Judgment under Uncertainty

By Camille Morvan, W. J. Jenkins. 2017

551 citations recorded by the source corpus.

Subfields: General Decision Sciences, Management Science and Operations Research

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Citations in the corpus

Manipulating and Measuring Model Interpretability (2018, background): “Second, when past predictions are visible, they might exert an anchoring effect [26] on subsequent predictions, swaying new predictions in the direction of the past predictions.”
The future of employment: How susceptible are jobs to computerisation? (2017, background): “Humans, in contrast, must fulfill a range of tasks unrelated to their occupation, such as sleeping, necessitating occasional sacrifices in their occupational performance (Kahneman et al., 1982).”
The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good (2016, background): “The history of human decision-making – particularly when it comes to questions of power in resource allocation, fairness, justice, and other public goods – is wrought with innumerable examples of extreme bias, leading towards corrupt, inefficient or unjust processes and outcomes [2, 34, 70, 87].”
Determinants of individual investment decisions in investment-based crowdfunding (2018, unknown): “Heuristics influence investment choices of individuals (Agnew, 2006; Benartzi, 2001) but can also lie at the origin of biases (Tversky & Kahneman, 1974).”
Leader corruption depends on power and testosterone (2015, background): “Although not a social norm, presenting this option as the “default” engenders a norm of sorts that can be thought of as an anchor point (Tversky & Kahneman, 1974); thus, to the extent that individuals decide something different from this anchor point by invoking the antisocial decision as a…”
Divergence between individual perceptions and objective indicators of tail risks: Evidence from floodplain residents in New York City (2015, unknown): “This behaviour can be explained by an availability bias as shown by Tversky and Kahneman (1973; 1974).2 For example, individuals who have recently experienced a flood may find it easier to imagine that a flood will occur again in the future and, therefore, have a higher perceived likelihood than…”
Preferences for Truth‐Telling (2016, methodology): “Our strategy to shift beliefs is based on an anchoring procedure (Tversky and Kahneman 1974): we ask subjects to think about the behavior of hypothetical participants in the F_LOW experiment and we anchor them to think about participants who reported the high state more or less often.”
When should the Ask be a Nudge? The Effect of Default Amounts on Charitable Donations (2016, unknown): “Anchoring has been shown to impact decisions in many contexts (Ariely, Loewenstein, and Prelec, 2003; Epley and Gilovich, 2006; Tversky and Kahneman, 1974), by”
Anthropomorphism as Cognitive Bias (2017, background): “Intuitive anthropomorphic bias is one kind of cognitive bias that results from reasoning heuristics applied in our unconscious (e.g., Tversky and Kahneman 1974).”
Big Data Research in Information Systems: Toward an Inclusive Research Agenda (2016, background): “For instance, behavioral economics is a well-established area (Tversky & Kahneman, 1974).”
Confronting Abusive Language Online: A Survey from the Ethical and Human Rights Perspective (2020, background): “Tversky and Kahneman (1974) were the first psychologists that showed how humans employ heuristics to make judgements under uncertainty.”
Response to Travel Information: A Behavioural Review (2015, background): “Tversky and Kahneman (1974) asked subjects to estimate the number of African member states in the United Nations while the subjects were given the winning number derived from a spinning roulette.”
Understanding Agency Problems in Headquarters-Subsidiary Relationships in Multinational Corporations: A Contextualized Model (2018, background): “…bounded rationality as consisting of three dimensions: (a) limited information-processing capacities (e.g., Simon, 1957), (b) cognitive economizing (i.e., reliance on mental shortcuts and heuristics; e.g., Simon, 1990), and (c) cognitive biases and errors (e.g., Tversky & Kahneman, 1974).”
Moving Opportunism to the Back Seat: Bounded Rationality, Costly Conflict, and Hierarchical Forms (2016, background): “Although heuristics generally assist decision making, they can also lead to large systematic errors in judgment (Tversky & Kahneman, 1974).”
On doing better science: From thrill of discovery to policy implications (2017, background): “The key issue here has to do with measurement (Wright, 2016); human judgment, even expert judgment is fallible (Dawes, Faust, & Meehl, 1989) and processes information in expectancy-based ways (Fiske, 1995; Tversky & Kahneman, 1974) 5 .”
Heuristics: Tools for an Uncertain World (2015, methodology): “Despite general acknowledgments that heuristics are “quite useful” (Tversky & Kahneman, 1974, p. 1124) and “highly economical and usually effective” (p. 1131), those benefits are typically qualified by emphasizing that heuristics “lead to severe and systematic errors” (p. 1124).”