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Fast Polyhedral Adaptive Conjoint Estimation

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Cited by:

  1. Joel Steckel & Russell Winer & Randolph Bucklin & Benedict Dellaert & Xavier Drèze & Gerald Häubl & Sandy Jap & John Little & Tom Meyvis & Alan Montgomery & Arvind Rangaswamy, 2005. "Choice in Interactive Environments," Marketing Letters, Springer, vol. 16(3), pages 309-320, December.
  2. Danaf, Mazen & Guevara, C. Angelo & Ben-Akiva, Moshe, 2023. "A control-function correction for endogeneity in random coefficients models: The case of choice-based recommender systems," Journal of choice modelling, Elsevier, vol. 46(C).
  3. Rod Mccoll & Yann Truong & Antonella La Rocca, 2019. "Service guarantees as a base for positioning in B2B," Post-Print hal-02326105, HAL.
  4. 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.
  5. 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.
  6. John Hauser & Gerard J. Tellis & Abbie Griffin, 2006. "Research on Innovation: A Review and Agenda for," Marketing Science, INFORMS, vol. 25(6), pages 687-717, 11-12.
  7. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part I. Integrative synthesis of empirical evidence and conceptualisation of external validity," Papers 2102.02940, arXiv.org.
  8. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods," Journal of choice modelling, Elsevier, vol. 41(C).
  9. Murray, Kyle B. & Häubl, Gerald, 2009. "Personalization without Interrogation: Towards more Effective Interactions between Consumers and Feature-Based Recommendation Agents," Journal of Interactive Marketing, Elsevier, vol. 23(2), pages 138-146.
  10. Yupeng Chen & Raghuram Iyengar & Garud Iyengar, 2017. "Modeling Multimodal Continuous Heterogeneity in Conjoint Analysis—A Sparse Learning Approach," Marketing Science, INFORMS, vol. 36(1), pages 140-156, January.
  11. Nikhil Bhat & Vivek F. Farias & Ciamac C. Moallemi & Deeksha Sinha, 2020. "Near-Optimal A-B Testing," Management Science, INFORMS, vol. 66(10), pages 4477-4495, October.
  12. Dimitris Bertsimas & Velibor V. Mišić, 2017. "Robust Product Line Design," Operations Research, INFORMS, vol. 65(1), pages 19-37, February.
  13. Dong, Songting & Ding, Min & Huber, Joel, 2010. "A simple mechanism to incentive-align conjoint experiments," International Journal of Research in Marketing, Elsevier, vol. 27(1), pages 25-32.
  14. Arinze Christian Nwoba & Nathaniel Boso & Matthew J. Robson, 2021. "Corporate sustainability strategies in institutional adversity: Antecedent, outcome, and contingency effects," Business Strategy and the Environment, Wiley Blackwell, vol. 30(2), pages 787-807, February.
  15. Fay, Scott & Mitra, Deb & Wang, Qiong, 2009. "Ask or infer? Strategic implications of alternative learning approaches in customization," International Journal of Research in Marketing, Elsevier, vol. 26(2), pages 136-152.
  16. Srinivasan, V. Seenu & Netzer, Oded, 2007. "Adaptive Self-Explication of Multi-attribute Preferences," Research Papers 1979, Stanford University, Graduate School of Business.
  17. Hauser, John R., 2014. "Consideration-set heuristics," Journal of Business Research, Elsevier, vol. 67(8), pages 1688-1699.
  18. Pantourakis, Michail & Tsafarakis, Stelios & Zervoudakis, Konstantinos & Altsitsiadis, Efthymios & Andronikidis, Andreas & Ntamadaki, Vasiliki, 2022. "Clonal selection algorithms for optimal product line design: A comparative study," European Journal of Operational Research, Elsevier, vol. 298(2), pages 585-595.
  19. Danaf, Mazen & Guevara, Angelo & Atasoy, Bilge & Ben-Akiva, Moshe, 2020. "Endogeneity in adaptive choice contexts: Choice-based recommender systems and adaptive stated preferences surveys," Journal of choice modelling, Elsevier, vol. 34(C).
  20. 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.
  21. Dimitris Bertsimas & Allison O'Hair, 2013. "Learning Preferences Under Noise and Loss Aversion: An Optimization Approach," Operations Research, INFORMS, vol. 61(5), pages 1190-1199, October.
  22. Steven M. Shugan, 2004. "Endogeneity in Marketing Decision Models," Marketing Science, INFORMS, vol. 23(1), pages 1-3.
  23. Jimmy Q. Li & Paat Rusmevichientong & Duncan Simester & John N. Tsitsiklis & Spyros I. Zoumpoulis, 2015. "The Value of Field Experiments," Management Science, INFORMS, vol. 61(7), pages 1722-1740, July.
  24. Martijn G. de Jong & Jan-Benedict E. M. Steenkamp & Bernard P. Veldkamp, 2009. "A Model for the Construction of Country-Specific Yet Internationally Comparable Short-Form Marketing Scales," Marketing Science, INFORMS, vol. 28(4), pages 674-689, 07-08.
  25. Jong Seok Kim, 2017. "Empirical Analysis Of Consumer Willingness To Pay For Smart Phone Attributes In Multi-Countries," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 21(02), pages 1-37, February.
  26. 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.
  27. Alexandre Belloni & Robert Freund & Matthew Selove & Duncan Simester, 2008. "Optimizing Product Line Designs: Efficient Methods and Comparisons," Management Science, INFORMS, vol. 54(9), pages 1544-1552, September.
