Abstract
In several recent reviews, authors have argued for the pervasive use of fast-and-frugal heuristics in human judgment. They have provided an overview of heuristics and have reiterated findings corroborating that such heuristics can be very valid strategies leading to high accuracy. They also have reviewed previous work that implies that simple heuristics are actually used by decision makers. Unfortunately, concerning the latter point, these reviews appear to be somewhat incomplete. More important, previous conclusions have been derived from investigations that bear some noteworthy methodological limitations. I demonstrate these by proposing a new heuristic and provide some novel critical findings. Also, I review some of the relevant literature often not—or only partially—considered. Overall, although some fast-and-frugal heuristics indeed seem to predict behavior at times, there is little to no evidence for others. More generally, the empirical evidence available does not warrant the conclusion that heuristics are pervasively used.
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Ayal, S., & Hochman, G. (2009). Ignorance or integration: The cognitive processes underlying choice behavior. Journal of Behavioral Decision Making, 22, 455–474.
Birnbaum, M. H. (2008a). Evaluation of the priority heuristic as a descriptive model of risky decision making: Comment on Brandstätter, Gigerenzer, and Hertwig (2006). Psychological Review, 115, 253–260.
Birnbaum, M. H. (2008b). New tests of cumulative prospect theory and the priority heuristic: Probability-outcome tradeoff with branch splitting. Judgment & Decision Making, 3, 304–316.
Birnbaum, M. H., & LaCroix, A. R. (2008). Dimension integration: Testing models without trade-offs. Organizational Behavior & Human Decision Processes, 105, 122–133.
Brandstätter, E., Gigerenzer, G., & Hertwig, R. (2006). Making choices without trade-offs: The priority heuristic. Psychological Review, 113, 409–432.
Bröder, A. (2000). Assessing the empirical validity of the “take-the-best” heuristic as a model of human probabilistic inference. Journal of Experimental Psychology: Learning, Memory, & Cognition, 26, 1332–1346.
Bröder, A., & Eichler, A. (2006). The use of recognition information and additional cues in inferences from memory. Acta Psychologica, 121, 275–284.
Bröder, A., & Gaissmaier, W. (2007). Sequential processing of cues in memory-based multiattribute decisions. Psychonomic Bulletin & Review, 14, 895–900.
Bröder, A., & Newell, B. R. (2008). Challenging some common beliefs: Empirical work within the adaptive toolbox metaphor. Judgment & Decision Making, 3, 205–214.
Busemeyer, J. R., & Johnson, J. G. (2004). Computational models of decision making. In D. J. Koehler & N. Harvey (Eds.), Blackwell handbook of judgment and decision making (pp. 133–154). Malden, MA: Blackwell.
Busemeyer, J. R., & Townsend, J. T. (1993). Decision field theory: A dynamic-cognitive approach to decision making in an uncertain environment. Psychological Review, 100, 432–459.
Dougherty, M. R., Franco-Watkins, A. M., & Thomas, R. (2008). Psychological plausibility of the theory of probabilistic mental models and the fast and frugal heuristics. Psychological Review, 115, 199–213.
Dougherty, M. R., Gettys, C. F., & Odgen, E. E. (1999). MINERVA-DM: A memory process model for judgments of likelihood. Psychological Review, 106, 180–209.
Erdfelder, E., Auer, T.-S., Hilbig, B. E., Assfalg, A., Moshagen, M., & Nadarevic, L. (2009). Multinomial processing tree models: A review of the literature. Zeitschrift für Psychologie, 217, 108–124.
Erdfelder, E., Küpper-Tetzel, C. E., & Mattern, S. (in press). Threshold models of recognition and the recognition heuristic. Judgment & Decision Making.
Fiedler, K. (2010). How to study cognitive decision algorithms: The case of the priority heuristic. Judgment & Decision Making, 5, 21–32.
Frosch, C. A., McCloy, R., Beaman, C. P., & Goddard, K. (2010). Time to decide: Frugality vs. congruity in comparative judgment. Manuscript submitted for publication.
Gigerenzer, G. (2008). Why heuristics work. Perspectives on Psychological Science, 3, 20–29.
