ArticlePDF Available

Reasoning the Fast and Frugal Way: Models of Bounded Rationality


Abstract and Figures

Humans and animals make inferences about the world under limited time and knowledge. In contrast, many models of rational inference treat the mind as a Laplacean Demon, equipped with unlimited time, knowledge, and computational might. Following Herbert Simon's notion of satisficing, this chapter proposes a family of algorithms based on a simple psychological mechanism: one-reason decision making. These fast-and-frugal algorithms violate fundamental tenets of classical rationality: It neither looks up nor integrates all information. By computer simulation, a competition was held between the satisficing "take-the-best" algorithm and various "rational" inference procedures (e.g., multiple regression). The take-the-best algorithm matched or outperformed all competitors in inferential speed and accuracy. This result is an existence proof that cognitive mechanisms capable of successful performance in the real world do not need to satisfy the classical norms of rational inference.
Content may be subject to copyright.
A preview of the PDF is not available
... However, several authors challenge these assumptions and argue that human rationality is bounded by restricted information availability, cognitive capacity, and environmental complexity (Green and Shapiro, 2014;Kahneman, 2003;Simon, 1990Simon, , 1959. In response to the limited explanatory power of rational choice theory, the concept of bounded rationality has been suggested and explored in recent decades (Gigerenzer and Goldstein, 1996;Gigerenzer and Selten, 2001a;Simon, 1990Simon, , 1972. Bounded rationality can be conceptualized in various forms, for example through satisficing heuristics or fast and frugal decision tree heuristics (Gigerenzer and Goldstein, 1996;Gigerenzer and Selten, 2001b;Schilirò, 2018;Simon, 1972). ...
... In response to the limited explanatory power of rational choice theory, the concept of bounded rationality has been suggested and explored in recent decades (Gigerenzer and Goldstein, 1996;Gigerenzer and Selten, 2001a;Simon, 1990Simon, , 1972. Bounded rationality can be conceptualized in various forms, for example through satisficing heuristics or fast and frugal decision tree heuristics (Gigerenzer and Goldstein, 1996;Gigerenzer and Selten, 2001b;Schilirò, 2018;Simon, 1972). As a psychological theory, the Theory of Planned Behaviour (TPB) assumes that attitude, subjective norms (SN), and perceived behavioural control (PBC) form intentions and therefore determine decisions (Ajzen, 1991;Scalco et al., 2017). ...
... In this case, decision-makers simplify decisions by evaluating specific criteria or cues in a predetermined order until a cue leads a decision. Thus, decision-makers applying this heuristic also take shortcuts and process only certain information (Gigerenzer and Gaissmaier, 2011;Gigerenzer and Goldstein, 1996;Schilirò, 2018). ...
Advancing the transition towards more sustainable agriculture requires policy interventions that support farmers' adoption of sustainable practices. Models can support policy-makers in developing and testing interventions. For these models to provide reliable support, their underlying assumptions need to reflect reality and hence adequately represent human decision-making. This study compares several approaches that represent human decision-making. The comparison is applied to farmers' decision to adopt agroforestry. An agent-based simulation model is calibrated to a case study in rural Rwanda, where socio-economic survey data was collected from 145 small-scale farmers. Of these farmers, 72 were randomly selected to participate in a role-playing game, during which the players decided about adopting agroforestry. The game was conducted to validate the tested decision-making approaches. The simulations show that the decision-making approaches predict significantly different agroforestry adoption rates. Compared with the role-playing game, the Theory of Planned Behaviour exhibits the highest validity. Rational choice theory and the econometric approach overestimate implementation. Bounded rationality approaches underestimate the share of adopters. The results highlight the importance of adequately representing farmers' adoption decisions in models for providing reliable forecasts and effective policy support.
... In a radically novel paradigm (represented at the bottom of the figure), a user's personal device embeds human cognitive models, of how the user brain would process available data, and is thus able to automatically decide which data is relevant (and thus to be presented) to the user, out of the possibly huge set of data available in the network environment. The human brain performs this task using so called cognitive heuristics, i.e., simple, rapid, yet very effective schemes to assess the relevance of information under partial knowledge ([GG92], [GG96]). Cognitive heuristics are fast, frugal and adaptive strategies of the brain that allow humans to face complex situations by addressing simpler problems [MGG10]. ...
... The use of cognitive heuristics to develop effective algorithms for data collection in the cyber-physical world has been first proposed in [CMP13], where, two of the several cognitive models present in the cognitive psychology literature are considered [GG96] [G08] [MGSG10]: the Recognition Heuristic and the Take the Best Heuristic. ...
