pages 19-38, Palgrave Macmillan.
    40. V. Srinivasan & Allan Shocker, 1973. "Linear programming techniques for multidimensional analysis of preferences," Psychometrika, Springer;The Psychometric Society, vol. 38(3), pages 337-369, September.
    41. Arnaud De Bruyn & John C. Liechty & Eelko K. R. E. Huizingh & Gary L. Lilien, 2008. "Offering Online Recommendations with Minimum Customer Input Through Conjoint-Based Decision Aids," Marketing Science, INFORMS, vol. 27(3), pages 443-460, 05-06.
    42. Dapeng Cui & David Curry, 2005. "Prediction in Marketing Using the Support Vector Machine," Marketing Science, INFORMS, vol. 24(4), pages 595-615, January.
    43. Gregory Dobson & Shlomo Kalish, 1993. "Heuristics for Pricing and Positioning a Product-Line Using Conjoint and Cost Data," Management Science, INFORMS, vol. 39(2), pages 160-175, February.
    44. Richard D. McBride & Fred S. Zufryden, 1988. "An Integer Programming Approach to the Optimal Product Line Selection Problem," Marketing Science, INFORMS, vol. 7(2), pages 126-140.
    45. Theodoros Evgeniou & Constantinos Boussios & Giorgos Zacharia, 2005. "Generalized Robust Conjoint Estimation," Marketing Science, INFORMS, vol. 24(3), pages 415-429, May.
    46. Theodoros Evgeniou & Massimiliano Pontil & Olivier Toubia, 2007. "A Convex Optimization Approach to Modeling Consumer Heterogeneity in Conjoint Estimation," Marketing Science, INFORMS, vol. 26(6), pages 805-818, 11-12.
    47. Gerald Häubl & Valerie Trifts, 2000. "Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids," Marketing Science, INFORMS, vol. 19(1), pages 4-21, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. James Agarwal & Wayne DeSarbo & Naresh K. Malhotra & Vithala Rao, 2015. "An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 19-40, March.
    2. Hauser, John R., 2014. "Consideration-set heuristics," Journal of Business Research, Elsevier, vol. 67(8), pages 1688-1699.
    3. Olivier Toubia & Eric Johnson & Theodoros Evgeniou & Philippe Delquié, 2013. "Dynamic Experiments for Estimating Preferences: An Adaptive Method of Eliciting Time and Risk Parameters," Management Science, INFORMS, vol. 59(3), pages 613-640, June.
    4. Xinfang (Jocelyn) Wang & Jeffrey D. Camm & David J. Curry, 2009. "A Branch-and-Price Approach to the Share-of-Choice Product Line Design Problem," Management Science, INFORMS, vol. 55(10), pages 1718-1728, October.
    5. Theodoros Evgeniou & Massimiliano Pontil & Olivier Toubia, 2007. "A Convex Optimization Approach to Modeling Consumer Heterogeneity in Conjoint Estimation," Marketing Science, INFORMS, vol. 26(6), pages 805-818, 11-12.
    6. Michael Yee & Ely Dahan & John R. Hauser & James Orlin, 2007. "Greedoid-Based Noncompensatory Inference," Marketing Science, INFORMS, vol. 26(4), pages 532-549, 07-08.
    7. Jeffrey D. Camm & James J. Cochran & David J. Curry & Sriram Kannan, 2006. "Conjoint Optimization: An Exact Branch-and-Bound Algorithm for the Share-of-Choice Problem," Management Science, INFORMS, vol. 52(3), pages 435-447, March.
    8. Halme, Merja & Kallio, Markku, 2011. "Estimation methods for choice-based conjoint analysis of consumer preferences," European Journal of Operational Research, Elsevier, vol. 214(1), pages 160-167, October.
    9. Ghaderi, Mohammad & Kadziński, Miłosz, 2021. "Incorporating uncovered structural patterns in value functions construction," Omega, Elsevier, vol. 99(C).
    10. Daria Dzyabura & John R. Hauser, 2011. "Active Machine Learning for Consideration Heuristics," Marketing Science, INFORMS, vol. 30(5), pages 801-819, September.
    11. Dongling Huang & Lan Luo, 2016. "Consumer Preference Elicitation of Complex Products Using Fuzzy Support Vector Machine Active Learning," Marketing Science, INFORMS, vol. 35(3), pages 445-464, May.
    12. Arjan Verschoor & Ben D’Exelle, 2022. "Probability weighting for losses and for gains among smallholder farmers in Uganda," Theory and Decision, Springer, vol. 92(1), pages 223-258, February.
    13. Simon Gächter & Eric J. Johnson & Andreas Herrmann, 2022. "Individual-level loss aversion in riskless and risky choices," Theory and Decision, Springer, vol. 92(3), pages 599-624, April.
    14. Kpegli, Yao Thibaut & Corgnet, Brice & Zylbersztejn, Adam, 2023. "All at once! A comprehensive and tractable semi-parametric method to elicit prospect theory components," Journal of Mathematical Economics, Elsevier, vol. 104(C).
    15. Scholz, Michael & Dorner, Verena & Schryen, Guido & Benlian, Alexander, 2017. "A configuration-based recommender system for supporting e-commerce decisions," European Journal of Operational Research, Elsevier, vol. 259(1), pages 205-215.
    16. Dimitris Bertsimas & Velibor V. Mišić, 2017. "Robust Product Line Design," Operations Research, INFORMS, vol. 65(1), pages 19-37, February.
    17. repec:cup:judgdm:v:4:y:2009:i:3:p:200-213 is not listed on IDEAS
    18. Immanuel Lampe & Daniel Würtenberger, 2019. "Loss Aversion And The Demand For Index Insurance," Working Papers on Finance 1907, University of St. Gallen, School of Finance.
    19. Michalek, Jeremy J. & Ebbes, Peter & Adigüzel, Feray & Feinberg, Fred M. & Papalambros, Panos Y., 2011. "Enhancing marketing with engineering: Optimal product line design for heterogeneous markets," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 1-12.
    20. Maoqi Liu & Li Zheng & Changchun Liu & Zhi‐Hai Zhang, 2023. "From share of choice to buyers' welfare maximization: Bridging the gap through distributionally robust optimization," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1205-1222, April.
    21. Maldonado, Sebastián & Montoya, Ricardo & Weber, Richard, 2015. "Advanced conjoint analysis using feature selection via support vector machines," European Journal of Operational Research, Elsevier, vol. 241(2), pages 564-574.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:mktlet:v:19:y:2008:i:3:p:337-354. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.