George Wright

Bio: George Wright is an academic researcher from University of Strathclyde. The author has contributed to research in topics: Scenario planning & Delphi method. The author has an hindex of 45, co-authored 155 publications receiving 10890 citations. Previous affiliations of George Wright include Durham University & University of Leeds.

Decision Analysis for Management Judgment

Abstract: In an increasingly complex world, decision analysis has a major role to play in helping decision-makers to gain insights into the problems they face. Decision Analysis for Management Judgment is unique in its breadth of coverage of decision analysis methods. It covers both the psychological problems that are associated with unaided managerial decision making and the decision analysis methods designed to overcome them. It is presented and explained in a clear, straightforward manner without using mathematical notation. The fourth edition has been fully revised and updated and includes a number of changes to reflect the latest developments in the field.

Expert Opinions in Forecasting: The Role of the Delphi Technique

Abstract: Expert opinion is often necessary in forecasting tasks because of a lack of appropriate or available information for using statistical procedures. But how does one get the best forecast from experts? One solution is to use a structured group technique, such as Delphi, for eliciting and combining expert judgments. In using the Delphi technique, one controls the exchange of information between anonymous panelists over a number of rounds (iterations), taking the average of the estimates on the final round as the group judgment. A number of principles are developed here to indicate how to conduct structured groups to obtain good expert judgments. These principles, applied to the conduct of Delphi groups, indicate how many and what type of experts to use (five to 20 experts with disparate domain knowledge); how many rounds to use (generally two or three); what type of feedback to employ (average estimates plus justifications from each expert); how to summarize the final forecast (weight all experts’ estimates equally); how to word questions (in a balanced way with succinct definitions free of emotive terms and irrelevant information); and what response modes to use (frequencies rather than probabilities or odds, with coherence checks when feasible). Delphi groups are substantially more accurate than individual experts and traditional groups and somewhat more accurate than statistical groups (which are made up of noninteracting individuals whose judgments are aggregated). Studies support the advantage of Delphi groups over traditional groups by five to one with one tie, and their advantage over statistical groups by 12 to two with two ties. We anticipate that by following these principles, forecasters may be able to use structured groups to harness effectively expert opinion.

The next generation of scenarios for climate change research and assessment

Abstract: Advances in the science and observation of climate change are providing a clearer understanding of the inherent variability of Earth's climate system and its likely response to human and natural influences. The implications of climate change for the environment and society will depend not only on the response of the Earth system to changes in radiative forcings, but also on how humankind responds through changes in technology, economies, lifestyle and policy. Extensive uncertainties exist in future forcings of and responses to climate change, necessitating the use of scenarios of the future to explore the potential consequences of different response options. To date, such scenarios have not adequately examined crucial possibilities, such as climate change mitigation and adaptation, and have relied on research processes that slowed the exchange of information among physical, biological and social scientists. Here we describe a new process for creating plausible scenarios to investigate some of the most challenging and important questions about climate change confronting the global community.

Social Media and Fake News in the 2016 Election

Abstract: Following the 2016 U.S. presidential election, many have expressed concern about the effects of false stories (“fake news”), circulated largely through social media. We discuss the economics of fake news and present new data on its consumption prior to the election. Drawing on web browsing data, archives of fact-checking websites, and results from a new online survey, we find: (i) social media was an important but not dominant source of election news, with 14 percent of Americans calling social media their “most important” source; (ii) of the known false news stories that appeared in the three months before the election, those favoring Trump were shared a total of 30 million times on Facebook, while those favoring Clinton were shared 8 million times; (iii) the average American adult saw on the order of one or perhaps several fake news stories in the months around the election, with just over half of those who recalled seeing them believing them; and (iv) people are much more likely to believe stories that favor their preferred candidate, especially if they have ideologically segregated social media networks.

Heuristics and Biases: The Psychology of Intuitive Judgment

Abstract: A review is presented of the book “Heuristics and Biases: The Psychology of Intuitive Judgment,” edited by Thomas Gilovich, Dale Griffin, and Daniel Kahneman.

Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment.

Abstract: Perhaps the simplest and the most basic qualitative law of probability is the conjunction rule: The probability of a conjunction, P (A&B) cannot exceed the probabilities of its constituents, P (A) and P (B), because the extension (or the possibility set) of the conjunction is included in the extension of its constituents. Judgments under uncertainty, however, are often mediated by intuitive heuristics that are not bound by the conjunction rule. A conjunction can be more representative than one of its constituents, and instances of a specific category can be easier to imagine or to retrieve than instances of a more inclusive category. The representativeness and availability heuristics therefore can make a conjunction appear more probable than one of its constituents. This phenomenon is demonstrated in a variety of contexts including estimation of word frequency, personality judgment, medical prognosis, decision under risk, suspicion of criminal acts, and political forecasting. Systematic violations of the conjunction rule are observed in judgments of lay people and of experts in both between-subjects and within-subjects comparisons. Alternative interpretations of the conjunction fallacy are discussed and attempts to combat it are explored.