Heuristics and Biases: The Calibration of Expert Judgment: Heuristics and Biases Beyond the Laboratory

By Derek J. Koehler, Lyle A. Brenner, Dale W. Griffin. 2002

142 citations recorded by the source corpus.

Subfields: Artificial Intelligence, General Decision Sciences, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/cf6da46b565829ddddb2691929c302699744becf

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Colin Mason
2. Donald B. Smith
3. Dean A. Shepherd
4. Dale W. Griffin
5. Richard T. Harrison

In General Decision Sciences

1. Mathew L. A. Hayward
2. Dean A. Shepherd
3. Dale W. Griffin
4. Daniel Kahneman
5. G. Pallier

In Management Science and Operations Research

1. Colin Mason
2. Mathew L. A. Hayward
3. Dean A. Shepherd
4. Dale W. Griffin

Citations in the corpus

• A Hubris Theory of Entrepreneurship (2006, background): “For example, when environments are marked by high base rates of success and highly diagnostic and unambiguous evidence, judges are typically underconfident in their predictions (Lichtenstein et al. 1982, Koehler et al. 2002).”
• Heuristics, learning and the business angel investment decision-making process (2015, background): “…high level of domain specific expertise, such as the angel investment decision process, that may or may not be overridden by deliberate judgements (Gilovich et al. 2002, 4–5; Dawes et al. 2002; De Bondt and Thaler 2002; Fischhoff 2002; Henrion and Fischhoff 2002; Koehler et al. 2002; Tetlock 2002).”