More generally, decision-making is the cognitive process
of selecting a course of action from among multiple alternatives. Common
examples include shopping
and deciding what to eat. Decision-making is said to be a psychological
construct. This means that although we can never "see" a decision, we
can infer from observable behaviour that a decision has been made. Therefore we
conclude that a psychological event that we call "decision making"
has occurred. It is a construction that imputes commitment to action. That is,
based on observable actions, we assume that people have made a commitment to
effect the action.
In general there are three ways of analyzing
consumer buying decisions. They are:
Economic models - These models are largely
quantitative and are based on the assumptions of rationality and near perfect
knowledge. The consumer is seen to maximize their utility. See consumer theory. Game theory can also be
used in some circumstances.
Psychological models - These models
concentrate on psychological and cognitive processes such as motivation and
need recognition. They are qualitative rather than quantitative and build on sociological
factors like cultural influences and family influences.
Consumer behaviour models - These are
practical models used by marketers. They typically blend both economic and
psychological models.
Neuroscience has become
both a useful tool and a source of theory development and testing in buyer
decision-making research, and using neuroimaging devices in order to
investigate consumer behavior developed under the name of Neuromarketing. What is
going on inside the head of the consumer as measured by various neuroimaging
and biological correlates like genes and hormones can provide new insights and
new ways to test theory, so this is a great opportunity for the decision-making
researcher.[1]
There are 5 stages which a consumer often
goes through when he/she around their Purchase. These stages also exist because
of normal human psychology. These 5 stages are:
- Problem/Need Recognition- This is in general the first stage in which the consumer recognizes that what essentially is the problem or need and hence accordingly a consumer can identify the product or kind of product, which would be required by the consumer. Page text.[2]
- Information Search- In information search, the consumer searches about the product, which would satisfy the need, which has been recognized by the consumer in the stage previous to this one.[2]
- Evaluation of Alternatives - In this stage, the consumer evaluates the different alternatives which the consumer comes across, when the consumer was searching for information. Generally in the information search the consumer comes across quite a few products and thus now the consumer has to evaluate and understand which product would be properly suited for the consumer.[2]
- Purchase- After the consumer has evaluated all the options and would be having the intention to buy any product, there could be now only two things which might just change the decision of the consumer of buying the product that is what the other peers of the consumer think of the product and any unforeseen circumstances. Unforeseen circumstances for example in this case could be financial losses, which led to not buying of the product.[2]
- Post Purchase Behavior- After the purchase the consumer might just go through post purchase dissonance in which the consumer feels that buying the other product would be better. But a company should really take care of it, taking care of post purchase dissonance doesn't only spread good words for the product but also increases the chance of frequent repurchase.[2]
Nobel laureate Herbert A. Simon sees economic decision making
as a vain attempt to be rational. He claims (in 1947 and 1957) that if a
complete analysis is to be done, a decision will be immensely complex. He also
says that peoples' information processing ability is very limited. The
assumption of a perfectly rational
economic actor is unrealistic. Often we are influenced by emotional and
non-rational considerations. When we try to be rational we are at best only
partially successful.
Models of Buyer Decision Making
In an early study of the buyer decision
process literature, Frank Nicosia (Nicosia, F. 1966; pp 9–21) identified three
types of buyer decision-making models. They are the univariate model (He
called it the "simple scheme".) in which only one behavioural
determinant was allowed in a stimulus-response
type of relationship; the multi-variate model (He called it a "reduced
form scheme".) in which numerous independent
variables were assumed to determine buyer behaviour; and finally the
"system of equations" model (He called it a "structural
scheme" or "process scheme".) in which numerous functional
relations (either univariate or multi-variate) interact in a complex system of
equations.
He concluded that only this third type of
model is capable of expressing the complexity of buyer decision processes. In
chapter 7, Nicosia builds a comprehensive model involving five modules. The
encoding module includes determinants like "attributes of the brand",
"environmental factors", "consumer's attributes",
"attributes of the organization", and "attributes of the
message". Other modules in the system include, consumer decoding, search
and evaluation, decision and consumption.
