Individual judgment often systematically deviates from the optimal beliefs and choices hypothesized by rational-agent models, leading to cognitive illusions and biases in judgment. Researchers have observed an enormous number of biased beliefs and behaviors in laboratory and field studies since 1970s, such as confirmatory bias, overconfidence, false correlation, base-rate neglect, herd behavior, etc. This biased way of judgment reveals the limitations of rational-agent models and has been an important concern in management & decision science, behavioral economics, psychology, and sociology. Pertaining studies concerning biased judgment in psychology attempt to model and understand the nature of these biases by un-riddling the mental processes of judgment, resulting in various influential perspectives. In particular, individuals’ internal motivational constraints and cognitive deficits are widely concerned by researchers and are regarded as the main mechanisms for the formation of biased judgment. In terms of motivational perspective, researchers attribute selective exposure, information distortion and confirmatory bias to the motivation of cognitive coherence, and ascribe biases in social judgments, like obedience and herd behavior, to the motivation of affiliation. In terms of cognitive perspective, researchers attribute biases in judgment to heuristic search and attribution substitution induced by individuals’ limited cognitive resources in the process of information processing. Previous studies have shed substantial light on individuals’ motivation and cognition, but little on individuals’ interactions with the environment and the biasing impact of these interactions. However, as claimed by Simon, bounded rationality is the result of interplay of the mind and environment. In order to understand human behavior, one first has to understand the environment in which the behaviors take place. In 2000, Fiedler introduced the concept of " sampling” in an important paper published in Psychological Review, emphasizing the impact of distribution of information in the environment on the acquisition process of decision samples（information sampling）and judgment. Many biases in judgment can be attributed to biased sampling, namely decision-makers consciously or unconsciously take the biased and incomplete information samples they draw from the population as the representation of the environment. As the environment component of Simon’s bounded rationality, the biased sampling perspective plays a constructive role in providing alternative accounts for the existing decision biases. In the last decade, the biased sampling perspective has received much attention. Inspired by the perspective of information sampling, researchers discover a new bias effect " description-experience gap”. In addition, the idea of information sampling is integrated into the decision-making models in management and economics, e.g. query theory, decision field theory, leaky-competing accumulator model and decision by sampling. However, although a variety of researchers have attempted to explore the formation mechanism of judgment from the perspective of biased sampling, relatively little attention has been given to this perspective in China. In response to this situation, in current research, an alternative account for the mechanisms underlying biased judgment is presented, which highlights individuals’ information sampling from the environment in the spirit of the biased sampling approach launched by the influential figures like Fiedler, Juslin, Denrell, Le Mens, Hertwig, etc. This paper proceeds as follows: by introducing the conception of sampling proposed by Fiedler, the specific psychological and environmental mechanisms are induced, and resulting biases in judgment are elaborated. Then, the description-experience gap, a typical bias resulting from biased information sampling, is comprehensively delineated, followed by several enlightening sampling-based decision models. Based on a literature review, this paper appeals to the academia for future scholarly endeavors from the perspective of biased information sampling, especially the investigation of the characteristics of the environment which are more likely to lead to biased information sampling. It adds to the theoretical foundations of biased judgment, and provides practical implications for understanding and correcting the bounded rationality of human decision-making.
/ Journals / Foreign Economics & Management
Foreign Economics & Management
Shaohua Zheng, Editor-in-Chief Rong Lu, Vice Editor-in-Chief
Home > All Issues > 2017 > No.12 > Article Details
How Does Biased Information Sampling Lead to Biases in Judgment: A Review from a Biased Sampling Perspective
Foreign Economics & Management Vol. 39, Issue 12, pp. 23 - 37 (2017) DOI:10.16538/j.cnki.fem.2017.12.002
 Anderson M C, Bjork R A, Bjork E L. Remembering can cause forgetting: Retrieval dynamics in long-term memory[J]. Journal of Experimental Psychology: Learning, Memory, and Cognition, 1994, 20(5): 1063-1087.
