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Article

Fast and Frugal Heuristics  

Konstantinos V. Katsikopoulos

Polymath, and also political scientist, Herbert Simon dared to point out that the amounts of time, information, computation, and other resources required for maximizing utility far exceed what is possible when real people have to make real decisions in the real world. In psychology, there are two main approaches to studying actual human judgment and decision making—the heuristics-and-bias and the fast-and-frugal-heuristics research programs. A distinctive characteristic of the fast-and-frugal-heuristics program is that it specifies formal models of heuristics and attempts to determine when people use them and what performance they achieve. These models rely on a few pieces of information that are processed in computationally simple ways. The information and computation are within human reach, which means that people rely on information they have relatively easy access to and employ simple operations such as summing or comparing numbers. Research in the laboratory and in the wild has found that most people use fast and frugal heuristics most of the time if a decision must be made quickly, information is expensive financially or cognitively to gather, or a single/few attributes of the problem strongly point towards an option. The ways in which people switch between heuristics is studied in the framework of the adaptive toolbox. Work employing computer simulations and mathematical analyses has uncovered conditions under which fast and frugal heuristics achieve higher performance than benchmarks from statistics and machine learning, and vice versa. These conditions constitute the theory of ecological rationality. This theory suggests that fast and frugal heuristics perform better than complex optimization models if the available information is of low quality or scarce, or if there exist dominant options or attributes. The bias-variance decomposition of statistical prediction error, which is explained in layperson’s terms, underpins these claims. Research on fast and frugal heuristics suggests a governance approach not based on nudging, but on boosting citizen competence.

Article

Bounded Rationality and Cognitive Limits in Political Decision Making  

Brooke N. Shannon, Zachary A. McGee, and Bryan D. Jones

Bounded rationality conceives of people engaging in politics as goal oriented but endowed with cognitive and emotional architectures that limit their abilities to pursue those goals rationally. Political institutions provide the critical link between micro- and macro-processes in political decision-making. They act to (a) compensate for those bounds on rationality; (b) make possible cooperative arrangements not possible under the assumptions of full or comprehensive rationality; and (c) fall prey to the same cognitive and emotional limits or canals that individual humans do. The cognitive limitations that hamper individuals are not only replicated at the organizational level but are in fact causal.

Article

Adaptive Learning in Macroeconomics  

George W. Evans and Bruce McGough

While rational expectations (RE) remains the benchmark paradigm in macro-economic modeling, bounded rationality, especially in the form of adaptive learning, has become a mainstream alternative. Under the adaptive learning (AL) approach, economic agents in dynamic, stochastic environments are modeled as adaptive learners forming expectations and making decisions based on forecasting rules that are updated in real time as new data become available. Their decisions are then coordinated each period via the economy’s markets and other relevant institutional architecture, resulting in a time-path of economic aggregates. In this way, the AL approach introduces additional dynamics into the model—dynamics that can be used to address myriad macroeconomic issues and concerns, including, for example, empirical fit and the plausibility of specific rational expectations equilibria. AL can be implemented as reduced-form learning, that is, the implementation of learning at the aggregate level, or alternatively, as discussed in a companion contribution to this Encyclopedia, Evans and McGough, as agent-level learning, which includes pre-aggregation analysis of boundedly rational decision making. Typically learning agents are assumed to use estimated linear forecast models, and a central formulation of AL is least-squares learning in which agents recursively update their estimated model as new data become available. Key questions include whether AL will converge over time to a specified RE equilibrium (REE), in which cases we say the REE is stable under AL; in this case, it is also of interest to examine what type of learning dynamics are observed en route. When multiple REE exist, stability under AL can act as a selection criterion, and global dynamics can involve switching between local basins of attraction. In models with indeterminacy, AL can be used to assess whether agents can learn to coordinate their expectations on sunspots. The key analytical concepts and tools are the E-stability principle together with the E-stability differential equations, and the theory of stochastic recursive algorithms (SRA). While, in general, analysis of SRAs is quite technical, application of the E-stability principle is often straightforward. In addition to equilibrium analysis in macroeconomic models, AL has many applications. In particular, AL has strong implications for the conduct of monetary and fiscal policy, has been used to explain asset price dynamics, has been shown to improve the fit of estimated dynamic stochastic general equilibrium (DSGE) models, and has been proven useful in explaining experimental outcomes.