Some neuromarketing research
papers examined how approach motivation as indexed by electroencephalographic
(EEG) asymmetry over the prefrontal cortex predicts purchase decision when
brand and price are varied. In a within-subjects design, the participants were
presented purchase decision trials with 14 different grocery products (seven
private label and seven national brand products) whose prices were increased
and decreased while their EEG activity was recorded. The results showed that
relatively greater left frontal activation (i.e., higher approach motivation)
during the pre-decision period predicted an affirmative purchase decision.
The
relationship of frontal EEG asymmetry with purchase decision was stronger for
national brand products compared with private label products and when the price
of a product was below a normal price (i.e., implicit reference price) compared
with when it was above a normal price. Higher perceived need for a product and
higher perceived product quality were associated with greater relative left
frontal activation.[3]
Cognitive and Personal Biases in Decision
Making
It is generally agreed that biases can creep into our
decision making processes, calling into question the correctness of a decision.
Below is a list of some of the more common cognitive biases.
Selective search for evidence - We tend to be
willing to gather facts
that support certain conclusions but disregard other facts that support different
conclusions.
- Selective perception - We actively screen out information that we do not think is salient.
- Premature termination of search for evidence - We tend to accept the first alternative that looks like it might work.
- Conservatism and inertia - Unwillingness to change thought patterns that we have used in the past in the face of new circumstances.
- Experiential limitations - Unwillingness or inability to look beyond the scope of our past experiences; rejection of the unfamiliar.
- Wishful thinking or optimism - We tend to want to see things in a positive light and this can distort our perception and thinking.
- Recency - We tend to place more attention on more recent information and either ignore or forget more distant information.
- Repetition bias - A willingness to believe what we have been told most often and by the greatest number of different of sources.
- Anchoring - 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 - We reject something if we have a bias against the person, organization, or group to which the person belongs: We are inclined to accept a statement by someone we like.
- 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.
- Inconsistency - The unwillingness to apply the same decision criteria in similar situations.
- Attribution asymmetry - We tend to attribute our success to our abilities and talents, but we attribute our failures to bad luck and external factors. We attribute other's success to good luck, and their failures to their mistakes.
- Role fulfillment - We conform to the decision-making expectations that others have of someone in our position.
- Underestimating uncertainty and the illusion of control - We tend to underestimate future uncertainty because we tend to believe we have more control over events than we really do.
- Faulty generalizations - In order to simplify an extremely complex world, we tend to group things and people. These simplifying generalizations can bias decision-making processes.
- Ascription of causality - We tend to ascribe causation even when the evidence only suggests correlation. Just because birds fly to the equatorial regions when the trees lose their leaves, does not mean that the birds migrate because the trees lose their leaves.
Cognition
In science, cognition is the
set of all mental
abilities and processes
related to knowledge:
attention, memory & working memory, judgment & evaluation, reasoning & "computation", problem solving & decision making, comprehension & production
of language, etc. Human
cognition is conscious and unconscious, concrete or abstract, as well as
intuitive (like knowledge of a language) and conceptual (like a model of a
language). Cognitive processes use existing knowledge and generate new
knowledge.
These processes are analyzed from different
perspectives within different contexts, notably in the fields of linguistics, anesthesia, neuroscience, psychiatry, psychology, education, philosophy, anthropology, biology, systemics, and computer science.[1][page needed]
These and other different approaches to the analysis of cognition are
synthesized in the developing field of cognitive science,
a progressively autonomous academic
discipline. Within psychology and philosophy, the concept of
cognition is closely related to abstract concepts such as mind and intelligence. It
encompasses the mental
functions, mental
processes (thoughts),
and states of intelligent
entities (humans,
collaborative groups, human organizations, highly autonomous machines, and artificial
intelligences).[2]
Thus, the term's usage varies across
disciplines; for example, in psychology
and cognitive
science, "cognition" usually refers to an information
processing view of an individual's psychological functions.
