A Satisficing Choice Model

Published Online:https://doi.org/10.1287/mksc.1120.0732

References

  • Bettman JR, Johnson EJ, Payne JW, Robertson T, Kassarjian H. Consumer decision making. Handbook of Consumer Behavior (1991) (Prentice Hall, New York) 50–84Google Scholar
  • Casella G, George EI. Explaining the Gibbs sampler. Amer. Statistician (1992) 49(4):327–335Google Scholar
  • Chandon P, Hutchinson JW, Bradlow ET, Young SH. Does in-store marketing work? Effects of the number and position of shelf facings on brand attention and evaluation at the point of purchase. J. Marketing (2009) 73(6):1–17CrossrefGoogle Scholar
  • Coombs CH. Mathematical models in psychological scaling. J. Amer. Statist. Assoc. (1951) 46(256):480–489CrossrefGoogle Scholar
  • Dawes RM. Social selection based on multidimensional criteria. J. Abnormal Soc. Psych. (1964) 68(1):104–109CrossrefGoogle Scholar
  • Duan JA, McAlister L, Sinha S. Reexamining Bayesian model-comparison evidence of cross-brand pass-through. Marketing Sci. (2011) 30(3):550–561LinkGoogle Scholar
  • Elrod T. Recommendations for validation of choice models. Proc. Sawtooth Software Conf. (2002) (Sawtooth Software, Sequim, WA) 225–243Google Scholar
  • Elrod T, Johnson RD, White J. A new integrated model of noncompensatory and compensatory decision strategies. Organ. Behav. Human Decision Processes (2004) 95(1):1–19CrossrefGoogle Scholar
  • Erdem T, Keane MP. Decision-making under uncertainty: Capturing dynamic brand choice processes in turbulent consumer goods markets. Marketing Sci. (1996) 15(1):1–20LinkGoogle Scholar
  • Fader PS, McAlister L. An elimination by aspects model of consumer response to promotion calibrated on UPC scanner data. J. Marketing Res. (1990) 27(3):322–332CrossrefGoogle Scholar
  • Gelfand AE, Dey DK. Bayesian model choice: Asymptotics and exact calculations. J. Roy. Statist. Soc. Ser. B (1994) 56(3):501–514Google Scholar
  • Gelfand AE, Smith AFM. Sampling based approaches to calculating marginal densities. J. Amer. Statist. Assoc. (1990) 85(410):398–409CrossrefGoogle Scholar
  • Gigerenzer G, Todd PM, Gigerenzer G, Todd PM. ABC Research Group Fast and frugal heuristics: The adaptive toolbox. Simple Heuristics That Make Us Smart (1999) (Oxford University Press, New York) 3–36Google Scholar
  • Gilbride TJ, Allenby GM. A choice model with conjunctive, disjunctive, and compensatory screening rules. Marketing Sci. (2004) 23(3):391–406LinkGoogle Scholar
  • Gilbride TJ, Allenby GM. Estimating heterogeneous EBA and economic screening rule choice models. Marketing Sci. (2006) 25(5):494–509LinkGoogle Scholar
  • Guadagni PM, Little JDC. A logit model of brand choice calibrated on scanner data. Marketing Sci. (1983) 2(3):203–238LinkGoogle Scholar
  • Gupta S. Impact of sales promotions on when, what, and how much to buy. J. Marketing Res. (1988) 25(4):342–355CrossrefGoogle Scholar
  • Hauser JR, Wernerfelt B. An evaluation cost model of consideration sets. J. Consumer Res. (1990) 16(4):393–408CrossrefGoogle Scholar
  • Heidelberger P, Welch PD. Simulation run length control in the presence of an initial transient. Oper. Res. (1983) 31(6):1109–1144LinkGoogle Scholar
  • Jedidi K, Kohli R. Probabilisitc subset-conjunctive models for heterogeneous consumers. J. Marketing Res. (2005) 42(4):483–494CrossrefGoogle Scholar
  • Johnson EJ, Meyer RJ, Ghose S. When choice models fail: Compensatory models in negatively correlated environments. J. Marketing Res. (1989) 26(3):255–270CrossrefGoogle Scholar
  • Kahneman D, Tversky A. Prospect theory: An analysis of decision under risk. Econometrica (1979) 47(2):263–292CrossrefGoogle Scholar
  • Kamakura WA, Russell GJ. A probabilistic choice model for market segmentation and elasticity structure. J. Marketing Res. (1989) 26(4):379–390CrossrefGoogle Scholar
  • Kohli R, Jedidi K. Representation and inference of lexicographic preference models and their variants. Marketing Sci. (2007) 26(3):380–399LinkGoogle Scholar
  • Lee AY. Effects of implicit memory on memory-based versus stimulus-based brand choice. J. Marketing Res. (2002) 39(4):440–454CrossrefGoogle Scholar
  • Lenk PJ. Simulation pseudo-bias correction to the harmonic mean estimator of integrated likelihoods. J. Comput. Graphical Statist. (2009) 18(4):941–960CrossrefGoogle Scholar
  • Liechty J, Pieters R, Wedel M. Global and local covert visual attention: Evidence from a Bayesian hidden Markov model. Psychometrika (2003) 68(4):519–541CrossrefGoogle Scholar
  • Loomes G, Starmer C, Sugden R. Observing violations of transitivity by experimental methods. Econometrica (1991) 59(2):425–439CrossrefGoogle Scholar
  • Mehta N, Rajiv S, Srinivasan K. Price uncertainty and consumer search: A structural model of consideration set formation. Marketing Sci. (2003) 22(1):58–84LinkGoogle Scholar