Article

Foreign Policy Decision Making  

James M. Goldgeier

Decision makers, acting singly or in groups, influence the field of international relations by shaping the interactions among nations. It is therefore important to understand how those decision makers are likely to behave. Some scholars have developed elegant formal theories of decision making to demonstrate the utility of rational choice approaches in the study of international relations, while others have chosen to explain the patterns of bias that exist when leaders face the difficult task of making decisions and formulating policy. Among them are Herbert Simon, who introduced “bounded rationality” to allow leaders to short-circuit the decision process, and Elizabeth Kier, who has shown how organizational cultures shaped the development of military doctrine during the interwar period. The literature on foreign policy decision making during the Cold War looked inside the black box to generate analyses of bureaucratic politics and individual mindsets. Because decision making involves consensus seeking among groups, leaders will often avoid making choices so that they will not antagonize key members of the bureaucracy. Scholars have also investigated the role of “policy entrepreneurs” in the decision-making process, bringing individual agents into organizational, diplomatic and political processes. Over time, the field of policy decision making has evolved to help us understand not only why leaders often calculate so poorly but even more importantly, why systematic patterns of behavior are more or less likely under certain conditions.

Article

Behavioral Public Administration  

Lars Tummers

Behavioral public administration is an interdisciplinary research field that studies public administration topics by connecting insights from public administration with psychology and, more broadly, the behavioral sciences. Behavioral public administration scholars study important public problems such as discrimination, corruption, and burnout. Various public administration scholars—including Herbert Simon—have stressed the importance of connecting psychology and public administration. Yet until the early 2010s, public administration did not work systematically on this connection. This has changed profoundly with the development of various overview articles, dedicated special issues in general public administration journals, and development of new journals. Behavioral public administration has several uses. First, behavioral public administration tests and extends theories and concepts from psychology in political-administrative settings. Examples include tests of prospect theory and the choice overload hypothesis in public-administrative settings. Second, it tests and extends the micro-foundations of public administration theories and concepts, such as concerning co-production and isomorphism. Third, behavioral public administration scholars develop new theories and concepts. This has probably been less widespread than the previous two uses, but is nonetheless already apparent in, for instance, concepts such as public service motivation, policy alienation, and administrative burden. Fourth, behavioral public administration can help in tackling practical public problems. Insights from behavioral public administration have been used to increase diversity within public organizations and reduce burnout. The field of behavioral public administration can develop further. The field could move beyond one-shot single studies and aim to build cumulative knowledge. This can be done via large-scale collaborations and replications. In addition, it is also beneficial if behavioral public administration scholars broaden their methodological toolkit to answer different kinds of research questions. It should not only focus on causal inference questions but also on questions concerning description of societal problems (e.g. via representative surveys) or concerning prediction (e.g. by using machine learning).

