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
Nicole K. Drumhiller
A growing body of the scholarship within security studies looks at the influence that crisis has on decision making. Critical areas of focus provide insight into the political leader as a key decision maker, groups as decision-making bodies, and the impact of organizational culture and bureaucratic politics. With crises becoming more complex, the security of states can be impacted in a variety of ways. Under extreme stress, a leader can succumb to flawed decision making as a result of information-processing errors and cognitive biases which skew the way that information is assessed. These decisions can lead to policies and responses to security situations that may impact one or more political entities. When a looming threat is no longer imminent, attention turns inward and investigations into threat preparedness and decision-making processes are carried out. While the stress from the threat itself subsides, leaders can still feel the effects of extreme stress as inquiries into decision making can lead to questions of accountability and blame placement.
A look at crisis decision making also requires a foundational understanding for how someone’s leadership style will impact the way that information is sought and how advisory member guidance will be utilized. As leaders surround themselves with supporting advisory groups, it is important to consider the overall impact that advisory groups play during times of crisis, as well as the functionality of advisory group decision making. Broadening this out to the organizational level, when assessing the impact that crisis has on decision making, it is essential to also consider how organizational dynamics and culture might come to be impacted by crises as well.
Article
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
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
Céline Colombo and Marco R. Steenbergen
Heuristics have rapidly become a core concept in the study of political behavior. The term heuristic stems from the ancient Greek heuriskein, which means “to discover.” In psychology and political science, the term is used to describe cognitive shortcuts in decision making under uncertainty. The key idea is that decision makers with limited time, information, or resources use such shortcuts, thereby bypassing a certain amount of information to reach appropriate decisions. In this sense, heuristics contrast with classical rational choice. Using heuristics allows efficient decision making but can lead to biases, errors, and suboptimal decisions. Heuristics allow decision makers to draw inferences, to fill in information gaps, and to form an impression of the decision at hand. Indeed, they may be the only way to come to grips with uncertainty, especially when a decision is urgent. In political science, the concept of heuristics, originating in mathematics, economics, and psychology, has long been hailed as a possible remedy to citizens’ lack of political knowledge. Citizens participate in democratic decisions, but these decisions often pose high cognitive and informational demands. Ideally, citizens with little information about a political issue or about a candidate could use heuristics in order to reach decisions resembling those of their more well-informed peers. More recently, however, the possible biases introduced by reliance on heuristics, in particular partisan bias and a lack of consideration of different alternatives, has received more attention. Moreover, some studies show that heuristics can be used most efficiently by voters who are relatively well informed and highly interested in politics. The question of whether, or under which circumstances, heuristics can be a useful tool for democratic decision making has not yet been answered conclusively.
Article
Sjoerd Stolwijk
The representativeness heuristic was defined by Kahneman and Tversky as a decision-making shortcut in which people judge probabilities “by the degree to which A is representative of B, that is, by the degree to which A resembles B.” People who use this cognitive shortcut bypass more detailed processing of the likelihood of the event in question but instead focus on what (stereotypic) category it appears to fit and the associations they have about that category. Simply put: If it looks like a duck, it probably is a duck. The representativeness heuristic usually works well and provides valid inferences about likelihood. This is why political scientists saw it as an important part of a solution to an enduring problem in their field: How can people make political decisions when so many studies show they lack even basic knowledge about politics? According to these scholars, voters do not need to be aware of all actions and opinions of a political candidate running for office. To make up their mind on who to vote for, they can rely on cues that represent the performance and issue position of candidates, such as the party they are affiliated with, their ranking in the polls, and whether (for instance) they act/appear presidential. In other words, they need to answer the question: Does this candidate fit my image of a successful president? The resulting low-information rationality provides voters with much confidence in their voting decision, even though they do not know all the details about the history of each candidate. Using heuristics allows relatively uninformed citizens to act as if they were fully informed.
Despite this optimistic view of heuristics at their introduction to the discipline, they originated from research showing how heuristic use is accompanied by systematic error. Tversky and Kahneman argue that using the representativeness heuristic leads to an overreliance on similarity to a category and a neglect of prior probability, sample size, and the reliability and validity of the available cue. Kuklinsky and Quirk first warned about the potential effect of these biases in the context of political decision-making. Current research often examines the effects of specific cues/stereotypes, like party, gender, race, class, or more context-specific heuristics like the deservingness heuristic. Another strand of research has started exploring the effect of the representativeness heuristic on decision-making by political elites, rather than voters. Future studies can integrate these findings to work toward a fuller understanding of the effects of the representativeness heuristic in political decision-making, more closely consider individual differences and the effects of different contexts, and map the consequences that related systematic biases might have.
Article
Anthony C. Lopez
The application of evolutionary theories or models to explain political decision making is
quickly maturing, fundamentally interdisciplinary, and irreducibly complex. This
hybridization has yielded significant benefits, including real progress toward understanding
the conditions under which cooperation is possible, and a clearer understanding of the
apparently “irrational” drivers of political violence.
Decision making requires a nervous system that conditions motivation and behavior upon
adaptively relevant cues in the environment. Such systems do not exist because they maximize
utility, enlightenment, or scientific truth; they exist because on average they led to
outcomes that were reproductively beneficial in ancestral environments. The reproductive
challenges faced by our ancestors included not only ecological problems of predator
avoidance but also political problems such as inter-group threat and the distribution of
resources within groups. Therefore, evolutionary approaches to political decision making
require direct and deep engagement of the logic whereby natural selection builds
adaptations. This view of human psychology yields valuable insights on the domain
specificity of political decision making as well as the psychological consequences of
mismatch between modern and ancestral environments. In other words, there is accumulating
evidence that many of the complex adaptations of the human brain were designed to solve the
many problems of ancestral politics.
