Low Carbon Readiness Index: A short measure to predict private low carbon behaviour

https://doi.org/10.1016/j.jenvp.2018.06.005Get rights and content

Highlights

  • Low Carbon Readiness Index (LCRI) is a three-item measure of low carbon strivings.

  • LCRI predicts reported low carbon behaviours, and reduction in actual energy use.

  • LCRI can be used to develop low carbon policies and monitor their implementation.

Abstract

This paper presents a theoretical argument that low carbon strivings – personal goals to reduce carbon footprint in the household – can predict a wide range of diverse behaviours to reduce greenhouse gas emissions, and reports four studies to validate Low Carbon Readiness Index (LCRI), a short, three-item measure of low carbon strivings. It is a simple and easy-to-use indicator of the general public's readiness to transition to a fully low carbon lifestyle. LCRI is associated with validated measures predicting environmentally significant reported behaviour (Study 1), multiple low carbon behavioural clusters (Study 2 & 3), and predicts reduction in actual energy use, arguably an aggregate measure of actual low carbon behaviours (Study 4). LCRI can be used to develop low carbon policies and monitor their implementation.

Introduction

Human-caused greenhouse gas (GHG) emissions are a major driver of climate change (IPCC, 2014) and the private sphere currently makes up about a third of total emissions (Wright, Osman, & Ashworth, 2009). For private citizens, the immediate means to reduce GHG emissions is to modify their behaviours in the domain of household and personal travel (DEFRA, 2008; Gardner & Stern, 2008; Pears, 2011). Reductions can be achieved by using infrastructure that is energy efficient (e.g. efficient appliances, insulation) and that makes renewable energy available (e.g. solar panels), and by adopting routines that conserve energy (e.g. temperature curtailment) and minimise waste (e.g. composting). While it may be difficult to implement all possible measures to reduce GHG emissions, most people could make at least some changes. However, although a recent survey found that climate change is globally seen as a major threat (Pew Research Center, 2017), transition to low carbon living in the private sphere remains slow.

In order to aid policy making and implementation that promotes the reduction of GHG emissions in the private sphere, we present a short and easy-to-use three-item measure called the Low Carbon Readiness Index (LCRI). Note that the name of the measure references carbon for ease of communication as discernible from the standard practice of converting GHGs to carbon equivalents. Nevertheless, the items for this measure are phrased in terms of “greenhouse gasses” to capture other types of GHGs (e.g., methane) as well, so as to be relevant for a broader set of household behaviours including waste reduction (i.e., those aimed at reducing methane). The LCRI is designed to measure personal motivation to transition to low carbon living, and to predict a wide range of diverse behaviours that can reduce household GHG emissions. We report four studies to validate the claim and close the paper by discussing how the LCRI can be used to support efforts to promote low carbon living.

Although a number of approaches have been used to predict environmental behaviour (e.g., Gifford, 2014; for a review), the Reasoned Action Approach (RAA: Ajzen, 1991; Fishbein & Ajzen, 1975; Fishbein & Ajzen, 2010) has been one of the most widely used. Many of its applications have focused on specific environmental behaviours, such as composting (Mannetti, Pierro, & Livi, 2004; Taylor & Todd, 1995), use of energy-saving light bulbs, unbleached paper, water and meat consumption (Harland, Staats, & Wilke, 1999), and mode of travel (Bamberg & Schmidt, 2003; Harland et al., 1999; Heath & Gifford, 2002; Verplanken, Aarts, Knippenberg, & Moonen, 1998), although there has been an effort to conceptualize a generalized use of the Reasoned Action Approach (Kaiser & Gutscher, 2003). This focus on specific behaviour is partly due to the RAA's principle of compatibility, which suggests that predictors of a behaviour must be measured at the level of specificity compatible with the behaviour. For instance, to predict a specific behaviour such as “installing solar panels for my house next month”, its predictor must also be specified in terms of its four elements, action (installing), target (solar panels), context (my house), and time (next month).

Nevertheless, the same methodological principle suggests that a general category of behaviours can be predicted by predictors if they have compatible levels of specificity (Ajzen & Fishbein, 1977; Fishbein & Ajzen, 2010). Thus, “intentions to perform a range of behaviours that can potentially reduce carbon emissions in the household” should be able to predict a diverse array of low carbon behaviours. We suggest that such generalized intentions are conceptually akin to personal goals (Carver, 2015). Indeed, Kashima, Paladino, and Margetts (2014) showed that environmental strivings, personal goals to improve the natural environment – a construct based on Emmons's (1986) personal strivings – predicted a wide range of pro-environmental behaviours including green shopping, green talk, driving less, as well as willingness to pay a “Sustainability Fee” at the university (Margetts & Kashima, 2017). Analogously, we suggest that personal goals to reduce carbon emissions may be conceptualized as low carbon strivings, and the Low Carbon Readiness Index (LCRI), a measure of this construct developed from the environmental strivings measure, should be able to predict a wide range of low carbon behaviour within the household.