  28. Mingyu Joo & Michael L. Thompson & Greg M. Allenby6, 2019. "Optimal Product Design by Sequential Experiments in High Dimensions," Management Science, INFORMS, vol. 65(7), pages 3235-3254, July.
  29. John R. Hauser & Olivier Toubia, 2005. "The Impact of Utility Balance and Endogeneity in Conjoint Analysis," Marketing Science, INFORMS, vol. 24(3), pages 498-507, August.
  30. Olivier Toubia & John R. Hauser, 2007. "—On Managerially Efficient Experimental Designs," Marketing Science, INFORMS, vol. 26(6), pages 851-858, 11-12.
  31. Steven M. Shugan, 2003. "Editorial: Journal Rankings: Save the Outlets for Your Research," Marketing Science, INFORMS, vol. 22(4), pages 437-441.
  32. Ghaderi, Mohammad & Kadziński, Miłosz, 2021. "Incorporating uncovered structural patterns in value functions construction," Omega, Elsevier, vol. 99(C).
  33. Maxime C. Cohen & Ilan Lobel & Renato Paes Leme, 2020. "Feature-Based Dynamic Pricing," Management Science, INFORMS, vol. 66(11), pages 4921-4943, November.
  34. Hema Yoganarasimhan & Ebrahim Barzegary & Abhishek Pani, 2020. "Design and Evaluation of Personalized Free Trials," Papers 2006.13420, arXiv.org.
  35. Tsafarakis, Stelios & Zervoudakis, Konstantinos & Andronikidis, Andreas & Altsitsiadis, Efthymios, 2020. "Fuzzy self-tuning differential evolution for optimal product line design," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1161-1169.
  36. Eggers, Felix & Sattler, Henrik, 2009. "Hybrid individualized two-level choice-based conjoint (HIT-CBC): A new method for measuring preference structures with many attribute levels," International Journal of Research in Marketing, Elsevier, vol. 26(2), pages 108-118.
  37. Daniel McFadden, 2014. "The new science of pleasure: consumer choice behavior and the measurement of well-being," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 2, pages 7-48, Edward Elgar Publishing.
  38. 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.
  39. Theodoros Evgeniou & Constantinos Boussios & Giorgos Zacharia, 2005. "Generalized Robust Conjoint Estimation," Marketing Science, INFORMS, vol. 24(3), pages 415-429, May.
  40. 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.
  41. Robert Dunlea & Leslie Lenert, 2015. "Understanding Patients’ Preferences for Referrals to Specialists for an Asymptomatic Condition," Medical Decision Making, , vol. 35(6), pages 691-702, August.
  42. 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.
  43. 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.
  44. Joffre Swait & Rick L. Andrews, 2003. "Enriching Scanner Panel Models with Choice Experiments," Marketing Science, INFORMS, vol. 22(4), pages 442-460, September.
  45. Tan Wang & Genaro Gutierrez, 2022. "Robust Product Line Design by Protecting the Downside While Minding the Upside," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 194-217, January.
  46. Dominique Olié Lauga & Elie Ofek, 2009. "Market Research and Innovation Strategy in a Duopoly," Marketing Science, INFORMS, vol. 28(2), pages 373-396, 03-04.
  47. Rajeev Kohli & Khaled Boughanmi & Vikram Kohli, 2019. "Randomized Algorithms for Lexicographic Inference," Operations Research, INFORMS, vol. 67(2), pages 357-375, March.
  48. Dimitris Bertsimas & Velibor V. Mišić, 2017. "Robust Product Line Design," Operations Research, INFORMS, vol. 65(1), pages 19-37, February.
  49. Dimitris Bertsimas & Velibor V. Mišić, 2019. "Exact First-Choice Product Line Optimization," Operations Research, INFORMS, vol. 67(3), pages 651-670, May.
  50. Díaz, Verónica & Montoya, Ricardo & Maldonado, Sebastián, 2023. "Preference estimation under bounded rationality: Identification of attribute non-attendance in stated-choice data using a support vector machines approach," European Journal of Operational Research, Elsevier, vol. 304(2), pages 797-812.
  51. Steven M. Shugan, 2004. "The Impact of Advancing Technology on Marketing and Academic Research," Marketing Science, INFORMS, vol. 23(4), pages 469-475.
  52. 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.
  53. 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.
  54. Furrer, Olivier & Sudharshan, Devanathan & Tsiotsou, Rodoula H. & Liu, Ben S., 2016. "A framework for innovative service design," FSES Working Papers 476, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
  55. Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2011. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Management Science, INFORMS, vol. 57(8), pages 1485-1509, August.
  56. Decker, Reinhold & Trusov, Michael, 2010. "Estimating aggregate consumer preferences from online product reviews," International Journal of Research in Marketing, Elsevier, vol. 27(4), pages 293-307.
  57. Orbach Yair & Fruchter Gila E., 2010. "A Utility-Based Diffusion Model Applied to the Digital Camera Case," Review of Marketing Science, De Gruyter, vol. 8(1), pages 1-28, June.
  58. 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.
  59. 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.
  60. Min Ding & Young-Hoon Park & Eric T. Bradlow, 2009. "Barter Markets for Conjoint Analysis," Management Science, INFORMS, vol. 55(6), pages 1003-1017, June.
  61. Anocha Aribarg & Neeraj Arora & Moon Young Kang, 2010. "Predicting Joint Choice Using Individual Data," Marketing Science, INFORMS, vol. 29(1), pages 139-157, 01-02.
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