Article

Bounded Rationality in Public Administration  

JoBeth Shafran, Bryan D. Jones, and Connor Dye

Bounded rationality is the notion that while humans want to be fully rational beings and weigh the costs and benefits when making a decision, they cannot do so due to cognitive and emotional limitations. The role of human nature in the study and design of organizations can be examined through three general approaches that are explained using metaphors: organization as machine, organization as hierarchy, and organization as canal. The organization-as-machine approach ignores the principles of bounded rationality by assuming the organizational members perform straightforward cost–benefit responses to the incentives put forward by the operators. Later developments in organizational scholarship incorporate elements of bounded rationality and allowed researchers to link human cognitive capacities to the basic organizational features, giving us two new conceptions of organization: organization as hierarchy and organization as canal. Organization as hierarchy focuses on the organization’s use of subunits to create divisions of labor to expand the capacity to process information and problem-solve. Organization as canal recognizes that the weaknesses of human cognition are still channeled into the organizational structure, making it difficult for organizations to update their preferences and assumptions as they receive new information. These principles of bounded rationality in organizational theory can be applied to policy-making institutions. Hierarchical organizations delegate information processing to the subunits, allowing them to attend to the various policy environments and process incoming information. While the collective organization attends to many issues at once, the rules and procedures that are present within the organization and the cognitive limits of decision makers, prevent proportional information processing. Political institutions are unable to respond efficiently to changes in the environment. Thus, organizational adjustment to the environment is characterized as disjointed and episodic as opposed to smooth and incremental. Punctuated equilibrium theory applies these tenets of bounded rationality to a theory of policy change. Congress has been a vehicle for studying bounded rationality in organizations and theories of policy change, as it is a formal institution with bureaucratic elements and is subject to the constraints faced by any formal organization.

Article

Cognitive Approaches to Foreign Policy Analysis  

Aaron Rapport

Cognitive theory encompasses mental activities such as the observation of different stimuli in an environment; the memorization and recall of information; pattern recognition and problem representation; and complex activities like social judgments, analytic reasoning, and learning. Cognitive psychology also highlights the constraints that prevent individuals from acting as utility-maximizing, fully rational decision-makers. These constraints lead people to rely on a regularly occurring set of cognitive mechanisms to simplify the decision-making process. Scholars of foreign policy have drawn from several prominent areas of cognitive psychology to inform their research. One such area looks at the beliefs and belief systems that are the building blocks for most judgments. Researchers have also examined how actors use cognitive biases and heuristics to cope with uncertainty, which is abundant in foreign policy settings. An important set of cognitive mechanisms examined in Foreign Policy Analysis (FPA) relates to judgments about policy risks and costs. Factors that facilitate and inhibit learning are crucial for understanding the conditions under which such judgments may improve over time. No cognitive process operates in a vacuum; instead these processes are moderated by an individual’s group context and emotions. There are several challenges in applying cognitive theory to FPA. Such theories are biased toward populations that are Western, educated, industrialized, rich, and democratic. They are usually first tested using controlled experiments that measure group-level differences; whereas FPA scholars are often interested in the cognitive processes of individual leaders operating in chaotic environments. Individual-level psychological mechanisms may augment or offset one another, as well as interact with variables at the governmental, societal, and international levels of analysis in unpredictable ways. In light of these challenges, FPA scholars who employ cognitive psychology may wish to conceive of their enterprise as a historical science rather than a predictive one.

Article

Lexicographic Decision Rule  

Özgür Şimşek

The lexicographic decision rule is one of the simplest methods of choosing among decision alternatives. It is based on a simple priority ranking of the attributes available. According to the lexicographic decision rule, a decision alternative is better than another alternative if and only if it is better than the other alternative in the most important attribute on which the two alternatives differ. In other words, the lexicographic decision rule does not allow trade-offs among the various attributes. For example, if quality is considered to be more important than cost, no difference in price can compensate for a difference in quality: The lexicographic decision rule chooses the item with the best quality regardless of the cost. Over the years, the lexicographic decision rule has been compared to various statistical learning methods, including multiple linear regression, support vector machines, decision trees, and random forests. The results show that the lexicographic decision rule can sometimes compete remarkably well with more complex statistical methods and even outperform them, despite its naively simple structure. These results have stimulated a rich scientific literature on why, and under what conditions, lexicographic decision rules yield accurate decisions. Due to the simplicity of its decision process, its fast execution time, and the robustness of its performance in various decision environments, the lexicographic decision rule is considered to be a plausible model of human decision making. In particular, the lexicographic decision rule is put forward as a model of how the human mind implements bounded rationality to make accurate decisions when information is scarce, time is short, and computational capacity is limited.

