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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.
Human performance with regard to decisions has been the subject of active research from several perspectives:
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.
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:
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.
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.
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.
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.
According to B. Aubrey Fisher, there are four stages or phases that should be involved in all group decision-making:
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:
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.
Reference class forecasting was developed to eliminate or reduce cognitive biases in decision-making.
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.
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).
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:
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:
“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:
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.
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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.
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