Adoption of low carbon behaviours (e.g., turning off the light) typically requires an abandonment of pre-existing routinized high carbon behaviours (i.e., keeping the light on), which have been repeatedly practised in people's everyday activities within their household. That these pre-existing behaviours are difficult to change can be understood from at least two perspectives (Kurz, Gardner, Verplanken, & Abraham, 2015). First, psychologically speaking, repeated acts can form a habit (e.g., Verplanken, 2005; Wood & Neal, 2007), so that when a contextual cue is present, the act is likely performed unreflectively (Neal, Wood, & Quinn, 2006). Past behaviour, therefore, is the dominant predictor of future behaviour in the same context (e.g. Danner, Aarts, & Vries, 2008; Knussen, Yule, MacKenzie, & Wells, 2004) and Ouellette and Wood's (1998) meta-analysis provides evidence. Second, the pre-existing behaviours are embedded in socio-cultural context. From a sociological perspective (e.g., Shove, Pantzar, & Watson, 2012), they constitute practices – a set of routinized behaviours that accompany (i) the capacity to perform physical actions or procedures (competence), (ii) things that are used to carry out the behaviour (material), and (iii) knowledge, emotion and motivation (meaning). Cultural understandings shared amongst people maintain a “community of practice” that structures multiple individuals' behaviours (Shove, 2012; Shove et al., 2012) and their relationships (Hargreaves, 2011). Any change to a system of practices tends to disrupt the status quo, and therefore tends to be resisted.

However, dual process perspectives (e.g., Borland, 2013; Kahneman, 2011; Sloman, 1996; Triandis, 1977; see Evans, 2008, for a recent review) suggest that these habitual practices can be cognitively regulated under some circumstances. To use Kahneman's (2011) well known nomenclature, system 1 processes are non-volitional mental processes (including habit) that are reactive to the immediate environment (Fazio, 1990; Kahneman, 2011). In contrast, system 2 processes are deliberative and reflective. They can implicate higher order goals and aspirations that may be incongruent with the system 1 processes, and are effortful, difficult to sustain, and frequently unsuccessful (see Borland, 2013). To change pre-existing high carbon behaviours to low carbon alternatives requires an override of easy system 1 processes by more difficult system 2 processes. Nonetheless, as Wood, Labrecque, Lin, and Rünger (2014; also see Triandis, 1977) noted, the mental processes governing habit performance will typically occur in tandem with other, more intentional and goal-oriented, processes. This creates a possibility for system 2-guided behaviour changes to occur across different contexts over a period of time. Thus, low carbon strivings may exert effects when there are opportunities for system 2 processes to regulate behaviour, thus cumulatively leading to a low carbon lifestyle over time.

There are at least two classes of factors that may moderate a general tendency to engage in low carbon behaviour this way. One is the perceived effectiveness of a given behaviour in helping achieve the personal goal to reduce GHG emissions. Even if people are highly motivated to attain the personal goal of reducing GHG emissions, if they wrongly believe that a given behaviour is ineffective in doing so, they may not engage in system 2-guided self-regulation of the behaviour (Kashima et al., 2014). There is also considerable diversity in the way people perceive the effectiveness of different behaviours in reducing energy consumption (Attari, DeKay, Davidson, & De Bruin, 2010). The other class of factors is the extent to which people have actual control over their behaviour (e.g. Fishbein & Ajzen, 2010); we may call this actual difficulty. As sociological perspectives highlight, behaviour change requires competences and materials (Shove et al., 2012). If people do not have control over a GHG reduction behaviour due to their lack of skills, resources, or opportunities (e.g. renters cannot install solar panels), or if the behaviour is actually very difficult (rather than perceived to be difficult) to perform, people may not be able to carry it out even if they have strong personal goals to reduce GHGs and they know its effectiveness. Variation introduced by these factors reduces the correspondence between general striving for GHG reductions and low carbon behaviour.

The foregoing discussion provides a theoretical justification for the methodological principle of compatibility (e.g., Fishbein & Ajzen, 2010). A measure of a construct with a low level of specificity such as low carbon strivings can predict, not single-act criterion with a specified act, target, context, and time, but multiple-act criteria which capture a wide range of diverse behaviours with different configurations of act, target, context, and time. Nonetheless, creating a meaningful measure of diverse low carbon behaviours is difficult because low carbon behaviours in the household are highly heterogeneous, including daily curtailment behaviours (e.g. regulating heater use), occasional compensatory behaviours (e.g. carbon offsetting), and long-term investment in efficient infrastructure (e.g. energy efficient fridge).

