Showing papers on "Recognition heuristic published in 2017"

Heuristics are Tools for Uncertainty

Abstract: Heuristics are commonly viewed in behavioral economics as inferior strategies resulting from agents’ cognitive limitations. Uncertainty is generally reduced to a form of risk, quantifiable in some probabilistic format. We challenge both conceptualizations and connect heuristics and uncertainty in a functional way: When uncertainty does not lend itself to risk calculations, heuristics can fare better than complex, optimization-based strategies if they satisfy the criteria for being ecological rational. This insight emerges from merging Knightian uncertainty with the study of fast-and-frugal heuristics. For many decision theorists, uncertainty is an undesirable characteristic of a situation, yet in the world of business it is considered a necessary condition for profit. In this article, we argue for complementing the study of decision making under risk using probability theory with a systematic study of decision making under uncertainty using formal models of heuristics. In doing so, we can better understand decision making in the real world and why and when simple heuristics are successful.

Linking process and measurement models of recognition-based decisions.

Abstract: When making inferences about pairs of objects, one of which is recognized and the other is not, the recognition heuristic states that participants choose the recognized object in a noncompensatory way without considering any further knowledge. In contrast, information-integration theories such as parallel constraint satisfaction (PCS) assume that recognition is merely one of many cues that is integrated with further knowledge in a compensatory way. To test both process models against each other without manipulating recognition or further knowledge, we include response times into the r-model, a popular multinomial processing tree model for memory-based decisions. Essentially, this response-time-extended r-model allows to test a crucial prediction of PCS, namely, that the integration of recognition-congruent knowledge leads to faster decisions compared to the consideration of recognition only-even though more information is processed. In contrast, decisions due to recognition-heuristic use are predicted to be faster than decisions affected by any further knowledge. Using the classical German-cities example, simulations show that the novel measurement model discriminates between both process models based on choices, decision times, and recognition judgments only. In a reanalysis of 29 data sets including more than 400,000 individual trials, noncompensatory choices of the recognized option were estimated to be slower than choices due to recognition-congruent knowledge. This corroborates the parallel information-integration account of memory-based decisions, according to which decisions become faster when the coherence of the available information increases. (PsycINFO Database Record

"The Gaze Heuristic:" Biography of an Adaptively Rational Decision Process.

Abstract: This article is a case study that describes the natural and human history of the gaze heuristic. The gaze heuristic is an interception heuristic that utilizes a single input (deviation from a constant angle of approach) repeatedly as a task is performed. Its architecture, advantages, and limitations are described in detail. A history of the gaze heuristic is then presented. In natural history, the gaze heuristic is the only known technique used by predators to intercept prey. In human history the gaze heuristic was discovered accidentally by Royal Air Force (RAF) fighter command just prior to World War II. As it was never discovered by the Luftwaffe, the technique conferred a decisive advantage upon the RAF throughout the war. After the end of the war in America, German technology was combined with the British heuristic to create the Sidewinder AIM9 missile, the most successful autonomous weapon ever built. There are no plans to withdraw it or replace its guiding gaze heuristic. The case study demonstrates that the gaze heuristic is a specific heuristic type that takes a single best input at the best time (take the best2 ). Its use is an adaptively rational response to specific, rapidly evolving decision environments that has allowed those animals/humans/machines who use it to survive, prosper, and multiply relative to those who do not.

The reliance on recognition and majority vote heuristics over privacy concerns when selecting smartphone apps among German and US consumers

Abstract: The smartphone app market is a prime example of a digital market where consumers are tasked with selecting one option among a plethora of alternatives, at times indistinguishable from one another. Building upon findings on information processing and decision-making, we postulate that consumers follow simple (rather than complex) heuristic rules to navigate the app market. In particular, we focus on two such strategies: the recognition heuristic and the majority vote heuristic. App privacy information was also considered as a potentially salient cue in the decision-making process, given the personal data stored on smartphones. Results of a mixed-method design (behavioral analysis and think-aloud protocols) study with German (N = 18) and US (N = 25) students find a dominance of the recognition heuristic. Decisions are further supported by majority vote heuristics. Privacy information is largely disregarded, particularly by US participants. Implications for app market design and engagement are discussed.

Use of the recognition heuristic depends on the domain’s recognition validity, not on the recognition validity of selected sets of objects

Abstract: According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.

Conflict and Bias in Heuristic Judgment.

Abstract: Conflict has been hypothesized to play a key role in recruiting deliberative processing in reasoning and judgment tasks. This claim suggests that changing the task so as to add incorrect heuristic responses that conflict with existing heuristic responses can make individuals less likely to respond heuristically and can increase response accuracy. We tested this prediction in experiments involving judgments of argument strength and word frequency, and found that participants are more likely to avoid heuristic bias and respond correctly in settings with 2 incorrect heuristic response options compared with similar settings with only 1 heuristic response option. Our results provide strong evidence for conflict as a mechanism influencing the interaction between heuristic and deliberative thought, and illustrate how accuracy can be increased through simple changes to the response sets offered to participants. (PsycINFO Database Record

Heuristics elements of information-seeking strategies and tactics: a conceptual analysis

