Motivation and emotion/Book/2024/Comprehensive action determination model

Comprehensive action determination model:
What is the CADM and how can it be applied to understanding human motivation?

Overview

Figure 1: Water footprint

Scenario

You're exploring how university students’ water use habits relate to their broader attitudes towards sustainability. Specifically, you’ve noticed that some students leave taps running or wastewater during breaks, and you want to understand why this happens. You’re curious about the internal and external factors that influence this behaviour, like whether students are unaware of the environmental impact of their actions, or if they just don’t prioritize sustainability in their daily routines. Additionally, you want to investigate how their broader attitudes toward the environment influence their actions. You have come across an “integrated model” of behaviour. This model combines elements from various theories to provide a more comprehensive understanding of how people act. You think this model could be useful for analysing why students might neglect simple conservation practices like turning off taps, despite being able to adopt more sustainable habits.

The Comprehensive action determination model is a theoretical framework designed to explain human behaviour. It proposes that behaviour is directly predicted by three processes: habitual, situational, and intentional, and indirectly influenced by normative processes. This complex model can aid research in understanding human motivation by breaking down the processes, evaluating the outcomes, and examining the underlying context behind behaviour.

Focus questions

What is motivation?
What is the Comprehensive Action Determination Model (CADM)?
What are the underpinning theories behind the CADM?
How can the CADM be applied to understanding human motivation?

What is motivation?

Defining behaviour is needed to understand motivation. Behaviour can be defined as the way an individual acts, the way they talk, the way they communicate, and how they conduct themselves. Essentially, behaviour encompasses all actions. Motivation, on the other hand, is the "why" behind behaviour — the reasons underlying why we act in certain ways. Theorists explain motivation as the attribute that moves us to do or not to do something (Lai, 2011). The word motivation comes from the Latin verb movere, meaning "to move." This is a fitting term, as motivation is what moves a person to make certain choices, act, expend effort, and persist in those actions (Dörnyei & Ushioda, 2021). Motivation also has significant effects on emotions. For example, when individuals achieve their set goals, they experience joy and satisfaction, which can further drive motivation in the future. However, the reverse can also occur: a lack of motivation can lead to negative emotions and frustration toward a certain behaviour, which may then affect future behaviour (Bradley & Lang, 2007). Motivation is said to have three important components that drive behaviour: direction, intensity, and persistence. Direction refers to how motivation influences the choices we make and the goals we set. Intensity refers to how motivation influences how hard we work toward achieving goals. Finally, persistence refers to how motivation affects how long we continue to work toward goals (Dörnyei & Ushioda, 2021). Over the years, many theories have been developed to understand motivation. These include Herzberg's Two-factor theory (Herzberg et al., 1959; Herzberg et al., 2011), Self-determination theory (Deci, 1972, 2000), and probably the most famous of them all, Maslow's hierarchy of needs (Maslow, 1943). As depicted in Figure 2, Maslow’s hierarchy is a 5-step pyramid where "higher" needs (such as self-actualisation) can only be achieved by satisfying "lower" order needs (such as physiological needs). Theorists argue that it is unrealistic to create an elaborate super-theory to understand motivation due to its complexity and the countless variables that affect it. They contend that the complexity of motivation cannot be fully understood through a single theory or model (Dörnyei & Ushioda, 2021). So, how can we understand human motivation? Are there any theories or models that can be applied to this complex phenomenon?

Comprehensive action determination model (CADM)

The Comprehensive action determination model was first proposed by Klöckner and Blöbaum in 2010 (Klöckner & Blöbaum, 2010). They argue that one of the main goals of environmental psychology is to understand what determines people's actions, particularly in relation to environmental influences. Klöckner and Blöbaum also note that several well-established models—or, as they term them, "action models" or "action determination models"—have been proposed. However, none of these models alone provide an adequate representation of the multiple factors that determine behaviour (Klöckner & Blöbaum, 2010). They further argue that integrated approaches combining two models—the Theory of planned behaviour (Ajzen, 1991) and the Norm-activation model (Schwartz, 1977)—have shown promise (Onwezen et al., 2013; Liu et al., 2017), especially when the concept of habit is incorporated (Klöckner et al., 2003). Additionally, Klöckner and Blöbaum highlight that the Ipsative theory of behaviour offers a valuable perspective on the situational determination of behaviour (Klöckner & Blöbaum, 2010). However, while these theories (the Theory of planned behaviour and the Norm-Activation Model) have proven successful in specific domains, all models exhibit limitations in other areas (Klöckner & Blöbaum, 2010). The CADM unifies the Theory of Planned Behaviour, the Norm-Activation Model, the Ipsative Theory of behaviour , and the concept of habit into one integrated framework. Klöckner and Blöbaum propose that combining these existing theories into a single model may result in a more universally applicable framework that accounts for all relevant factors and influences affecting behaviour , thereby providing a comprehensive explanation of behaviour al outcomes (Klöckner & Blöbaum, 2010).

