Decision-making

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Sample flowchart representing a decision process when confronted with a lamp that fails to light LampFlowchart.svg
Sample flowchart representing a decision process when confronted with a lamp that fails to light

In psychology, decision-making (also spelled decision making and decisionmaking) is regarded as the cognitive process resulting in the selection of a belief or a course of action among several possible alternative options. It could be either rational or irrational. The decision-making process is a reasoning process based on assumptions of values, preferences and beliefs of the decision-maker. [1] Every decision-making process produces a final choice, which may or may not prompt action.

Contents

Research about decision-making is also published under the label problem solving, particularly in European psychological research. [2]

Overview

Decision-making can be regarded as a problem-solving activity yielding a solution deemed to be optimal, or at least satisfactory. It is therefore a process which can be more or less rational or irrational and can be based on explicit or tacit knowledge and beliefs. Tacit knowledge is often used to fill the gaps in complex decision-making processes. [3] Usually, both of these types of knowledge, tacit and explicit, are used together in the decision-making process.

Human performance has been the subject of active research from several perspectives:

A major part of decision-making involves the analysis of a finite set of alternatives described in terms of evaluative criteria. Then the task might be to rank these alternatives in terms of how attractive they are to the decision-maker(s) when all the criteria are considered simultaneously. Another task might be to find the best alternative or to determine the relative total priority of each alternative (for instance, if alternatives represent projects competing for funds) when all the criteria are considered simultaneously. Solving such problems is the focus of multiple-criteria decision analysis (MCDA). This area of decision-making, although long established, has attracted the interest of many researchers and practitioners and is still highly debated as there are many MCDA methods which may yield very different results when they are applied to exactly the same data. [5] This leads to the formulation of a decision-making paradox. Logical decision-making is an important part of all science-based professions, where specialists apply their knowledge in a given area to make informed decisions. For example, medical decision-making often involves a diagnosis and the selection of appropriate treatment. But naturalistic decision-making research shows that in situations with higher time pressure, higher stakes, or increased ambiguities, experts may use intuitive decision-making rather than structured approaches. They may follow a recognition-primed decision that fits their experience, and arrive at a course of action without weighing alternatives. [6]

The decision-maker's environment can play a part in the decision-making process. For example, environmental complexity is a factor that influences cognitive function. [7] A complex environment is an environment with a large number of different possible states which come and go over time. [8] Studies done at the University of Colorado have shown that more complex environments correlate with higher cognitive function, which means that a decision can be influenced by the location. One experiment measured complexity in a room by the number of small objects and appliances present; a simple room had less of those things. Cognitive function was greatly affected by the higher measure of environmental complexity, making it easier to think about the situation and make a better decision. [7]

Problem solving vs. decision making

It is important to differentiate between problem solving, or problem analysis, and decision-making. Problem solving is the process of investigating the given information and finding all possible solutions through invention or discovery. Traditionally, it is argued that problem solving is a step towards decision making, so that the information gathered in that process may be used towards decision-making. [9] [ page needed ]

Characteristics of problem solving
Characteristics of decision-making

Analysis paralysis

When a group or individual is unable to make it through the problem-solving step on the way to making a decision, they could be experiencing analysis paralysis. Analysis paralysis is the state that a person enters where they are unable to make a decision, in effect paralyzing the outcome. [12] [13] Some of the main causes for analysis paralysis is the overwhelming flood of incoming data or the tendency to overanalyze the situation at hand. [14] There are said to be three different types of analysis paralysis. [15]

Extinction by instinct

On the opposite side of analysis paralysis is the phenomenon called extinction by instinct. Extinction by instinct is the state that a person is in when they make careless decisions without detailed planning or thorough systematic processes. [16] Extinction by instinct can possibly be fixed by implementing a structural system, like checks and balances into a group or one's life. Analysis paralysis is the exact opposite where a group's schedule could be saturated by too much of a structural checks and balance system. [16]