  • Mehta N, Rajiv S, Srinivasan K. Role of forgetting in memory-based choice decisions: A structural model. Quant. Marketing Econom. (2004) 2(2):107–140CrossrefGoogle Scholar
  • Netzer O, Toubia O, Bradlow ET, Dahan E, Evgeniou T, Feinberg FM, Feit EM, et al. Beyond conjoint analysis: Advances in preference measurement. Marketing Lett. (2008) 19(3):337–354CrossrefGoogle Scholar
  • Osborne MJ, Rubinstein A. A Course in Game Theory (1994) (MIT Press, Cambridge, MA) Google Scholar
  • Pieters R, Malhotra NK. A review of eye-tracking research in marketing. Review of Marketing Research (2008) 4(Emerald Group Publishing, Bingley, UK) 123–147CrossrefGoogle Scholar
  • Pieters R, Warlop L. Visual attention during brand choice: The impact of time pressure and task motivation. Internat. J. Res. Marketing (1999) 16(1):1–16CrossrefGoogle Scholar
  • Pieters R, Warlop L, Wedel M. Breaking through the clutter: Benefits of advertising originality and familiarity for brand attention and memory. Management Sci. (2002) 48(6):765–781LinkGoogle Scholar
  • Reutskaja E, Nagel R, Camerer CF, Rangel A. Search dynamics in consumer choice under time pressure: An eye-tracking study. Amer. Econom. Rev. (2011) 101(2):900–926CrossrefGoogle Scholar
  • Roberts JH, Lattin JM. Development and testing of a model of consideration set composition. J. Marketing Res. (1991) 28(4):429–440CrossrefGoogle Scholar
  • Rossi PE, Allenby GM, McCulloch R. Bayesian Statistics and Marketing (2005) (John Wiley & Sons, Hoboken, NJ) CrossrefGoogle Scholar
  • Rottenstreich Y, Sood S, Brenner L. Feeling and thinking in memory-based versus stimulus-based choices. J. Consumer Res. (2007) 33(4):461–469CrossrefGoogle Scholar
  • Russo EJ, Leclerc F. An eye-fixation analysis of choice processes for consumer nondurables. J. Consumer Res. (1994) 21(2):274–290CrossrefGoogle Scholar
  • Schwartz B, Ward A, Monterosso J, Lyubomirsky S, White K, Lehman DR. Maximizing versus satisficing: Happiness is a matter of choice. J. Personality Soc. Psych. (2002) 83(5):1178–1197CrossrefGoogle Scholar
  • Shi SW, Wedel M, Pieters R. Information acquisition during online decision making: A model-based exploration using eye-tracking data. Management Sci. (2012) . ForthcomingGoogle Scholar
  • Shugan SM. The cost of thinking. J. Consumer Res. (1980) 7(2):99–111CrossrefGoogle Scholar
  • Simon HA. A behavioral model of rational choice. Quart. J. Econom. (1955) 69(1):99–118CrossrefGoogle Scholar
  • Smith BJ. boa: An R package for MCMC output convergence assessment and posterior inference. J. Statist. Software (2007) 21(11):1–37CrossrefGoogle Scholar
  • Sun B. Promotion effect on endogenous consumption. Marketing Sci. (2005) 24(3):430–443LinkGoogle Scholar
  • Swait J. A non-compensatory choice model incorporating attribute cutoffs. Transportation Res. Part B (2001) 35(10):903–928CrossrefGoogle Scholar
  • Swait J, Adamowicz W. The influence of task complexity on consumer choice: A latent class model of decision strategy switching. J. Consumer Res. (2001) 28(1):135–148CrossrefGoogle Scholar
  • Teixeira TS, Wedel M, Pieters R. Moment-to-moment optimal branding in TV commercials: Preventing avoidance by pulsing. Marketing Sci. (2010) 29(5):783–804LinkGoogle Scholar
  • Tversky A. Elimination by aspects: A theory of choice. Psych. Rev. (1972) 79(4):281–299CrossrefGoogle Scholar
  • van Diepen PMJ, de Graef P, d’Ydewalle G, Findlay JM, Walker R, Kentridge RW. Chronometry of foveal information extraction during scene perception. Eye Movement Research: Mechanisms, Processes and Applications (1995) (Elsevier, Amsterdam) 349–362CrossrefGoogle Scholar
  • van der Lans R, Pieters R, Wedel M. Competitive brand salience. Marketing Sci. (2008a) 27(5):922–931LinkGoogle Scholar
  • van der Lans R, Pieters R, Wedel M. Eye-movement analysis of search effectiveness. J. Amer. Statist. Assoc. (2008b) 103(482):452–461CrossrefGoogle Scholar
  • von Neumann J, Morgenstern O. Theory of Games and Economic Behavior (1947) 2nd ed.(Princeton University Press, Princeton, NJ) Google Scholar
  • Williams HCWL, de Dios Ortuzar J. Behavioural theories of dispersion and the mis-specification of travel demand models. Transportation Res. Part B (1982) 16(3):167–219CrossrefGoogle Scholar
  • Wolfe JM, Horowitz TS. What attributes guide the deployment of visual attention and how do they do it? Nature Rev. Neurosci. (2004) 5(6):1–7CrossrefGoogle Scholar
  • Wolfe JM, Yu KP, Stewart MI, Shorter AD, Friedman-Hill SR, Cave KR. Limitations on the parallel guidance of visual search: Color × color and orientation × orientation conjunctions. J. Experiment. Psych.: Human Perception Performance (1990) 16(4):879–892CrossrefGoogle Scholar
  • Zhang J, Wedel M, Pieters R. Sales effects of attention to feature advertisements: A Bayesian mediation analysis. J. Marketing Res. (2009) 46(5):669–681CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.