IDEAS home Printed from https://ideas.repec.org/r/inm/ormksc/v26y2007i4p532-549.html
   My bibliography  Save this item

Greedoid-Based Noncompensatory Inference

Citations

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


Cited by:

  1. Paola Manzini & Marco Mariotti, 2009. "Consumer choice and revealed bounded rationality," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 41(3), pages 379-392, December.
  2. Jeffrey E. Harris & Mariana Gerstenblüth & Patricia Triunfo, 2018. "Smokers’ Rational Lexicographic Preferences for Cigarette Package Warnings: A Discrete Choice Experiment with Eye Tracking," Documentos de Trabajo (working papers) 0218, Department of Economics - dECON.
  3. Pere Mir-Artigues, 2022. "Combining preferences and heuristics in analysing consumer behaviour," Evolutionary and Institutional Economics Review, Springer, vol. 19(2), pages 523-543, September.
  4. Petri, Henrik & Voorneveld, Mark, 2016. "Characterizing lexicographic preferences," Journal of Mathematical Economics, Elsevier, vol. 63(C), pages 54-61.
  5. Zhenghui Sha & Yun Huang & Jiawei Sophia Fu & Mingxian Wang & Yan Fu & Noshir Contractor & Wei Chen, 2018. "A Network-Based Approach to Modeling and Predicting Product Coconsideration Relations," Complexity, Hindawi, vol. 2018, pages 1-14, January.
  6. Volker Kuppelwieser & Fouad Ben Abdelaziz & Olfa Meddeb, 2020. "Unstable interactions in customers’ decision making: an experimental proof," Annals of Operations Research, Springer, vol. 294(1), pages 479-499, November.
  7. Carson, Richard T. & Louviere, Jordan J., 2014. "Statistical properties of consideration sets," Journal of choice modelling, Elsevier, vol. 13(C), pages 37-48.
  8. Mridu Prabal Goswami & Manipushpak Mitra & Debapriya Sen, 2022. "A Characterization of Lexicographic Preferences," Decision Analysis, INFORMS, vol. 19(2), pages 170-187, June.
  9. 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.
  10. Simon P. Anderson & Régis Renault, 2013. "The Advertising Mix for a Search Good," Management Science, INFORMS, vol. 59(1), pages 69-83, April.
  11. Brighton, Henry & Gigerenzer, Gerd, 2015. "The bias bias," Journal of Business Research, Elsevier, vol. 68(8), pages 1772-1784.
  12. Neeraj Arora & Ty Henderson & Qing Liu, 2011. "Noncompensatory Dyadic Choices," Marketing Science, INFORMS, vol. 30(6), pages 1028-1047, November.
  13. Uwe Dulleck & Franz Hackl & Bernhard Weiss & Rudolf Winter-Ebmer, 2008. "Buying Online: Sequential Decision Making by Shopbot Visitors," NCER Working Paper Series 31, National Centre for Econometric Research.
  14. Nathan Berg & Gerd Gigerenzer, 2010. "As-if behavioral economics: neoclassical economics in disguise?," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(1), pages 133-166.
  15. Hauser, John R., 2014. "Consideration-set heuristics," Journal of Business Research, Elsevier, vol. 67(8), pages 1688-1699.
  16. Nicolas Houy, 2011. "Common characterizations of the untrapped set and the top cycle," Theory and Decision, Springer, vol. 70(4), pages 501-509, April.
  17. John Hauser, 2011. "A marketing science perspective on recognition-based heuristics (and the fast-and-frugal paradigm)," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 6(5), pages 396-408, July.
  18. repec:cup:judgdm:v:4:y:2009:i:3:p:200-213 is not listed on IDEAS
  19. repec:cup:judgdm:v:6:y:2011:i:5:p:396-408 is not listed on IDEAS
  20. Krecik, Markus, 2024. "A needs-based framework for approximating decisions and well-being," Discussion Papers 2024/2, Free University Berlin, School of Business & Economics.
  21. Mandler, Michael & Manzini, Paola & Mariotti, Marco, 2012. "A million answers to twenty questions: Choosing by checklist," Journal of Economic Theory, Elsevier, vol. 147(1), pages 71-92.
  22. 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.
  23. Berg, Nathan, 2014. "Success from satisficing and imitation: Entrepreneurs' location choice and implications of heuristics for local economic development," Journal of Business Research, Elsevier, vol. 67(8), pages 1700-1709.
  24. Kim, Youngju & Hardt, Nino & Kim, Jaehwan & Allenby, Greg M., 2022. "Conjunctive screening in models of multiple discreteness," International Journal of Research in Marketing, Elsevier, vol. 39(4), pages 1209-1234.
  25. Daria Dzyabura & John R. Hauser, 2011. "Active Machine Learning for Consideration Heuristics," Marketing Science, INFORMS, vol. 30(5), pages 801-819, September.
  26. 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.
  27. 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.
  28. Anocha Aribarg & Thomas Otter & Daniel Zantedeschi & Greg M. Allenby & Taylor Bentley & David J. Curry & Marc Dotson & Ty Henderson & Elisabeth Honka & Rajeev Kohli & Kamel Jedidi & Stephan Seiler & X, 2018. "Advancing Non-compensatory Choice Models in Marketing," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 82-92, March.
  29. Pathak, Parag A. & Shi, Peng, 2021. "How well do structural demand models work? Counterfactual predictions in school choice," Journal of Econometrics, Elsevier, vol. 222(1), pages 161-195.
  30. Rajeev Kohli & Khaled Boughanmi & Vikram Kohli, 2019. "Randomized Algorithms for Lexicographic Inference," Operations Research, INFORMS, vol. 67(2), pages 357-375, March.
  31. Dimitris Bertsimas & Velibor V. Mišić, 2019. "Exact First-Choice Product Line Optimization," Operations Research, INFORMS, vol. 67(3), pages 651-670, May.
  32. Song Lin & Juanjuan Zhang & John R. Hauser, 2015. "Learning from Experience, Simply," Marketing Science, INFORMS, vol. 34(1), pages 1-19, January.
  33. 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.
  34. repec:dau:papers:123456789/12407 is not listed on IDEAS
  35. 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.
  36. Bremer, Lucas & Heitmann, Mark & Schreiner, Thomas F., 2017. "When and how to infer heuristic consideration set rules of consumers," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 516-535.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.