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Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs

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Cited by:

  1. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2011. "Individually adapted sequential Bayesian conjoint-choice designs in the presence of consumer heterogeneity," International Journal of Research in Marketing, Elsevier, vol. 28(4), pages 378-388.
  2. Min Ding & Rajdeep Grewal & John Liechty, 2005. "Incentive-aligned conjoint analysis," Framed Field Experiments 00139, The Field Experiments Website.
  3. Leon Yang Chu & Hao Zhang, 2011. "Optimal Preorder Strategy with Endogenous Information Control," Management Science, INFORMS, vol. 57(6), pages 1055-1077, June.
  4. Voleti, Sudhir & Srinivasan, V. & Ghosh, Pulak, 2017. "An approach to improve the predictive power of choice-based conjoint analysis," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 325-335.
  5. Karim Lounici & Massimiliano Pontil & Alexandre B. Tsybakov & Sara Van De Geer, 2010. "Oracle Inequalities and Optimal Inference under Group Sparsity," Working Papers 2010-35, Center for Research in Economics and Statistics.
  6. Kick, Markus & Littich, Martina, 2015. "Brand and Reputation as Quality Signals on Regulated Markets," EconStor Preprints 182503, ZBW - Leibniz Information Centre for Economics.
  7. Lilibeth A. Acosta & Damasa B. Magcale-Macandog & K. S. Kavi Kumar & Xuefeng Cui & Elena A. Eugenio & Paula Beatrice M. Macandog & Arnold R. Salvacion & Jemimah Mae A. Eugenio, 2016. "The Role of Bioenergy in Enhancing Energy, Food and Ecosystem Sustainability Based on Societal Perceptions and Preferences in Asia," Agriculture, MDPI, vol. 6(2), pages 1-26, April.
  8. Lee, Ungki & Kang, Namwoo & Lee, Ikjin, 2020. "Choice data generation using usage scenarios and discounted cash flow analysis," Journal of choice modelling, Elsevier, vol. 37(C).
  9. Patricia M. Herman & Maia Ingram & Charles E. Cunningham & Heather Rimas & Lucy Murrieta & Kenneth Schachter & Jill Guernsey Zapien & Scott C. Carvajal, 2016. "A Comparison of Methods for Capturing Patient Preferences for Delivery of Mental Health Services to Low-Income Hispanics Engaged in Primary Care," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 9(4), pages 293-301, August.
  10. Sigurdsson, Valdimar & Larsen, Nils Magne & Alemu, Mohammed Hussen & Gallogly, Joseph Karlton & Menon, R. G. Vishnu & Fagerstrøm, Asle, 2020. "Assisting sustainable food consumption: The effects of quality signals stemming from consumers and stores in online and physical grocery retailing," Journal of Business Research, Elsevier, vol. 112(C), pages 458-471.
  11. Lieven, Theo, 2015. "Policy measures to promote electric mobility – A global perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 82(C), pages 78-93.
  12. Nick Huntington‐Klein, 2018. "College Choice As A Collective Decision," Economic Inquiry, Western Economic Association International, vol. 56(2), pages 1202-1219, April.
  13. Ana Oliveira-Brochado & Francisco Vitorino Martins, 2008. "Aspectos Metodológicos da Segmentação de Mercado: Base de Segmentação e Métodos de Classificação," FEP Working Papers 261, Universidade do Porto, Faculdade de Economia do Porto.
  14. Theodoros Evgeniou & Constantinos Boussios & Giorgos Zacharia, 2005. "Generalized Robust Conjoint Estimation," Marketing Science, INFORMS, vol. 24(3), pages 415-429, May.
  15. Robert Zeithammer & Peter Lenk, 2006. "Bayesian estimation of multivariate-normal models when dimensions are absent," Quantitative Marketing and Economics (QME), Springer, vol. 4(3), pages 241-265, September.
  16. DeSarbo, Wayne S. & Kim, Youngchan & Wedel, Michel & Fong, Duncan K. H., 1998. "A Bayesian approach to the spatial representation of market structure from consumer choice data," European Journal of Operational Research, Elsevier, vol. 111(2), pages 285-305, December.
  17. 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.
  18. Katharina Keller & Christian Schlereth & Oliver Hinz, 2021. "Sample-based longitudinal discrete choice experiments: preferences for electric vehicles over time," Journal of the Academy of Marketing Science, Springer, vol. 49(3), pages 482-500, May.
  19. 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.
