123 publications classées par:
type de publication
: Revue avec comité de lecture
Articles Garcia-Retamero R., Cookely E. & Hoffrage U. (2015). Visual aids improve diagnostic inferences and metacognitive judgment calibration. Frontiers in Psychology, 6(932), 1-12. [doi] [pdf] [url] [web of science] [abstract]
Visual aids can improve comprehension of risks associated with medical treatments, screenings, and lifestyles. Do visual aids also help decision makers accurately assess their risk comprehension? That is, do visual aids help them become well calibrated? To address these questions, we investigated the benefits of visual aids displaying numerical information and measured accuracy of self-assessment of diagnostic inferences (i.e., metacognitive judgment calibration) controlling for individual differences in numeracy. Participants included 108 patients who made diagnostic inferences about three medical tests on the basis of information about the sensitivity and false-positive rate of the tests and disease prevalence. Half of the patients received the information in numbers without a visual aid, while the other half received numbers along with a grid representing the numerical information. In the numerical condition, many patients-especially those with low numeracy-misinterpreted the predictive value of the tests and profoundly overestimated the accuracy of their inferences. Metacognitive judgment calibration mediated the relationship between numeracy and accuracy of diagnostic inferences. In contrast, in the visual aid condition, patients at all levels of numeracy showed high-levels of inferential accuracy and metacognitive judgment calibration. Results indicate that accurate metacognitive assessment may explain the beneficial effects of visual aids and numeracy-a result that accords with theory suggesting that metacognition is an essential part of risk literacy. We conclude that well-designed risk communications can inform patients about healthrelevant numerical information while helping them assess the quality of their own risk comprehension.
Hafenbrädl S. & Hoffrage U. (2015). Toward an ecological analysis of Bayesian inferences: How task characteristics influence responses. Frontiers in Psychology, 6(939), 1-15. [doi] [pdf] [url] [web of science] [abstract]
In research on Bayesian inferences, the specific tasks, with their narratives and characteristics, are typically seen as exchangeable vehicles that merely transport the structure of the problem to research participants. In the present paper, we explore whether, and possibly how, task characteristics that are usually ignored influence participants' responses in these tasks. We focus on both quantitative dimensions of the tasks, such as their base rates, hit rates, and false-alarm rates, as well as qualitative characteristics, such as whether the task involves a norm violation or not, whether the stakes are high or low, and whether the focus is on the individual case or on the numbers. Using a data set of 19 different tasks presented to 500 different participants who provided a total of 1,773 responses, we analyze these responses in two ways: first, on the level of the numerical estimates themselves, and second, on the level of various response strategies, Bayesian and non-Bayesian, that might have produced the estimates. We identified various contingencies, and most of the task characteristics had an influence on participants' responses. Typically, this influence has been stronger when the numerical information in the tasks was presented in terms of probabilities or percentages, compared to natural frequencies - and this effect cannot be fully explained by a higher proportion of Bayesian responses when natural frequencies were used. One characteristic that did not seem to influence participants' response strategy was the numerical value of the Bayesian solution itself. Our exploratory study is a first step toward an ecological analysis of Bayesian inferences, and highlights new avenues for future research.
Hoffrage U., Hafenbrädl S. & Bouquet C. (2015). Natural frequencies facilitate diagnostic inferences of managers. Frontiers in Psychology, 6(642), 1-11. [doi] [pdf] [web of science] [abstract]
In Bayesian inference tasks, information about base rates as well as hit rate and false-alarm rate needs to be integrated according to Bayes' rule after the result of a diagnostic test became known. Numerous studies have found that presenting information in a Bayesian inference task in terms of natural frequencies leads to better performance compared to variants with information presented in terms of probabilities or percentages. Natural frequencies are the tallies in a natural sample in which hit rate and false-alarm rate are not normalized with respect to base rates. The present research replicates the beneficial effect of natural frequencies with four tasks from the domain of management, and with management students as well as experienced executives as participants. The percentage of Bayesian responses was almost twice as high when information was presented in natural frequencies compared to a presentation in terms of percentages. In contrast to most tasks previously studied, the majority of numerical responses were lower than the Bayesian solutions. Having heard of Bayes' rule prior to the study did not affect Bayesian performance. An implication of our work is that textbooks explaining Bayes' rule should teach how to represent information in terms of natural frequencies instead of how to plug probabilities or percentages into a formula.
Hoffrage U. & Koller M. (2015). Chances und risks in medical risk communication = Chancen und Risiken der Risikokommunikation in der Medizin. GMS German Medical Science - an Interdisciplinary Journal, 13(Doc07), 1-15. [doi] [pdf] [abstract]
Communication between physicians and patients in everyday life is marked by a number of disruptive factors. Apart from specific interests, mistakes, and misunderstandings on both sides, there are main factors that contribute to the risk in risk communication. Using the example of mammography screening, the current work demonstrates how the meaning of test results and the informative value of measures taken to reduce risk are often misunderstood. Finally, the current work provides examples of successful risk communication.¦Kommunikation, die im Alltag zwischen Ärzten und Patienten stattfindet, wird durch eine Reihe störender Faktoren begleitet. Neben spezifischen Interessen sind es vor allem Fehler und Missverständnisse, die von beiden Seiten zum Risiko der Risikokommunikation beitragen. Am Beispiel des Mammographie-Screenings wird dargestellt, wie die Bedeutung von Testergebnissen und die Aussagekraft von Maßnahmen, die zur Reduktion von Risiken ergriffen werden, oft missverstanden wird. Ferner wird gezeigt, wie eine gelungene Risikokommunikation aussehen kann.
Hoffrage U., Krauss S., Martignon L. & Gigerenzer G. (2015). Natural frequencies improve Bayesian reasoning in simple and complex inference tasks. Frontiers in Psychology, 6(1473), 1-14. [doi] [pdf] [url] [web of science] [abstract]
Representing statistical information in terms of natural frequencies rather than probabilities improves performance in Bayesian inference tasks. This beneficial effect of natural frequencies has been demonstrated in a variety of applied domains such as medicine, law, and education. Yet all the research and applications so far have been limited to situations where one dichotomous cue is used to infer which of two hypotheses is true. Real-life applications, however, often involve situations where cues (e.g., medical tests) have more than one value, where more than two hypotheses (e.g., diseases) are considered, or where more than one cue is available. In Study 1, we show that natural frequencies, compared to information stated in terms of probabilities, consistently increase the proportion of Bayesian inferences made by medical students in four conditions-three cue values, three hypotheses, two cues, or three cues-by an average of 37 percentage points. In Study 2, we show that teaching natural frequencies for simple tasks with one dichotomous cue and two hypotheses leads to a transfer of learning to complex tasks with three cue values and two cues, with a proportion of 40 and 81% correct inferences, respectively. Thus, natural frequencies facilitate Bayesian reasoning in a much broader class of situations than previously thought.