... Building upon the recognition heuristic, an algorithm is proposed that is inspired by the Take-the-Best cognitive scheme. This algorithm uses the reference model, in the cognitive literature, of Goldstein and Gigerenzer [GG96] and exploits the recognition heuristic in order to simplify and limit the complexity of the data selection task. This is done by recursive creation of small subsets of all the discovered data from which the relevant data is sorted out. ...
Cyber-Physical convergence, the fast expansion of the Internet at its edge, and tighter interactions between human users and their personal mobile devices push towards an Internet where the human user becomes more central than ever, and where their personal devices become their proxies in the cyber world, in addition to acting as a fundamental tool to sense the physical world. The current Internet paradigm, which is infrastructure-centric, is not the right one to cope with such emerging scenario with a wider range of applications. This calls for a radically new Internet paradigm, that we name the Internet of People (IoP), where the humans and their personal devices are not seen merely as end users of applications, but become active elements of the Internet. Note that IoP is not a replacement of the current Internet infrastructure, but it exploits legacy Internet services as (reliable) primitives to achieve end-to-end connectivity on a global-scale. In this visionary paper, we first discuss the key features of the IoP paradigm along with the underlying research issues and challenges. Then we present emerging networking and computing paradigms that are anticipating IoP
... Building on the literature of emotions and bounded rationality, we hypothesize that family firm owners who tend to make decisions emotionally are less likely to systematically evaluate whether their goals (that is, maintaining control) and a course of action (such as issuing equity to external investors) are without contradiction (which may be the case if investors are unlikely to interfere with management). Instead, owners may be more likely to base their consideration of external equity on their socioemotional need for control alone (Gigerenzer and Goldstein 1996). In other words, even if expected investor interference is low, we expect to find a more negative relationship between need for control and consideration of external equity for family firms that base decisions on emotions, than for family firms that do not base their decisions on emotions. ...
... Third, we support prior propositions that emotions are a source of bounded rationality (e.g., Hanoch 2002;Kaufman 1999;Muramatsu and Hanoch 2005). Specifically, we find evidence that emotionally acting family firms heuristically reject external equity based on their need for control alone (Gigerenzer and Goldstein 1996) even if they do not expect investors to interfere with management. ...
In today’s volatile and uncertain economic environment, family firms are facing a multitude of new challenges such as an increase in global competition and market disruption caused by technological advances and digitalization (e.g., Plötner et al. 2020). To remain competitive, they need to understand and address these challenges systematically. To support them in this endeavor, in this dissertation, I conducted four studies to examine three of these challenges: (1) mastering the digitalization of their business, (2) coping with the COVID-19 pandemic, and (3) accessing capital to finance new in-vestments and remain competitive.
... A different perspective on heuristics is provided by Gigerenzer (1996), Gigerenzer and Goldstein (1996) and Gigerenzer (2016) in their "fast and frugal heuristics approach" emerging from the "adaptive-behaviour-and-cognition programme". According to this approach, heuristics are models for fast and frugal decisions that can provide effective solutions with limited information and processing. ...
Purpose This paper aims to provide a wide picture of studies on heuristics for international decision-making with a focus on foreign market entry. This paper systematically reviews studies published in the international business and international marketing domain to examine heuristically based decisions for foreign market entry. Design/methodology/approach This paper proposes a systematic literature review and an in-depth analysis of 32 papers published between 1997 and 2021 dealing with foreign market entry and the use of heuristics for international decision-making. Findings Even if the marketing and management literature is in many ways permeable to the debate around heuristics developed in experimental psychology and cognitive science, international business and international marketing studies on the one hand recognize that international decision-making, especially when dealing with foreign market entry, is strongly characterized by uncertainty, on the other hand, there isn’t a developed and systematized literature about it. This paper shows key topics and areas fundamental to foreign market entry in which heuristics are applied by decision makers and their effectiveness. Originality/value A systematic review of the use of heuristics for foreign market entry decision-making can represent a useful step for a more organic development of knowledge about the more general use of heuristics for international decision-making. Understanding the decision-making process on the modes of entry in foreign markets is a key topic for international marketing and international business scholars and practitioners.
... Today, two main schools exist in thinking about heuristics. The first focuses on what we call "positive heuristics," defined as heuristics that help people make better decisions, such as the recognition heuristic and the take-the-best heuristic, demonstrated by Gigerenzer and Goldstein (1996) and Gigerenzer (2002). Gerd Gigerenzer is the leading proponent of this school. ...
Full-text available
Heuristics are fast and frugal rules of thumb, used to simplify complex decisions. First, the paper identifies two schools of thought in heuristics scholarship, one of positive and one of negative heuristics. Second, the paper explains why heuristics work, based on Occam's razor. Third, it outlines five steps for teasing out project leaders' tacit heuristics, illustrating each step with real-life examples. The five steps emphasize the role of Aristotelian phronesis in developing effective heuristics. Fourth, the paper gives examples of project leaders who have deliberated about their heuristics and made them explicit. Finally, the author presents his own heuristics to illustrate in detail how heuristics can work in practice to improve project leadership. Readers are encouraged to develop and improve their own heuristics, and guidance is given for how to do this.
