Correct option is A
The Compensatory decision-making rule involves evaluating each alternative in terms of each relevant attribute and computing a total score by summing up weighted attributes. The basic premise is that a high rating on one attribute can compensate for a low rating on another. This method assumes that the consumer is highly involved in the purchase and has access to detailed attribute information for each brand.
In the scenario described, the consumer evaluates multiple brands, assigns weights to each attribute (such as price, processor, brand reputation, battery life), and calculates an overall score for each brand. The brand with the highest total score is chosen. This step-by-step quantitative comparison is characteristic of the compensatory model.
Information Booster:
Compensatory rules are rational and deliberate, used especially in high-involvement purchases like laptops.
Consumers using this method tend to gather extensive information.
They assign importance weights to each attribute.
They compute a weighted sum of ratings for each alternative.
The brand with the highest overall utility or score is selected.
It is ideal for expensive and durable goods where detailed comparison is warranted.
It allows for trade-offs: one weak feature can be offset by another strong one.
Additional Knowledge:
(b) Conjunctive Rule: In this model, the consumer sets minimum acceptable cutoffs for each attribute and eliminates options that do not meet these cutoffs. It’s a non-compensatory rule, meaning no trade-offs are allowed — a poor score in any one attribute leads to elimination, regardless of other scores.
(c) Affect Referral Rule: Here, the consumer makes a decision based on overall impression or affect (emotional response) rather than specific attribute evaluations. It's intuitive and fast, often used when a consumer already has a favorite brand and skips rational analysis.
(d) Lexicographic Rule: In this approach, the consumer chooses the brand that scores highest on the most important attribute. If there's a tie, the process continues with the second most important attribute, and so on. This method does not consider total scores, and there's no compensation among attributes.