Article

Foreign Policy Decision Making: Evolution, Models, and Methods  

David Brulé and Alex Mintz

Choices made by individuals, small groups, or coalitions representing nation-states result in policies or strategies with international outcomes. Foreign policy decision-making, an approach to international relations, is aimed at studying such decisions. The rational choice model is widely considered to be the paradigmatic approach to the study of international relations and foreign policy. The evolution of the decision-making approach to foreign policy analysis has been punctuated by challenges to rational choice from cognitive psychology and organizational theory. In the late 1950s and early 1960s, scholars began to ponder the deterrence puzzle as they sought to find solutions to the problem of credibility. During this period, cross-disciplinary research on organizational behavior began to specify a model of decision making that contrasted with the rational model. Among these models were the bounded rationality/cybernetic model, organizational politics model, bureaucratic politics model, prospect theory, and poliheuristic theory. Despite these and other advances, the gulf between the rational choice approaches and cognitive psychological approaches appears to have stymied progress in the field of foreign policy decision-making. Scholars working within the cognitivist school should develop theories of decision making that incorporate many of the cognitive conceptual inputs in a logical and coherent framework. They should also pursue a multi-method approach to theory testing using experimental, statistical, and case study methods.

Article

Intuition in Management  

Eugene Sadler-Smith

An extensive literature has accumulated during the past three quarters of a century on the topic of intuition in management. The beginnings of management intuition scholarship are to be found in Chester Barnard’s insightful speculations on the role and significance of logical and non-logical processes in managerial work. Barnard’s thinking impacted profoundly Herbert Simon’s foundational concept of bounded rationality, which shed much needed light on how managerial decision-making is accomplished in real-world settings by using intuition as well as analysis. In parallel, management researchers in common with scholars in a wide range of applied fields also drew on Daniel Kahneman, Amos Tversky, and colleagues’ seminal behavioral decision research and its focus on the systematic errors and biases that accrue in managers’ intuitive judgments as the result of the use of heuristics (e.g., representativeness, availability, anchoring and adjustment, and affect heuristics). In recent years management researchers have drawn on further insights from Klein and colleagues’ work in naturalistic decision-making (NDM) (e.g., the “recognition primed decision-making model,” RPD) to conceptualize managerial work as expert performance and in understanding expert-versus-novice differences using the “skill acquisition model” (SAM). In recent years managerial intuition research has alighted on the dual-process theories of Epstein, Evans, Stanovich, and others as a conceptual foundation for further theorizing and research in terms of System 1 (also referred to as Type 1) and System 2 (Type 2) processing. More recently still, research in neurology (e.g., the “somatic marker hypothesis”) and social cognitive neuroscience (e.g., the specification of complementary “reflexive (X)” and “reflective (C)” systems) has mapped the physiological and neural correlates of intuitive processing and begun to inform not only intuition research but decision research more widely in management and organization studies. These various developments have shed light on how intuitive decision-making is accomplished in managerial work across diverse management subfields including entrepreneurship, business ethics, human resources, and strategic management. More recently, scholars are turning to paradox theory and process philosophy as alternative ways of viewing the phenomenon of intuition in organizations.