Groupthink is another occurrence that falls under the idea of extinction by instinct. Groupthink is when members in a group become more involved in the “value of the group (and their being part of it) higher than anything else”; thus, creating a habit of making decisions quickly and unanimously. In other words, a group stuck in groupthink is participating in the phenomenon of extinction by instinct. [17]

Information overload

Information overload is "a gap between the volume of information and the tools we have to assimilate" it. [18] Information used in decision-making is to reduce or eliminate the uncertainty. [19] Excessive information affects problem processing and tasking, which affects decision-making. [20] Psychologist George Armitage Miller suggests that humans' decision making becomes inhibited because human brains can only hold a limited amount of information. [21] Crystal C. Hall and colleagues described an "illusion of knowledge", which means that as individuals encounter too much knowledge, it can interfere with their ability to make rational decisions. [22] Other names for information overload are information anxiety, information explosion, infobesity, and infoxication. [23] [24] [25] [26]

Decision fatigue

Decision fatigue is when a sizable amount of decision-making leads to a decline in decision-making skills. People who make decisions in an extended period of time begin to lose mental energy needed to analyze all possible solutions. Impulsive decision-making and decision avoidance are two possible paths that extend from decision fatigue. Impulse decisions are made more often when a person is tired of analysis situations or solutions; the solution they make is to act and not think. [27] Decision avoidance is when a person evades the situation entirely by not ever making a decision. Decision avoidance is different from analysis paralysis because this sensation is about avoiding the situation entirely, while analysis paralysis is continually looking at the decisions to be made but still unable to make a choice. [28] [ self-published source ]

Post-decision analysis

Evaluation and analysis of past decisions is complementary to decision-making. See also mental accounting and Postmortem documentation.

Neuroscience

Decision-making is a region of intense study in the fields of systems neuroscience, and cognitive neuroscience. Several brain structures, including the anterior cingulate cortex (ACC), orbitofrontal cortex, and the overlapping ventromedial prefrontal cortex are believed to be involved in decision-making processes. A neuroimaging study [29] found distinctive patterns of neural activation in these regions depending on whether decisions were made on the basis of perceived personal volition or following directions from someone else. Patients with damage to the ventromedial prefrontal cortex have difficulty making advantageous decisions. [30] [ page needed ]

A common laboratory paradigm for studying neural decision-making is the two-alternative forced choice task (2AFC), in which a subject has to choose between two alternatives within a certain time. A study of a two-alternative forced choice task involving rhesus monkeys found that neurons in the parietal cortex not only represent the formation of a decision [31] but also signal the degree of certainty (or "confidence") associated with the decision. [32] A 2012 study found that rats and humans can optimally accumulate incoming sensory evidence, to make statistically optimal decisions. [33] Another study found that lesions to the ACC in the macaque resulted in impaired decision-making in the long run of reinforcement guided tasks suggesting that the ACC may be involved in evaluating past reinforcement information and guiding future action. [34] It has recently been argued that the development of formal frameworks will allow neuroscientists to study richer and more naturalistic paradigms than simple 2AFC decision tasks; in particular, such decisions may involve planning and information search across temporally extended environments. [35]

Emotions

Emotion appears able to aid the decision-making process. Decision-making often occurs in the face of uncertainty about whether one's choices will lead to benefit or harm (see also Risk). The somatic marker hypothesis is a neurobiological theory of how decisions are made in the face of uncertain outcomes. [36] This theory holds that such decisions are aided by emotions, in the form of bodily states, that are elicited during the deliberation of future consequences and that mark different options for behavior as being advantageous or disadvantageous. This process involves an interplay between neural systems that elicit emotional/bodily states and neural systems that map these emotional/bodily states. [37] A recent lesion mapping study of 152 patients with focal brain lesions conducted by Aron K. Barbey and colleagues provided evidence to help discover the neural mechanisms of emotional intelligence. [38] [39] [40]

Decision-making techniques

Decision-making techniques can be separated into two broad categories: group decision-making techniques and individual decision-making techniques. Individual decision-making techniques can also often be applied by a group.

Group

Individual

Steps

A variety of researchers have formulated similar prescriptive steps aimed at improving decision-making.

