Decision-making can be regarded as the cognitive process resulting in the selection of a belief or a course of action among several alternative possibilities. Every decision-making process produces a final choice that may or may not prompt action. Decision-making is the study of identifying and choosing alternatives based on the values and preferences of the decision maker. Decision-making is one of the central activities of management and is a huge part of any process of implementation.
- 1 Overview
- 2 Rational and irrational decision-making
- 3 Information overload
- 4 Problem analysis & decision-making
- 5 Everyday techniques
- 6 Stages of group decision-making
- 7 Decision-making steps
- 8 Cognitive and personal biases
- 9 Post-decision analysis
- 10 Cognitive styles
- 11 Neuroscience
- 12 Decision-making in adolescents vs. adults
- 13 See also
- 14 References
- 15 External links
Human performance with regard to decisions has been the subject of active research from several perspectives:
- Psychological: examining individual decisions in the context of a set of needs, preferences and values the individual has or seeks.
- Cognitive: the decision-making process regarded as a continuous process integrated in the interaction with the environment.
- Normative: the analysis of individual decisions concerned with the logic of decision-making and rationality and the invariant choice it leads to.
Decision-making can also be regarded as a problem-solving activity terminated by a solution deemed to be satisfactory. It is, therefore, a reasoning or emotional process which can be rational or irrational and can be based on explicit assumptions or tacit assumptions. Rational choice theory encompasses the notion that people try to maximize benefits while minimizing costs.
Some have argued that most decisions are made unconsciously. Jim Nightingale states that "we simply decide without thinking much about the decision process." In a controlled environment, such as a classroom, instructors might try to encourage students to weigh pros and cons before making a decision. This strategy is known as Franklin's rule. However, because such a rule requires time, cognitive resources and full access to relevant information about the decision, this rule may not best describe how people make decisions.
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. Some[which?] research using naturalistic methods shows, however, that in situations with higher time pressure, higher stakes, or increased ambiguities, experts use intuitive decision-making rather than structured approaches – following a recognition primed decision that fits their experience – and arrive at a course of action without weighing alternatives. Recent robust decision research has formally integrated uncertainty into its decision-making model. Decision analysis recognized and included uncertainties in its theorizing since its conception in 1964.
A major part of decision-making involves the analysis of a finite set of alternatives described in terms of evaluative criteria. Information overload occurs when there is a substantial gap between the capacity of information and the ways in which people may or can adapt. The overload of information can be related to problem≠ processing and tasking, which effects decision-making. These criteria may be benefit or cost in nature. Then the problem 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 goal might be to just 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 multi-criteria decision analysis (MCDA), also known as multi-criteria decision-making (MCDM). This area of decision-making, although very old, has attracted the interest of many researchers and practitioners and is still highly debated as there are many MCDA/MCDM methods which may yield very different results when they are applied on exactly the same data. This leads to the formulation of a decision-making paradox.
In regards to management and decision-making, each level of management is responsible for different things. Top level managers look at and create strategic plans where the organization's vision, goals, and values are taken into account to create a plan that is cohesive with the mission statement. For mid-level managers, tactical plans are created with specific steps with actions that need to be executed to meet the strategic objective. Finally, the front-line managers are responsible for creating and executing operational plans. These plans include the policies, processes, and procedures of the organization. Each must take into account the overall goals and processes of the organization.
The environment can also play a part in the decision making process. It is important to know that environmental complexity is a factor that influences cognitive function and well being.  A complex environment is an environment with a large number of different possible states which come and go over time.  It is in different states at different times and different in different places as opposed to the same all over.  Peter Godfrey-Smith, professor at Stamford University, states "whether a particular type of complexity is relevant to an organism depends on what the organism is like- size, needs, habits and physiology."  Studies done at the University of Colorado have shown that more complex environments correlate with higher cognitive function meaning a decision can be influenced by the location. The experiment measured complexity in a room by the number of small objects and appliances present whereas 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.
Rational and irrational decision-making
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. This theory states that people make decisions by determining the likelihood of a potential outcome, the value of the outcome, multiplying the two, and then choosing the more positive of the two outcomes. For example, with a 50% chance of winning $20 or a 90% chance of winning $10, people are thought to be more likely to choose the first option (.50 X $20 = $10 : .90 X $10 = $9 :: $10 > $9).