  20. Burmester, Alexa B. & Eggers, Felix & Clement, Michel & Prostka, Tim, 2016. "Accepting or fighting unlicensed usage: Can firms reduce unlicensed usage by optimizing their timing and pricing strategies?," International Journal of Research in Marketing, Elsevier, vol. 33(2), pages 343-356.
  21. Ramya Neelamegham & Pradeep Chintagunta, 1999. "A Bayesian Model to Forecast New Product Performance in Domestic and International Markets," Marketing Science, INFORMS, vol. 18(2), pages 115-136.
  22. Salak, B. & Kienast, F. & Olschewski, R. & Spielhofer, R. & Wissen Hayek, U. & Grêt-Regamey, A. & Hunziker, M., 2022. "Impact on the perceived landscape quality through renewable energy infrastructure. A discrete choice experiment in the context of the Swiss energy transition," Renewable Energy, Elsevier, vol. 193(C), pages 299-308.
  23. Peter E. Rossi & Greg M. Allenby, 2003. "Bayesian Statistics and Marketing," Marketing Science, INFORMS, vol. 22(3), pages 304-328, July.
  24. Zsolt Sándor & Michel Wedel, 2002. "Profile Construction in Experimental Choice Designs for Mixed Logit Models," Marketing Science, INFORMS, vol. 21(4), pages 455-475, February.
  25. Sinha, Ashish & Gazley, Aaron & Ashill, Nicholas J., 2008. "Measuring Customer Based Brand Equity using Hierarchical Bayes Methodology," Australasian marketing journal, Elsevier, vol. 16(1), pages 3-19.
  26. Suzanne B. Shu & Robert Zeithammer & John W. Payne, 2018. "The Pivotal Role of Fairness: Which Consumers Like Annuities?," NBER Working Papers 25067, National Bureau of Economic Research, Inc.
  27. 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.
  28. Max J. Pachali & Peter Kurz & Thomas Otter, 0. "How to generalize from a hierarchical model?," Quantitative Marketing and Economics (QME), Springer, vol. 0, pages 1-38.
  29. Xavier Fernández-i-Marín & Carolin H Rapp & Christian Adam & Oliver James & Anita Manatschal, 2021. "Discrimination against mobile European Union citizens before and during the first COVID-19 lockdown: Evidence from a conjoint experiment in Germany," European Union Politics, , vol. 22(4), pages 741-761, December.
  30. Burbano, Vanessa & Padilla, Nicolas & Meier, Stephan, 2020. "Gender Differences in Preferences for Meaning at Work," IZA Discussion Papers 13053, Institute of Labor Economics (IZA).
  31. Charles Cunningham & Ken Deal & Yvonne Chen, 2010. "Adaptive Choice-Based Conjoint Analysis," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 3(4), pages 257-273, December.
  32. 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.
  33. Anja Dieckmann & Katrin Dippold & Holger Dietrich, 2009. "Compensatory versus noncompensatory models for predicting consumer preferences," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 4(3), pages 200-213, April.
  34. 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.
  35. Braun, Alexander & Schmeiser, Hato & Schreiber, Florian, 2016. "On consumer preferences and the willingness to pay for term life insurance," European Journal of Operational Research, Elsevier, vol. 253(3), pages 761-776.
  36. Pradeep K. Chintagunta & Harikesh S. Nair, 2011. "Structural Workshop Paper --Discrete-Choice Models of Consumer Demand in Marketing," Marketing Science, INFORMS, vol. 30(6), pages 977-996, November.
  37. 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.
  38. Friebe, Christian A. & Flotow, Paschen von & Täube, Florian A., 2013. "Exploring the link between products and services in low-income markets—Evidence from solar home systems," Energy Policy, Elsevier, vol. 52(C), pages 760-769.
  39. Sandeep R. Chandukala & Yancy D. Edwards & Greg M. Allenby, 2011. "Identifying Unmet Demand," Marketing Science, INFORMS, vol. 30(1), pages 61-73, 01-02.
  40. Yves L. Grize, 2015. "Applications of Statistics in the Field of General Insurance: An Overview," International Statistical Review, International Statistical Institute, vol. 83(1), pages 135-159, April.
  41. Butori, Raphaëlle & De Bruyn, Arnaud, 2013. "So you want to delight your customers: The perils of ignoring heterogeneity in customer evaluations of discretionary preferential treatments," International Journal of Research in Marketing, Elsevier, vol. 30(4), pages 358-367.
  42. Jin, Ying & Su, Meng, 2009. "Recommendation and repurchase intention thresholds: A joint heterogeneity response estimation," International Journal of Research in Marketing, Elsevier, vol. 26(3), pages 245-255.