Abstract: Purpose The purpose of this paper is to elaborate the picture of strategies and tactics for information seeking and searching by focusing on the heuristic elements of such strategies and tactics. Design/methodology/approach A conceptual analysis of a sample of 31 pertinent investigations was conducted to find out how researchers have approached heuristics in the above context since the 1970s. To achieve this, the study draws on the ideas produced within the research programmes on Heuristics and Biases, and Fast and Frugal Heuristics. Findings Researchers have approached the heuristic elements in three major ways. First, these elements are defined as general level constituents of browsing strategies in particular. Second, heuristics are approached as search tips. Third, there are examples of conceptualizations of individual heuristics. Familiarity heuristic suggests that people tend to prefer sources that have worked well in similar situations in the past. Recognition heuristic draws on an all-or-none distinction of the information objects, based on cues such as information scent. Finally, representativeness heuristic is based on recalling similar instances of events or objects and judging their typicality in terms of genres, for example. Research limitations/implications As the study focuses on three heuristics only, the findings cannot be generalized to describe the use of all heuristic elements of strategies and tactics for information seeking and searching. Originality/value The study pioneers by providing an in-depth analysis of the ways in which the heuristic elements are conceptualized in the context of information seeking and searching. The findings contribute to the elaboration of the conceptual issues of information behavior research.

Simple models in finance: a mathematical analysis of the probabilistic recognition heuristic

Abstract: This research has been partly supported by grants from the Agencia Nacional de Innovacion e Investigacion (ANII), Uruguay

The memory state heuristic: A formal model based on repeated recognition judgments.

Abstract: The recognition heuristic (RH) theory predicts that, in comparative judgment tasks, if one object is recognized and the other is not, the recognized one is chosen. The memory-state heuristic (MSH) extends the RH by assuming that choices are not affected by recognition judgments per se, but by the memory states underlying these judgments (i.e., recognition certainty, uncertainty, or rejection certainty). Specifically, the larger the discrepancy between memory states, the larger the probability of choosing the object in the higher state. The typical RH paradigm does not allow estimation of the underlying memory states because it is unknown whether the objects were previously experienced or not. Therefore, we extended the paradigm by repeating the recognition task twice. In line with high threshold models of recognition, we assumed that inconsistent recognition judgments result from uncertainty whereas consistent judgments most likely result from memory certainty. In Experiment 1, we fitted 2 nested multinomial models to the data: an MSH model that formalizes the relation between memory states and binary choices explicitly and an approximate model that ignores the (unlikely) possibility of consistent guesses. Both models provided converging results. As predicted, reliance on recognition increased with the discrepancy in the underlying memory states. In Experiment 2, we replicated these results and found support for choice consistency predictions of the MSH. Additionally, recognition and choice latencies were in agreement with the MSH in both experiments. Finally, we validated critical parameters of our MSH model through a cross-validation method and a third experiment. (PsycINFO Database Record

Measuring Age-Related Differences in Using a Simple Decision Strategy

Abstract: . According to the recognition heuristic, decision makers base their inferences on recognition alone, assuming that recognized objects have larger criterion values than unrecognized ones. Knowing that recognition is a valid cue and thus using the recognition heuristic should increase with age. This was tested in two experiments with preadolescents (N = 140), adolescents (N = 186), and adults (N = 78). The results show, as expected, a monotonic age-related trend in the improvement of domain-specific knowledge but, unexpectedly, a non-monotonic one for using the recognition heuristic. More specifically, use of the recognition heuristic increased from preadolescents to adolescents, but then dropped for adults.

A plausible Decision Heuristics Model: Fallibility of human judgment as an endogenous problem

Abstract: This study meditates about mental heuristic rules as a representation of bounded rationality in individual decision making. The heuristic process presented here represents simultaneously limited computational capacity, the capacity to determine relevant information in complex contexts around beliefs, and time as an endogenous part of decision. The mathematical model of this heuristic rule correlates to the fallibility of the agent depending on the relative outcome of the alternatives in exogenous terms; the availability of only part of the information regarding the alternatives concert by beliefs; and the amount of time the decision maker is willing to spend on a decision based on previous experience and knowing that there is a tradeoff between time and fallibility. The resulting mathematical model can be applied to many disciplines like such as opinion models, game theory, the comparison of systems of distribution of authority, and fields that utilize the technique of agent-based models (ABM) that use individual behavior to study the macroscopic results of interactions.

Further evidence for the memory state heuristic: Recognition latency predictions for binary inferences

Abstract: According to the recognition heuristic (RH), for decision domains where recognition is a valid predictor of a choice criterion, recognition alone is used to make inferences whenever one object is recognized and the other is not, irrespective of further knowledge. Erdfelder, KA¼pper-Tetzel, and Mattern (2011) questioned whether the recognition judgment itself affects decisions or rather the memory strength underlying it. Specifically, they proposed to extend the RH to the memory state heuristic (MSH), which assumes a third memory state of uncertainty in addition to recognition certainty and rejection certainty. While the MSH already gathered significant support, one of its basic and more counterintuitive predictions has not been tested so far: In guessing pairs (none of the objects recognized), the object more slowly judged as unrecognized should be preferred, since it is more likely to be in a higher memory state. In this paper, we test this prediction along with other recognition latency predictions of the MSH, thereby adding to the body of research supporting the MSH.