GOFER

In the 1980s, psychologist Leon Mann and colleagues developed a decision-making process called GOFER, which they taught to adolescents, as summarized in the book Teaching Decision Making To Adolescents. [45] The process was based on extensive earlier research conducted with psychologist Irving Janis. [46] GOFER is an acronym for five decision-making steps: [47]

  1. Goals clarification: Survey values and objectives.
  2. Options generation: Consider a wide range of alternative actions.
  3. Facts-finding: Search for information.
  4. Consideration of Effects: Weigh the positive and negative consequences of the options.
  5. Review and implementation: Plan how to review the options and implement them.

Other

In 2007, Pam Brown of Singleton Hospital in Swansea, Wales, divided the decision-making process into seven steps: [48]

  1. Outline the goal and outcome.
  2. Gather data.
  3. Develop alternatives (i.e., brainstorming).
  4. List pros and cons of each alternative.
  5. Make the decision.
  6. Immediately take action to implement it.
  7. Learn from and reflect on the decision.

In 2008, Kristina Guo published the DECIDE model of decision-making, which has six parts: [49]

  1. Define the problem
  2. Establish or Enumerate all the criteria (constraints)
  3. Consider or Collect all the alternatives
  4. Identify the best alternative
  5. Develop and implement a plan of action
  6. Evaluate and monitor the solution and examine feedback when necessary

In 2009, professor John Pijanowski described how the Arkansas Program, an ethics curriculum at the University of Arkansas, used eight stages of moral decision-making based on the work of James Rest: [50] : 6 

  1. Establishing community: Create and nurture the relationships, norms, and procedures that will influence how problems are understood and communicated. This stage takes place prior to and during a moral dilemma.
  2. Perception: Recognize that a problem exists.
  3. Interpretation: Identify competing explanations for the problem, and evaluate the drivers behind those interpretations.
  4. Judgment: Sift through various possible actions or responses and determine which is more justifiable.
  5. Motivation: Examine the competing commitments which may distract from a more moral course of action and then prioritize and commit to moral values over other personal, institutional or social values.
  6. Action: Follow through with action that supports the more justified decision.
  7. Reflection in action.
  8. Reflection on action.

Group stages

There are four stages or phases that should be involved in all group decision-making: [51]

It is said that establishing critical norms in a group improves the quality of decisions, while the majority of opinions (called consensus norms) do not. [52]

Conflicts in socialization are divided in to functional and dysfunctional types. Functional conflicts are mostly the questioning the managers assumptions in their decision making and dysfunctional conflicts are like personal attacks and every action which decrease team effectiveness. Functional conflicts are the better ones to gain higher quality decision making caused by the increased team knowledge and shared understanding. [53]

Rational and irrational

In economics, it is thought that if humans are rational and free to make their own decisions, then they would behave according to rational choice theory. [54] : 368–370  Rational choice theory says that a person consistently makes choices that lead to the best situation for themselves, taking into account all available considerations including costs and benefits; the rationality of these considerations is from the point of view of the person themselves, so a decision is not irrational just because someone else finds it questionable.

In reality, however, there are some factors that affect decision-making abilities and cause people to make irrational decisions –for example, to make contradictory choices when faced with the same problem framed in two different ways (see also Allais paradox).

Rational decision making is a multi-step process for making choices between alternatives. The process of rational decision making favors logic, objectivity, and analysis over subjectivity and insight. Irrational decision is more counter to logic. The decisions are made in haste and outcomes are not considered. [55]

One of the most prominent theories of decision making is subjective expected utility (SEU) theory, which describes the rational behavior of the decision maker. [56] The decision maker assesses different alternatives by their utilities and the subjective probability of occurrence. [56]

Rational decision-making is often grounded on experience and theories that are able to put this approach on solid mathematical grounds so that subjectivity is reduced to a minimum, see e.g. scenario optimization.