Gigerenzer, G., & Brighton, H. (2009). Homo heuristicus: Why biased minds make better inferences. Topics in Cognitive Science, 1, 107–143.
Gigerenzer, G., & Goldstein, D. G. (1996). Reasoning the fast and frugal way: Models of bounded rationality. Psychological Review, 103, 650–669.
Gigerenzer, G., Hoffrage, U., & Goldstein, D. G. (2008). Fast and frugal heuristics are plausible models of cognition: Reply to Dougherty, Franco-Watkins, and Thomas (2008). Psychological Review, 115, 230–237.
Glöckner, A. (2008). How evolution outwits bounded rationality: The efficient interaction of automatic and deliberate processes in decision making and implications for institutions. In C. Engel & W. Singer (Eds.), Better than conscious? Implications for performance and institutional analysis (pp. 259–284). Cambridge, MA: MIT Press.
Glöckner, A. (2009). Investigating intuitive and deliberate processes statistically: The multiple-measure maximum likelihood strategy classification method. Judgment & Decision Making, 4, 186–199.
Glöckner, A., & Betsch, T. (2008a). Do people make decisions under risk based on ignorance? An empirical test of the priority heuristic against cumulative prospect theory. Organizational Behavior & Human Decision Processes, 107, 75–95.
Glöckner, A., & Betsch, T. (2008b). Modeling option and strategy choices with connectionist networks: Towards an integrative model of automatic and deliberate decision making. Judgment & Decision Making, 3, 215–228.
Glöckner, A., & Betsch, T. (2008c). Multiple-reason decision making based on automatic processing. Journal of Experimental Psychology: Learning, Memory, & Cognition, 34, 1055–1075.
Glöckner, A., & Betsch, T. (2010). Accounting for critical evidence while being precise and avoiding the strategy selection problem in a parallel constraint satisfaction approach: A reply to Marewski (2010). Journal of Behavioral Decision Making, 23, 468–472.
Glöckner, A., Betsch, T., & Schindler, N. (2010). Coherence shifts in probabilistic inference tasks. Journal of Behavioral Decision Making, 23, 439–462.
Glöckner, A., & Bröder, A. (in press). Processing of recognition information and additional cues: A model-based analysis of choice, confidence, and response time. Judgment & Decision Making.
Glöckner, A., & Herbold, A.-K. (in press). An eye-tracking study on information processing in risky decisions: Evidence for compensatory strategies based on automatic processes. Journal of Behavioral Decision Making.
Glöckner, A., & Moritz, S. (2009). A fine-grained analysis of the jumping-to-conclusions bias in schizophrenia: Data-gathering, response confidence, and information integration. Judgment & Decision Making, 4, 587–600.
Glöckner, A., & Witteman, C. (2010). Beyond dual-process models: A categorization of processes underlying intuitive judgment and decision making. Thinking & Reasoning, 16, 1–25.
Goldstein, D. G., & Gigerenzer, G. (1999). The recognition heuristic: How ignorance makes us smart. In G. Gigerenzer, P. M. Todd, & the ABC Research Group (Eds.), Simple heuristics that make us smart (pp. 37–58). New York: Oxford University Press.
Goldstein, D. G., & Gigerenzer, G. (2002). Models of ecological rationality: The recognition heuristic. Psychological Review, 109, 75–90.
Goldstein, D. G., & Gigerenzer, G. (2009). Fast and frugal forecasting. International Journal of Forecasting, 25, 760–772.
Hardman, D. (2009). Judgment and decision making. Malden, MA: Blackwell.
Hausmann, D., & Läge, D. (2008). Sequential evidence accumulation in decision making: The individual desired level of confidence can explain the extent of information acquisition. Judgment & Decision Making, 3, 229–243.
Hausmann, D., Läge, D., Pohl, R. F., & Bröder, A. (2007). Testing quickEst: No evidence for the quick-estimation heuristic. European Journal of Cognitive Psychology, 19, 446–456.