Hoffrage U. & Marewski J. N. (2015). Unveiling the Lady in Black: Modeling and aiding intuition. Journal of Applied Research in Memory and Cognition, 4(3), 145-163. [doi] [web of science] [abstract]
The cognitive and decision science literature on modeling and aiding intuitions in organizations is rich, but segregated. This special issue offers a sample of that literature, stimulating exchange and inspiring intuitions about intuition. A total of 16 articles bring together diverse approaches, such as naturalistic-decision-making, heuristics-and-biases, dual-processes, ACT-R, CLARION, Brunswikian, and Quantum-Probability-Theory, many of them co-authored by their founders. The articles cover computational models and verbal theories; experimental and observational work; laboratory and naturalistic research. Comprising various domains, such as consulting, investment, law, police, and morality, the articles relate intuition to implicit cognition, emotions, scope insensitivity, expertise, and representative experimental design. In this article, we map intuition across poles such as Enlightenment/Romanticism, reason/emotion, objectivity/subjectivity, inferences/qualia, Taylorism/universal scholarship, System 2/System 1, dichotomies/dialectics, and science/art. We discuss intuitions as inspirations, instincts, inferences, and insights. Finally, we review the contributions to this special issue, placing them into historical, philosophical, and societal contexts.
Hoffrage U. & Marewski J. N. (2015). Unveiling the Lady in Black: Brunswikian (and other) approaches to intuition. The Brunswik Society Newsletter, 30, 15-19. [abstract]
In September 2015, the Journal of Applied Research in Memory and Cognition (JARMAC) published a special issue on "Modeling and Aiding Intuition in Organizational Decision Making", edited by Julian Marewski and Ulrich Hoffrage (2015). The issue contained 17 articles - all are open access and can be downloaded at http://www.sciencedirect.com/science/journal/22113681/4/3. In the present article, we will give an overview of our introduction to this special issue. We will focus on those parts (and on the discussion of those papers in the special issue) that are related to Brunswikian approaches. There are three such links to the work of Egon Brunswik: (1) the conceptualization of intuition as inference, (2) the notion of quasirationality, and (3) the methodological imperative of using a representative design when studying intuition where it can be been built, namely in natural environments.
Koller M. & Hoffrage U. (2015). Societal perspectives on risk awareness and risk competence = Gesellschaftliche Perspektiven von Risikowahrnehmung und Risikokompetenz. GMS German Medical Science - an Interdisciplinary Journal, 13(Doc08), 1-12. [doi] [pdf] [url] [abstract]
Medical risks can be assessed by objectifiable therapeutic features; however, these risks are also characterised to a considerable degree by individual and social values. People tend to strive towards both freedom as well as safety; in a medical context, these two aims are taken into account by shared decision-making models and by stricter regulations in the pharmaceutical sector. Media reports on medical risks are caught between providing information and economic interests, and this conflict particularly complicates rational discussions about unexpected risks (for instance, in the field of natural medicine). Thus, it is necessary to create the type of information culture which allows differentiating between real and less pronounced risks.¦Risiken innerhalb der Medizin sind nicht bloß durch objektivierbare Eigenschaften von Therapien fassbar, sondern in erheblichem Maße durch individuelle und gesellschaftliche Werte geprägt. Individuen streben gleichermaßen nach Freiheit und Sicherheit - im medizinischen Kontext wird dem durch partizipative Entscheidungsmodelle einerseits und Verschärfungen der Regularien im Arzneimittelsektor andererseits Rechnung getragen. Die mediale Berichterstattung über Risiken im Gesundheitsbereich findet im Spannungsfeld zwischen Aufklärung und wirtschaftlichen Interessen statt, was insbesondere eine rationale Diskussion über unerwartete Risiken (z.B. in der Naturheilkunde) erschwert. Es gilt daher eine Informationskultur zu schaffen, die es erlaubt, echte von weniger ausgeprägten Risiken zu unterscheiden.
Marewski J. N. & Hoffrage U. (2015). Special issue and call for commentaries: Modeling and aiding intuition in organizational decision making. The Brunswik Society Newsletter, 30, 28-31. [abstract]
With the present contribution to the Brunswik Society Newsletter, we like to draw attention to a special issue on "Modeling and Aiding Intuition in Organizational Decision Making" (Marewski & Hoffrage, 2015) that recently appeared in the Journal of Applied Research in Memory and Cognition (JARMAC); http://www.sciencedirect.com/science/journal/22113681/4/3), and we solicit commentaries on the articles and opinion pieces published in this issue.
Marewski J. N. & Hoffrage U. (2015). Modeling and aiding intuition in organizational decision making [Special Issue]. Journal of Applied Research in Memory and Cognition, 4(3), 145-312.
White C. M., Hoffrage U. & Reisen N. (2015). Choice deferral can arise from absolute evaluation or relative comparison. Journal of Experimental Psychology: Applied, 21(2), 140-157. [doi] [web of science] [abstract]
When choosing among several options, people may defer choice for either of 2 reasons: because none of the options is good enough or because there is uncertainty regarding which is the best. These reasons form the basis of the 2-stage, 2-threshold (2S2T) framework, which posits that a different kind of processing corresponds to these 2 reasons for choice deferral: absolute evaluations and relative comparisons, respectively. Three experiments are reported in which each type of processing was triggered in different conditions either via different payoff structures or different degrees of attribute knowledge. The effects of the 3 main independent variables (the size of the choice set, the utility of the best option, and the number of competitive options) differed depending on the payoff structure or attribute knowledge conditions in ways predicted by the 2S2T framework. Implications for consumer decision making, marketing, and eyewitness identification are discussed.
Woike J. K., Hoffrage U. & Petty J. S. (2015). Picking profitable investments: The success of equal weighting in simulated venture capitalist decision making. Journal of Business Research, 68(8), 1705-1716. [doi] [pdf] [web of science] [abstract]
Using computer simulation,we investigate the impact of different strategies on the financial performance of VCs. We compare simple heuristics such as equal weighting and fast and frugal trees with more complex machine learning and regression models and analyze the impact of three factors: VC learning, the statistical properties of the investment environment, and the amount of information available in a business plan. We demonstrate that the performance of decision strategies and the relative quality of decision outcomes change critically between environments in which different statistical relationships hold between information contained in business plans and the likelihood of financial success. The Equal Weighting strategy is competitive with more complex investment decision strategies and its performance is robust across environments. Learning only from those plans that the simulated VC invested in, drastically reduces the VC's potential to learn from experience. Lastly, the results confirm that decision strategies differ in respect to the impact of added information on the outcomes of decisions. Finally, we discuss real-world implications for the practice of VCs and research on VC decision making.
Dietz J., Antonakis J., Hoffrage U., Krings F., Marewski J. N. & Zehnder C. (2014). Teaching evidence-based management with a focus on producing local evidence. Academy of Management Learning and Education, 13(3), 397-414. [doi] [pdf] [abstract]
We present an approach to teaching evidence-based management (EBMgt) that trains future managers how to produce local evidence. Local evidence is causally interpretable data, collected on-site in companies to address a specific business problem. Our teaching method is a variant of problem-based learning, a method originally developed to teach evidence-based medicine. Following this method, students learn an evidence-based problem-solving cycle for addressing actual business cases. Executing this cycle, students use and produce scientific evidence through literature searches and the design of local, experimental tests of causal hypotheses. We argue the value of teaching EBMgt with a focus on producing local evidence, how it can be taught, and what can be taught. We conclude by outlining our contribution to the literature on teaching EBMgt and by discussing limitations of our approach.