Rational decision is generally seen as the best or most likely decision to achieve the set goals or outcome. [57]

Children, adolescents, and adults

Children

It has been found that, unlike adults, children are less likely to have research strategy behaviors. One such behavior is adaptive decision-making, which is described as funneling and then analyzing the more promising information provided if the number of options to choose from increases. Adaptive decision-making behavior is somewhat present for children, ages 11–12 and older, but decreases in presence the younger they are. [58] The reason children are not as fluid in their decision making is because they lack the ability to weigh the cost and effort needed to gather information in the decision-making process. Some possibilities that explain this inability are knowledge deficits and lack of utilization skills. Children lack the metacognitive knowledge necessary to know when to use any strategies they do possess to change their approach to decision-making. [58]

When it comes to the idea of fairness in decision making, children and adults differ much less. Children are able to understand the concept of fairness in decision making from an early age. Toddlers and infants, ranging from 9–21 months, understand basic principles of equality. The main difference found is that more complex principles of fairness in decision making such as contextual and intentional information do not come until children get older. [59]

Adolescents

During their adolescent years, teens are known for their high-risk behaviors and rash decisions. Research [60] has shown that there are differences in cognitive processes between adolescents and adults during decision-making. Researchers have concluded that differences in decision-making are not due to a lack of logic or reasoning, but more due to the immaturity of psychosocial capacities that influence decision-making. Examples of their undeveloped capacities which influence decision-making would be impulse control, emotion regulation, delayed gratification and resistance to peer pressure. In the past, researchers have thought that adolescent behavior was simply due to incompetency regarding decision-making. Currently, researchers have concluded that adults and adolescents are both competent decision-makers, not just adults. However, adolescents' competent decision-making skills decrease when psychosocial capacities become present.

Research [61] has shown that risk-taking behaviors in adolescents may be the product of interactions between the socioemotional brain network and its cognitive-control network. The socioemotional part of the brain processes social and emotional stimuli and has been shown to be important in reward processing. The cognitive-control network assists in planning and self-regulation. Both of these sections of the brain change over the course of puberty. However, the socioemotional network changes quickly and abruptly, while the cognitive-control network changes more gradually. Because of this difference in change, the cognitive-control network, which usually regulates the socioemotional network, struggles to control the socioemotional network when psychosocial capacities are present.[ clarification needed ]

When adolescents are exposed to social and emotional stimuli, their socioemotional network is activated as well as areas of the brain involved in reward processing. Because teens often gain a sense of reward from risk-taking behaviors, their repetition becomes ever more probable due to the reward experienced. In this, the process mirrors addiction. Teens can become addicted to risky behavior because they are in a high state of arousal and are rewarded for it not only by their own internal functions but also by their peers around them. A recent study suggests that adolescents have difficulties adequately adjusting beliefs in response to bad news (such as reading that smoking poses a greater risk to health than they thought), but do not differ from adults in their ability to alter beliefs in response to good news. [62] This creates biased beliefs, which may lead to greater risk taking. [63]

Adults

Adults are generally better able to control their risk-taking because their cognitive-control system has matured enough to the point where it can control the socioemotional network, even in the context of high arousal or when psychosocial capacities are present. Also, adults are less likely to find themselves in situations that push them to do risky things. For example, teens are more likely to be around peers who peer pressure them into doing things, while adults are not as exposed to this sort of social setting. [64] [65]

Cognitive and personal biases

Biases usually affect decision-making processes. They appear more when decision task has time pressure, is done under high stress and/or task is highly complex. [66]

Here is a list of commonly debated biases in judgment and decision-making:

Cognitive limitations in groups

In groups, people generate decisions through active and complex processes. One method consists of three steps: initial preferences are expressed by members; the members of the group then gather and share information concerning those preferences; finally, the members combine their views and make a single choice about how to face the problem. Although these steps are relatively ordinary, judgements are often distorted by cognitive and motivational biases, include "sins of commission", "sins of omission", and "sins of imprecision". [74] [ page needed ]

