From <i>Risk, Uncertainty, and Profit</i>

Knight, Frank H.

doi:10.1017/cbo9780511817410.005

Cited by 3,792 publications

(4,956 citation statements)

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“…Both kinds of decisions can be understood as opposite entries on a continuum of uncertainty about what one is choosing between. In Knight (1921) time-honored terminology, decisions from description involve a priori probabilities (based, for instance, on transparent random mechanisms such as a fair die), whereas decisions from experience involve statistical probabilities; the latter must be gauged, if possible, from experience.…”

Section: The Description-experience Gapmentioning

confidence: 99%

How choice ecology influences search in decisions from experience

2012

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a b s t r a c tResearch into human decision-making has often sidestepped the question of search despite its importance across a wide range of domains such as search for food, mates, allies, visual targets or information. Recently, research on decisions from experience has made progress in finding out how individual characteristics shape search for information. Surprisingly little is known, however, about how the properties of the choice ecology shape people's search. To fill this void, we analyzed how two key ecological properties influence search effort: domain of choice (gains vs. losses) and experienced variance (variance vs. no variance). Many people search longer when facing the prospect of losses relative to gains. Moreover, most people search more in options in which they experience variance relative to options they experience as invariant. We conclude that two factors that have been identified as important determinants of choice also influence search of information.Ó 2012 Elsevier B.V. All rights reserved. IntroductionFor Herbert Simon, one of the most influential economists and cognitive scientists of the second half of the 20th century, search was perhaps the key cognitive process of human life. For instance, in his work with Allen Newell, he conceptualized problem-solving as search for a path through a problem space with the goal of finding a route linking the problem's initial state to the goal state via intermediate steps and subgoals (Newell & Simon, 1972). Search also figures prominently in his notion of ''satisficing'' (Simon, 1956(Simon, , 1990. Satisficing is a method one can recruit when choosing from a set of alternatives (e.g., job candidates, mates) that one encounters sequentially and when little is known about the possible alternatives further down the road. Satisficing means that the decision maker sets an aspiration level and terminates sequential search for alternatives as soon as one is found whose value exceeds the aspiration level. Finally, in a grand metaphor of human life, Simon (1996) depicted our existence as search through a ''life's maze'' (p. 166), representing a multiplicity of needs and wants, and the need to ''survive without drawing upon superhuman powers of intelligence and computation'' (p. 175).Notwithstanding the importance of search as a behavioral and cognitive process across a wide range of domains-foraging for food, visual search for targets, memory search in recall and recognition tasks, the search for information on the web, and the search for mates in social environments (Todd, Hills, & Robbins, 2012)-research on behavioral decision-making (e.g., research on inductive and logical reasoning) and cognition (e.g., research on moral reasoning) has often sidestepped questions of search by using tasks in which summary information is conveniently displayed before the respondents. Past research on risky choice exemplifies this methodological proclivity. Decision researchers, using choice between monetary 0010-0277/$ -see front matter Ó

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Section: The Description-experience Gapmentioning

confidence: 99%

How choice ecology influences search in decisions from experience

2012

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“…As early as 1921, Franck Knight paved the way for an essential debate on uncertainty, how it can be defined, and the extent to which it should be taken into account at either microeconomic or macroeconomic levels of economic analysis. Knight [10] placed particular emphasis on the distinction between 'known risk', which may be measured, and 'true uncertainty', which is unlikely to be measured: ''Uncertainty must be taken in a sense radically distinct from the familiar notion of risk, from which it has never been properly separated. The essential fact is that 'risk' means in some cases a quantity susceptible of measurement''.…”

Section: From the Knightian To The Bayesian Uncertaintymentioning

confidence: 99%

Towards a New Framework for Addressing Structural Uncertainty in Health Technology Assessment Guidelines

Ghabri¹,

Cleemput

Josselin

2017

PharmacoEconomics

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International audienceProviding scientific advice and recommendations for public decision making entails identifying, selecting and weighing evidence derived from multiple sources of information through a systematic approach, while taking into account ethical, cultural and societal factors. Integrated in the evaluation process are exchanges between regulatory agencies, private firms, scientific experts and government representatives. In the case of drugs and medical devices, health technology assessment (HTA) agencies are increasingly commissioned to evaluate innovations in order to provide government with recommendations and advice on reimbursement and/or pricing. To undertake this task, HTA agencies [1–6] in Europe and elsewhere have developed methodological guidelines on the economic evaluation of health technologies [7]. One component of these guidelines deals with ways for both manufacturers (pharmaceutical and medical device firms) and HTA agencies evaluators (modelers, economists and public health experts) to address uncertainty. Several types of uncertainty have indeed been identified in HTA: methodological, parameter and structural uncertainty. Most guidelines describe quite well how to deal with the first two categories, although there is still room for improvement. However, recommendations about how to tackle structural uncertainty remain largely elusive. HTA agencies and decision makers may thus be exposed to oversimplifying assessments and recommendations by putting aside complex forms of uncertainty such as struc-tural ‘deep’ uncertainty [8]. The editorial is not intended to promote new approaches to exploring structural uncertainty, rather to emphasizeconcerns related to the topic, such as definition and analysis. Our aim is therefore to highlight the need to renew the analytical framework guidance for HTA

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“…In his definition, Cantillon (1758) [19] introduced the notion of risk and adaptation to the market. Knight (1921) [20], in his definition of 'entrepreneurship', not only emphasised the risk and uncertainty factors, but also added that being an entrepreneur meant being able to take action in the face of unknown future events. For Drucker (1985) [21], the 'risk' factor exists only for the so-called entrepreneurs who have no knowledge about what they are doing.…”

Section: Entrepreneurship and Riskmentioning

confidence: 99%

“…On that basis and at this stage of our reflection, it is legitimate to wonder if: (a) entrepreneurs in French Overseas Departments doing business in the tourism industry are able to take action in the face of unknown future events [20]; (b) if the risks they are facing are due to the fact they have adopted an unsuitable strategy [21]. Indeed, Dehoorne, Saffache and Augier (2007) [33] explained that the biggest islands of the Caribbean have opted for a mass tourism strategy and the smallest islands for luxury tourism.…”

Section: Counter Argument: Haitimentioning

confidence: 99%