In reality, however, there are some factors that affect decision-making abilities and cause people to make irrational decisions, one of them being availability bias. Availability bias is the tendency for some items that are more readily available in memory to be judged as more frequently occurring. For example, someone who watches a lot of movies about terrorist attacks may think the frequency of terrorism to be higher than it actually is.
Information overload is "a gap between the volume of information and the tools we need to assimilate it." It is proven in some studies[which?] that the more information overload, the worse the quality of decisions made. There are five factors:
- Personal Information Factors: personal qualifications, experiences, attitudes etc.
- Information Characteristics: information quality, quantity and frequency
- Tasks and Process: standardized procedures or methods
- Organizational Design: organizations' cooperation, processing capacity and organization relationship
- Information Technology: IT management, and general technology
Hall, Ariss & Todorov with an assistant Rashar phinyor (2007) described an illusion of knowledge, meaning that as individuals encounter too much knowledge it actually interferes with their ability to make rational decisions.
Problem analysis & decision-making
It is important to differentiate between problem analysis and decision-making. The concepts are completely separate from one another. Traditionally, it is argued that problem analysis must be done first, so that the information gathered in that process may be used towards decision-making.
- Problem analysis
- Analyze performance, what should the results be against what they actually are
- Problems are merely deviations from performance standards
- Problem must be precisely identified and described
- Problems are caused by a change from a distinctive feature
- Something can always be used to distinguish between what has and hasn't been affected by a cause
- Causes to problems can be deducted from relevant changes found in analyzing the problem
- Most likely cause to a problem is the one that exactly explains all the facts
- Objectives must first be established
- Objectives must be classified and placed in order of importance
- Alternative actions must be developed
- The alternative must be evaluated against all the objectives
- The alternative that is able to achieve all the objectives is the tentative decision
- The tentative decision is evaluated for more possible consequences
- The decisive actions are taken, and additional actions are taken to prevent any adverse consequences from becoming problems and starting both systems (problem analysis and decision-making) all over again
- There are steps that are generally followed that result in a decision model that can be used to determine an optimal production plan.
- In a situation featuring conflict, role-playing may be helpful for predicting decisions to be made by involved parties.
Making a decision without planning is fairly common, but does not often end well. Planning allows for decisions to be made comfortably and in a smart way. Planning makes decision-making a lot more simple than it is.
Decision will get four benefits out of planning: 1. Planning give chance to the establishment of independent goals. It is a conscious and directed series of choices. 2. Planning provides a standard of measurement. It is a measurement of whether you are going towards or further away from your goal. 3. Planning converts values to action. You think twice about the plan and decide what will help advance your plan best. 4. Planning allows for limited resources to be committed in an orderly way. Always govern the use of what is limited to you. (e.g. money, time, etc.)
Analysis paralysis is the state of over-analyzing (or over-thinking) a situation, or citing sources, so that a decision or action is never taken, in effect paralyzing the outcome.
Group decision-making techniques
- Consensus decision-making tries to avoid "winners" and "losers". Consensus requires that a majority approve a given course of action, but that the minority agree to go along with the course of action. In other words, if the minority opposes the course of action, consensus requires that the course of action be modified to remove objectionable features.
- Voting-based methods.
- Range voting lets each member score one or more of the available options. The option with the highest average is chosen. This method has experimentally been shown to produce the lowest Bayesian regret among common voting methods, even when voters are strategic.
- Majority requires support from more than 50% of the members of the group. Thus, the bar for action is lower than with unanimity and a group of "losers" is implicit to this rule.
- Plurality, where the largest block in a group decides, even if it falls short of a majority.
- Delphi method is structured communication technique for groups, originally developed for collaborative forecasting but has also been used for policy making.
- Dotmocracy is a facilitation method that relies on the use of special forms called Dotmocracy Sheets to allow large groups to collectively brainstorm and recognize agreement on an unlimited number of ideas they have authored.
Individual decision-making techniques
- Pros and cons: listing the advantages and disadvantages of each option, popularized by Plato and Benjamin Franklin. Contrast the costs and benefits of all alternatives. Also called "rational decision-making".