 Appelt K C, Hardisty D J, Weber E U. Asymmetric discounting of gains and losses: A query theory account[J]. Journal of Risk and Uncertainty, 2011, 43(2): 107-126.
 Asch S E. Opinions and social pressure[J]. Scientific American, 1955, 193(5): 31-35.
 Barron G, Ursino G. Underweighting rare events in experience based decisions: Beyond sample error[J]. Journal of Economic Psychology, 2013, 39: 278-286.
 Baumeister R F, Leary M R. The need to belong: desire for interpersonal attachments as a fundamental human motivation[J]. Psychological Bulletin, 1995, 117(3): 497-529.
 Bhatia S. Associations and the accumulation of preference[J]. Psychological Review, 2013, 120(3): 522-543.
 Brown G D A, Gardner J, Oswald A J, et al. Does wage rank affect employees’ well-being?[J]. Industrial Relations: A Journal of Economy and Society, 2008, 47(3): 355-389.
 Busemeyer J R, Johnson J G. Micro-process models of decision making[A]. Sun R. The Cambridge handbook of computational psychology[M]. Cambridge, MA: Cambridge University Press, 2008: 302-321.
 Busemeyer J R, Townsend J T. Decision field theory: A dynamic-cognitive approach to decision making in an uncertain environment[J]. Psychological Review, 1993, 100(3): 432-459.
 Camilleri A R, Newell B R. The long and short of it: Closing the description-experience “gap” by taking the long-run view[J]. Cognition, 2013, 126(1): 54-71.
 Chaiken S, Liberman A, Eagly A H. Heuristic and systematic information processing within and beyond the persuasion context[A]. Uleman J S, Bargh J A. Unintended thought[M]. New York: Guilford, 1989: 212-252.
 Chambers J R, Windschitl P D. Biases in social comparative judgments: the role of nonmotivated factors in above-average and comparative-optimism effects[J]. Psychological Bulletin, 2004, 130(5): 813-838.
 Cowan N. Metatheory of storage capacity limits[J]. Behavioral and Brain Sciences, 2001, 24(1): 154-176.
 Davidai S, Gilovich T, Ross L D. The meaning of default options for potential organ donors[J]. Proceedings of the National Academy of Sciences of the United States of America, 2012, 109(38): 15201-15205.
 Denrell J, Le Mens G. Information sampling, belief synchronization, and collective illusions[J]. Management Science, 2016, 63(2): 528-547.
 Denrell J, Le Mens G. Information sampling, conformity and collective mistaken beliefs[A]. Proceedings of the 35th annual conference of the cognitive science society[C]. Austin, TX: Cognitive Science Society, 2013: 2177-2182.
 Denrell J. Why most people disapprove of me: Experience sampling in impression formation[J]. Psychological Review, 2005, 112(4): 951-978.
 Diederich A. Dynamic stochastic models for decision making under time constraints[J]. Journal of Mathematical Psychology, 1997, 41(3): 260-274.
 Diederich A. MDFT account of decision making under time pressure[J]. Psychonomic Bulletin & Review, 2003, 10(1): 157-166.
 Ditto P H, Scepansky J A, Munro G D, et al. Motivated sensitivity to preference-inconsistent information[J]. Journal of Personality and Social Psychology, 1998, 75(1): 53-69.
 Dufau S, Grainger J, Ziegler J C. How to say “no” to a nonword: A leaky competing accumulator model of lexical decision[J]. Journal of Experimental Psychology: Learning, Memory, and Cognition, 2012, 38(4): 1117-1128.
 Feiler D C, Tong J D, Larrick R P. Biased judgment in censored environments[J]. Management Science, 2013, 59(3): 573-591.
 Fiedler K, Juslin P. Taking the interface between mind and environment seriously[A]. Fiedler K, Juslin P. Information sampling and adaptive cognition[M]. New York: Cambridge University Press, 2006: 1-29.
 Fiedler K. Beware of samples! A cognitive-ecological sampling approach to judgment biases[J]. Psychological Review, 2000, 107(4): 659-676.