This discussion begins by distinguishing evolutionary approaches from other frameworks used
to explain political decision making, such as rational choice, or realism in international
relations. Since evolutionary models of political decision making have now produced decades
of original theoretical and empirical contributions, we are in a useful position to take
stock of this research landscape. Doing so crystalizes the promises, perils, and scope of
evolutionary approaches to politics.
Article
Inbal Hakman, Alex Mintz, and Steven B. Redd
Poliheuristic theory addresses the “why” and “how” of decision making. It focuses on how decision makers use heuristics en route to choice by addressing both the process and the choice related to the decision task. More specifically, decision makers use a two-stage process wherein a more complicated choice set is reduced to one that is more manageable through the use of these heuristics, or cognitive shortcuts. In the second stage, decision makers are more likely to employ maximizing and analytical strategies in making a choice. Poliheuristic theory also focuses on the political consequences of decision making, arguing that decision makers will refrain from making politically costly decisions.
While poliheuristic theory helps us better understand how decision makers process information and make choices, it does not specifically address how choice sets and decision matrices were created in the first place. Applied decision analysis (ADA) rectifies this shortcoming by focusing on how leaders create particular choice sets and matrices and then how they arrive at a choice. It does so by first identifying the decision maker’s choice set or decision matrix; that is, the alternatives or options available to choose from as well as the criteria or dimensions upon which the options will be evaluated. ADA then focuses on uncovering the decision maker’s decision code through the use of multiple decision models.
Combining poliheuristic theory with ADA allows researchers to more fully explain decision making in general and crisis decision making in particular. An application of poliheuristic theory and ADA to decision making pertaining to the Fukushima nuclear disaster reveals that even in this high-stress crisis environment decision makers followed the two-stage process as predicted by poliheuristic theory. More specifically, in the first stage, decision makers simplified the decision task by resorting to cognitive heuristics (i.e., decision making shortcuts) to eliminate politically damaging alternatives such as voluntary evacuation. In the second stage, decision makers conducted a more analytical evaluation of the compulsory evacuation options.
Article
Nichole M. Bauer
Women are under-represented at every level of elected office in the United States. As of 2018, women held just under 20% of seats in Congress, 25% of state legislative seats across the country, only six women serve as governor, and, of course, a woman has yet to win the presidency. The political under-representation of women is not unique to the American context. Indeed, women’s under-representation is a feature of other Western Democracies. Even under the leadership of female prime ministers, women hold only 32% of seats in the United Kingdom parliament and 31% of seats in the German parliament. Conventional wisdom suggests that feminine stereotypes may disadvantage female candidates. Feminine stereotypes characterize women as sensitive, emotional, and weak, and these are qualities voters do not traditionally associate with political leadership. Rather, voters associate political leadership with masculine traits such as being tough, aggressive, or assertive. The extent to which voters use these stereotypes in political decision making in the American context is not entirely clear.
There are three ways that feminine and masculine stereotypes can affect political decision making: candidate strategies, campaign news coverage, and vote choice decision. The alignment between masculine stereotypes and political leadership frequently pressures female candidates to emphasize masculine qualities over feminine qualities in campaign messages. Motivating these masculine messages is the perception that voters see female candidates as lacking the masculine qualities voters desire in political leaders. Male candidates, because of the alignment between masculinity and leadership roles, do not face this pressure. Female candidates will, however, highlight feminine stereotypes when these strategies will afford them a distinct electoral advantage. The use of masculinity in candidate strategy leads the news media, in turn, to use masculine stereotypes rather than feminine stereotypes in their coverage of both female and male candidates.
The ways that candidates and the news media engage with gender stereotypes affects how voters use these concepts to form impressions of female and male candidates. Voters will use feminine stereotypes as heuristics to form impressions of the ideological and issue priorities of female candidates. Feminine stereotypes can hurt the electoral prospects of female candidates, but the negative effect of feminine stereotypes only occurs under a limited set of conditions. Voters will use feminine stereotypes to rate female candidates negatively when female candidates explicitly emphasize feminine qualities, such as being warm or compassionate, in campaign messages. But, voters respond positively to female candidates who emphasize positive masculine qualities. In sum, whether gender stereotypes affect voter decision-making depends on the extent to which voters see messages, either from campaigns or the news media, that reflect femininity or masculinity.
Article
Richard R. Lau
A decision strategy is a set of mental and physical operations that a decision maker uses to reach a choice among two or more alternatives. Once the alternatives have been identified, a decision strategy involves gathering information about at least some of the different alternatives under considerations and making judgments about them. A decision strategy will include a mechanism for selecting the best alternative—for example, select the alternative with the highest probability of success. Decision strategies differ along two primary dimensions: how much information is gathered, and how comparable that information is across alternatives. Four major types of decision strategies include classic rational choice (relatively deep search, equally distributed across alternatives), confirmatory motivated reasoning (relatively deep search, unequally distributed across alternatives), fast and frugal (relatively shallow search, equally distributed across alternatives), and heuristic-based intuitive (shallow search, unequally distributed across alternatives). Although standard rating scales have been developed to help ascertain which strategies a decision maker prefers, the best method for determining which strategy is being employed is to directly observe information gathering while the decision is being made. An important task for future research is to more clearly explicate the situations when different decision strategies perform particularly well or particularly poorly.