- Simple prioritization: choosing the alternative with the highest probability-weighted utility for each alternative (see Decision analysis).
- Satisficing: examining alternatives only until an acceptable one is found. Contrasted with maximizing, in which many or all alternatives are examined in order to find the best option.
- Elimination by aspects: choosing between alternatives using Mathematical psychology The technique was introduced by Amos Tversky in 1972. It is a covert elimination process that involves comparing all available alternatives by aspects. The decision-maker chooses an aspect; any alternatives without that aspect are then eliminated. The decision-maker repeats this process with as many aspects as needed until there remains only one alternative
- Preference trees: In 1979, Tversky and Shmuel Sattach updated the elimination by aspects technique by presenting a more ordered and structured way of comparing the available alternatives. This technique compared the alternatives by presenting the aspects in a decided and sequential order. It became a more hierarchical system in which the aspects are ordered from general to specific
- Acquiesce to a person in authority or an "expert"; "just following orders".
- Flipism: flipping a coin, cutting a deck of playing cards, and other random or coincidence methods
- Prayer, tarot cards, astrology, augurs, revelation, or other forms of divination.
- Taking the most opposite action compared to the advice of mistrusted authorities (parents, police officers, partners...)
- Opportunity cost: calculating the opportunity cost of each options and decide the decision.
- Bureaucratic: set up criteria for automated decisions.
- Political: negotiate choices among interest groups.
- Participative decision-making (PDM): a methodology in which a single decision-maker, in order to take advantage of additional input, opens up the decision-making process to a group for a collaborative effort.
- Use of a structured decision-making method.
Individual decision-making techniques can often be applied by a group as part of a group decision-making technique.
A need to use software for a decision-making process is emerging for individuals and businesses. This is due to increasing decision complexity and an increase in the need to consider additional stakeholders, categories, elements or other factors that effect decisions.
Stages of group decision-making
According to B. Aubrey Fisher, there are four stages or phases that should be involved in all group decision-making:
- Orientation. Members meet for the first time and start to get to know each other.
- Conflict. Once group members become familiar with each other, disputes, little fights and arguments occur. Group members eventually work it out.
- Emergence. The group begins to clear up vague opinions by talking about them.
- Reinforcement. Members finally make a decision and provide justification for it.
It is said that critical norms in a group improves the quality of decisions, while the majority of opinions (called consensus norms) do not. This is due to collaboration between one another, and when group members get used to, and familiar with, each other, they will tend to argue and create more of a dispute to agree upon one decision. This does not mean that all group members fully agree; they may not want argue further just to be liked by other group members or to "fit in".
Each step in the decision-making process may include social, cognitive and cultural obstacles to successfully negotiating dilemmas. It has been suggested that becoming more aware of these obstacles allows one to better anticipate and overcome them. The Arkansas program presents eight stages of moral decision-making based on the work of James Rest:
- Establishing community: creating and nurturing 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.
- Perception: recognizing that a problem exists.
- Interpretation: identifying competing explanations for the problem, and evaluating the drivers behind those interpretations.
- Judgment: sifting through various possible actions or responses and determining which is more justifiable.
- Motivation: examining the competing commitments which may distract from a more moral course of action and then prioritizing and committing to moral values over other personal, institutional or social values.
- Action: following through with action that supports the more justified decision. Integrity is supported by the ability to overcome distractions and obstacles, developing implementing skills, and ego strength.
- Reflection in action.
- Reflection on action.
- Outline your goal and outcome.
- Gather data.
- Develop alternatives (i.e., brainstorming)
- List pros and cons of each alternative.
- Make the decision.
- Immediately take action to implement it.
- Learn from and reflect on the decision.
Cognitive and personal biases
Biases usually creep into decision-making processes. Many different people have made a decision about the same question (e.g. "Should I have a doctor look at this troubling breast cancer symptom I've discovered?" "Why did I ignore the evidence that the project was going over budget?") and then craft potential cognitive interventions aimed at improving the outcome of decision-making.
Here is a list of commonly debated biases in judgment and decision-making.
- Selective search for evidence (aka confirmation bias; Scott Plous, 1993). People tend to be willing to gather facts that support certain conclusions but disregard other facts that support different conclusions. Individuals who are highly defensive in this manner show significantly greater left prefrontal cortex activity as measured by EEG than do less defensive individuals.