... As the name suggests, this is decision making on the basis of a single criterion. Researchers argued that if simple decision strategies could outperform rational models, and do so while expending less cognitive effort, it was far more rational for the decision maker to employ these strategies than the supposedly rational, normative ones (Czerlinski, Gigerenzer, & Goldstein, 1999;Gigerenzer & Goldstein, 1996;Gigerenzer & Selten, 2001). In other words, the route to the best decision performance is not always through using computationally demanding normative strategies, but cognitively-efficient ones which lead to the best overall perfonnance in terms of accuracy achieved for the amount of effort spent. ...
p>The Effort-Accuracy framework (E-Af) of decision making predicts that as computational demands of a decision increase and supersede cognitive resources, the decision maker adopts increasingly cognitively-economical strategies of information processing (Payne, Bettman and Johnson, 1993). However, these predictions have not been systematically tested, and the framework does not sufficiently distinguish between the effects of different sources of task demand (e.g. increased decision complexity vs. increased decision difficulty). This research program aimed to explore the predictions of the E-Af, through manipulating the balance between task demands and the cognitive resources of the decision maker. Specifically, it examined the effects of increasing objective levels of task demand, through both increased difficulty and complexity, on the information acquisition process underlying decision making in groups that represent three levels of cognitive resources: diminished (older adults), cognitively-optimal (young adults), and enhanced (experts). The results presented in this thesis provide broad support for the predictions of the E-Af. All decision makers adopted more cognitively-economical decision strategies as task demand increased, with the cognitively-diminished group demonstrating the most, and the cognitively-enhanced group demonstrating the least, cognitive economy. The results also suggest that both demand source and decision domain (the topic of the decision) influence the information acquisition process, and as such must be considered as factors in future decision making research. In addition, this thesis provides an insight into both older adult and expert decision making.</p
... With a value of w 0.75, we see considerable asymmetry as the most important attribute contributes nearly 26.5% of the likelihood of the situation being favorable or not, with the second most important attribute contributing 19.9% and the succeeding attributes declining from that magnitude (14.9%, 11.2%, 8.4%, … ). As w declines further, we see that increasingly only a handful of attributes are largely determinative of whether the opportunity is likely to be favorable or not. 10 Such settings with few factors being largely determinative of the outcome are likely to be amenable to deploying "simple rules" (Gigerenzer and Goldstein 1996, Eisenhardt and Sull 2001, Gigerenzer and Gaissmaier 2011, Bingham and Eisenhardt 2011 in the sense that identifying whether one or two attributes take on a specific value should suffice to categorize more or less promising opportunities. Conversely, as w approaches one, actors need to be more fox-like (Tetlock 2005) and take into consideration multiple factors that influence whether an opportunity is favorable or not. ...
Learning from experience is a central mechanism underlying organizational capabilities. However, in examining how organizations learn from past experiences, much of the literature has focused on situations in which actors are facing a repeated event. We direct attention to a relatively underexamined question: when an organization experiences a largely idiosyncratic series of events, at what level of granularity should these events, and the associated actions and outcomes, be encoded? How does generalizing from experience impact the wisdom of future choices and what are the boundary conditions or factors that might mitigate the degree of desired generalization? To address these questions, we develop a computational model that incorporates how characteristics of opportunities (e.g., acquisition candidates, new investments, product development) might be encoded so that experiential learning is possible even when the organization’s experience is a series of unique events. Our results highlight the power of learning through generalization in a world of novelty as well as the features of the problem environment that reduce this “power.”
... A more recent and large body of research found that the cognitive costs are not necessarily as high as the classical theory suggested. Research on adaptive decision-making (Payne, Bettman, & Johnson, 1993) and fast and frugal heuristics (such as Gigerenzer & Goldstein, 1996;Gigerenzer & Gaissmaier, 2011) established that humans could be good information processors when using simple heuristics. Simple heuristics use little of the large amounts of data available when the information is valid and the heuristic fits the choice environment well. ...
In our information-rich world, people face a great many choice alternatives involving both small and large stakes, from jam and chocolate to health and pension plans. Though classic economics and psychology have both traditionally emphasized the benefits of more information and greater choice, a sizable and parallel body of research has demonstrated that having too much information or too many choices can lead to information and choice overload, choice paralysis, and negative affective states connected with both the decisions process and the choice outcome. This chapter offers a concise summary of evidence collected by researchers for more than half a century on how people deal with large amounts of information and how they make choices from sets with multiple alternatives. The simple cost-benefit model proposed in earlier research is discussed in relation to the mechanism underlying the choice-overload phenomenon.
