MARK1001 Chap.7 Attitudes and Behaviour
Attitudes and Behaviour
Attitude measures depend on the response task: ratings, rankings, choices and open associations do not provide identical evidence. Aggregate results can remain stable while individuals change responses, and usage can shape attitudes as well as follow them.
This chapter applies the response-level relation RR = RL + 20 and the Theory of Planned Behaviour, which separates attitude, subjective norm and perceived control before intention and action. The empirical relation is an aggregate response benchmark expressed in percentage points, not a buying probability or proof of causation.
The planned-behaviour model helps locate a weak evaluation, social expectation or control belief, but intention remains intermediate. Actual opportunity, habit and changed circumstances must be observed before a marketer interprets non-action as failed persuasion.
What this chapter covers
- 01
Attitude measurement
- 02
Response stability
- 03
Aggregate patterns
- 04
Attitude and usage
- 05
Response-level relation
- 06
Subjective norm
- 07
Perceived control
Worked example · free
A control barrier blocks favourable intention
- +1State that attitude appears favourable.
- +1State that subjective norm appears supportive.
- +1Identify weak perceived and actual control caused by opening hours.
- +1Extend access or add an after-hours return option.
- +1Measure completed returns among previously constrained workers.
Key terms
- Attitude
- An evaluation of an object, brand, behaviour or idea observed through a defined measurement task.
- Perceived control
- A consumer's belief about their capability and opportunity to perform a behaviour.
- Response level
- The proportion of a sample giving a specified attitudinal response on the first occasion.
- Subjective norm
- Perceived social pressure from important others concerning a behaviour.
Attitudes and Behaviour FAQ
Why can aggregate attitudes look stable?
A similar percentage can endorse an attribute in two waves even when different individuals supply the response. Aggregate stability therefore does not establish individual stability. Repeated-response analysis must identify the same respondents and consider response level, wording and ordinary measurement variation.
How do I use the RR relation?
Apply RR = RL + 20 using percentage points. If response level is 45%, predicted repeat rate is 65%. Treat the result as an aggregate empirical benchmark, not an individual purchase probability or proof that the attitude causes behaviour.
What blocks intention from becoming behaviour?
Actual opportunity, perceived control, habit and changed circumstances can interrupt the path. The Theory of Planned Behaviour directs attention to evaluation, social pressure and capability, but measurement should still include the behaviour itself and whether the consumer genuinely had a chance to perform it.
Exam move
Practise converting rating, ranking and choice questions into statements about exactly what was measured. Plot several RL values with RR twenty points higher and label the units. For each planned-behaviour case, diagnose whether attitude, norm or control is weakest, then propose an intervention and a behavioural outcome measure. Start with measurement wording.
A rating, agreement item, ranking, choice task and behavioural record reveal different things, so rewrite every result as a precise claim about the response obtained. Separate attitude toward an object from attitude toward performing a behaviour. Record the target, action, context and time when the distinction matters. Build a two-wave table that shows stable group percentages alongside changing individual answers.
Explain why aggregate stability does not establish individual stability and why repeated respondents are needed to estimate repeat response. Then calculate the empirical relation RR = RL + 20 for several response levels. Use percentage points, show each substitution and check the zero-to-one-hundred boundary. Treat the line as an aggregate benchmark rather than a causal law or an individual purchase probability.
Draw the Theory of Planned Behaviour from memory with attitude, subjective norm and perceived behavioural control feeding intention, followed by behaviour. Add actual control and habit as boundary notes. For each scenario, quote one fact supporting each construct and identify the weakest link. Do not prescribe attitude communication when the problem is access, skill or opportunity.
Turn recommendations into interventions at the diagnosed link: change expected outcomes, show credible norms or remove a control barrier. Pair intention measures with actual behaviour and an opportunity measure so non-action is not automatically read as failed persuasion. Practise a five-mark response with one mark for construct identification, supporting evidence, rival or boundary, intervention and behavioural outcome.
Finish by designing a small before-and-after test. Specify who had access, what changed, what action was recorded and what result would weaken the diagnosis. Then alter one fact, such as a service closure or peer disapproval, and rewrite the conclusion. This keeps the planned-behaviour model causal and conditional rather than a checklist attached to every case.
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