- Premature termination of search for evidence. People tend to accept the first alternative that looks like it might work.
- Cognitive inertia. Unwillingness to change existing thought patterns in the face of new circumstances.
- Selective perception. We actively screen out information that we do not think is important (see also prejudice). In one demonstration of this effect, discounting of arguments with which one disagrees (by judging them as untrue or irrelevant) was decreased by selective activation of right prefrontal cortex.
- Wishful thinking. A tendency to want to see things in a certain – usually positive – light, which can distort perception and thinking.
- Choice-supportive bias occurs when people distort their memories of chosen and rejected options to make the chosen options seem more attractive.
- Recency. People tend to place more attention on more recent information and either ignore or forget more distant information (see semantic priming). The opposite effect in the first set of data or other information is termed primacy effect.
- Repetition bias. A willingness to believe what one has been told most often and by the greatest number of different sources.
- Anchoring and adjustment. Decisions are unduly influenced by initial information that shapes our view of subsequent information.
- Group think. Peer pressure to conform to the opinions held by the group.
- Source credibility bias. A tendency to reject a person's statement on the basis of a bias against the person, organization, or group to which the person belongs. People preferentially accept statement by others that they like (see prejudice).
- Incremental decision-making and escalating commitment. We look at a decision as a small step in a process and this tends to perpetuate a series of similar decisions. This can be contrasted with "zero-based decision-making" (see slippery slope).
- Attribution asymmetry. People tend to attribute their own success to internal factors, including abilities and talents, but explain their failures in terms of external factors such as bad luck. The reverse bias is shown when people explain others' success or failure.
- Role fulfillment. A tendency to conform to others' decision-making expectations.
- Underestimating uncertainty and the illusion of control. People tend to underestimate future uncertainty because of a tendency to believe they have more control over events than they really do.
- Framing bias. This is best avoided by using numeracy with absolute measures of efficacy.
- Sunk-cost fallacy. A specific type of framing effect that affects decision-making. It involves an individual making a decision about a current situation based on what they have previously invested in the situation. A possible example to this would be an individual that is refraining from dropping a class that that they are most likely to fail, due to the fact that they feel as though they have done so much work in the course thus far.
- Prospect theory. Involves the idea that when faced with a decision-making event, an individual is more likely to take on a risk when evaluating potential losses, and are more likely to avoid risks when evaluating potential gains. This can influence one's decision-making depending if the situation entails a threat, or opportunity.
Reference class forecasting was developed to eliminate or reduce cognitive biases in decision-making.
Influence of Myers-Briggs type
According to behavioralist Isabel Briggs Myers, a person's decision-making process depends to a significant degree on their cognitive style. 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[who?] psychologists say that the MBTI lacks reliability and validity and is poorly constructed.
Other studies suggest that these national or cross-cultural differences 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.
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 recognise that a decision turned out to be sub-optimal).
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.”
In his book, 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. According to Katsenelinboigen, the two styles reflect two basic approaches to the uncertainty: deterministic (combinational style) and indeterministic (positional style). Katsenelinboigen’s definition of the two styles are the following.
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The combinational style is characterized by:
- a very narrow, clearly defined, primarily material goal; and
- a program that links the initial position with the final outcome.
In defining the combinational style in chess, Katsenelinboigen writes:
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.
The positional style is distinguished by:
- a positional goal; and
- a formation of semi-complete linkages between the initial step and final outcome.
“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."
The positional style serves to:
- create a predisposition to the future development of the position;
- induce the environment in a certain way;
- absorb an unexpected outcome in one’s favor;
- avoid the negative aspects of unexpected outcomes.
- "As the game progressed and defense became more sophisticated the combinational style of play declined. ... The positional style of chess does not eliminate the combinational one with its attempt to see the entire program of action in advance. The positional style merely prepares the transformation to a combination when the latter becomes feasible.”
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 recent neuroimaging study 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.
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 but also signal the degree of certainty (or "confidence") associated with the decision. Another recent 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. A 2012 study found that rats and humans can optimally accumulate incoming sensory evidence, to make statistically optimal decisions.
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 outcome. 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. A recent lesion mapping study of 152 patients with focal brain lesions conducted by Barbey and colleagues provides evidence to help characterize the neural mechanisms of emotional intelligence.