Full-text available
Background Sustainable transport is fundamental to progress in realising the agenda of sustainable development, as a quarter of energy-related global greenhouse gas emissions come from the transport sector. In developing countries, metropolitan areas have adopted the agenda to better serve the urban population with safe, affordable, and environmentally-friendly transport systems. However, this drive must include relevant indicators and how their operationalisation can deal with institutional barriers, such as challenges to cross-sectoral coordination. Objective This study aims to explore context-specific indicators for developing countries, focusing on the case of the Jakarta metropolitan area. Methods Expert judgement was used to assess the selection criteria. The participants were experts from government institutions, non-government organisations, and universities. Results The findings show that safety, public transport quality, transport cost, air pollution, and accessibility are contextual indicators for application in developing countries. Similarities are shown with the research results from other indexes/sets of indicators for developing countries, for example, the Sustainable Urban Transport Index (SUTI) of UN ESCAP. However, some of these indicators leave room for improvement, such as the balance between strategic and operational levels of application. Conclusion Therefore, this research suggests that global sets of indicators should be adjusted before being implemented in particular developing country contexts.
Full-text available
This study addresses the question whether an ‘attention reminder’ in discrete choice experiments (DCE) affects preferences, willingness to pay (WTP), and attribute non-attendance (ANA). We report on an experiment which elicited preferences for livestock market facilities from 960 randomly selected farm households in Ethiopia. Basic diagnostic comparisons of the estimations showed that taste parameters are significantly different and the WTP values of two (out of eight) facilities are different between before and after the reminder. Latent class model based ANA analysis revealed that the reminder has increased fully compensatory choice behavior [full attention] among sample respondents. The mixed logit models estimated in WTP space also showed that the WTP values are slightly smaller for most of the facilities after the reminder. In terms of relative importance, veterinary clinic, fenced shed, and watering trough facilities are the three livestock market facilities valued most by the farm households both before and after the reminder. Our results imply that researchers studying behaviors of rural communities in developing countries using DCEs might be able to address issues related to heuristics if they reminded respondents of the need to pay attention to all elements in the experiment unless understanding the choice decision making process itself is the point of interest. Empirically, livestock market development initiatives need to take into account farmers’ clear and consistent prioritization of the market facilities.
The term ‘bounded rationality’ is used to designate rational choice that takes into account the cognitive limitations of the decision-maker — limitations of both knowledge and computational capacity. Bounded rationality is a central theme in the behavioural approach to economics, which is deeply concerned with the ways in which the actual decision–making process influences the decisions that are reached.
This literature review of decision making (how people make choices among desirable alternatives), culled from the disciplines of psychology, economics, and mathematics, covers the theory of riskless choices, the application of the theory of riskless choices to welfare economics, the theory of risky choices, transitivity of choices, and the theory of games and statistical decision functions. The theories surveyed assume rational behavior: individuals have transitive preferences ("… if A is preferred to B, and B is preferred to C, then A is preferred to C."), choosing from among alternatives in order to "… maximize utility or expected utility." 209-item bibliography. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The study of scientific discovery—where do new ideas come from?—has long been denigrated by philosophers as irrelevant to analyzing the growth of scientific knowledge. In particular, little is known about how cognitive theories are discovered, and neither the classical accounts of discovery as either probabilistic induction (e.g., H. Reichenbach, 1938) or lucky guesses (e.g., K. Popper, 1959), nor the stock anecdotes about sudden "eureka" moments deepen the insight into discovery. A heuristics approach is taken in this review, where heuristics are understood as strategies of discovery less general than a supposed unique logic discovery but more general than lucky guesses. This article deals with how scientists' tools shape theories of mind, in particular with how methods of statistical inference have turned into metaphors of mind. The tools-to-theories heuristic explains the emergence of a broad range of cognitive theories, from the cognitive revolution of the 1960s up to the present, and it can be used to detect both limitations and new lines of development in current cognitive theories that investigate the mind as an "intuitive statistician." (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Many decisions are based on beliefs concerning the likelihood of uncertain events such as the outcome of an election, the guilt of a defendant, or the future value of the dollar. Occasionally, beliefs concerning uncertain events are expressed in numerical form as odds or subjective probabilities. In general, the heuristics are quite useful, but sometimes they lead to severe and systematic errors. The subjective assessment of probability resembles the subjective assessment of physical quantities such as distance or size. These judgments are all based on data of limited validity, which are processed according to heuristic rules. However, the reliance on this rule leads to systematic errors in the estimation of distance. This chapter describes three heuristics that are employed in making judgments under uncertainty. The first is representativeness, which is usually employed when people are asked to judge the probability that an object or event belongs to a class or event. The second is the availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development, and the third is adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.