Garcia-Retamero R. & Hoffrage U. (2013). Visual representation of statistical information improves diagnostic inferences in doctors and their patients. Social Science and Medicine, 83, 27-33. [doi] [web of science] [abstract]
Doctors and patients have difficulty inferring the predictive value of a medical test from information about the prevalence of a disease and the sensitivity and false-positive rate of the test. Previous research has established that communicating such information in a format the human mind is adapted to-namely natural frequencies-as compared to probabilities, boosts accuracy of diagnostic inferences. In a study, we investigated to what extent these inferences can be improved-beyond the effect of natural frequencies-by providing visual aids. Participants were 81 doctors and 81 patients who made diagnostic inferences about three medical tests on the basis of information about prevalence of a disease, and the sensitivity and false-positive rate of the tests. Half of the participants received the information in natural frequencies, while the other half received the information in probabilities. Half of the participants only received numerical information, while the other half additionally received a visual aid representing the numerical information. In addition, participants completed a numeracy scale. Our study showed three important findings: (1) doctors and patients made more accurate inferences when information was communicated in natural frequencies as compared to probabilities; (2) visual aids boosted accuracy even when the information was provided in natural frequencies; and (3) doctors were more accurate in their diagnostic inferences than patients, though differences in accuracy disappeared when differences in numerical skills were controlled for. Our findings have important implications for medical practice as they suggest suitable ways to communicate quantitative medical data.
Marewski J. N. & Hoffrage U. (2013). Processes models, environmental analyses, and cognitive architectures: Quo vadis quantum probability theory? (Commentary on Pothos and Busemeyer). Behavioral and Brain Sciences, 36, 297-298. [doi] [abstract]
A lot of research in cognition and decision making suffers from a lack of formalism. The quantum probability program could help to improve this situation, but we wonder whether it would provide even more added value if its presumed focus on outcome models were complemented by process models that are, ideally, informed by ecological analyses and integrated into cognitive architectures.
Gonin M., Palazzo G. & Hoffrage U. (2012). Neither Bad Apple nor Bad Barrel: How the Societal Context Impacts Unethical Behavior in Organizations. Business Ethics: A European Review, 21(1), 31-46. [doi] [pdf] [url] [abstract]
Every time another corporate scandal captures media headlines, the 'bad apple vs. bad barrel' discussion starts anew. Yet this debate overlooks the influence of the broader societal context on organizational behavior. In this article, we argue that misbehaviors of organizations (the 'barrels') and their members (the 'apples') cannot be addressed properly without a clear understanding of their broader context (the 'larder'). Whereas previously, a strong societal framework dampened the practical application of the Homo economicus concept (business actors as perfectly rational and egocentric utility-maximizing agents without any moral concern), specialization, individualization and globalization led to a business world disembedded from broader societal norms. This emancipated business world promotes a literal interpretation of Homo economicus among business organizations and their members. Consequently, we argue that the first step toward 'healthier' apples and barrels is to sanitize the larder, that is, adapt the framework in which organizations and their members evolve.Chaque fois qu'un nouveau scandale fait la une des médias, la question de savoir si le problème se situe au niveau des individus (des 'pommes isolées') ou au niveau des organisations (les 'caisses de pommes') refait surface. Ce débat tend néanmoins à sous-estimer l'influence du contexte sociétal plus large sur le comportement dans les organisations. Dans cet article, nous soutenons l'idée que les scandales éthiques dans les organisations ou parmi leurs membres ne peuvent être compris correctement sans une vision plus précise de leur contexte plus large (la 'cave à pommes'). Si dans le passé un contexte sociétal fort permettait d'adoucir les applications pratiques de l'Homo economicus (qui considère l'acteur économique comme un agent parfaitement rationnel et égocentrique cherchant à maximiser son utilité sans réflexion morale), l'individualisation et la globalisation ont conduit à un monde économique désencastré et déconnecté des normes sociales plus larges. Ce monde économique autonome promouvoit une interprétation littérale de l'Homo economicus parmi les entreprises et leurs employés. Il en résulte que le premier pas vers des pommes moins pourries passe par un assainissement de la cave, c'est-à-dire l'adoption d'un cadre socio-normatif qui permet un recadrage du contexte dans lequel les organisations économiques et leurs acteurs agissent.
Marewski J. N. & Hoffrage U. (2012). Call for papers: Modeling and aiding intuitions in organizational decision making. Journal of Applied Research in Memory and Cognition, 1(4), 267-268. [url]
Palazzo G., Krings F. & Hoffrage U. (2012). Ethical Blindness. Journal of Business Ethics, 109(3), 323-338. [doi] [url] [abstract]
Many models of (un)ethical decision making assume that people decide rationally and are in principle able to evaluate their decisions from a moral point of view. However, people might behave unethically without being aware of it. They are ethically blind. Adopting a sensemaking approach, we argue that ethical blindness results from a complex interplay between individual sensemaking activities and context factors.
Hoffrage U. (2011). Recognition judgments and the performance of the recognition heuristic depend on the size of the reference class. Judgment and Decision Making, 6(1), 43-57. [pdf] [abstract]
In a series of three experiments, participants made inferences about which one of a pair of two objects scored higher on a criterion. The first experiment was designed to contrast the prediction of Probabilistic Mental Model theory (Gigerenzer, Hoffrage, & Kleinbölting, 1991) concerning sampling procedure with the hard-easy effect. The experiment failed to support the theory's prediction that a particular pair of randomly sampled item sets would differ in percentage correct; but the observation that German participants performed practically as well on comparisons between U.S. cities (many of which they did not even recognize) than on comparisons between German cities (about which they knew much more) ultimately led to the formulation of the recognition heuristic. Experiment 2 was a second, this time successful, attempt to unconfound item difficulty and sampling procedure. In Experiment 3, participants' knowledge and recognition of each city was elicited, and how often this could be used to make an inference was manipulated. Choices were consistent with the recognition heuristic in about 80% of the cases when it discriminated and people had no additional knowledge about the recognized city (and in about 90% when they had such knowledge). The frequency with which the heuristic could be used affected the percentage correct, mean confidence, and overconfidence as predicted. The size of the reference class, which was also manipulated, modified these effects in meaningful and theoretically important ways.
White C.M., Hafenbrädl S., Hoffrage U., Reisen N. & Woike J.K. (2011). Are groups more likely to defer choice than their members?. Judgment and Decision Making, 6(3), 239-251. [pdf] [web of science] [abstract]
When faced with a choice, instead of selecting an option one can normally select none of them (i.e., defer choice). Previous research has occasionally investigated when and why individuals defer choice, but has almost never looked at these questions when groups of people make choices. There are separate reasons to predict that groups may be equally as likely, more likely, or less likely to defer choice as are individuals, so we re-analyzed some previously published data and conducted a new experiment to address this. We found that small groups of people tended to defer choice more often than their members would. Assuming that the groups used a plurality rule but gave additional weight to individual preferences to defer choice allowed the groups' responses to be predicted quite well. Several possible explanations of these findings are discussed.
Berg N. & Hoffrage U. (2010). Compressed environments: Unbounded optimizers should sometimes ignore information. Minds and Machines, 20(2), 259-275. [doi]
Berg N., Hoffrage U. & Abramczuk K. (2010). Fast Acceptance by Common Experience: FACE-recognition in Schelling's model of neighborhood segregation. Judgment and Decision Making, 5(5), 391-410. [pdf]
Garcia-Retamero R., Hoffrage U., Müller S. M. & Maldonado A. (2010). The influence of causal knowledge in Two-Alternative Forced-Choice Tasks. Open Psychology Journal, 3, 136-144. [doi] [pdf] [url] [abstract]
Making decisions can be hard, but it can also be facilitated. Simple heuristics are fast and frugal but nevertheless fairly accurate decision rules that people can use to compensate for their limited computational capacity, time, and knowledge when making decisions. These heuristics are effective to the extent that they can exploit the structure of information in the environment in which they operate. They require knowledge about the predictive value of probabilistic cues. However, it is often difficult to keep track of all the available cues in the environment and how they relate to any relevant criterion. We suggest that knowledge about the causal structure of the environment helps decision makers focus on a manageable subset of cues, thus effectively reducing the potential computational complexity inherent in even relatively simple decision-making tasks. Specifically, we claim that causal knowledge can act as a meta-cue for identifying highly valid cues and help to estimate cue-validities. Causal knowledge, however, can also bias people's decisions. We review experimental evidence that tested these hypotheses.