 Fiedler K. Information ecology and the explanation of social cognition and behavior[A]. Kruglanski A, Higgins E T. Social psychology: Handbook of basic principles[M]. 2nd ed. New York: Guilford, 2007: 176-200.
 Fox C R, Hadar L. "Decisions from experience" = sampling error+ prospect theory: Reconsidering Hertwig, Barron, Weber & Erev (2004)[J]. Judgment and Decision Making, 2006, 1(2): 159-161.
 Galesic M, Olsson H, Rieskamp J. Social sampling explains apparent biases in judgments of social environments[J]. Psychological Science, 2012, 23(12): 1515-1523.
 Glöckner A, Hilbig B E, Henninger F, et al. The reversed description-experience gap: Disentangling sources of presentation format effects in risky choice[J]. Journal of Experimental Psychology: General, 2016, 145(4): 486-508.
 Goldstein D G, Johnson E J, Herrmann A, et al. Nudge your customers toward better choices[J]. Harvard Business Review, 2008, 86(12): 99-105.
 Hardisty D J, Johnson E J, Weber E U. A dirty word or a dirty world? Attribute framing, political affiliation, and query theory[J]. Psychological Science, 2010, 21(1): 86-92.
 Hau R, Pleskac T J, Hertwig R. Decisions from experience and statistical probabilities: Why they trigger different choices than a priori probabilities[J]. Journal of Behavioral Decision Making, 2010, 23(1): 48-68.
 Hau R, Pleskac T J, Kiefer J, et al. The description–experience gap in risky choice: The role of sample size and experienced probabilities[J]. Journal of Behavioral Decision Making, 2008, 21(5): 493-518.
 Hertwig R, Barron G, Weber E U, et al. Decisions from experience and the effect of rare events in risky choice[J]. Psychological Science, 2004, 15(8): 534-539.
 Hertwig R, Erev I. The description–experience gap in risky choice[J]. Trends in Cognitive Sciences, 2009, 13(12): 517-523.
 Hertwig R, Pleskac T J. Decisions from experience: Why small samples?[J]. Cognition, 2010, 115(2): 225-237.
 Hertwig R, Pleskac T J. The game of life: How small samples render choice simpler[A]. Chater N, Oaksford M. The probabilistic mind: Prospects for Bayesian cognitive science[M]. Oxford: Oxford University Press, 2008: 209-236.
 Hills T T, Hertwig R. Information search in decisions from experience: Do our patterns of sampling foreshadow our decisions?[J]. Psychological Science, 2010, 21(12): 1787-1792.
 Huber J, Payne J W, Puto C. Adding asymmetrically dominated alternatives: Violations of regularity and the similarity hypothesis[J]. Journal of Consumer Research, 1982, 9(1): 90-98.
 Johnson E J, Goldstein D. Do defaults save lives?[J]. Science, 2003, 302(5649): 1338-1339.
 Johnson E J, Häubl G, Keinan A. Aspects of endowment: A query theory of value construction[J]. Journal of Experimental Psychology: Learning, Memory, and Cognition, 2007, 33(3): 461-474.
 Juslin P, Winman A, Hansson P. The naïve intuitive statistician: a naive sampling model of intuitive confidence intervals[J]. Psychological Review, 2007, 114(3): 678-703.
 Kahneman D, Frederick S. Representativeness revisited: Attribute substitution in intuitive judgment[A]. Gilovich T, Griffin D, Kahneman D. Heuristics and biases: The psychology of intuitive judgment[M]. New York: Cambridge University Press, 2002: 49-81.
 Kahneman D, Tversky A. Prospect theory: An analysis of decision under risk[J]. Econometrica, 1979, 47(2): 263-292.
 Kahneman D. Maps of bounded rationality: Psychology for behavioral economics[J]. The American Economic Review, 2003, 93(5): 1449-1475.
 Kareev Y. Good sampling, distorted views[A]. Fielder K, Juslin P. Information sampling and adaptive cognition[M]. New York: Cambridge University Press, 2006: 33-52.