Underpinning theories of CADM

To understand the comprehensive action determination model, an understanding of the underpinning models, theories and theoretical concepts is required. As stated in the previous paragraph these are the theory of planned behaviour, the Norm-activation model, the Ipsative theory of behaviour and the theoretical concept of habit.

Theory of planned behaviour

The Theory of planned behaviour was first proposed by Ajzen in 1991 (Ajzen, 1991). The theory consists of three constructs: behavioural intention, attitude toward behaviour, and subjective norms. Firstly, behavioural intention refers to the motivation behind a behaviour; the stronger the intention, the more likely the behaviour is to be performed. Secondly, attitude refers to how positively or negatively a person evaluates a specific behaviour. Thirdly, subjective norms refer to the social pressures to perform or not perform a given behaviour. Perceived behavioural control is also a key construct in the Theory of Planned Behaviour, and it refers to how a person perceives the difficulty of performing a specific behaviour (Asare, 2015). The theory suggests that attitudes toward the behaviour, subjective norms, and perceived behavioural control all influence behavioural intention, which in turn leads to behaviour, as depicted in Figure 3. Klockner and Blobaum (2010) argue that the Theory of planned behaviour focuses too much on intention while neglecting the role of objective situational constraints, habits, and personal norms.

Norm-activation model

The Norm-activation model was first proposed by Schwartz in 1977 (Schwartz, 1977). The model suggests that behaviour is predicted by personal norms. Schwartz (1977) defines personal norms as “feelings of moral obligation, not as intentions” (Onwezen et al., 2013). The model posits that personal norms are influenced by two factors: awareness of consequences and awareness of needs (sometimes referred to as the ascription of responsibility). Awareness of consequences refers to the understanding that performing or not performing a certain behaviour leads to specific outcomes. Awareness of needs involves the feeling of responsibility to perform a particular behaviour (Onwezen et al., 2013; Klöckner & Blöbaum, 2010). As depicted in Figure 4, both awareness of consequences and awareness of needs predict personal norms, which in turn predict behaviour. Klockner and Blobaum (2010) identify limitations of the model, stating that “The Norm-activation model focuses on personal norms but underestimates the roles of habits, intentions, attitudes, and the situational context.”

Ipsative theory of behaviour

The Ipsative theory of behaviour was proposed by Frey (1988). The theory suggests that a person's behaviour can be limited or obstructed by the absence of genuine or perceived opportunities, influenced by both internal and external circumstances (Tanner, 1999). The theory consists of three presumptions about human behaviour. Firstly, objective constraints are assumed to influence behaviour. These constraints determine what a person can do, what they ought to do, or what they are permitted to do within a specific society. These variables make up the "objective possibility set," which limits or hinders people's ability to engage in certain activities. Notably, these constraints exist independently of individual perceptions (Tanner, 1999). Secondly, ipsative constraints prevent the activation of alternative behaviours. Ipsative constraints form the "ipsative possibility set," which individuals regard as relevant to their behavioural decisions (Tanner, 1999; Klockner & Blobaum, 2010). Finally, subjective constraints are believed to directly affect preferences rather than determining participation in specific actions. In essence, they influence a person's willingness to act (Tanner, 1999). Klockner and Blobaum (2010) argue that while the Ipsative theory of behaviour effectively outlines the objective and subjective aspects of situations as predictors of behaviour, it overlooks intentional, habitual, and normative processes.

Habits

The theoretical concept of habit was incorporated into the CADM to address limitations found in the Theory of planned behaviour and the Norm-activation model in predicting repetitive behaviours (Klockner & Blobaum, 2010). Habits can be defined as learned tendencies to repeat previous behaviours. They are activated by contextual elements that are often linked to past performances, such as specific locations, preceding actions in a sequence, and particular individuals (Woods & Neal, 2007). The concept of habit was added to account for structural differences between actions that are frequent and those that are rare or performed for the first time. When decisions are frequently made with satisfying outcomes, the influence of decision-making in given situations decreases, resulting in more automated behavioural patterns (Triandis, 1979; Klockner & Blobaum, 2010). Klockner and Blobaum (2010) note that although the concept of habit recognises the interaction between intentions and habits, it does not fully account for non-automatic situational facilitation, constraints on behaviour, or normative processes.

How does the CADM work?