Reisen N. & Hoffrage U. (2010). The InterActive Choice Aid: A new approach to supporting online consumer decision making. AIS Transactions on Human-Computer Interaction, 2(4), 112-126. [pdf] [abstract]
Interactive Choice Aid (ICA) is a decision aid, introduced in this paper, that systematically assists consumers with online purchase decisions. ICA integrates aspects from prescriptive decision theory, insights from descriptive decision research, and practical considerations; thereby combining pre-existing best practices with novel features. Instead of imposing an objectively ideal but unnatural decision procedure on the user, ICA assists the natural process of human decision-making by providing explicit support for the execution of the user's decision strategies. The application contains an innovative feature for in-depth comparisons of alternatives through which users' importance ratings are elicited interactively and in a playful way. The usability and general acceptance of the choice aid was studied; results show that ICA is a promising contribution and provides insights that may further improve its usability.
Garcia-Retamero R. & Hoffrage U. (2009). Influencia de las creencias causales en los procesos de toma de decisiones (Influence of causal knowledge on decision-making processes). Revista Mexicana de Psicología, 26(1), 103-111.
White C. M. & Hoffrage U. (2009). Testing the tyranny of too much choice against the allure of more choice. Psychology and Marketing, 26, 280-298.
Berg N. & Hoffrage U. (2008). Rational ignoring with unbounded cognitive capacity. Journal of Economic Psychology, 29, 792-809. [doi]
Gigerenzer G., Hoffrage U. & Goldstein D. G. (2008). Fast and frugal heuristics are plausible models of congition: Reply to Dougherty, Franco-Watkins, and Thomas (2008). Psychological Review, 115, 230-239.
Gigerenzer G., Hoffrage U. & Goldstein D. G. (2008). Postscript: Fast and frugal heuristics. Psychological Review, 115, 238-239.
Hoffrage U., Garcia-Retamero R. & Czienskowski U. (2008). Compound cue processing in linearly and nonlinearly separable environments. The Psychological Record, 58, 303-316.
Reisen N., Hoffrage U. & Mast F. W. (2008). Identifying decision strategies in a consumer choice situation. Judgment and Decision Making, 3(8), 641-658. [pdf]
Rieskamp J. & Hoffrage U. (2008). Inferences under time pressure: how opportunity costs affect strategy selection. Acta Psychologica, 127, 258-276.
Garcia-Retamero R., Hoffrage U. & Dieckmann A. (2007). When one cue is not enough: combining fast and frugal heuristics with compound cue processing. Quarterly Journal of Experimental Psychology, 60(9), 1197-1215.
Garcia-Retamero R., Hoffrage U., Dieckmann A. & Ramos M. M. (2007). Compound cue processing within the fast and frugal heuristics approach in non-linearly separable environments. Learning and Motivation, 38, 16-34.
Gigerenzer G. & Hoffrage U. (2007). The role of representation in Bayesian reasoning: correcting common misconceptions [Commentary on Barbey and Sloman]. Behavioral and Brain Sciences, 30, 264-267.
Reimer T., Hoffrage U. & Katsikopoulos K. V. (2007). Entscheidungsheuristiken in Gruppen [Heuristics in group decision-making]. NeuroPsychoEconomics, 2, 7-29.
Reimer T., Kuendig S., Hoffrage U., Park E. & Hinsz V. (2007). Effects of the information environment on group discussions and decisions in the hidden-profile paradigm. Communication Monographs, 74, 1-28.
Garcia-Retamero R. & Hoffrage U. (2006). How causal knowledge simplifies decision-making. Minds and Machines, 16, 365-380.
Reimer T. & Hoffrage U. (2006). The ecological rationality of simple group heuristics: effects of group member strategies on decision accuracy. Theory and Decision, 60, 403-438.
Reimer T. & Hoffrage U. (2005). Can simple group heuristics detect hidden profiles in randomly generated environments. Swiss Journal of Psychology, 64, 21-37.
Dhami M., Hertwig R. & Hoffrage U. (2004). The role of representative design in an ecological approach to cognition. Psychological Bulletin, 130, 959-988.
Hoffrage U. & Reimer T. (2004). Models of bounded rationality: The approach of fast and frugal heuristics. Management Revue, 15, 437-459.
Betsch T., Hoffmann K., Hoffrage U. & Plessner H. (2003). Intuition beyond recognition : when less familiar events are liked more. Experimental Psychology, 50, 49-54.
Hertwig R., Fanselow C. & Hoffrage U. (2003). Hindsight bias : how knowledge and heuristics affect our reconstruction of the past. Memory, 11, 357-377.
Hoffrage U. (2003). Risikokommunikation bei Brustkrebsfrüherkennung und Hormonersatztherapie. [Risk communication in the early identification of breast cancer and hormone-replacement therapy]. Zeitschrift für Gesundheitspsychologie, 11, 76-86.
Hoffrage U. & Pohl R. F. (2003). Research on hindsight bias: a rich past, a productive present, and a challenging future. Memory, 11, 329-335.
Hoffrage U. & Pohl R. F. (2003). Hindsight Bias [Special Issue]. Memory, 11(4/5), 329-504.
Hoffrage U., Weber A., Hertwig R. & Chase V. (2003). How to keep children save in traffic : find the daredevils while they are young. Journal of Experimental Psychology : Applied, 11, 249-260.
Hoffrage U., Gigerenzer G., Krauss S. & Martignon L. (2002). Representation facilitates reasoning : what natural frequencies are and what they are not. Cognition, 84, 343-352.
Hoffrage U., Lindsey S., Hertwig R. & Gigerenzer G. (2002). Response to Brian Butterworth: 'Statistics: What seems natural?'. Science, 292(5518), 853.
Kurzenhäuser S. & Hoffrage U. (2002). Teaching bayesian reasoning: an evaluation of a classroom tutorial for medical students. Medical Teacher, 24(5), 516-521.
Martignon L. & Hoffrage U. (2002). Fast, frugal and fit : simple heuristics for paired comparison. Theory and Decision, 52, 29-71.
Hertwig R. & Hoffrage U. (2001). Eingeschränkte und ökologische Rationalität : ein Forschungsprogramm. [Bounded and ecological rationality: A research program]. Psychologische Rundschau, 52, 11-19.
Hertwig R. & Hoffrage U. (2001). Empirische Evidenz für einfache Heuristiken. Eine Antwort auf Bröder. Psychologische Rundschau, 52, 162-165.
Hoffrage U. (2001). Does knowing who is rational tell us why and when people are irrational ?. Theory and Psychology, 11, 852-855.
Hoffrage U. (2000). Why the analysis of cognitive processes matters. Behavioral and Brain Sciences, 23, 679-680.
Hoffrage U., Hertwig R. & Gigerenzer G. (2000). Hindsight bias : a by-product of knowledge updating?. Journal of Experimental Psychology : Learning, Memory, and Cognition, 26, 566-581.