  43. Olivier Toubia & Duncan I. Simester & John R. Hauser & Ely Dahan, 2003. "Fast Polyhedral Adaptive Conjoint Estimation," Marketing Science, INFORMS, vol. 22(3), pages 273-303.
  44. Pengyuan Wang & Eric Bradlow & Edward George, 2014. "Meta-analyses using information reweighting: An application to online advertising," Quantitative Marketing and Economics (QME), Springer, vol. 12(2), pages 209-233, June.
  45. 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.
  46. 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.
  47. Jonas B. Pendzialek & Dusan Simic & Stephanie Stock, 2017. "Measuring customer preferences in the German statutory health insurance," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(7), pages 831-845, September.
  48. Yu-Cheng Ku & Tsun-Feng Chiang & Sheng-Mao Chang, 2017. "Is what you choose what you want?—outlier detection in choice-based conjoint analysis," Marketing Letters, Springer, vol. 28(1), pages 29-42, March.
  49. Kessels, Roselinde & Jones, Bradley & Goos, Peter, 2019. "Using Firth's method for model estimation and market segmentation based on choice data," Journal of choice modelling, Elsevier, vol. 31(C), pages 1-21.
  50. Qing Liu & Angela Dean & David Bakken & Greg Allenby, 2009. "Studying the level-effect in conjoint analysis: An application of efficient experimental designs for hyper-parameter estimation," Quantitative Marketing and Economics (QME), Springer, vol. 7(1), pages 69-93, March.
  51. Huber, Joel & Train, Kenneth, 2000. "On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths," Department of Economics, Working Paper Series qt7zm4f51b, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
  52. Anjulie Hähnchen & Bernhard Baumgartner, 2020. "The Impact of Price Bundling on the Evaluation of Bundled Products: Does It Matter How You Frame It?," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 72(1), pages 39-63, February.
  53. Max J. Pachali & Peter Kurz & Thomas Otter, 2020. "How to generalize from a hierarchical model?," Quantitative Marketing and Economics (QME), Springer, vol. 18(4), pages 343-380, December.
  54. Atanu Adhikari, 2016. "Adjacent Price Anchoring and Consumer’s Willingness to Pay: A Bayesian Approach," Working papers 215, Indian Institute of Management Kozhikode.
  55. YiChun Miriam Liu & Jeff D. Brazell & Greg M. Allenby, 2022. "Non-linear pricing effects in conjoint analysis," Quantitative Marketing and Economics (QME), Springer, vol. 20(4), pages 397-430, December.
  56. Crabbe, M. & Vandebroek, M., 2012. "Improving the efficiency of individualized designs for the mixed logit choice model by including covariates," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2059-2072.
  57. Botta, Enrico, 2019. "An experimental approach to climate finance: the impact of auction design and policy uncertainty on renewable energy equity costs in Europe," Energy Policy, Elsevier, vol. 133(C).
  58. Paul E. Green & Abba M. Krieger & Yoram Wind, 2001. "Thirty Years of Conjoint Analysis: Reflections and Prospects," Interfaces, INFORMS, vol. 31(3_supplem), pages 56-73, June.
  59. James Cochran & David Curry & Rajesh Radhakrishnan & Jon Pinnell, 2014. "Political engineering: optimizing a U.S. Presidential candidate’s platform," Annals of Operations Research, Springer, vol. 215(1), pages 63-87, April.
  60. Meixner, Oliver & Kubinger, Magdalena & Haghirian, Parissa & Haas, Rainer, 2018. "Empirical Research in Foreign Cultures: The Case of Japanese Rice," 2018 International European Forum (163rd EAAE Seminar), February 5-9, 2018, Innsbruck-Igls, Austria 276881, International European Forum on System Dynamics and Innovation in Food Networks.
  61. Penz, R. Frederic & Hörisch, Jacob & Tenner, Isabell, 2022. "Investors in environmental ventures want good money—and a clean conscience: How framing, interest rates, and the environmental impact of crowdlending projects influence funding decisions," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
  62. Meixner, Oliver & Haas, Rainer, 2017. "The Difficulties in Measuring Individual Utilities of Product Attributes: A Choice Based Experiment," 2018 International European Forum (163rd EAAE Seminar), February 5-9, 2018, Innsbruck-Igls, Austria 276887, International European Forum on System Dynamics and Innovation in Food Networks.
  63. Hein, Maren & Kurz, Peter & Steiner, Winfried J., 2019. "On the effect of HB covariance matrix prior settings: A simulation study," Journal of choice modelling, Elsevier, vol. 31(C), pages 51-72.