Cognitive styles

Optimizing vs. satisficing

Herbert A. Simon coined the phrase "bounded rationality" to express the idea that human decision-making is limited by available information, available time and the mind's information-processing ability. Further psychological research has identified individual differences between two cognitive styles: maximizers try to make an optimal decision, whereas satisficers simply try to find a solution that is "good enough". Maximizers tend to take longer making decisions due to the need to maximize performance across all variables and make tradeoffs carefully; they also tend to more often regret their decisions (perhaps because they are more able than satisficers to recognize that a decision turned out to be sub-optimal). [75]

Intuitive vs. rational

The psychologist Daniel Kahneman, adopting terms originally proposed by the psychologists Keith Stanovich and Richard West, has theorized that a person's decision-making is the result of an interplay between two kinds of cognitive processes: an automatic intuitive system (called "System 1") and an effortful rational system (called "System 2"). System 1 is a bottom-up, fast, and implicit system of decision-making, while system 2 is a top-down, slow, and explicit system of decision-making. [76] System 1 includes simple heuristics in judgment and decision-making such as the affect heuristic, the availability heuristic, the familiarity heuristic, and the representativeness heuristic.

Combinatorial vs. positional

Styles and methods of decision-making were elaborated by Aron Katsenelinboigen, the founder of predispositioning theory. In his analysis on styles and methods, Katsenelinboigen referred to the game of chess, saying that "chess does disclose various methods of operation, notably the creation of predisposition-methods which may be applicable to other, more complex systems." [77] : 5 

Katsenelinboigen states that apart from the methods (reactive and selective) and sub-methods randomization, predispositioning, programming), there are two major styles: positional and combinational. Both styles are utilized in the game of chess. The two styles reflect two basic approaches to uncertainty: deterministic (combinational style) and indeterministic (positional style). Katsenelinboigen's definition of the two styles are the following.

The combinational style is characterized by:

In defining the combinational style in chess, Katsenelinboigen wrote: "The combinational style features a clearly formulated limited objective, namely the capture of material (the main constituent element of a chess position). The objective is implemented via a well-defined, and in some cases, unique sequence of moves aimed at reaching the set goal. As a rule, this sequence leaves no options for the opponent. Finding a combinational objective allows the player to focus all his energies on efficient execution, that is, the player's analysis may be limited to the pieces directly partaking in the combination. This approach is the crux of the combination and the combinational style of play. [77] : 57 

The positional style is distinguished by:

"Unlike the combinational player, the positional player is occupied, first and foremost, with the elaboration of the position that will allow him to develop in the unknown future. In playing the positional style, the player must evaluate relational and material parameters as independent variables. ... The positional style gives the player the opportunity to develop a position until it becomes pregnant with a combination. However, the combination is not the final goal of the positional player –it helps him to achieve the desirable, keeping in mind a predisposition for the future development. The pyrrhic victory is the best example of one's inability to think positionally." [78]

The positional style serves to:

Influence of Myers–Briggs type

According to Isabel Briggs Myers, a person's decision-making process depends to a significant degree on their cognitive style. [79] [ page needed ] Myers developed a set of four bi-polar dimensions, called the Myers–Briggs Type Indicator (MBTI). The terminal points on these dimensions are: thinking and feeling; extroversion and introversion; judgment and perception; and sensing and intuition. She claimed that a person's decision-making style correlates well with how they score on these four dimensions. For example, someone who scored near the thinking, extroversion, sensing, and judgment ends of the dimensions would tend to have a logical, analytical, objective, critical, and empirical decision-making style. However, some psychologists say that the MBTI lacks reliability and validity and is poorly constructed. [80] [81]

Other studies suggest that these national or cross-cultural differences in decision-making exist across entire societies. For example, Maris Martinsons has found that American, Japanese and Chinese business leaders each exhibit a distinctive national style of decision-making. [82]

The Myers–Briggs typology has been the subject of criticism regarding its poor psychometric properties. [83] [84] [85]

General decision-making style (GDMS)

In the general decision-making style (GDMS) test developed by Suzanne Scott and Reginald Bruce, there are five decision-making styles: rational, intuitive, dependent, avoidant, and spontaneous. [86] [87] These five different decision-making styles change depending on the context and situation, and one style is not necessarily better than any other. In the examples below, the individual is working for a company and is offered a job from a different company.