Hoffrage U., Kurzenhäuser S. & Gigerenzer G. (2000). Wie kann man die Bedeutung medizinischer Testbefunde besser verstehen und kommunizieren ? [How to improve the communication and understanding of medical test results?]. Zeitschrift für ärztliche Fortbildung und Qualitätssicherung, 94, 713-719.
Hoffrage U., Lindsey S., Hertwig R. & Gigerenzer G. (2000). Communicating statistical information. Science, 290, 2261-2262.
Todd P. M. & Gigerenzer G. (2000). How can we open up the adaptive toolbox. Behavioral and Brain Sciences, 23, 767-780.
Gigerenzer G. & Hoffrage U. (1999). Overcoming difficulties in Bayesian reasoning : a reply to Lewis and Keren (1999) and Mellers and McGraw (1999). Psychological Review, 106, 425-430.
Gigerenzer G., Hoffrage U. & Ebert A. (1998). AIDS counseling for low-risk clients. Aids Care, 10, 197-211.
Hoffrage U. & Gigerenzer G. (1998). Using natural frequencies to improve diagnostic inferences. Academic Medicine, 73, 538-540.
Hertwig R., Gigerenzer G. & Hoffrage U. (1997). The reiteration effect in hindsight bias. Psychological Review, 104, 194-202.
Gigerenzer G. & Hoffrage U. (1995). How to improve Bayesian reasoning without instruction : frequency formats. Psychological Review, 102, 684-704.
Gigerenzer G., Hoffrage U. & Kleinbölting H. (1991). Probabilistic mental models : a Brunswikian theory of confidence. Psychological Review, 98, 506-528.
Livres Hertwig R., Hoffrage U. & the ABC Research Group (2013). Simple heuristics in a social world. Oxford University Press, New York, NY. [doi] [url] [abstract]
This book invites readers to discover the simple heuristics that people use to navigate the complexities and surprises of environments populated with others. The social world is a terrain where humans and other animals compete with conspecifics for myriad resources, including food, mates, and status, and where rivals grant the decision maker little time for deep thought, protracted information search, or complex calculations. The social world also encompasses domains, however, where social animals such as humans learn from one another how to deal with the vagaries of a natural world that both inflicts unforeseeable hazards and presents useful opportunities and dare to trust and forge alliances with one another to boost their chances of success. According to the book's thesis, the undeniable complexity of the social world does not dictate cognitive complexity as many scholars of rationality argue. Rather, it entails circumstances that render optimization impossible or computationally arduous: intractability, the existence of incommensurable considerations, and competing goals. With optimization beyond reach, less can be more. That is, heuristics-simple strategies for making decisions when time is pressing and careful deliberation an unaffordable luxury-become indispensible mental tools. As accurate or even more accurate than complex methods when used in the appropriate environments, these heuristics are good descriptive models of how people make many decisions and inferences, but their impressive performance also poses a normative challenge for optimization models. In short, the homo socialis may prove to be a homo heuristicus whose intelligence reflects ecological rather than logical rationality.
Hertwig R., Hoffrage U. & the ABC Research Group (2012). Simple heuristics in a social world. Oxford University Press, Oxford, UK. [doi] [url] [abstract]
Simple Heuristics in a Social World invites readers to discover the simple heuristics that people use to navigate the complexities and surprises of environments populated with others. The social world is a terrain where humans and other animals compete with conspecifics for myriad resources, including food, mates, and status, and where rivals grant the decision maker little time for deep thought, protracted information search, or complex calculations. Yet, the social world also encompasses domains where social animals such as humans can learn from one another and can forge alliances with one another to boost their chances of success.¦According to the book's thesis, the undeniable complexity of the social world does not dictate cognitive complexity as many scholars of rationality argue. Rather, it entails circumstances that render optimization impossible or computationally arduous: intractability, the existence of incommensurable considerations, and competing goals. With optimization beyond reach, less can be more. That is, heuristics--simple strategies for making decisions when time is pressing and careful deliberation an unaffordable luxury--become indispensible mental tools. As accurate as or even more accurate than complex methods when used in the appropriate social environments, these heuristics are good descriptive models of how people make many decisions and inferences, but their impressive performance also poses a normative challenge for optimization models. In short, the Homo socialis may prove to be a Homo heuristicus whose intelligence reflects ecological rather than logical rationality.
Todd P. M., Gigerenzer G. & the ABC Research Group (Ulrich Hoffrage is member of the ABC Research Group) (2012). Ecological rationality - Intelligence in the world. Oxford University Press, New York, NY. [doi] [url] [abstract]
The idea that more information and more computation yield better decisions has long shaped our vision of rationality. Yet humans and other animals typically rely on simple heuristics or rules of thumb to solve adaptive problems, focusing on one or a few important cues and ignoring the rest, and shortcutting computation rather than striving for as much as possible. In this book, the authors argue that in an uncertain world, more information and computation are not always better, and instead ask when, and why, less can be more. The answers to these questions constitute the idea of ecological rationality, as explored in the chapters in this book: how people can be effective decision makers by using simple heuristics that fit well to the structure of their environment. When people wield the right tool from the mind's adaptive toolbox for a particular situation, they can make good choices with little information or computation-enabling simple strategies to excel by exploiting the reliable patterns in the world to do some of the work. Heuristics are not good or bad, "biased" or "unbiased," on their own, but only in relation to the setting in which they are used. The authors show heuristics and environments fitting together to produce good decisions in domains including sports competitions, the search for a parking space, business group meetings, and doctor/patient interactions. The message of Ecological Rationality is to study mind and environment in tandem. Intelligence is not only in the mind but also in the world, captured in the structures of information inherent in our physical, biological, social, and cultural surroundings.
Büchel F., Glück J., Hoffrage U., Stant P. & Wirth J. (Eds.) (2002). Fremdenfeindlichkeit und Rechtsextremismus : Dokumentation einer multidisziplinären Vortragsreihe. Leske und Budrich, Leverkusen.
Gigerenzer G., Todd P. M. & the ABC Research Group (Eds.) (1999). Simple heuristics that make us smart. Oxford University Press, New York.
Parties de livre Hoffrage U. (2007). Hindsight Bias. In R. F., Baumeister & K. D., Vohs (Eds.), Encyclopedia of social psychology (pp. 430-431). Sage, Thousand Oaks, CA. [doi]
Hoffrage U. & Vitouch O. (2007). Evolutionäre Psychologie des Denkens und Problemlösens [Evolutionary psychology of thinking and problem solving]. In Müsseler J. (Ed.), Allgemeine Psychologie (pp. 630-679). Spektrum Akademischer Verlag, Heidelberg.
Hoffrage U. & Hertwig R. (2006). Which world should be represented in representative design?. In Fiedler K. & Juslin P. (Eds.), Information sampling and adaptive cognition (pp. 381-408). Cambridge University Press, Cambridge.
Wassner C. & Hoffrage U. (2006). Irren ist wahrscheinlich: praktische Anwendungsbeispiele zur besseren Vermittlung von Wahrscheinlichkeiten. In Meyer J. (Ed.), Anregungen zum Stochastikunterricht (Vol. 3, pp. 78-85). Franz Beck, Hildesheim.
Hoffrage U. (2005). Heuristics: fast and frugal. In Everitt B. C. & Howell D. C. (Eds.), Encyclopedia of Statistics in Behavioral Science (Vol. 2, pp. 795-799). Wiley, Chichester, UK.