Hertwig, R., Herzog, S. M., Schooler, L. J., & Reimer, T. (2008). Fluency heuristic: A model of how the mind exploits a by-product of information retrieval. Journal of Experimental Psychology: Learning, Memory, & Cognition, 34, 1191–1206.
Hilbig, B. E. (2008a). Individual differences in fast-and-frugal decision making: Neuroticism and the recognition heuristic. Journal of Research in Personality, 42, 1641–1645.
Hilbig, B. E. (2008b). One-reason decision making in risky choice? A closer look at the priority heuristic. Judgment & Decision Making, 3, 457–462.
Hilbig, B. E. (2010). Precise models deserve precise measures: A methodological dissection. Judgment & Decision Making, 5, 272–284.
Hilbig, B. E., Erdfelder, E., & Pohl, R. F. (2010). One-reason decision-making unveiled: A measurement model of the recognition heuristic. Journal of Experimental Psychology: Learning, Memory, & Cognition, 36, 123–134.
Hilbig, B. E., & Pohl, R. F. (2008). Recognizing users of the recognition heuristic. Experimental Psychology, 55, 394–401.
Hilbig, B. E., & Pohl, R. F. (2009). Ignoranceversus evidence-based decision making: A decision time analysis of the recognition heuristic. Journal of Experimental Psychology: Learning, Memory, & Cognition, 35, 1296–1305.
Hilbig, B. E., Pohl, R. F., & Bröder, A. (2009). Criterion knowledge: A moderator of using the recognition heuristic? Journal of Behavioral Decision Making, 22, 510–522.
Hilbig, B. E., Scholl, S. G., & Pohl, R. F. (2010). Think orblink—Is the recognition heuristic an “intuitive” strategy? Judgment & Decision Making, 5, 300–309.
Hogarth, R. M., & Karelaia, N. (2007). Heuristic and linear models of judgment: Matching rules and environments. Psychological Review, 114, 733–758.
Holyoak, K. J., & Simon, D. (1999). Bidirectional reasoning in decision making by constraint satisfaction. Journal of Experimental Psychology: General, 128, 3–31.
Jekel, M., Nicklisch, A., & Glöckner, A. (2010). Implementation of the multiple-measure maximum likelihood strategy classification method in R: Addendum to Glöckner (2009) and practical guide for application. Judgment & Decision Making, 5, 54–63.
Johnson, E. J., Schulte-Mecklenbeck, M., & Willemsen, M. C. (2008). Process models deserve process data: Comment on Brandstätter, Gigerenzer, and Hertwig (2006). Psychological Review, 115, 263–272.
Juslin, P., & Olsson, H. (2004). Note on the rationality of rule-based versus exemplar-based processing in human judgment. Scandinavian Journal of Psychology, 45, 37–47.
Juslin, P., & Persson, M. (2002). PROBabilities from EXemplars (PROBEX): A “lazy” algorithm for probabilistic inference from generic knowledge. Cognitive Science, 26, 563–607.
Lee, M. D., & Cummins, T. D. (2004). Evidence accumulation in decision making: Unifying the “take the best” and the “rational” models. Psychonomic Bulletin & Review, 11, 343–352.
Marewski, J. N., Gaissmaier, W., & Gigerenzer, G. (2010). Good judgments do not require complex cognition. Cognitive Processing, 11, 103–121.
Marewski, J. N., Gaissmaier, W., Schooler, L. J., Goldstein, D. G., & Gigerenzer, G. (2009). Do voters use episodic knowledge to rely on recognition? In N. A. Taatgen & H. van Rijn (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society (pp. 2232–2237). Austin, TX: Cognitive Science Society.
Marewski, J. N., Gaissmaier, W., Schooler, L. J., Goldstein, D. G., & Gigerenzer, G. (2010). From recognition to decisions: Extending and testing recognition-based models for multi-alternative inference. Psychonomic Bulletin & Review, 17, 287–309.
McCloy, R., Beaman, C. P., Frosch, C. A., & Goddard, K. (2010). Fast and frugal framing effects? Journal of Experimental Psychology: Learning, Memory, & Cognition, 36, 1043–1052.
Newell, B. R. (2005). Re-visions of rationality? Trends in Cognitive Sciences, 9, 11–15.