Although it is unclear whether the studies generalize to all processing, subconscious processes have been implicated in the initiation of conscious volitional movements. See the Neuroscience of free will.
Decision-making in adolescents vs. adults
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During their adolescent years, teens are known for their high-risk behaviors and rash decisions. There has not, however, been that much research in this area. Recent research has shown, though, that there are some 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, capacities that influence decision-making. Examples 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.
Recent research 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.
This is why 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.
- Daniel Kahneman, Amos Tversky (2000). Choice, Values, Frames. Cambridge University Press. ISBN 0-521-62172-0.
- Schacter, Gilbert, Wegner (2011). Psychology. Worth. p. 369.
- J. Nightingale (2008). Think Smart - Act Smart: Avoiding The Business Mistakes That Even Intelligent People Make. John Wiley & Sons. p. 1. ISBN 9780470224366.
- Kutty, Ambalika D., and Himanshu Kumar Shee. "Too much info!" Monash Business Review 3.3 (2007): 8+. Academic OneFile. Web. 3 Mar. 2013.
- Triantaphyllou, E. (2000). Multi-Criteria Decision Making: A Comparative Study. Dordrecht, Netherlands: Kluwer Academic Publishers (now Springer). p. 320. ISBN 0-7923-6607-7.
- Schacter, Gilbert, Wegner (2011). Psychology. Worth. pp. 368–370.
- Quoted sentenced saide by Paul Saffo; website written by John Foley. "Managing Information: Infoglut". Retrieved 2013-04-19.
- Hall, C.C., Ariss, L. & Todorov, A. 2007. The illusion of knowledge: When more information reduces accuracy and increases confidence. Organizational Behavior and Human Decision Processes, 103: 277-290
- Kepner, Charles H.; Tregoe, Benjamin B. (1965). "The Rational Manager: A Systematic Approach to Problem Solving and Decision-Making". McGraw-Hill.
- Monahan, G. (2000). Management Decision Making. Cambridge: Cambridge University Press. pp. 33–40. ISBN 0-521-78118-3.
- J. Scott Armstrong (2001). Principles of Forecasting: A Handbook for Researchers and Practitioners. Kluwer Academic Publishers.
- "Decision Making Techniques". Virtualsalt.com. 1998-07-03. Retrieved 2012-11-03.
- Leicherova, V., Januska, M. Recommendations for the Selection of the Appropriate Decision-Making Style for the Selected Problem Situations Using the Vroom-Yetton-Jago Model. In Vision 2020: Innovation Development Sustainability Economic Growth. Wien: International Business Information Management Association (IBIMA), 2013. s. 908-920. ISBN 978-0-9860419-0-7
- Bell Jr., Whitfield J., ed. (1956). Mr. Franklin: A Selection from His Personal Letters. New Haven, CT: Yale University Press.
- Benjamin Franklin's 1772 letter to Joseph Priestley - ProCon.org
- Batley, Richard; Daly, Andrew (October 2006). "On the equivalence between elimination-by-aspects and generalised extreme value models of choice behaviour". Journal of Mathematical Psychology 50 (5): 456–467. doi:10.1016/j.jmp.2006.05.003.
- Tversky, Amos (July 1972). "Elimination by aspects: A theory of choice". Psychological Review 79 (4): 281–299. doi:10.1037/h0032955.
- Tversky, Amos; Sattath, Shmuel (November 1979). "Preference trees". Psychological Review 86 (6): 542–573. doi:10.1037/0033-295X.86.6.542.
- Random Decision Making App for Windows 8 devices
- Krapohl, Donald. "A Structured Methodology for Group Decision Making". AugmentedIntel.com. AugmentedIntel. Retrieved 26 April 2013.
- B. Aubrey Fisher. "Interact System Model of Decision Emergence". McGraw - Hill. Retrieved 3 May 2014.
- Postmes, T; Spears, Russell; Cihangir, Sezgin (2001). "Quality of decision making and group norms". Journal of Personality and Social Psychology 80 (6): 918–930. doi:10.1037/0022-3518.104.22.1688. PMID 11414374.
- The Role of Learning Theory in Building Effective College Ethics Curricula. Pijanowski. 2009, p.6. Retrieved 2012-01-12.