Hoffrage U., Hertwig R. & Gigerenzer G. (2005). Die ökologische Rationalität einfacher Entscheidungs- und Urteilsheuristiken [The ecological rationality of simple decision and judgment heuristics]. Rationalität im Prozess kultureller Evolution: Rationalitätsunterstellungen als eine Bedingung der Möglichkeit substantieller Rationalität des Handelns (pp. 65-89). Tübingen, Deutschland: Mohr Siebeck.
Hoffrage U., Kurzenhäuser S. & Gigerenzer G. (2005). Understanding the results of medical tests: why the representation of statistical information matters. In Bibace R., Laird J. D., Noller K. L. & Valsiner J. (Eds.), Science and medicine in dialogue: thinking through particulars and universals (pp. 83-98). Praeger Publishers, Westport.
Schlegelberger B. & Hoffrage U. (2005). Implikationen der genetischen Beratung bei Hochrisiko-Familien für erblichen Brust- und Eierstockkrebs. In Gerhardus M. A., Schleberger H., Schlegelberger B. & Schwarz F. K. (Eds.), BRCA - Erblicher Brust- und Eierstockkrebs: Beratung, Testverfahren, Kosten (pp. 33-58). Springer Verlag, Berlin.
Todd P. M., Hertwig R. & Hoffrage U. (2005). Evolutionary cognitive psychology. In Buss D. M. (Ed.), The handbook of evolutionary psychology (pp. 776-802). Wiley, 111 River Street, Hoboken, NJ 07030-5774. [url]
Hoffrage U. (2004). Overconfidence. In Pohl R.F. (Ed.), Cognitive illusions: Fallacies and biases in thinking, judgement, and memory (pp. 235-254). Hove, UK. Psychology Press.
Hoffrage U. & Gigerenzer G (2004). How to improve the diagnostic inferences of medical experts. In Kurz-Milcke E. & Gigerenzer G. (Eds.), Experts in science and society (pp. 249-268). Kluwer Academic/Plenum Publishers, New York.
Kurz-Milcke E. M., Gigerenzer G. & Hoffrage U (2004). Representations of uncertainty and change: Three case studies with experts. In Smith K., Johnson P. & Shanteau J. (Eds.), Psychological investigations of competence in decision making (pp. 188-225). Cambridge University Press, Cambridge, U.K.
Hertwig R. & Hoffrage U. (2002). Technology needs psychology : how natural frequencies foster insight in medical and legal experts. In Sedlmeier P. & Betsch T. (Eds.), Etc.: frequency processing and cognition (pp. 285-302). Oxford University Press, Oxford.
Hoffrage U. & Vitouch O. (2002). Evolutionspsychologie des Denkens und Problemlösens. In Müsseler J. & Prinz W. (Eds.), Allgemeine Psychologie (pp. 734-794). Spektrum Akademischer Verlag, Heidelberg.
Sadrieh A., Güth W., Hammerstein P., Harnad S., Hoffrage U., Kuon B. et al. (2001). Is there evidence for an adaptive toolbox ?. In Gigerenzer G. & Selten R. (Eds.), Bounded rationality : the adaptive toolbox (pp. 83-102). MIT University Press, Cambridge.
Hertwig R., Hoffrage U. & Martignon L. (1999). Quick estimation : letting the environment do the work. In Gigerenzer G., Todd P. M. & the ABC Research Group (Eds.), Simple heuristics that make us smart (pp. 209-234). Oxford University Press, New York.
Hoffrage U. & Hertwig R. (1999). Hindsight bias : a price worth paying for fast and frugal memory. In Gigerenzer G., Todd P. M. & the ABC Research Group (Eds.), Simple heuristics that make us smart (pp. 191-208). Oxford University Press.
Krauss S., Martignon L. & Hoffrage U. (1999). Simplifying Bayesian inference : the general case. In Magnani L., Nersessian N. J. & Thagard P. (Eds.), Model-based reasoning in scientific discovery (pp. 165-179). Kluwer Academic / Plenum Publishers.
Martignon L. & Hoffrage U. (1999). Why does one-reason decision making work ? A case study in ecological rationality. In Gigerenzer G., Todd P. M. & the ABC Research Group (Eds.), Simple heuristics that make us smart (pp. 119–140). Oxford University Press, New York.
Rieskamp J. & Hoffrage U. (1999). When do people use simple heuristics, and how can we tell. In Gigerenzer G., Todd P. M. & the ABC Research Group (Eds.), Simple heuristics that make us smart (pp. 141-167). Oxford University Press.
Hoffrage U. (1993). Die Illusion der Sicherheit bei Entscheidungen unter Unsicherheit. [The illusion of certainty in decisions under uncertainty]. In Hell W., Fiedler K. & Gigerenzer G. (Eds.), Kognitive Täuschungen (pp. 73-97). Spektrum Akademischer Verlag.
Chapitre Hoffrage U. (in press). Overconfidence. In Pohl R. F. (Ed.), Cognitive illusions: Intriguing phenomena in thinking, judgement, and memory. Psychology Press, Hove, UK. [abstract]
Overconfidence occurs if our confidences related to our judgments, inferences, or predictions are too high when compared to the corresponding accuracy. For the current review, I commence with (1) a brief overview of the three most frequently used tasks and measures, then (2) present classroom demonstrations, (3) summarize some major findings, (4) introduce and evaluate models and theoretical accounts, (5) discuss the functional value of overconfidence, (6) briefly mention its relevance in applied settings, and (7) conclude with some final remarks, a summary, and a list of further literature.
Berg N., Abramczuk K. & Hoffrage U. (2013). Fast acceptance by common experience: Augmenting schelling's neighborhood segregation model with FACE-recognition. In R. Hertwig, U. Hoffrage & the ABC Research Group (Eds.), Simple heuristics in a social world (pp. 225-257). Oxford University Press, New York, NY. [doi] [url] [abstract]
Schelling (1969, 1971a,b, 1978) observed that macro-level patterns do not necessarily reflect micro-level intentions, desires or goals. In his classic model on neighborhood segregation, which initiated a large and influential literature, individuals with no desire to be segregated from those who belong to other social groups, nevertheless, wind up clustering with their own type. Most extensions of Schelling's model have replicated this result. There is an important mismatch, however, between theory and observation that has received relatively little attention. Whereas Schelling-inspired models typically predict large degrees of segregation starting from virtually any initial condition, the empirical literature documents considerable heterogeneity in measured levels of segregation. This chapter introduces a mechanism that can produce significantly higher levels of integration and, therefore, brings predicted distributions of segregation more in line with real-world observation. As in the classic Schelling model, agents in a simulated world want to stay or move to a new location depending on the proportion of neighbors they judge to be acceptable. In contrast to the classic model, however, agents' classifications of their neighbors as acceptable or not depend lexicographically on recognition first and group type (e.g., ethnic stereotyping) second. The FACE-recognition model nests classic Schelling: when agents have no recognition memory, judgments about the acceptability of a prospective neighbor rely solely on his or her group type (as in the Schelling model). A very small amount of recognition memory eventually leads to different classifications that, in turn, produce dramatic macro-level effects resulting in significantly higher levels of integration. A novel implication of the FACE-recognition model concerns the large potential impact of policy interventions that generate modest numbers of face-to-face encounters with members of other social groups. The model describes a new co-evolutionary process in which individual-level classifications of others and the macro-structure of the social environment jointly and substantively influence one another.