Newell, B. R., & Bröder, A. (2008). Cognitive processes, models and metaphors in decision research. Judgment & Decision Making, 3, 195–204.
Newell, B. R., Collins, P., & Lee, M. D. (2007). Adjusting the spanner: Testing an evidence accumulation model of decision making. In D. McNamara & G. Trafton (Eds.), Proceedings of the 29th Annual Conference of the Cognitive Science Society (pp. 533–538). Austin, TX: Cognitive Science Society.
Newell, B. R., & Fernandez, D. (2006). On the binary quality of recognition and the inconsequentially of further knowledge: Two critical tests of the recognition heuristic. Journal of Behavioral Decision Making, 19, 333–346.
Newell, B. R., & Lee, M. D. (in press). The right tool forthe job? Comparing an evidence accumulation and a naive strategy selection model of decision making. Journal of Behavioral Decision Making.
Newell, B. R., Rakow, T., Weston, N. J., & Shanks, D. R. (2004). Search strategies in decision making: The success of “success.” Journal of Behavioral Decision Making, 17, 117–137.
Newell, B. R., & Shanks, D. R. (2003). Take the best or look at the rest? Factors influencing “one-reason” decision making. Journal of Experimental Psychology: Learning, Memory, & Cognition, 29, 53–65.
Newell, B. R., & Shanks, D. R. (2004). On the role of recognition in decision making. Journal of Experimental Psychology: Learning, Memory, & Cognition, 30, 923–935.
Newell, B. R., Weston, N. J., & Shanks, D. R. (2003). Empirical tests of a fast-and-frugal heuristic: Not everyone “takes-the-best.” Organizational Behavior & Human Decision Processes, 91, 82–96.
Oppenheimer, D. M. (2003). Not so fast! (and not so frugal!): Rethinking the recognition heuristic. Cognition, 90, B1-B9.
Pachur, T., Bröder, A., & Marewski, J. (2008). The recognition heuristic in memory-based inference: Is recognition a non-compensatory cue? Journal of Behavioral Decision Making, 21, 183–210.
Pachur, T., & Hertwig, R. (2006). On the psychology of the recognition heuristic: Retrieval primacy as a key determinant of its use. Journal of Experimental Psychology: Learning, Memory, & Cognition, 32, 983–1002.
Pohl, R. F. (2006). Empirical tests of the recognition heuristic. Journal of Behavioral Decision Making, 19, 251–271.
Reimer, T., & Katsikopoulos, K. V. (2004). The use of recognition in group decision-making. Cognitive Science, 28, 1009–1029.
Richter, T., & Späth, P. (2006). Recognition is used as one cue among others in judgment and decision making. Journal of Experimental Psychology: Learning, Memory, & Cognition, 32, 150–162.
Rieskamp, J. (2008). The probabilistic nature of preferential choice. Journal of Experimental Psychology: Learning, Memory, & Cognition, 34, 1446–1465.
Schooler, L. J., & Hertwig, R. (2005). How forgetting aids heuristic inference. Psychological Review, 112, 610–628.
Schweickart, O., Brown, N. R., & Lee, P. J. (2009, November). On the role of recognition and magnitude-comparison in binary decision tasks. Paper presented at the Annual Meeting of the Society for Judgment and Decision Making, Boston.
Snook, B., & Cullen, R. M. (2006). Recognizing National Hockey League greatness with an ignorance-based heuristic. Canadian Journal of Experimental Psychology, 60, 33–43.
Wikipedia (n.d.). List of cities proper by population. Retrieved October 2009 from http://en.wikipedia.org/wiki/List_of_cities_proper_by_population.
Zhao, J., & Oppenheimer, D. M. (2010). Beyond binary: Limitations of the binary choice paradigm for studying judgment heuristics. Manuscript submitted for publication.
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Hilbig, B.E. Reconsidering “evidence” for fast-and-frugal heuristics. Psychon Bull Rev 17, 923–930 (2010). https://doi.org/10.3758/PBR.17.6.923
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DOI: https://doi.org/10.3758/PBR.17.6.923