Efficient Choice Designs for a Consider-Then-Choose Model
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DOI: 10.1287/mksc.1100.0629
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- Rajeev Kohli & Kamel Jedidi, 2005. "Probabilistic Subset Conjunction," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 737-757, December.
- Fasheng Sun & Min-Qian Liu & Dennis K. J. Lin, 2009. "Construction of orthogonal Latin hypercube designs," Biometrika, Biometrika Trust, vol. 96(4), pages 971-974.
- Timothy J. Gilbride & Greg M. Allenby, 2004. "A Choice Model with Conjunctive, Disjunctive, and Compensatory Screening Rules," Marketing Science, INFORMS, vol. 23(3), pages 391-406, October.
- Timothy J. Gilbride & Greg M. Allenby, 2006. "Estimating Heterogeneous EBA and Economic Screening Rule Choice Models," Marketing Science, INFORMS, vol. 25(5), pages 494-509, September.
- Lussier, Denis A & Olshavsky, Richard W, 1979. "Task Complexity and Contingent Processing in Brand Choice," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 6(2), pages 154-165, Se.
- Zhu, Wei & Timmermans, Harry, 2009. "Modelling pedestrian go-home decisions: A comparison of linear and nonlinear compensatory, and conjunctive non-compensatory specifications," Journal of Retailing and Consumer Services, Elsevier, vol. 16(3), pages 227-231.
- Arora, Neeraj & Huber, Joel, 2001. "Improving Parameter Estimates and Model Prediction by Aggregate Customization in Choice Experiments," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(2), pages 273-283, September.
- Swait, Joffre, 2001. "A non-compensatory choice model incorporating attribute cutoffs," Transportation Research Part B: Methodological, Elsevier, vol. 35(10), pages 903-928, November.
- Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
- Jie Yu & Peter Goos & Martina Vandebroek, 2009. "Efficient Conjoint Choice Designs in the Presence of Respondent Heterogeneity," Marketing Science, INFORMS, vol. 28(1), pages 122-135, 01-02.
- C. Devon Lin & Rahul Mukerjee & Boxin Tang, 2009. "Construction of orthogonal and nearly orthogonal Latin hypercubes," Biometrika, Biometrika Trust, vol. 96(1), pages 243-247.
- 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.
- Kessels, Roselinde & Jones, Bradley & Goos, Peter & Vandebroek, Martina, 2009. "An Efficient Algorithm for Constructing Bayesian Optimal Choice Designs," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 279-291.
- Araña, Jorge E. & León, Carmelo J. & Hanemann, Michael W., 2008. "Emotions and decision rules in discrete choice experiments for valuing health care programmes for the elderly," Journal of Health Economics, Elsevier, vol. 27(3), pages 753-769, May.
- Olivier Toubia & John R. Hauser, 2007. "—On Managerially Efficient Experimental Designs," Marketing Science, INFORMS, vol. 26(6), pages 851-858, 11-12.
- David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
- 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.
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- Christian Schlereth & Fabian Schulz, 2014. "Schnelle und einfache Messung von Bedeutungsgewichten mit der Restricted-Click-Stream Analyse: Ein Vergleich mit etablierten Präferenzmessmethoden," Schmalenbach Journal of Business Research, Springer, vol. 66(8), pages 630-657, December.
- Lu, Zhentong, 2022. "Estimating multinomial choice models with unobserved choice sets," Journal of Econometrics, Elsevier, vol. 226(2), pages 368-398.
- 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.
- Daria Dzyabura & John R. Hauser, 2011. "Active Machine Learning for Consideration Heuristics," Marketing Science, INFORMS, vol. 30(5), pages 801-819, September.
- 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.
- Youyi Bi & Yunjian Qiu & Zhenghui Sha & Mingxian Wang & Yan Fu & Noshir Contractor & Wei Chen, 2021. "Modeling Multi-Year Customers’ Considerations and Choices in China’s Auto Market Using Two-Stage Bipartite Network Analysis," Networks and Spatial Economics, Springer, vol. 21(2), pages 365-385, June.
- 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.
- Xiangyu Gao & Stefanus Jasin & Sajjad Najafi & Huanan Zhang, 2022. "Joint Learning and Optimization for Multi-Product Pricing (and Ranking) Under a General Cascade Click Model," Management Science, INFORMS, vol. 68(10), pages 7362-7382, October.
- Ofer Mintz & Imran S. Currim & Ivan Jeliazkov, 2013. "Information Processing Pattern and Propensity to Buy: An Investigation of Online Point-of-Purchase Behavior," Marketing Science, INFORMS, vol. 32(5), pages 716-732, September.
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Keywords
experimental design; conjoint choice designs; D-optimality; consider-then-choose model; noncompensatory screening rules;All these keywords.
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