- Career coach - decision-making, Pulse, November 29, 2007, retrieved July 12, 2012 (subscription required)
- Blackhart, G. C.; Kline, J. P. (2005). "Individual differences in anterior EEG asymmetry between high and low defensive individuals during a rumination/distraction task". Personality and Individual Differences 39 (2): 427–437. doi:10.1016/j.paid.2005.01.027.
- Drake, R. A. (1993). "Processing persuasive arguments: 2. Discounting of truth and relevance as a function of agreement and manipulated activation asymmetry". Journal of Research in Personality 27 (2): 184–196. doi:10.1006/jrpe.1993.1013.
- Chua, E. F.; Rand-Giovannetti, E.; Schacter, D. L.; Albert, M.; Sperling, R. A. (2004). "Dissociating confidence and accuracy: Functional magnetic resonance imaging shows origins of the subjective memory experience". Journal of Cognitive Neuroscience 16 (7): 1131–1142. doi:10.1162/0898929041920568. PMID 15453969.
- Plous, 1993
- Perneger, T. V.; Agoritsas, T. (2011). "Doctors and Patients' Susceptibility to Framing Bias: A Randomized Trial". J Gen Intern Med 26 (12): 1411–1417. doi:10.1007/s11606-011-1810-x. PMC 3235613. PMID 21792695.
- Schacter, Gilbert, Wegner (2011)Psychology (2nd Edition), page 372, Worth Publishers
- Schacter, Gilbert, Wegner (2011) Psychology (2nd Edition), page 373, Worth Publishers.
- Myers, I. (1962) Introduction to Type: A description of the theory and applications of the Myers-Briggs type indicator, Consulting Psychologists Press, Palo Alto Ca., 1962.
- Martinsons, Maris G., Comparing the Decision Styles of American, Chinese and Japanese Business Leaders. Best Paper Proceedings of Academy of Management Meetings, Washington, DC, August 2001 
- "The science behind making decisions". Pri.Org. 2009-05-29. Retrieved 2012-11-03.
- Katsenelinboigen, Aron. The Concept of Indeterminism and Its Applications: Economics, Social Systems, Ethics, Artificial Intelligence, and Aesthetics. Praeger: Westport, Connecticut, 1997, p. 6.
- V. Ulea, The Concept of Dramatic Genre and The Comedy of A New Type. Chess, Literature, and Film. Southern Illinois University Press, 2002, pp. 17–18
- Selected Topics in Indeterministic Systems, Intersystems Publications: California, 1989, p. 21.
- Interactions between decision making and performance monitoring within prefrontal cortex
- Damasio, AR (1994). Descarte's Error: Emotion, reason and the human brain. New York: Picador. ISBN 0-333-65656-3.
- Roozbeh Kiani and Michael N. Shadlen, Representation of Confidence Associated with a Decision by Neurons in the Parietal Cortex
- Kennerly, et al. (2006)
- Brunton, et al. (2012)
- Nasir Naqvi, et al. "The Role of Emotion in Decision Making: A Cognitive Neuroscience Perspective", Current Directions in Psychological Science, doi:10.1111/j.1467-8721.2006.00448.x
- Barbey, Aron K.; Colom, Roberto; Grafman, Jordan. "Distributed neural system for emotional intelligence revealed by lesion mapping". Social Cognitive and Affective Neuroscience 9 (3): 265–272. doi:10.1093/scan/nss124.
- Yates, Diana. "Researchers Map Emotional Intelligence in the Brain". University of Illinois News Bureau. University of Illinois.
- HealthDay (2013-01-28). "Scientists Complete 1st Map of 'Emotional Intelligence' in the Brain". US News and World Report.
- Gardner, M.; Steinberg, L. (2005). "Peer Influence on Risk Taking, Risk Preference, and Risky Decision Making in Adolescence and Adulthood: An Experimental Study". Developmental Psychology 41 (4): 625. doi:10.1037/0012-1622.214.171.1245. PMID 16060809.
- Steinberg, L. (2007). "Risk Taking in Adolescence: New Perspectives". Brain and Behavioral Science 16 (2): 55–59. doi:10.1111/j.1467-8721.2007.00475.x.
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