Nonetheless, we can rely on behavioural clustering to construct meaningful behavioural criteria. Behavioural clustering is a phenomenon in which diverse behaviours tend to co-occur in a population, such that if a person engages in one behaviour in a cluster, he or she is also likely to engage in other behaviours in the cluster. Behaviour clusters are empirically identified using methods such as factor analysis, cluster analysis, and latent class analysis, and have been documented in environmental psychology. For example, in Norway, Bratt (1999) identified three behavioural clusters: recycling and information-based behaviours, transport behaviour, and residential energy consumption. In the UK, Gilg, Barr, and Ford (2005) found three clusters: shopping, composting, and reuse; domestic water and energy conservation; and recycling. In Germany, Mills and Schleich (2010) found that the likelihood of purchasing energy efficient household appliances and whitegoods was higher in homes that already had one or more energy efficient appliances. This effect was strong and consistent across appliance type, implying the existence of a “household appliance installation” cluster.

There is also evidence of higher order associations between different behavioural clusters. For example, Berger (1997) identified six clusters of pro-environmental household reported behaviour using principal components analysis in Canada: recycling, transportation, energy use, lawn chemicals, water use, and “other” consumer behaviours. She also found that the recycling cluster was associated with substantially increased levels of many other pro-environmental behaviours, including those that were not related to waste management. For example, she found that nearly twice as many recyclers used a programmable thermostat, composted, and used their own shopping bags (Thøgersen & Ölander, 2006). Behaviour clustering is conceptually related to spillover effects in which the performance of one environmental behaviour increases the likelihood of performing another (e.g., Lanzini & Thøgersen, 2014; Lauren, Fielding, Smith, & Louis, 2016; Margetts & Kashima, 2017; Thøgersen & Noblet, 2012; Thøgersen & Ölander, 2003; Thøgersen, 1999).

Thus, behavioural clusters identify naturally co-occurring actions across target, context, and time. Measures that capture a person's engagement with behavioural clusters amount to measuring broad and heterogeneous behaviours. We expect, therefore, that level of engagement with a low carbon behaviour cluster will depend on the perceived effectiveness and actual control that people have. However, we also expect that people who have a strong personal goal to reduce GHG emissions will be more likely to engage in the comprising behaviours of the cluster. We therefore hypothesise that low carbon strivings should be able to predict the extent to which people engage with low carbon behavioural clusters. This line of reasoning is consistent with Thøgersen and Ölander's (2003) finding that environmental values and environmental concern predicted participation in clusters focussed on recycling, food purchasing and transport. Similarly, when Truelove, Carrico, Weber, Raimi, and Vandenbergh (2014, p. 132) reviewed the literature on spillover from performing one low carbon behaviour to performing others within a cluster they concluded that this process occurs when there is “[s]ocial and internal pressure to live up to an assumed role”. We suggest that low carbon strivings can represent such higher order concerns, values, and standards.

Here, we present four studies that support the construct validity of the Low Carbon Readiness Index (LCRI) as an indicator of low carbon strivings, namely, personal goals to reduce carbon emissions in the household. First, to show convergent validity, we test whether LCRI is associated with other measures of pro-environmental orientations. Second, to show construct validity, we conduct two studies to test the coherence of the LCRI measure and whether LCRI is associated with self-reported behaviours and greater intentions to perform behaviours in low carbon behavioural clusters. Finally, we test whether LCRI can predict actual energy consumption, arguably an aggregate measure of actual household low carbon behaviours.

Section snippets

Study 1

We constructed LCRI and investigated its relationships with three measures of pro-environmental orientations: New Ecological Paradigm (Dunlap, Van Liere, Mertig, & Jones, 2000) as a benchmark of generalized environmental attitudes, environmental identity (Whitmarsh & O'Neill, 2010), and environmental striving (Kashima et al., 2014). We also included a measure of climate change beliefs because the most salient reason for reducing carbon emissions is likely to be climate change mitigation (Hulme,

Study 2

To further demonstrate LCRI's validity, its correlations with low carbon behavioural clusters and related intentions were examined. Reported behaviours included the installation of infrastructure and the performance of routine actions, initially selected from the description of a ‘green’ Australian household provided by Pears (2011) and the CSIRO Home Energy Saving Handbook (Wright et al., 2009). A pilot test (N = 50) confirmed that a community sample of Australians also listed the chosen

Study 3

Study 3 tested associations between LCRI and clusters of reported low carbon behaviours using a large representative sample of the Australian population. To begin to account for the practical factors and competing priorities that limit the successful pursuit of a low carbon goal, we examined the LCRI-behaviour relationship while controlling for potential confounds including demographic factors, perceived resources and importance of household comfort. We also conducted a latent class analysis to

Study 4

Study 4 examined LCRI's capacity to predict an aggregate measure of a large number of actual low carbon behaviours, namely, average daily energy use.

General discussion

Transformation to low carbon living requires a change in lifestyle. Four studies provided evidence for the construct validity of Low Carbon Readiness Index (LCRI), a short psychological measure that predicts a wide range of diverse low carbon behaviours in the household, and that can index general willingness to transition to low carbon lifestyle.

When LCRI items were subjected to principal component analysis, they consistently loaded on a single component with high levels of high internal

Declarations of interest

None.

Acknowledgements

This research is funded by the CRC (RP3012) for Low Carbon Living Ltd supported by the Cooperative Research Centres program, an Australian Government initiative.

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