It is also used in a branch of social psychology
called social
cognition to explain attitudes,
attribution,
and group dynamics.[3]
In cognitive psychology and cognitive engineering, cognition is typically
assumed to be information processing in a participant or operator’s mind or
brain.[2]
Cognition can in some specific and abstract sense also be artificial.[4]
Group Dynamics
Group dynamics is a system of behaviors and
psychological processes occurring within a social group (intragroup
dynamics), or between social groups (intergroup dynamics). The study of group
dynamics can be useful in understanding decision-making behavior, tracking the
spread of diseases in society, creating effective therapy techniques, and
following the emergence and popularity of new ideas and technologies.[1]
Group dynamics are at the core of understanding racism, sexism, and other forms
of social prejudice and discrimination. These applications of the field are
studied in psychology,
sociology, anthropology, political science,
epidemiology, education, social work, business, and
communication
studies.
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REFERENCES
- Yoon, C.; Gonzalez, R.; Bechara, A.; Berns, G. S.; Dagher, A. A.; Dube, L.; Huettel, S. A.; Kable, J. W.; Liberzon, I.; Plassmann, H.; Smidts, A.; Spence, C. (2012). "Decision neuroscience and consumer decision making". Marketing letters (Springer Science+Business Media, LLC 2012) 23: 473–485. doi:10.1007/s11002-012-9188-z.
- Kotler, Philip. "dl.ueb.edu.vn/bitstream/1247/2250/1/Marketing_Management_-_Millenium_Edition.pdf". Pearson Customer Publishing. Retrieved 28 December 2012.
- Niklas Ravaja, Outi Somervuori and Mikko Salminen (2012) Predicting purchase decision The role of hemispheric asymmetry over the frontal cortex, Journal of Neuroscience, Psychology, and Economics
- Carlyn, Marcia. “An Assessment of the Myers-Briggs Type Indicator.” Journal of Personality Assessment. 41.5 (1977): 461-73.
- Cheng, Many M., Peter F. Luckett, and Axel K. Schulz. “The Effects of Cognitive Style Diversity on Decision-Making Dyads: An Empirical Analysis in the Context of a Complex Task.” Behavioral Research in Accounting. 15 (2003): 39-62.
- Gardner, William L., and Mark J. Martinko. “Using the Myers-Briggs Type Indicator to Study Managers: A Literature Review and Research Agenda.” Journal of Management. 22.1 (1996): 45-83.
- Henderson, John C., and Paul C. Nutt. “Influence of Decision Style on Decision Making Behavior.” Management Science. 26.4 (1980): 371-386.
- Kennedy, Bryan R., and Ashely D. Kennedy. “Using the Myers-Briggs Type Indicator in Career Counseling.” Journal of Employment Counseling. 41.1 (2004): 38-44.
- Bettman, James R. (1979). "An Information Processing Theory of Consumer Choice." Addison-Wesley Educational Publishers.
- Yang, Haiyang and Ziv Carmon (2010), “Consumer Decision Making,” in Jagdeth Sheth & Naresh Malhotra (eds.), Wiley International Encyclopedia of Marketing, New York: Wiley.
- 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.
- Nicosia, F. (1966) Consumer Decision Processes, Prentice Hall, Englewood Cliffs, 1966.
- Pittenger, David J. “The Utility of the Myers-Briggs Type Indicator.” Review of Educational Research. 63:4 (1993): 467-488.
- Simon, H. (1947) Administrative behaviour, Macmillan, New York, 1947, (also 2nd edition 1957).
- Volkema, Roger J., and Ronald H. Gorman. "The Influence of Cognitive-Based Group Composition on Decision-Making Process and Outcome." Journal of Management Studies. 35.1 (1998): 105-121.
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