The Comprehensive action determination model proposes that behaviour is determined by three possible direct sources or processes: habitual, intentional, and situational as depicted in figure 5. Habitual processes include schemata, heuristics, and associations of behaviour; intentional processes include attitudes and intentions behind behaviour; and situational processes include both objective and subjective constraints on behaviour. A fourth process, the normative process, is also present, but it does not directly affect behaviour. Instead, it influences intentional and habitual processes. The normative process includes social norms, personal norms, and awareness of needs and consequences. Klockner and Blobaum (2010) explain that attitudes, subjective constraints (e.g., perceived behavioural control), and personal and social norms are used to generate intentions. They further explain that attitudes reflect cognitive and emotional beliefs about behaviour, while perceived behavioural control represents beliefs about the degree of control or determination one has over their actions. Additionally, personal and social norms shape the moral framework that guides the decision-making process leading to behaviour. Personal norms are rooted in an individual’s value system and can be seen as the motivations behind decision-making (Klockner & Blobaum, 2010). All these factors integrate in what Klockner and Blobaum (2010) describe as the "integrating stage," which generates intentions just before behaviour occurs. However, the normative process also influences habits, as it has higher temporal stability compared to attitudes and perceived behavioural control. Situational processes and perceived behavioural control are also thought to activate personal norms by creating awareness of needs and consequences, which then generate the formation of intentions. Habitual and situational processes are believed to interfere with intentional processes and can moderate the influence of intentions on behaviour. Perceived behavioural control is essential for activating both normative and intentional processes. As a result, situational influences affect both normative and intentional processes. Furthermore, habits are said to form through the successful execution of behaviour in specific situations, meaning situational processes also influence habitual behaviours. Finally, behaviour influences changes in personal norms, and habits, in turn, affect future behaviour (Klockner & Blobaum, 2010).

Utilizing the scenario presented at the start of the chapter, we can apply the Comprehensive Action Determination Model to analyse the situation in greater depth (Figure 6). According to Klockner and Blobaum (2010), behaviour is primarily predicted by intentions and perceived behavioural control. Intentions, in turn, are generated from perceived behavioural control, social norms, and attitudes. In this scenario, habitual processes, such as water usage habits, directly predict the likelihood of engaging in water conservation efforts and moderate the relationship between intention and conservation behaviour. While personal norms are identified as predictors of intention, they do not directly predict conservation behaviour. Personal norms are shaped by awareness of environmental needs and consequences and are activated through perceived behavioural control, which creates a sense of moral obligation. Moreover, social norms influence personal norms, as they are internalized from broader societal expectations and adapted into an individual’s value system (Klockner & Blobaum, 2010). Personal norms, being a stable psychological construct, also influence the formation of habits. Klockner and Blobaum (2010) further argue that both subjective constraints (such as perceived behavioural control) and objective constraints (such as access to water-saving tools or technologies) are direct predictors of conservation behaviour. Since habits tend to demonstrate long-term stability, water usage habits (a habitual process) should be influenced by perceived behavioural control and the availability of water-saving options. Both perceived behavioural control and access to water-saving technologies also act as mediators in the relationship between intention and water conservation behaviour. In other words, individuals’ intentions to conserve water are likely influenced by their existing water-related habits and the perceived control they have over their water usage. Finally, conservation behaviour feeds back onto personal norms and habits

Current research on the CADM

Since its proposal in 2010, the Comprehensive action determination model has gained some traction in recent literature. The research on this model is primarily focused on environmental behaviour (link to wiki) (Klockner, 2013). Environmental behaviour refers to actions, attitudes, and practices related to the environment. It encompasses how people interact with their physical surroundings, how they perceive environmental issues, and how their behaviours impact the environment, either positively or negatively. Current research applying the CADM includes studies on sustainable farming (Tan, 2024), food waste behaviour (Cheng et al., 2024), reducing personal clothing consumption (Joanes et al., 2020), and recycling behaviours (Klockner & Oppedal, 2011; Fang et al., 2021; Ofstad et al., 2017). Research conducted by Tan (2024) on sustainable farming found that the CADM was the most effective model for analysing and predicting persistent agricultural practices, contributing to a deeper understanding of behavioural determinants in sustainable agriculture. Cheng and colleagues (2024) also found the CADM to be effective in exploring food waste behaviours. The model showed positive results in studies of recycling behaviour (Klockner & Oppedal, 2011; Fang et al., 2021; Ofstad et al., 2017) and clothing consumption (Joanes et al., 2020). Although the CADM has shown notable success in recent applications and studies, it is important to recognise that the existing body of literature remains relatively limited. As such, there is a pressing need for further research to enhance the generalisability of these findings and ensure their applicability across a broader range of contexts and scenarios.