 Kareev Y. Seven (indeed, plus or minus two) and the detection of correlations[J]. Psychological Review, 2000, 107(2): 397-402.
 Khemlani S S, Oppenheimer D M. When one model casts doubt on another: A levels-of-analysis approach to causal discounting[J]. Psychological Bulletin, 2011, 137(2): 195-210.
 Koehler J J, Mercer M. Selection neglect in mutual fund advertisements[J]. Management Science, 2009, 55(7): 1107-1121.
 Le Mens G, Denrell J. Rational learning and information sampling: On the “naivety” assumption in sampling explanations of judgment biases[J]. Psychological Review, 2011, 118(2): 379-392.
 Lejarraga T, Hertwig R, Gonzalez C. How choice ecology influences search in decisions from experience[J]. Cognition, 2012, 124(3): 334-342.
 Lejarraga T. When experience is better than description: Time delays and complexity[J]. Journal of Behavioral Decision Making, 2010, 23(1): 100-116.
 Li Ailisha, Zhang Qinglin. Choice preference in decision-making[J]. Advances in Psychological Science, 2006, (4):618-624.
 Liu Tengfei, Xu Fuming, Ma Hongyu, et al. The new orientation of behavioral decision making: Experience-based decision making[J]. Advances in Psychological Science, 2012, (7), 1068-1079.
 Lord C G, Ross L, Lepper M R. Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence[J]. Journal of Personality and Social Psychology, 1979, 37(11): 2098-2109.
 Mehlhorn K, Ben-Asher N, Dutt V, et al. Observed variability and values matter: Toward a better understanding of information search and decisions from experience[J]. Journal of Behavioral Decision Making, 2014, 27(4): 328-339.
 Miller G A. The magical number seven, plus or minus two: Some limits on our capacity for processing information[J]. Psychological Review, 1956, 63(2): 81-97.
 Moore D A, Small D A. Error and bias in comparative judgment: on being both better and worse than we think we are[J]. Journal of Personality and Social Psychology, 2007, 92(6): 972-989.
 Muchnik L, Aral S, Taylor S J. Social influence bias: A randomized experiment[J]. Science, 2013, 341(6146): 647-651.
 Olivola C Y, Sagara N. Distributions of observed death tolls govern sensitivity to human fatalities[J]. Proceedings of the National Academy of Sciences of the United States of America, 2009, 106(52): 22151-22156.
 Oppenheimer D M, Kelso E. Information processing as a paradigm for decision making[J]. Annual Review of Psychology, 2015, 66: 277-294.
 Pettibone J C. Testing the effect of time pressure on asymmetric dominance and compromise decoys in choice[J]. Judgment and Decision Making, 2012, 7(4): 513-523.
 Petty R E, Cacioppo J T. Communication and persuasion: Central and peripheral routes to attitude change[M]. New York: Springer-Verlag, 1986.
 Polman E, Russo J E. Commitment to a developing preference and predecisional distortion of information[J]. Organizational Behavior and Human Decision Processes, 2012, 119(1): 78-88.
 Proeger T, Meub L. Overconfidence as a social bias: Experimental evidence[J]. Economics Letters, 2014, 122(2): 203-207.
 Rakow T, Demes K A, Newell B R. Biased samples not mode of presentation: Re-examining the apparent underweighting of rare events in experience-based choice[J]. Organizational Behavior and Human Decision Processes, 2008, 106(2): 168-179.
 Rakow T, Newell B R. Degrees of uncertainty: An overview and framework for future research on experience-based choice[J]. Journal of Behavioral Decision Making, 2010, 23(1): 1-14.
 Roe R M, Busemeyer J R, Townsend J T. Multialternative decision field theory: A dynamic connectionist model of decision making[J]. Psychological Review, 2001, 108(2): 370-392.
 Russo J E, Carlson K A, Meloy M G, et al. The goal of consistency as a cause of information distortion[J]. Journal of Experimental Psychology: General, 2008, 137(3): 456-470.
 Sanborn A N, Chater N. Bayesian brains without probabilities[J]. Trends in Cognitive Sciences, 2016, 20(12): 883-893.