Hafenbrädl S., Hoffrage U. & White C.M. (2013). The impact of affect on willingness-to-pay and desired-set-size. In C. Pammi & N. Srinivasan (Eds.), Progress in Brain Research, Decision making: Neural and behavioural approaches, progress in brain research (Vol. 202, pp. 21-35). Elsevier, Amsterdam, Netherlands. [doi] [url] [web of science] [abstract]
What role does affect play in economic decision making? Previous research showed that the number of items had a linear effect on the willingness-to-pay for those items when participants were computationally primed, whereas participants' willingness-to-pay was insensitive to the amount when they were affectively primed. We extend this research by also studying the impact of affect on nonmonetary costs of waiting for items to be displayed and of screening them in a computer task. We assessed these costs by asking participants how many items they desired to see before making their selection. In our experiment, the effect of priming on desired-set-size was even larger than on willingness-to-pay, which can be explained by the fact that the nonmonetary costs, waiting time, were real, whereas willingness-to-pay was hypothetical. Participants also reported their satisfaction with the choosing process and the chosen items; no linear or nonlinear relationship was found between the self-determined desired-set-size and satisfaction.
Hertwig R. & Hoffrage U. (2013). Simple heuristics: The foundations of adaptive social behavior. In R. HertwU. ig, Hoffrage & the ABC Research Group (Eds.), Simple heuristics in a social world (pp. 3-36). Oxford University Press, New York. [doi] [url] [abstract]
This chapter shows how simple heuristics can be an essential tool for navigating the complexities and vagaries of social environments. The research program on the nature of social rationality presented here can be summarized by the following theses: As perceived by the human mind, the social world (Umwelt) is complex, but not necessarily more complex than the nonsocial world. However complex the social world may be, its complexity does not require cognitive complexity; rather, it entails conditions that make simple heuristics indispensible, such as intractability, multiple competing goals, and incommensurable reasons. Much of reasoning and decision making occurring in human and animal social environments can be modeled in terms of simple heuristics. Although simple heuristics forgo extensive information search and complex calculations, they can be as accurate and even more accurate than more complex strategies and/or can be used to reach other goals that are valued in social environments (e.g., transparency, fairness, speed). Heuristics can be simultaneously successful and simple by coopting evolved capacities. The capacities themselves can represent complex adaptive specializations (e.g., memory, movement tracking). Simple heuristics per se are neither rational nor irrational. Their rationality is ecological. That is, their performance depends on the match between the architecture of the heuristic and the structure of the environment in which it is used. The heuristics' simplicity inoculates them against overfitting and enables them to achieve robust performance given small samples of information. Simple heuristics can model adaptive decision making both in games against nature and in social games. There is no social intelligence distinct from nonsocial intelligence. Simple heuristics are tools of moderate generalizability. Some can be used only in games against nature, whereas others are restricted to social games. Still other heuristics can be applied in both types of games. Shedding light on the adaptive toolbox of simple heuristics used to navigate social environments, and characterizing their strengths and weaknesses, can help us design environments and/or heuristics in ways that improve public welfare.
Reimer T. & Hoffrage U. (2013). Simple heuristics and information sharing in groups. In R. Hertwig, U. Hoffrage & the ABC Research Group (Eds.), Simple heuristics in a social world (pp. 319-342). Oxford University Press, New York, NY. [doi] [url] [abstract]
In today's world of business and politics, collaboration is a common and valued practice. A group's potential to outperform individual decision makers is especially apparent if the knowledge of the members of a team or committee is distributed such that each member typically favors an inferior option at the outset. This biased information distribution is called a hidden profile because the full information about the options (i.e., their profile) is initially hidden from every individual group member. Previous research indicated that groups have difficulties mastering the challenge of communicating and integrating unique information held by single group members. As a consequence, groups are typically not able to decide in favor of the best option when its profile is hidden. The chapter summarizes the results of simulation studies in which various decision strategies that a group may apply with respect to their ability to solve hidden-profile problems were compared. Specifically, the chapter describes the conditions under which compensatory strategies outperform simple heuristics, and vice versa. The chapter then reviews two experiments that focus on participants' performance as a function of how information is distributed within the group. Groups can solve hidden-profile problems if (a) group members enter discussions without preconceived opinions (naïve groups), and (b) information regarding the choice alternatives is presented in the form of common cues, which facilitates the application of a cue-based heuristic. The simulation studies and experiments support the notion of ecological rationality: The performance of strategies and of participants was affected by information structures of the environment, in particular, by the skewness of cue validities and by the distribution of cue values across group members.
Hertwig R., Hoffrage U. & Sparr R. (2012). How estimation can benefit from an imbalanced world. In P. M. Todd, G. Gigerenzer & the ABC Research Group (Eds.), Ecological rationality: Intelligence in the world (pp. 379-406). Oxford University Press, New York, NY. [doi] [url] [abstract]
This chapter analyzes how valuable the assumption of systematic environment imbalance is for performing rough-and-ready intuitive estimates, which people regularly do when inferring the quantitative value of an object (e.g., its frequency, size, value, or quality). The chapter outlines how systematic environment imbalance can be quantified using the framework of power laws. It investigates to what extent power-law characteristics and other statistical properties of real-world environments can be allies of two simple estimation heuristics, QuickEst and the mapping heuristic. The analyses, which involve comparing the estimation performances of the heuristics relative to more complex strategies, demonstrate that QuickEst could be particularly suited for deriving rough-and-ready estimates in skewed distributions with highly dispersed cue validities, whereas the mapping heuristic might be most suited when the cues have similar validities.
Kurzenhäuser S. & Hoffrage U. (2012). Designing risk communication in health. In P. M. Todd, G. Gigerenzer & the ABC Research Group (Eds.), Ecological rationality: Intelligence in the world (pp. 428-453). Oxford University Press, New York, NY. [doi] [url] [abstract]
This chapter explores how the representation of statistical information affects the understanding of risks and uncertainties in medical contexts. Using mammography screening as a prime example, it is shown that problems in understanding and dealing with numbers are often due to poorly designed information environments, rather than to internal deficiencies of the human mind. For three types of statistical information that physicians and patients often encounter-conditional probabilities, single-event probabilities, and relative risks-a representation is proposed that facilitates understanding. These are compared to the representations actually used in published materials about mammography screening. Factors in the environment that can contribute to innumeracy are identified and the question of why risks are not always communicated in a transparent manner is addressed. Finally, recommendations are formulated for changes, in both the information environment and the institutional and legal environments, that could help foster statistical thinking and informed decisions about medical screening.
Reimer T. & Hoffrage U. (2012). Ecological rationality for teams and committees: Heuristics in group decision making. In P.M. Todd, G. Gigerenzer & the ABC Research Group (Eds.), Ecological rationality: Intelligence in the world (pp. 335-359). Oxford University Press, New York, NY. [doi] [url] [abstract]
This chapter applies the concept of ecological rationality to the context of groups and teams. A summary of agent-based computer simulations is provided in which groups integrated member opinions on the basis of a majority rule. The simulations demonstrate that the performance of a group may be strongly affected by the decision strategies used by its individual members, and specify how this effect is moderated by environmental features. Group performance strongly depended on the distribution of cue validities. When validities were linearly distributed, groups using a compensatory strategy achieved the highest accuracy. Conversely, when cue validities followed a J-shaped distribution, groups using a simple noncompensatory heuristic performed best. While these effects were robust across different quantities of shared information, the validity of shared information exerted stronger effects on group performance. Consequences for prescriptive theories of group decision making are discussed.
