Closing the gap between intention and behavior: Insights from the Theory of Planned Behavior

The Intention-Behavior Gap: Why We Struggle to Follow Through

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Did you know that up to 80% of New Year's resolutions fail by February? Or that the global shopping-cart abandonment rate for e-commerce is around 70%¹? These eye-opening statistics illustrate a common phenomenon called the intention-behavior gap, where people’s intentions to perform a certain behavior do not always translate into actual behavior. The intention-behavior gap is a significant challenge in many areas of life, and it is relevant for marketers.

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In the field of marketing research, the intention-behavior gap poses a significant challenge for marketers who rely on consumers’ stated intentions to guide their decisions. For example, marketers often use measures of purchase intention to forecast future sales and develop marketing strategies. However, a consumer may express an intention to purchase a product, but then fail to follow through with the purchase, resulting in missed sales opportunities, inaccurate marketing forecasts, and wasted resources.

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To make matters more complicated, the intention-behavior gap can also make it difficult to identify so-called “intenders”. For the same reasons as above, marketers may be targeting the wrong consumers, resulting in suboptimal targeting and decreased marketing effectiveness.

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Given these challenges, marketers need to develop strategies to bridge the intention-behavior gap and improve their ability to accurately predict and influence consumer behavior. In the following sections, we will explore some potential strategies for bridging the intention-behavior gap in the context of marketing research, with a particular focus on the Theory of Planned Behavior framework.   

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The Theory of Planned Behavior: Understanding the Drivers of Human Behavior

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A widely used theory to explain the intention-behavior gap is the Theory of Planned Behavior (TPB), developed by social psychologist Icek Ajzen². According to TPB, behavior is primarily driven by a person’s intentions, which are influenced by their attitudes, subjective norms, and perceived behavioral control.

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• Attitudes: A person’s positive or negative evaluation of a behavior. For example, a person who has a positive attitude toward exercise is more likely to intend to go to the gym. 
• Subjective norms: A person’s perception of social pressure to perform or not perform a behavior. For example, a person who perceives that their friends and family expect them to exercise is more likely to intend to go to the gym. 
• Perceived behavioral control: A person’s belief in his or her ability to perform a behavior. For example, a person who feels confident in their ability to exercise regularly is more likely to intend to go to the gym.

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TPB is an extension of the earlier Theory of Reasoned Action (TRA), which proposed that behavior is primarily determined by attitudes and subjective norms. The TPB incorporated additional factors such as perceived behavioral control, which TRA did not address³.

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It should be noted that the TPB has also been criticized for oversimplifying the complexity of human behavior. Critics argue that other factors, such as emotions, habits, and environmental cues, may also play an important role in determining behavior. Sniehotta and colleagues, for example, argue that factors such as self-determination and anticipated regret may be better predictors of future behavior than perceived control⁴.

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In parallel with these criticisms, the TPB has been revised and extended over time to address the concerns and incorporate new findings. The Extended Theory of Planned Behavior (ETPB) added factors such as past behavior and habit strength, while the Integrative Model of Behavioral Prediction (IMBP) combined elements of TPB, TRA, and other related theories to create a more comprehensive model of behavior prediction.

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By and large, the TPB remains a valuable framework for understanding the intention-behavior gap and developing effective marketing strategies. The TPB has been applied not only in marketing research, but also in other fields such as health psychology, environmental psychology, and social psychology. In health psychology, for example, the TPB has been used to understand the factors that influence health-related behaviors such as exercise, medication adherence, and smoking cessation. In environmental psychology, the TPB has been used to understand the factors that influence pro-environmental behaviors such as recycling and energy conservation.

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Applying TPB to Marketing: Insights into Consumer’s Intention-Behavior Gap

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The TPB has been used extensively in marketing science, providing valuable insights into consumer decision-making processes. For example, a study on brand-following behavior on Twitter showed that all three factors in the TPB - attitude toward brand following, subjective norm, and perceived behavioral control - are positively associated with the intention to follow brands on Twitter, concluding that the TPB can be used to predict consumers’ brand-following behavior⁵. 

