The Black Swan: The Impact of the Highly Improbable

By S. Hannabuss. 2008

486 citations recorded by the source corpus.

Subfields: Literature and Literary Theory, Renewable Energy, Sustainability and the Environment, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/55a6cc83883f11de3bbdbedd28161011b04bfee0

How researchers see this paper

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

In Literature and Literary Theory

1. Michael J. Hume
2. Paola Annoni
3. David J. Teece
4. Andrea Saltelli
5. Bent Flyvbjerg
6. A. Sentance

In Renewable Energy, Sustainability and the Environment

1. Michael J. Hume
2. Paola Annoni
3. David J. Teece
4. Andrea Saltelli
5. Robert E Kopp
6. Gernot Wagner
7. Bent Flyvbjerg
8. A. Sentance

In Strategy and Management

1. Jiacan Yuan
2. R. Shwom
3. Elena Katok
4. John H. Kagel
5. Ido Erev
6. Michael J. Hume
7. Paola Annoni
8. Ernan Haruvy

Citations in the corpus

• Predictive Analytics in Information Systems Research (2011, unknown): “Knowledge of predictability (or unpredictability) is a fundamental component of scientific knowledge (see Mak-ridakis et al. 2009; Makridakis and Taleb 2009; Taleb 2007).”
• Prediction (2010, unknown): “The concept of dragon-kings has been introduced as a frontal refutal to the claim that “black swans” characterize the dynamics of most systems [155].”
• A capability theory of the firm: an economics and (Strategic) management perspective (2019, background): “Major unexpected shocks, dubbed ‘Black Swan events’ by financial theorist Nicholas Taleb (2007), occur ‘outside the model’.”
• Sixth International Conference on Sensitivity Analysis of Model Output How to avoid a perfunctory sensitivity analysis (2010, methodology): “This crisis is popularized today by Nassim Nicholas Taleb (Taleb 2007) in Economics, and Orrin H. Pilkey and Linda Pilkey Jarvis in Environmental Sciences (Pilkey and Pilkey Jarvis 2007).”
• Tipping elements and climate–economic shocks: Pathways toward integrated assessment (2016, background): “It is also important to keep in mind that one effect of a state shift may be to change the temporal and spatial correlations between extreme events, making once-rare “black swan” [Taleb, 2007] alignments of extremes much more likely.”
• Learning and the Economics of Small Decisions (2013, background): “Terkel (1996) shows that young rats learn to skin pine cones by observing their mothers.”
• The global credit boom: Challenges for macroeconomics and policy (2009, background): “Popular nancial market writers, such as Taleb (2004, 2007) and Soros (2008), have endorsed views of investor irrationality that are compatible with the existence of nancial cycles of the sort described by the Behavioural School.”
• Sensor Mania! The Internet of Things, Wearable Computing, Objective Metrics, and the Quantified Self 2.0 (2012, unknown): “There is an opportunity to make better tools (particularly since humans are more disposed to think in terms of story narratives than statistics as The Black Swan and other resources have noted [36]), and also to educate and set expectations about the salience and immediate utility of big streams of ”
• Rethinking financial contagion: Information transmission mechanism during the COVID-19 pandemic (2020, unknown): “The black swan metaphor has been widely used in finance literature beginning with Taleb (2007) who claims that the event can be considered as a black swan if it simultaneously has the three following attributes: (i) it is an outlier, i.e. it lies outside the realm of regular expectations, because…”