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What should we know about the Theory of Reasoned Action?

As enablers of change, it’s helpful to understand the different ways people have characterised change. In this episode we’re exploring one of the early models of change, the Theory of Reasoned Action. 

The Theory of Reasoned Action (TRA) was developed by the American psychologists Martin Fishbein and Icek Ajzen in the late 1960s. They formulated the theory after attempting to determine the differences between attitude and behaviour, as an improvement to the Information Integration Theory, which we discussed in a recent episode. Let’s explore TRA first, and then we’ll come back and compare it with the Information Integration Theory.

The Theory of Reasoned Action was a breath of fresh air bringing “a compelling and coherent structure on the field of attitudes, which was in relative disarray before their work” (Sheppard et al., 1988, p.340). The Theory of Reasoned Action distinguished between beliefs, attitudes, intentions and behaviours and was based on the assumption that humans make rational decisions. We probably need to spend an entire episode on the idea of rational decision making, so we’re not going to get side tracked now! But according to TRA, behaviour is determined by a person’s intentions, which are in turn influenced by their attitudes and subjective norms.

Attitudes refer to a person’s positive or negative evaluations of a behaviour, while subjective norms refer to the perceived social pressure to engage or not engage in a behaviour. You can see in the diagram below that these two factors combine to form a person’s intention to engage in a behaviour, which ultimately determines whether or not the behaviour is performed.

Figure 1. Interaction of the elements of the Theory of Reasoned Action. Source: Jackson et al. (2006, p. 2).


If we think about this in an extension context, TRA can be used to understand and predict farmers’ adoption of practices. If we can understand the attitudes and subjective norms of farmers, we can design interventions that are more likely to be effective in promoting behaviour change.

For example, if a farmer has a negative attitude towards a new practice, such as restoring a wetland, they are unlikely to adopt it. However, if the farmer perceives that their peers or community members endorse restoring wetlands, they may be more likely to adopt it because of these subjective norms. We could also undertake surveys or focus groups to assess farmers’ attitudes towards wetlands and perceived social pressures. We could then design a communication campaign or an education program to address any misperceptions or concerns, and highlight the benefits of wetlands (in this case). 

So TRA is useful as a model for understanding change because it forces us to step back and consider what attitudes and subjective norms might be influencing farmers’ decision making. This is really helpful as often we are too eager to jump into running activities without stopping to think about what the activities might need to address. We know that TRA has been used for a range of extension projects in New Zealand (Parminter, 2009; Parminter & Wilson, 2003a;Parminter & Wilson, 2003b).   

It is important to note that the model was developed to address behaviours (such as shopping for a new car) and not outcomes from the behaviours (for example owning a new car). It was designed for situations where the behaviour is a choice and all the information required to make that choice is available. We think this is an important point because sometimes in our context, we might be involved in programs that are promoting change on-farm, even though we don’t have all the information. We’re thinking about responses to climate change for example. We have great models and data, but ultimately there are a lot of things that might be useful, and experts don’t always agree on the most effective responses even when they agree there is a problem! Despite this, a detailed meta-analysis of TRA determined that the model was still able to provide useful predictions, even when applied to situations that didn’t quite match how it was supposed to be used (Jackson et al., 2006). There are a lot of studies that have confirmed TRA as a reasonable way to predict an individual’s intention or behaviour.

Other criticisms of TRA are that irrational decisions, habitual actions and other unintentional behaviours aren’t adequately explained by the model. Also, while it considers whether the behaviour achieves the desired outcome, it doesn’t take into account how much the decision maker cares about that particular outcome. TRA also relies on self-reported data which as we know is always subjective! So we need to keep these things in mind if we decide to use it in our work. 

Now we said we would come back to a comparison of the Theory of Reasoned Action and the Information Integration Theory. They are two psychological theories that attempt to explain and predict human behaviour. The key difference between them lies in the way they conceptualise attitudes. In TRA, attitudes are seen as a direct predictor of behaviour, while in IIT, attitudes are seen as one of several factors that influence behaviour. Specifically, IIT proposes that attitudes, along with other factors such as beliefs and values, are integrated or weighted to form an overall evaluation of a behaviour. This overall evaluation then influences behaviour.

In contrast, TRA suggests that attitudes alone can directly predict behaviour, although subjective norms are also important in determining intention to engage in the behaviour. Another key difference between these two theories is in their focus on behaviour change. TRA is specifically designed to explain and predict behaviour change, while IIT is a broader theory about how we integrate information into our thinking and therefore our decision making. Overall, both TRA and IIT are useful theories for understanding human behaviour, but they differ in their approach to conceptualising attitudes and their focus on behaviour change.

Well, that was a bit of a deep dive into psychological theory! But you’ve read our thoughts and now we’d like to hear yours! Add a comment below and tell us about your experiences with TRA, including any tips and further ideas about it. We don’t want this to be just a one-way conversation—join in by sharing your thoughts and ideas with us! 

Thanks folks for reading this Enablers of change episode. Remember to subscribe to our newsletter if you’d like to know when new episodes are available. And if you liked what you heard, please tell your friends so they too can join the conversation!


Fishbein, M. (1967). A behavior theory approach to the relations between beliefs about an object and the attitude toward the object. In M. Fishbein (Ed.), Readings in attitude theory and measurement (pp. 389-400). New York: John Wiley & Sons. 

Jackson, EL, Quaddus, M, Islam, N & Stanton, J. (2006). Hybrid Vigour of Behavioural Theories in the Agribusiness Research Domain. is It Possible? Journal of International Farm Management, 3(3): 25-39.

Parminter, T. G. (2009). An examination of the use of a human behaviour model for natural resource policy design and implementation by government (central and regional) agencies Doctoral dissertation, The University of Waikato. Available online. 

Parminter, T. G. & Wilson J. A. (2003a). Systemic Interventions into Biodiversity Management based upon the Theory of Reasoned Action. Proceedings of the 1st Australian Farming Systems Association Conference, p199. Available online.

Parminter, T. G., & Wilson, J. A. (2003b). Strategies to encourage the adoption of a case study of New Zealand farmers and their possum control practices. In Proceedings of the New Zealand Society of Animal Production, 63: 66-68. Available online. 

Sheppard, BH, Hartwick, J & Warshaw, PR 1988, ‘The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research’, Journal of consumer Research, 15(3): 325-43.

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