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Efficient Conjoint Choice Designs in the Presence of Respondent Heterogeneity

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  1. John M. Rose & Michiel C.J. Bliemer, 2014. "Stated choice experimental design theory: the who, the what and the why," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 7, pages 152-177, Edward Elgar Publishing.
  2. Palhazi Cuervo, Daniel & Kessels, Roselinde & Goos, Peter & Sörensen, Kenneth, 2016. "An integrated algorithm for the optimal design of stated choice experiments with partial profiles," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 648-669.
  3. Kessels, Roselinde, 2016. "Homogeneous versus heterogeneous designs for stated choice experiments: Ain't homogeneous designs all bad?," Journal of choice modelling, Elsevier, vol. 21(C), pages 2-9.
  4. 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.
  5. van Cranenburgh, Sander & Rose, John M. & Chorus, Caspar G., 2018. "On the robustness of efficient experimental designs towards the underlying decision rule," Transportation Research Part A: Policy and Practice, Elsevier, vol. 109(C), pages 50-64.
  6. Aiste Ruseckaite & Peter Goos & Dennis Fok, 2017. "Bayesian D-optimal choice designs for mixtures," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(2), pages 363-386, February.
  7. Chang Wang & Dries Goossens & Martina Vandebroek, 2018. "The Impact of the Soccer Schedule on TV Viewership and Stadium Attendance," Journal of Sports Economics, , vol. 19(1), pages 82-112, January.
  8. Bart Vermeulen & Peter Goos & Riccardo Scarpa & Martina Vandebroek, 2011. "Bayesian Conjoint Choice Designs for Measuring Willingness to Pay," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 48(1), pages 129-149, January.
  9. Denis Sauré & Juan Pablo Vielma, 2019. "Ellipsoidal Methods for Adaptive Choice-Based Conjoint Analysis," Operations Research, INFORMS, vol. 67(2), pages 315-338, March.
  10. KESSELS, Roselinde & BRADLEY, Jones & GOOS, Peter, 2012. "A comparison of partial profile designs for discrete choice experiments with an application in software development," Working Papers 2012004, University of Antwerp, Faculty of Business and Economics.
  11. Raphael Thomadsen & Robert P. Rooderkerk & On Amir & Neeraj Arora & Bryan Bollinger & Karsten Hansen & Leslie John & Wendy Liu & Aner Sela & Vishal Singh & K. Sudhir & Wendy Wood, 2018. "How Context Affects Choice," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 3-14, March.
  12. Apurba Shee & Calum G. Turvey & Ana Marr, 2021. "Heterogeneous Demand and Supply for an Insurance‐linked Credit Product in Kenya: A Stated Choice Experiment Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(1), pages 244-267, February.
  13. Danaf, Mazen & Atasoy, Bilge & de Azevedo, Carlos Lima & Ding-Mastera, Jing & Abou-Zeid, Maya & Cox, Nathaniel & Zhao, Fang & Ben-Akiva, Moshe, 2019. "Context-aware stated preferences with smartphone-based travel surveys," Journal of choice modelling, Elsevier, vol. 31(C), pages 35-50.
  14. Hillebrand, Sebastian & Teichert, Thorsten, 2020. "Successor selection in times of continuity and renewal - A discrete choice-experiment," WiSo-HH Working Paper Series 59, University of Hamburg, Faculty of Business, Economics and Social Sciences, WISO Research Laboratory.
  15. Timo Fischer & Gaétan de Rassenfosse, 2011. "Debt Financing of High-growth Startups," DRUID Working Papers 11-04, DRUID, Copenhagen Business School, Department of Industrial Economics and Strategy/Aalborg University, Department of Business Studies.
  16. Rossella Berni & Fabrizia Mealli, 2013. "Mode choice analysis of mobility in Florence. A choice experiment," Studi e approfondimenti 328, Istituto Regionale per la Programmazione Economica della Toscana.
  17. Fischer, Timo & Henkel, Joachim, 2013. "Complements and substitutes in profiting from innovation—A choice experimental approach," Research Policy, Elsevier, vol. 42(2), pages 326-339.
  18. Bliemer, Michiel C.J. & Rose, John M., 2010. "Construction of experimental designs for mixed logit models allowing for correlation across choice observations," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 720-734, July.
  19. Nedka Dechkova Nikiforova & Rossella Berni & Jesús Fernando López‐Fidalgo, 2022. "Optimal approximate choice designs for a two‐step coffee choice, taste and choice again experiment," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1895-1917, November.
  20. Andreas Falke & Harald Hruschka, 2017. "Setting prices in mixed logit model designs," Marketing Letters, Springer, vol. 28(1), pages 139-154, March.
  21. Hoenig, Daniel & Henkel, Joachim, 2015. "Quality signals? The role of patents, alliances, and team experience in venture capital financing," Research Policy, Elsevier, vol. 44(5), pages 1049-1064.
  22. Rossella Berni & Nedka Dechkova Nikiforova & Patrizia Pinelli, 2024. "An Optimal Design through a Compound Criterion for Integrating Extra Preference Information in a Choice Experiment: A Case Study on Moka Ground Coffee," Stats, MDPI, vol. 7(2), pages 1-16, June.
  23. John Rose & Michiel Bliemer, 2013. "Sample size requirements for stated choice experiments," Transportation, Springer, vol. 40(5), pages 1021-1041, September.
  24. Qing Liu & Neeraj Arora, 2011. "Efficient Choice Designs for a Consider-Then-Choose Model," Marketing Science, INFORMS, vol. 30(2), pages 321-338, 03-04.
  25. Qing Liu & Yihui (Elina) Tang, 2015. "Construction of Heterogeneous Conjoint Choice Designs: A New Approach," Marketing Science, INFORMS, vol. 34(3), pages 346-366, May.
  26. 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.
  27. Frischknecht, Bart D. & Eckert, Christine & Geweke, John & Louviere, Jordan J., 2014. "A simple method for estimating preference parameters for individuals," International Journal of Research in Marketing, Elsevier, vol. 31(1), pages 35-48.
  28. Yu, Jie & Goos, Peter & Vandebroek, Martina, 2010. "Comparing different sampling schemes for approximating the integrals involved in the efficient design of stated choice experiments," Transportation Research Part B: Methodological, Elsevier, vol. 44(10), pages 1268-1289, December.
  29. 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.
  30. Falke Andreas & Hruschka Harald, 2016. "A Monte Carlo Study of Design Procedures for the Semi-parametric Mixed Logit Model," Review of Marketing Science, De Gruyter, vol. 14(1), pages 21-67, June.
  31. Andreas Falke & Harald Hruschka, 2017. "A Monte Carlo study of design-generating algorithms for the latent class mixed logit model," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1035-1053, October.
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