  64. Carsten Herbes & Johannes Dahlin & Peter Kurz, 2020. "Consumer Willingness To Pay for Proenvironmental Attributes of Biogas Digestate-Based Potting Soil," Sustainability, MDPI, vol. 12(16), pages 1-19, August.
  65. Duncan Fong & Peter Ebbes & Wayne DeSarbo, 2012. "A Heterogeneous Bayesian Regression Model for Cross-sectional Data Involving a Single Observation per Response Unit," Psychometrika, Springer;The Psychometric Society, vol. 77(2), pages 293-314, April.
  66. Thorsten Teichert, 2001. "Nutzenermittlung in wahlbasierter Conjoint-Analyse: Ein Vergleich von Latent-Class- und hierarchischem Bayes-Verfahren," Schmalenbach Journal of Business Research, Springer, vol. 53(8), pages 798-822, December.
  67. Robert Steiger & Eva Posch & Gottfried Tappeiner & Janette Walde, 2020. "Effects of climate change on tourism demand considering individual seasonal preferences," Working Papers 2020-08, Faculty of Economics and Statistics, University of Innsbruck.
  68. B. P. S. Murthi & Sumit Sarkar, 2003. "The Role of the Management Sciences in Research on Personalization," Management Science, INFORMS, vol. 49(10), pages 1344-1362, October.
  69. Hauser, John R., 2014. "Consideration-set heuristics," Journal of Business Research, Elsevier, vol. 67(8), pages 1688-1699.
  70. Thomas S. Shively & Greg M. Allenby & Robert Kohn, 2000. "A Nonparametric Approach to Identifying Latent Relationships in Hierarchical Models," Marketing Science, INFORMS, vol. 19(2), pages 149-162, November.
  71. Peter Lenk, 2014. "Bayesian estimation of random utility models," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 20, pages 457-497, Edward Elgar Publishing.
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  73. Monica Johar & Vijay Mookerjee & Sumit Sarkar, 2014. "Selling vs. Profiling: Optimizing the Offer Set in Web-Based Personalization," Information Systems Research, INFORMS, vol. 25(2), pages 285-306, June.
  74. B. P. S. Murthi & Sumit Sarkar, 2003. "The Role of the Mangement Sciences in Research on Personalization," Review of Marketing Science Working Papers 2-2-1025, Berkeley Electronic Press.
  75. Byun, Hyunsuk & Lee, Chul-Yong, 2017. "Analyzing Korean consumers’ latent preferences for electricity generation sources with a hierarchical Bayesian logit model in a discrete choice experiment," Energy Policy, Elsevier, vol. 105(C), pages 294-302.
  76. 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.
  77. John R. Hauser, 2017. "Phenomena, theory, application, data, and methods all have impact," Journal of the Academy of Marketing Science, Springer, vol. 45(1), pages 7-9, January.
  78. Ondřej Vilikus, 2013. "Hybrid Approach to Choice-Based Conjoint Analysis," Acta Oeconomica Pragensia, Prague University of Economics and Business, vol. 2013(4), pages 3-19.
  79. Karniouchina, Ekaterina V. & Moore, William L. & van der Rhee, Bo & Verma, Rohit, 2009. "Issues in the use of ratings-based versus choice-based conjoint analysis in operations management research," European Journal of Operational Research, Elsevier, vol. 197(1), pages 340-348, August.
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  81. Terry Elrod & Gerald Häubl & Steven Tipps, 2012. "Parsimonious Structural Equation Models for Repeated Measures Data, with Application to the Study of Consumer Preferences," Psychometrika, Springer;The Psychometric Society, vol. 77(2), pages 358-387, April.
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  83. Hein, Maren & Goeken, Nils & Kurz, Peter & Steiner, Winfried J., 2022. "Using Hierarchical Bayes draws for improving shares of choice predictions in conjoint simulations: A study based on conjoint choice data," European Journal of Operational Research, Elsevier, vol. 297(2), pages 630-651.
  84. Schlereth, Christian & Skiera, Bernd & Schulz, Fabian, 2018. "Why do consumers prefer static instead of dynamic pricing plans? An empirical study for a better understanding of the low preferences for time-variant pricing plans," European Journal of Operational Research, Elsevier, vol. 269(3), pages 1165-1179.
