There are generally three ways of analyzing consumer buying decisions: •
Economic models – largely quantitative and are based on the assumptions of rationality and near perfect knowledge. The consumer is seen to maximize its utility. See
consumer theory.
Game theory can also be used in some circumstances. •
Psychological models – 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 behavior models – practical models used by marketers. They typically blend both economic and psychological models. 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 behavioral 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 behavior; and finally the
"system of equations" model (He called it a "structural scheme" or "process scheme".) in which numerous functional relations (either univariate or multivariate) 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. In recent years, the rise of digital ecosystems has led to the development of the
Online Consumer Decision Journey (OCDJ) model. This model highlights how digital touchpoints—such as social media, influencer content, and recommendation algorithms—disrupt the traditional linear decision-making path. For instance,
McKinsey’s Circular Decision Journey (2009) emphasizes that post-purchase experience feeds directly into future decision-making, forming a continuous loop rather than a straight line. Some
neuromarketing research papers examined how to 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 have presented purchase decision trials with 14 different grocery products (seven private labels 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 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. The higher perceived need for a product and higher perceived product quality were associated with greater relative left frontal activation. For any high-involvement product category, the decision-making time is normally long and buyers generally evaluate the information available very cautiously. They also utilize an active information search process. The risk associated with such a decision is very high. ==Neuroscience==