See also

Further reading

Related Research Articles

<span class="mw-page-title-main">Cognitive bias</span> Systematic pattern of deviation from norm or rationality in judgment

A cognitive bias is a systematic pattern of deviation from norm or rationality in judgment. Individuals create their own "subjective reality" from their perception of the input. An individual's construction of reality, not the objective input, may dictate their behavior in the world. Thus, cognitive biases may sometimes lead to perceptual distortion, inaccurate judgment, illogical interpretation, and irrationality.

A heuristic or heuristic technique is any approach to problem solving that employs a pragmatic method that is not fully optimized, perfected, or rationalized, but is nevertheless "good enough" as an approximation or attribute substitution. Where finding an optimal solution is impossible or impractical, heuristic methods can be used to speed up the process of finding a satisfactory solution. Heuristics can be mental shortcuts that ease the cognitive load of making a decision.

Heuristic reasoning is often based on induction, or on analogy[.] [...] Induction is the process of discovering general laws [...] Induction tries to find regularity and coherence [...] Its most conspicuous instruments are generalization, specialization, analogy. [...] Heuristic discusses human behavior in the face of problems [...that have been] preserved in the wisdom of proverbs.

Bounded rationality is the idea that rationality is limited when individuals make decisions, and under these limitations, rational individuals will select a decision that is satisfactory rather than optimal.

Satisficing is a decision-making strategy or cognitive heuristic that entails searching through the available alternatives until an acceptability threshold is met. The term satisficing, a portmanteau of satisfy and suffice, was introduced by Herbert A. Simon in 1956, although the concept was first posited in his 1947 book Administrative Behavior. Simon used satisficing to explain the behavior of decision makers under circumstances in which an optimal solution cannot be determined. He maintained that many natural problems are characterized by computational intractability or a lack of information, both of which preclude the use of mathematical optimization procedures. He observed in his Nobel Prize in Economics speech that "decision makers can satisfice either by finding optimum solutions for a simplified world, or by finding satisfactory solutions for a more realistic world. Neither approach, in general, dominates the other, and both have continued to co-exist in the world of management science".

<span class="mw-page-title-main">Behavioral economics</span> Academic discipline

Behavioral economics is the study of the psychological, cognitive, emotional, cultural and social factors involved in the decisions of individuals or institutions, and how these decisions deviate from those implied by classical economic theory.

<span class="mw-page-title-main">Decision theory</span> Branch of applied probability theory

Decision theory or the theory of rational choice is a branch of probability, economics, and analytic philosophy that uses the tools of expected utility and probability to model how individuals should behave rationally under uncertainty. It differs from the cognitive and behavioral sciences in that it is prescriptive and concerned with identifying optimal decisions for a rational agent, rather than describing how people really do make decisions. Despite this, the field is extremely important to the study of real human behavior by social scientists, as it lays the foundations for the rational agent models used to mathematically model and analyze individuals in fields such as sociology, economics, criminology, cognitive science, and political science.

Neuroeconomics is an interdisciplinary field that seeks to explain human decision-making, the ability to process multiple alternatives and to follow through on a plan of action. It studies how economic behavior can shape our understanding of the brain, and how neuroscientific discoveries can guide models of economics.

Managerial economics is a branch of economics involving the application of economic methods in the organizational decision-making process. Economics is the study of the production, distribution, and consumption of goods and services. Managerial economics involves the use of economic theories and principles to make decisions regarding the allocation of scarce resources. It guides managers in making decisions relating to the company's customers, competitors, suppliers, and internal operations.

<span class="mw-page-title-main">Loss aversion</span> Overall description of loss aversion theory

In cognitive science and behavioral economics, loss aversion refers to a cognitive bias in which the same situation is perceived as worse if it is framed as a loss, rather than a gain. It should not be confused with risk aversion, which describes the rational behavior of valuing an uncertain outcome at less than its expected value.