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  86. Acosta, Lilibeth A. & Enano, Nelson H. & Magcale-Macandog, Damasa B. & Engay, Kathreena G. & Herrera, Maria Noriza Q. & Nicopior, Ozzy Boy S. & Sumilang, Mic Ivan V. & Eugenio, Jemimah Mae A. & Lucht,, 2013. "How sustainable is bioenergy production in the Philippines? A conjoint analysis of knowledge and opinions of people with different typologies," Applied Energy, Elsevier, vol. 102(C), pages 241-253.
  87. Daria Dzyabura & Srikanth Jagabathula & Eitan Muller, 2019. "Accounting for Discrepancies Between Online and Offline Product Evaluations," Marketing Science, INFORMS, vol. 38(1), pages 88-106, January.
  88. 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.
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  90. Marc R. Dotson & Joachim Büschken & Greg M. Allenby, 2020. "Explaining Preference Heterogeneity with Mixed Membership Modeling," Marketing Science, INFORMS, vol. 39(2), pages 407-426, March.
  91. Timothy J. Gilbride & Peter J. Lenk & Jeff D. Brazell, 2008. "Market Share Constraints and the Loss Function in Choice-Based Conjoint Analysis," Marketing Science, INFORMS, vol. 27(6), pages 995-1011, 11-12.
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  93. Lüthi, Sonja & Wüstenhagen, Rolf, 2012. "The price of policy risk — Empirical insights from choice experiments with European photovoltaic project developers," Energy Economics, Elsevier, vol. 34(4), pages 1001-1011.
  94. Schlereth, Christian & Skiera, Bernd, 2012. "Measurement of consumer preferences for bucket pricing plans with different service attributes," International Journal of Research in Marketing, Elsevier, vol. 29(2), pages 167-180.
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  97. 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.
  98. Osman, Ahmed M.Y. & Wu, Jing & He, Xiaoning & Chen, Gang, 2021. "Eliciting SF-6Dv2 health state utilities using an anchored best-worst scaling technique," Social Science & Medicine, Elsevier, vol. 279(C).
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  101. John Liechty & Duncan Fong & Eelko Huizingh & Arnaud Bruyn, 2008. "Hierarchical Bayesian conjoint models incorporating measurement uncertainty," Marketing Letters, Springer, vol. 19(2), pages 141-155, June.
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  106. Lynd Bacon & Peter Lenk, 2012. "Augmenting discrete-choice data to identify common preference scales for inter-subject analyses," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 453-474, December.
  107. Elie Ofek & Muhamet Yildiz & Ernan Haruvy, 2007. "The Impact of Prior Decisions on Subsequent Valuations in a Costly Contemplation Model," Management Science, INFORMS, vol. 53(8), pages 1217-1233, August.
  108. Meixner, Oliver & Haas, Rainer, 2017. "The Difficulties in Measuring Individual Utilities of Product Attributes: A Choice Based Experiment," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 2017(1), June.
  109. Gabriela D. Oliveira & Luis C. Dias, 2020. "The potential learning effect of a MCDA approach on consumer preferences for alternative fuel vehicles," Annals of Operations Research, Springer, vol. 293(2), pages 767-787, October.
  110. Min Ding & Young-Hoon Park & Eric T. Bradlow, 2009. "Barter Markets for Conjoint Analysis," Management Science, INFORMS, vol. 55(6), pages 1003-1017, June.
  111. Park, Chan Su, 2004. "The robustness of hierarchical Bayes conjoint analysis under alternative measurement scales," Journal of Business Research, Elsevier, vol. 57(10), pages 1092-1097, October.
  112. Lüthi, Sonja & Prässler, Thomas, 2011. "Analyzing policy support instruments and regulatory risk factors for wind energy deployment--A developers' perspective," Energy Policy, Elsevier, vol. 39(9), pages 4876-4892, September.
  113. Andrews, Rick L. & Currim, Imran S. & Leeflang, Peter & Lim, Jooseop, 2008. "Estimating the SCAN⁎PRO model of store sales: HB, FM or just OLS?," International Journal of Research in Marketing, Elsevier, vol. 25(1), pages 22-33.
  114. Crabbe, Marjolein & Akinc, Deniz & Vandebroek, Martina, 2014. "Fast algorithms to generate individualized designs for the mixed logit choice model," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 1-15.
  115. Olivier Toubia & Martijn G. de Jong & Daniel Stieger & Johann Füller, 2012. "Measuring Consumer Preferences Using Conjoint Poker," Marketing Science, INFORMS, vol. 31(1), pages 138-156, January.
  116. Allenby, Greg M. & Rossi, Peter E., 1998. "Marketing models of consumer heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 57-78, November.
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