Hoffrage U. (2011). How people can behave irresponsibly and unethically without noticing it. In G. Palazzo & M. Wentland (Eds.), Practising responsible management in the 21st century (pp. 173-182). Pearson Education, Paris. [url]
Hoffrage U. & Hertwig R. (2011). Simple heuristics in a complex social world. In J. I. Krueger (Ed.), Social Judgment and Decision Making (pp. 135-150). Psychology Press, Hove, UK.
de Treville S., Hoffrage U. & Petty J. S. (2009). Managerial decision making and lead times: The impact of cognitive illusions. In Reiner G. (Ed.), Rapid modelling for increasing competitiveness (pp. 3-14). London, UK: Springer. [doi] [web of science] [abstract]
In this paper, we consider the impact of cognitive illusions on decision making in the operations management field, in areas ranging from product and process development to project management. Psychologists have studied the effects of overconfidence, the planning fallacy, illusions of control, anchoring, confirmation bias, hindsight bias, and associative memory illusions on individual judgment, thinking, and memory in many experiments, but little research has focused on operations management implications of these biases and illusions. Drawing on these psychological findings we discuss several of these cognitive illusions and their impact on operations managers, plant workers, technicians and engineers alike in a variety of operational settings. As in other contexts, these cognitive illusions are quite robust in operations management, but fortunately the impact of selected illusions can be substantially reduced through debiasing techniques. The examples discussed in this paper highlight the need for more operations-management-based research on the impact of cognitive illusions on decision making.
Skubisz C., Reimer T. & Hoffrage U. (2009). Communicating quantitative risk information. In C. S. Beck (Ed.), Communication yearbook (Vol. 33, pp. 177-211). New York, NY: Routledge.
Gigerenzer G., Hertwig R., Hoffrage U. & Sedlmeier P. (2008). Cognitive illusions reconsidered. In C. R., Plott & V. L., Smith (Eds.), Handbook of experimental economics results (Vol. 1, pp. 1018-1034). North Holland/Elsevier Press, Amsterdam, Netherlands. [doi] [url]
Gigerenzer G., Martignon L., Hoffrage U., Rieskamp J., Czerlinski J. & Goldstein D. (2008). One-reason decision making. In C. R. Plott & V. L. Smith (Eds.), Handbook of experimental economics results (Vol. 1, pp. 1004-1017). North Holland/Elsevier Press, Amsterdam, Netherlands. [doi] [url]
Hoffrage U. (2006). Evolutionäre Ansätze. In Frensch P. & Funke J. (Eds.), Handbuch der Psychologie: Kognition (pp. 400-405). Hogrefe, Göttingen.
Actes de conférence (partie) Woike J., Hoffrage U. & Hertwig R. (2012). Estimating quantities: Comparing simple heuristics and machine learning algorithms. In Villa A., Duch W., Erdi P., Masulli F. & Palm G. (Eds.), Lecture Notes in Computer Science, Artificial Neural Networks and Machine Learning, ICANN 2012 - 22nd International Conference on Artificial Neural Networks, Lausanne, Switzerland, September 11-14, 2012, 7553 (pp. 483-490). Springer Verlag, Heidelberg. [doi] [abstract]
Estimating quantities is an important everyday task. We analyzed the performance of various estimation strategies in ninety-nine real-world environments drawn from various domains. In an extensive simulation study, we compared two classes of strategies: one included machine learning algorithms such as general regression neural networks and classification and regression trees, the other two psychologically plausible and computationally much simpler heuristics (QEst and Zig-QEst). We report the strategies' ability to generalize from training sets to new data and explore the ecological rationality of their use; that is, how well they perform as a function of the statistical structure of the environment. While the machine learning algorithms outperform the heuristics when fitting data, Zig-QEst is competitive when making predictions out-of-sample.
Hafenbrädl S., Hoffrage U. & White C. M. (2008). Choosing how many options to choose from: does it depend on affective priming?. Advances in Consumer Research, vol. XXXVI.
de Treville S., Hoffrage U. & Petty J.S. (2006). Cognitive illusions in operations management. Proceedings of the 2006 Annual Meeting of the Academy of Management (pp. 17).
White C. M. & Hoffrage U. (2006). Introducing the Two-Stage, Two-Threshold model of choice deferral. Proceedings of the IAREP/SABE Congress on Behavioural Economics and Economic Psychology, July 5th-8th, 2006, Paris, France.
Berg N. & Hoffrage U. (2005). Environmental determinants of simple decision rules: no cognitive limitations needed. In Opwis K. & Perner I.-K. (Eds.), Proceedings of KogWis05 : the German Cognitive Science Conference 2005 (pp. 83-88). Schwabe Verlag, Basel.
Hoffrage U., Garcia-Retamero R. & Czienskowski U. (2005). The robustness of the Take The Best Configural Heuristic in linearly and nonlinearly separable environments. In Opwis K. & Perner I.-K. (Eds.), Proceedings of KogWis05. The German Cognitive Science Conference 2005 (pp. 83-88). Schwabe Verlag, Basel.
Hoffrage U., Garcia-Retamero R. & Czienskowski U. (2005). The robustness of the Take The Best Configural Heuristic in linearly and nonlinearly separable environments. In Bara B. G., Barsalou L. & Bucciarelli M. (Eds.), Proceedings of the CogSci2005 : XXVII Annual Conference of the Cognitive Science Society (pp. 971-976).
Hoffrage U., Hertwig R. & Fanselow C. (2003). Modeling the hindsight bias. In Detje F., Dörner D. & Schaub H. (Eds.), The logic of cognitive systems. Proceedings of the Fifth International Conference on Cognitive Modeling (pp. 259-260). Unveristät Bamberg, Bamberg.
Reimer T. & Hoffrage U. (2003). Information aggregation in groups : the approach of simple group heuristics (SIGH). In Alterman R. & Kirsch D. (Eds.), Proceedings of the Twenty-Fifth Annual Conference of the Cognitive Science Society. Erlbaum, Mahwah.
Hoffrage U. & Gigerenzer G. (1996). The impact of information representation on Bayesian reasoning. In Cottrell G. (Ed.), Proceedings of the 18th Annual Conference of the Cognitive Science Society (pp. 126-130). Lawrence Erlbaum, Mahwah.
Abstract Garcia-Retamero R., Maldonado A., Catena A., Hoffrage U., Herrera A. & Candido A. (2005). Causal beliefs and the outcome submaximality effect in cue competition in a decision making task [Abstract]. . The 20th bi-annual conference on Subjective Probability Utility and Decision Making (SPUDM20).
Rapports Hoffrage U., Gerhardus A., Christ M., Gadzicki D., Haverkamp A., Krauth C. et al. (2004). Die molekulargenetische Diagnostik des erblichen Brust- und Eierstockkrebs - BRCA: Beratungsprozesse - Testverfahren - Kosten. Ein Health Technology Assessment für den Bundesverband der AOK. Medizinische Hochschule Hannover.
Cahiers de recherche Reisen N., Kruthoff J.-P. & Hoffrage U. (2005). Deciding intuitively? Book review of "The power of intuition" by G. Klein (2004). University of Lausanne, Switzerland.
Thèses Hafenbrädl S., HOFFRAGE, U. (Dir.) (2013). Ethics, expectations and escalation : perspectives on managerial decision making. Université de Lausanne, Faculté des hautes études commerciales.
Non publié Hoffrage U., Martignon L., Krauss S. & Gigerenzer G. (2008). Bayesian reasoning and natural frequencies: Generalization to complex situations. Working paper.
Hafenbrädl S., White C. M. & Hoffrage U. (2007). Choosing how many options to choose from: Does it depend on affective priming?. Working paper.