A status quo bias or default bias is a cognitive bias which results from a preference for the maintenance of one's existing state of affairs. The current baseline is taken as a reference point, and any change from that baseline is perceived as a loss or gain. Corresponding to different alternatives, this current baseline or default option is perceived and evaluated by individuals as a positive.

As part of consumer behavior, the buying decision process is the decision-making process used by consumers regarding the market transactions before, during, and after the purchase of a good or service. It can be seen as a particular form of a cost–benefit analysis in the presence of multiple alternatives.

In psychology, the human mind is considered to be a cognitive miser due to the tendency of humans to think and solve problems in simpler and less effortful ways rather than in more sophisticated and effortful ways, regardless of intelligence. Just as a miser seeks to avoid spending money, the human mind often seeks to avoid spending cognitive effort. The cognitive miser theory is an umbrella theory of cognition that brings together previous research on heuristics and attributional biases to explain when and why people are cognitive misers.

Group decision-making is a situation faced when individuals collectively make a choice from the alternatives before them. The decision is then no longer attributable to any single individual who is a member of the group. This is because all the individuals and social group processes such as social influence contribute to the outcome. The decisions made by groups are often different from those made by individuals. In workplace settings, collaborative decision-making is one of the most successful models to generate buy-in from other stakeholders, build consensus, and encourage creativity. According to the idea of synergy, decisions made collectively also tend to be more effective than decisions made by a single individual. In this vein, certain collaborative arrangements have the potential to generate better net performance outcomes than individuals acting on their own. Under normal everyday conditions, collaborative or group decision-making would often be preferred and would generate more benefits than individual decision-making when there is the time for proper deliberation, discussion, and dialogue. This can be achieved through the use of committee, teams, groups, partnerships, or other collaborative social processes.

The framing effect is a cognitive bias in which people decide between options based on whether the options are presented with positive or negative connotations. Individuals have a tendency to make risk-avoidant choices when options are positively framed, while selecting more loss-avoidant options when presented with a negative frame. In studies of the bias, options are presented in terms of the probability of either losses or gains. While differently expressed, the options described are in effect identical. Gain and loss are defined in the scenario as descriptions of outcomes, for example, lives lost or saved, patients treated or not treated, monetary gains or losses.

Heuristics is the process by which humans use mental shortcuts to arrive at decisions. Heuristics are simple strategies that humans, animals, organizations, and even machines use to quickly form judgments, make decisions, and find solutions to complex problems. Often this involves focusing on the most relevant aspects of a problem or situation to formulate a solution. While heuristic processes are used to find the answers and solutions that are most likely to work or be correct, they are not always right or the most accurate. Judgments and decisions based on heuristics are simply good enough to satisfy a pressing need in situations of uncertainty, where information is incomplete. In that sense they can differ from answers given by logic and probability.

In psychology, economics and philosophy, preference is a technical term usually used in relation to choosing between alternatives. For example, someone prefers A over B if they would rather choose A than B. Preferences are central to decision theory because of this relation to behavior. Some methods such as Ordinal Priority Approach use preference relation for decision-making. As connative states, they are closely related to desires. The difference between the two is that desires are directed at one object while preferences concern a comparison between two alternatives, of which one is preferred to the other.

The dual systems model, also known as the maturational imbalance model, is a theory arising from developmental cognitive neuroscience which posits that increased risk-taking during adolescence is a result of a combination of heightened reward sensitivity and immature impulse control. In other words, the appreciation for the benefits arising from the success of an endeavor is heightened, but the appreciation of the risks of failure lags behind.

Valerie F. Reyna is an American psychologist and Professor of Human Development at Cornell University and an expert on false memory and risky decision making.

Emotional choice theory is a social scientific action model to explain human decision-making. Its foundation was laid in Robin Markwica’s monograph Emotional Choices published by Oxford University Press in 2018. It is associated with its own method for identifying emotions and tracing their influences on decision-making. Emotional choice theory is considered an alternative model to rational choice theory and constructivist perspectives.

References

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