Article

Agency Theory in Business and Management Research  

G. Tyge Payne and Oleg V. Petrenko

Agency theory is one the most prominent theoretical perspectives utilized in business and management research. Agency theory argues—using fundamental assumptions that agents are: (a) self-interested, (b) boundedly rational, and (c) different from principals in their goals and risk-taking preferences—that a problem occurs when one party (a principal) employs another (an agent) to make decisions and act in their stead. Essentially, the value of a principal-agent relationship is not optimized because the two contracted parties may have different interests and information is asymmetric (not equal). Agency costs are the result of principal and agent conflicts of interest and disagreements regarding actions that are taken. As such, monitoring and incentive-alignment systems are used to curb costs associated with opportunist behavior. Agency theory is commonly utilized to understand and explain corporate governance phenomena, including executive incentive alignment, board monitoring, and control of top managers; this strand of the literature is founded in economics and represents the bulk of the research in business and management. However, other important principal-agent relationships are commonly seen in business and society, such as with politicians/voters, brokers/investors, and lawyers/clients, and have benefited from the vast stream of research that has explored the principal-agent relationship in various forms and contexts. Also, alternative theoretical perspectives have emerged to accommodate variations of the principal-agent relationship. Namely, principal-principal agency, behavioral agency, and stewardship theories are prominent alternative theories that challenge, expand, or relax the basic assumptions of the classic theory to extend our understanding of important relationships and mechanisms in business and management.

Article

Judgment and Decision Making  

Priscila G. Brust-Renck, Rebecca B. Weldon, and Valerie F. Reyna

Everyday life is comprised of a series of decisions, from choosing what to wear to deciding what major to declare in college and whom to share a life with. Modern era economic theories were first brought into psychology in the 1950s and 1960s by Ward Edwards and Herbert Simon. Simon suggested that individuals do not always choose the best alternative among the options because they are bounded by cognitive limitations (e.g., memory). People who choose the good-enough option “satisfice” rather than optimize, because they are bounded by their limited time, knowledge, and computational capacity. Daniel Kahneman and Amos Tversky were among those who took the next step by demonstrating that individuals are not only limited but are inconsistent in their preferences, and hence irrational. Describing a series of biases and fallacies, they elaborated intuitive strategies (i.e., heuristics) that people tend to use when faced with difficult questions (e.g., “What proportion of long-distance relationships break up within a year?”) by answering based on simpler, similar questions (e.g., “Do instances of swift breakups of long-distance relationships come readily to mind?”). More recently, the emotion-versus-reason debate has been incorporated into the field as an approach to how judgments can be governed by two fundamentally different processes, such as intuition (or affect) and reasoning (or deliberation). A series of dual-process approaches by Seymour Epstein, George Lowenstein, Elke Weber, Paul Slovic, and Ellen Peters, among others, attempt to explain how a decision based on emotional and/or impulsive judgments (i.e., system 1) should be distinguished from those that are based on a slow process that is governed by rules of reasoning (i.e., system 2). Valerie Reyna and Charles Brainerd and other scholars take a different approach to dual processes and propose a theory—fuzzy-trace theory—that incorporates many of the prior theoretical elements but also introduces the novel concept of gist mental representations of information (i.e., essential meaning) shaped by culture and experience. Adding to processes of emotion or reward sensitivity and reasoning or deliberation, fuzzy-trace theory characterizes gist as insightful intuition (as opposed to crude system 1 intuition) and contrasts it with verbatim or precise processing that does not consist of meaningful interpretation. Some of these new perspectives explain classic paradoxes and predict new effects that allow us to better understand human judgment and decision making. More recent contributions to the field include research in neuroscience, in particular from neuroeconomics.

Article

The Politics of Evidence-Based Policy Making  

Paul Cairney

“Evidence-based policy making” (EBPM) has become a popular term to describe the need for more scientific and less ideological policy making. Some compare it to “evidence-based medicine,” which describes moves to produce evidence, using commonly-held scientific principles regarding a hierarchy of evidence, which can directly inform practice. Policy making is different: there is less agreement on what counts as good evidence, and more things to consider when responding to evidence. Our awareness of these differences between science and policy are not new. Current debates resemble a postwar policy science agenda, to produce more scientific and “rational” policy analysis, which faced major empirical and normative obstacles: the world is not that simple, and an overly technocratic approach to policy undermines much-needed political debate. To understand modern discussions of EBPM, key insights from previous discussions must be considered: policy making is both “rational” and “irrational”; it takes place in complex policy environments or systems, whose properties should be understood in some depth; and it can and should not be driven by “the evidence” alone.