 Simon H A. Models of bounded rationality: Empirically grounded economic reason[M]. Cambridge: MIT Press, 1982.
 Simon H A. Rational choice and the structure of the environment[J]. Psychological Review, 1956, 63(2): 129-138.
 Simonson I. Choice based on reasons: The case of attraction and compromise effects[J]. Journal of Consumer Research, 1989, 16(2): 158-174.
 Stewart N, Chater N, Brown G D A. Decision by sampling[J]. Cognitive Psychology, 2006, 53(1): 1-26.
 Thaler R H, Sunstein C R. Nudge: Improving decisions about health, wealth, and happiness[M]. New Haven, CT: Yale University Press, 2008.
 Thaler R. Toward a positive theory of consumer choice[J]. Journal of Economic Behavior & Organization, 1980, 1(1): 39-60.
 Ting H, Wallsten T S. A query theory account of the effect of memory retrieval on the sunk cost bias[J]. Psychonomic Bulletin & Review, 2011, 18(4): 767-773.
 Trueblood J S, Brown S D, Heathcote A. The multiattribute linear ballistic accumulator model of context effects in multialternative choice[J]. Psychological Review, 2014, 121(2): 179-205.
 Tsetsos K, Gao J, McClelland J L, et al. Using time-varying evidence to test models of decision dynamics: Bounded diffusion vs. the leaky competing accumulator model[J]. Frontiers in Neuroscience, 2012, 6: 79.
 Tversky A, Kahneman D. Judgment under uncertainty: Heuristics and biases[J]. Science, 1974, 185(4157): 1124-1131.
 Tversky A, Kahneman D. Loss aversion in riskless choice: A reference-dependent model[J]. The Quarterly Journal of Economics, 1991, 106(4): 1039-1061.
 Tversky A. Elimination by aspects: A theory of choice[J]. Psychological Review, 1972, 79(4): 281-299.
 Tversky A. Features of similarity[J]. Psychological Review, 1977, 84(4): 327-352.
 Ungemach C, Stewart N, Reimers S. How incidental values from the environment affect decisions about money, risk, and delay[J]. Psychological Science, 2011, 22(2): 253-260.
 Usher M, McClelland J L. Loss aversion and inhibition in dynamical models of multialternative choice[J]. Psychological Review, 2004, 111(3): 757-769.
 Usher M, McClelland J L. The time course of perceptual choice: The leaky, competing accumulator model[J]. Psychological Review, 2001, 108(3): 550-592.
 Vul E, Goodman N, Griffiths T L, et al. One and done? Optimal decisions from very few samples[J]. Cognitive Science, 2014, 38(4): 599-637.
 Wang T, Wang D S. Why Amazon's ratings might mislead you: The story of herding effects[J]. Big Data, 2014, 2(4): 196-204.
 Weber E U, Johnson E J, Milch K F, et al. Asymmetric discounting in intertemporal choice: A query-theory account[J]. Psychological Science, 2007, 18(6): 516-523.
 Weber E U, Shafir S, Blais A R. Predicting risk sensitivity in humans and lower animals: Risk as variance or coefficient of variation[J]. Psychological Review, 2004, 111(2): 430-445.
 Wulff D U, Hills T T, Hertwig R. Online product reviews and the description–experience gap[J]. Journal of Behavioral Decision Making, 2015, 28(3): 214-223.
 Zhang Li, Fu Xiaolan, Sun Yuhao. A cognitive-ecological sampling approach to judgment biases[J]. Advances in Psychological Science, 2003, (6): 601-606.
Cite this article
Ma Dandan, Cen Yonghua, Wu Chengyao. How Does Biased Information Sampling Lead to Biases in Judgment: A Review from a Biased Sampling Perspective[J]. Foreign Economics & Management, 2017, 39(12): 23–37.
Export Citations as: For
Previous: Same-sex Attraction or Same-sex Repulsion: A Study on the Gender Spillover Effect of Female Directors on Female Senior Managers in Chinese Listed Companies