Limitations to the CADM

The Comprehensive action determination model has two notable limitations: complexity and being data intensive. The model’s complex nature can be seen as a significant drawback. It can be difficult to interpret initially, as it combines elements from the Theory of Planned Behaviour, the Norm-Activation Model, the Ipsative Theory of Behaviour, and the concept of habit. This complexity is further compounded by the presence of numerous variables that not only influence each other but also interact in intricate ways, with some variables acting as mediators, moderators, or both. These interrelationships make it challenging to fully understand how each factor contributes to the overall behaviour being studied. The interplay between these variables often requires careful analysis to untangle their individual and combined effects on the model’s outcomes. The complex nature of the CADM may not be practical in situations where quick decisions are needed, as the analysis of CADM is typically too thorough for such rapid decision-making. Secondly, the model is limited by its data-intensive nature. As noted earlier, its complexity means that analysing each variable within the dataset can be challenging. This data analysis process is often time-consuming and labour-intensive, making it difficult to replicate the model with different populations or in various contexts. The need for large, detailed datasets also poses challenges for scalability and generalisation, further complicating its application across diverse groups or settings. As a result, its practical use may be constrained in environments where data availability is limited or where the computational resources required for analysis are not feasible.

CADM and understanding human motivation

Examining context

The Comprehensive action determination model allows researchers to examine the context behind human behaviour. Examining the context behind behaviour helps researchers gain deeper insights into the motivations that drive specific behaviours. Furthermore, it allows researchers to assess the strength of the motivation in relation to the context. Additionally, Normative process such as personal norms and social norms are known to influence intentions which lead to behaviour. Based on the behaviour, researchers can identify if social norms such as cultural norms or societal expectations have a stronger influence on intentions more than personal norms, even though it is said by Klockner and Blobaum (2010) that personal norms are affected by social norms. The use of the CADM in behavioural research provides a framework for breaking down the contexts underlying behaviours and the motivations that are involved, offering valuable insights into both individual and collective action.

Evaluating outcomes

Using the Comprehensive action determination model in longitudinal studies helps researchers explore how past behaviours influence future actions. By following participants over time, these studies offer insights into how behaviours, habits, and perceived control in specific situations shape future behaviour. The CADM allows researchers to track patterns and identify the motivations driving behaviour change. One key area where CADM is valuable is studying habit formation. Repeated behaviours can become automatic over time, requiring less mental effort and fostering a sense of control. The model helps explain how certain behaviour turn into habits by examining past actions, the emotional and cognitive states tied to them, and the environments in which they occur. Researchers can track how habits develop, strengthen, or fade, and how they motivate future decisions. The CADM also emphasises the role of feedback loops in behaviour change. Positive or negative outcomes from past behaviours can strengthen or weaken future actions. These feedback loops can either reinforce existing behaviours or lead to changes. The model allows researchers to trace these feedback mechanisms and how they impact future behaviour. By using CADM in longitudinal studies, researchers can better understand how past behaviour’s motivate future actions. This approach sheds light on the role of habits, perceived control, situational factors, and feedback in shaping behaviour over time. The insights gained can help develop more effective strategies for behaviour change and intervention, providing a deeper understanding of the factors that motivate long-term behaviour.

Understanding behavioural processes

The Comprehensive action determination model offers a valuable framework for understanding human motivation by systematically breaking down the various behavioural processes that drive actions. This model allows researchers to dissect the factors influencing motivation at different stages, such as habitual and situational processes. By applying the CADM, studies can identify specific points in the motivational process where individuals may excel such as during moments of strong goal commitment or accomplishment as well as areas where motivation may falter, such as in the face of adversity or lack of support. The CADM provides a deeper understanding of how different variables interact to either enhance or undermine motivation, ultimately helping to design more effective strategies for fostering sustained effort and engagement across various contexts.

Conclusion

Motivation is the fundamental "why" behind Behaviour; it fuels drive to pursue goals, overcome challenges, and sustain effort over time. It is the explanation behind behaviour. Understanding motivation is important because it helps us identify the driving forces behind behaviour. The Comprehensive action determination model explains how individuals make decisions in relation to habitual, intentional, situational and normative processes, all of which affect each other in complex ways. The CADM integrates preexisting "action determination models," such as the Theory of Planned Behaviour, the Norm-Activation Model, the Ipsative Theory of Behaviour, and the theoretical concept of habit, into what is believed to be a comprehensive model of behaviour. The CADM can be applied to understanding human motivation by examining the context behind behaviour and the underlying motives that influence such contexts. It can be used to evaluate outcomes to investigate how past behaviour can motivate and shape future actions. Finally, by understanding the behavioural processes within the CADM, researchers can identify where motivation may excel or falter, depending on the outcomes of behaviour. Motivation is the core driver of behaviour, influencing how goals are set and achieved. The Comprehensive action determination model helps explain how motivation interacts with various factors like habits, intentions, and situational influences. By understanding this model, Researcher can gain insight into the underlying motives behind actions and improve decision-making, ultimately shaping future behaviour.

Learning features

References

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External links

Motivation (Healthdirect)
Theory of planned behaviour (Wikipedia)

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