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Similarly, TPB has been applied to the understanding of purchase intention and behavior⁶ as well as advertising appeal⁷, and many brands have applied this theory to their own marketing practices, such as Nike’s loyalty program⁸.

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Another useful application of TPB in marketing research is to better define “intenders”. Of the three factors in TPB, while marketers often consider only the “attitude” factor to find intenders, the other two factors - subjective norm and perceived behavioral control - can increase the likelihood of identifying true intenders.

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In particular, the literature suggests that the social norm can be particularly useful for this purpose, with “descriptive norms” being the preferred measure for gathering information about what behaviors are typically engaged in. For example, a typical question for descriptive norms in the context of alcohol consumption might be “How many drinks do you think your typical peer consumes on average on a given occasion?” Previous findings consistently show that individuals who have higher levels of descriptive norms for peer drinking are more likely to engage in drinking^9-12.

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The third factor, “perceived behavioral control”, may also be useful in preventing undesirable behaviors, such as smoking cessation.

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In conclusion, while it’s not perfect and doesn’t account for every factor that influences behavior, the TPB is a powerful tool for understanding why people do or don’t do what they say they “intend” to do. By understanding the factors that drive behavior – attitudes, subjective norms, and perceived behavioral control – brands can improve their marketing strategies and create more effective campaigns. So if you want to bridge the gap between what people say they’ll do and what they actually do, TPB is a framework that’s worth exploring.

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References

1. Baymard Institute. (2023). 48 Cart Abandonment Rate Statistics 2023. https://baymard.com/lists/cart-abandonment-rate
2. Ajzen I (1991) The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50: 179 – 211.
3. Montaño DE, Kasprzyk D (2008) Theory of reasoned action, theory of planned behavior, and the integrated behavioral model. In K. Glanz, B. K. Rimer, & K. Viswanath (Eds.), Health behavior and health education: Theory, research, and practice (pp. 67 – 96). Jossey-Bass.
4. Sniehotta FF, Presseau J, Auraújo-Soares V (2014) Time to retire the theory of planned behaviour. Health Psychology Review, 8: 1 – 7.
5. Shu-Chuan C, Chen H-T, Sung Y (2016) Following brands on Twitter: and extension of thory of planned behavior. International Journal of Advertising, 35: 421 – 437.
6. Nam C, Dong H, Lee Y-A (2017) Factors influencing consumers’ purchase intention of green sportswear. Fashion and Textiles, 4: 2
7. Raza SH, Bakar HA, Mohamad B (2018) Relationships between the advertising appeal and behavioral intention: The mediating role of the attitude towards advertising appeal and moderating role of cultural norm. Journal of Business and Retail Management Research, 12: 185 – 193.
8. Phan T-D (2019, Dec 19) How Nike’s Loyalty programme leads the market by applying theory of planned behavior. LinkedIn. https://www.linkedin.com/pulse/how-nikes-loyalty-programme-led-market-applying-theory-phan/
9. McAlaney J, McMahon J (2007) Normative beliefs, misperceptions, and heavy episodic drinking in a British student sample. J Stud Alcohol Drugs, 68: 385 – 392. 
10. Neighbors C, O’Connor RM, Lewis MA, Chawla N, Lee CA, Fossos N (2008) The relative impact of injunctive norms on college student drinking: the role of reference group. Psychol Addict Behav, 22: 576 – 581.
11. DiBello AM, Miller MB, Neighbors C, Reid A, Carey KB (2018) The relative strength of attitudes versus perceived drinking norms as predictors of alcohol use. Addict Behav, 80: 39 – 46.
12. Lac A, Donaldson CD (2018) Testing competing models of injunctive and descriptive norms for proximal and distal reference groups on alcohol attitudes and behavior. Addict Behav, 78: 153 – 159.

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