IDEAS home Printed from https://ideas.repec.org/r/eee/ejores/v219y2012i2p368-378.html
   My bibliography  Save this item

Willingness-to-pay estimation with choice-based conjoint analysis: Addressing extreme response behavior with individually adapted designs

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Mayer, Stefan & Klein, Robert & Seiermann, Stephanie, 2013. "A simulation-based approach to price optimisation of the mixed bundling problem with capacity constraints," International Journal of Production Economics, Elsevier, vol. 145(2), pages 584-598.
  2. Pleshcheva, Vlada, 2019. "Metric and Scale Effects in Consumer Preferences for Environmental Benefits," Rationality and Competition Discussion Paper Series 147, CRC TRR 190 Rationality and Competition.
  3. 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.
  4. Basem Al-Omari & Joviana Farhat & Mujahed Shraim, 2023. "The Role of Web-Based Adaptive Choice-Based Conjoint Analysis Technology in Eliciting Patients’ Preferences for Osteoarthritis Treatment," IJERPH, MDPI, vol. 20(4), pages 1-15, February.
  5. Jonas Schmidt & Tammo H. A. Bijmolt, 2020. "Accurately measuring willingness to pay for consumer goods: a meta-analysis of the hypothetical bias," Journal of the Academy of Marketing Science, Springer, vol. 48(3), pages 499-518, May.
  6. Christian Schlereth & Bernd Skiera, 2017. "Two New Features in Discrete Choice Experiments to Improve Willingness-to-Pay Estimation That Result in SDR and SADR: Separated (Adaptive) Dual Response," Management Science, INFORMS, vol. 63(3), pages 829-842, March.
  7. 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.
  8. Ronald B. Larson, 2019. "Promoting demand-based pricing," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(1), pages 42-51, February.
  9. Larson, Ronald B., 2017. "Selling Demand-Based Pricing," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259135, Agricultural and Applied Economics Association.
  10. 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.
  11. 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.
  12. Lukas Kornher & Martin Schellhorn & Saskia Vetter, 2019. "Disgusting or Innovative-Consumer Willingness to Pay for Insect Based Burger Patties in Germany," Sustainability, MDPI, vol. 11(7), pages 1-20, March.
  13. Hendrik Jöntgen & Nicholas Valentin Lingnau & Oliver Hinz & Roland Holten, 2024. "This is why we pay—Motivational factors for supporting subscription-based crowdfunding campaigns," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-21, December.
  14. Arif Yustian Maulana Noor & Hery Toiba & Budi Setiawan & Abdul Wahib Muhaimin & Adhitya Marendra Kiloes, 2022. "The application of choice experiments in a study on consumer preference for agri-food products: A literature review," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(5), pages 189-197.
  15. Lehmann, Nico & Sloot, Daniel & Ardone, Armin & Fichtner, Wolf, 2021. "The limited potential of regional electricity marketing – Results from two discrete choice experiments in Germany," Energy Economics, Elsevier, vol. 100(C).
  16. 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.
  17. Will, Christian & Lehmann, Nico & Baumgartner, Nora & Feurer, Sven & Jochem, Patrick & Fichtner, Wolf, 2022. "Consumer understanding and evaluation of carbon-neutral electric vehicle charging services," Applied Energy, Elsevier, vol. 313(C).
  18. Jella Pfeiffer & Michael Scholz, 2013. "A Low-Effort Recommendation System with High Accuracy," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(6), pages 397-408, December.
  19. 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.
  20. K. Valerie Carl & Cristina Mihale-Wilson & Jan Zibuschka & Oliver Hinz, 2024. "A consumer perspective on Corporate Digital Responsibility: an empirical evaluation of consumer preferences," Journal of Business Economics, Springer, vol. 94(7), pages 979-1024, October.
  21. 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.
  22. A. Cristina Mihale-Wilson & Jan Zibuschka & Oliver Hinz, 2019. "User preferences and willingness to pay for in-vehicle assistance," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(1), pages 37-53, March.
  23. Frank Ebbers & Jan Zibuschka & Christian Zimmermann & Oliver Hinz, 2021. "User preferences for privacy features in digital assistants," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 411-426, June.
  24. Halme, Merja & Kallio, Markku, 2014. "Likelihood estimation of consumer preferences in choice-based conjoint analysis," European Journal of Operational Research, Elsevier, vol. 239(2), pages 556-564.
  25. Schlereth, Christian & Eckert, Christine & Schaaf, René & Skiera, Bernd, 2014. "Measurement of preferences with self-explicated approaches: A classification and merge of trade-off- and non-trade-off-based evaluation types," European Journal of Operational Research, Elsevier, vol. 238(1), pages 185-198.
  26. Scholz, Michael & Pfeiffer, Jella & Rothlauf, Franz, 2017. "Using PageRank for non-personalized default rankings in dynamic markets," European Journal of Operational Research, Elsevier, vol. 260(1), pages 388-401.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.