Consumers’ energy-saving decisions are often driven by their perception of what works best. If, for instance, someone thinks that using less heating is the most efficient action to save energy at home, they will try to prioritise this action over others. However, research in psychology and behavioural science shows that these perceptions are frequently inaccurate (Lesic et al., 2018). Instead of being based on objective knowledge, they are often shaped by cognitive biases and mental shortcuts (called heuristics), frequently leading to systematic errors. As a result, consumers may focus on ineffective energy-saving actions. Understanding the cognitive biases underlying consumers’ perceptions of energy usage is thus crucial for designing interventions that effectively support energy-saving efforts of households.
How do consumers estimate energy consumption at home?
A common error in energy-related judgements is underestimating the energy use of some appliances while overestimating it for others (Attari et al., 2010; Lesic et al., 2018). Moreover, judgements of energy usage are easily influenced by factors like how the question is asked (Lesic et al., 2018) or what reference point is provided (Frederick et al., 2011). This suggests that consumers do not have strong and accurate ideas about energy consumption of their home appliances, making it difficult to identify the most efficient energy-saving actions.
Researchers have examined the cognitive mechanisms behind these misperceptions, identifying heuristics that shape consumer judgments about energy use. One of them is the “availability heuristic”, whereby people overestimate the likelihood of events that come to their minds more easily (Tversky & Kahneman, 1974). Applied to energy consumption, one study indeed observed higher estimates of energy use for appliances or activities that are more cognitively accessible, such as those used, done or thought of more frequently (e.g., use of computers or cooking) relative to those less accessible (e.g., outdoor grills, gas lamps) (Schley & DeKay, 2015). Cognitive accessibility of appliances, however, correlates only weakly with their actual energy consumption, leading to inaccurate judgements of energy use.
Another cognitive bias at play is “attribute substitution” (Kahneman & Frederick, 2002), whereby people unconsciously replace a complex question (e.g., “How much energy does this use?”) with a simpler one (“Is it big or hot?”). Estimating energy consumption of an appliance is a complex task indeed, and empirical evidence confirms that attribute substitution takes place. Specifically, consumers tend to use the physical characteristics of appliances (e.g., size, temperature) as cues revealing energy usage (Cowen & Gatersleben, 2017; Schille-Hudson et al., 2019). Particularly appliance size is commonly used, with larger appliances perceived as more energy-consuming (Schille-Hudson et al., 2019).
It is important to note that while heuristics like those mentioned above are commonly associated with errors in decision-making, this is not always the case (Gigerenzer & Gaissmaier, 2011). In fact, some physical characteristics of appliances can be rather good indicators of energy consumption. Appliance temperature, in particular, as well as size, seem to correlate with energy consumption, whereas frequency of appliance usage is not a reliable indicator of this (see the figure below and Schille-Hudson et al., 2019).
Heuristics for estimating energy use: Relying on appliance temperature and size are linked to more accurate estimates of energy use compared to “electronic-ness” of an appliance or the frequency of its use
Source: Schille-Hudson et al., 2019 (Figure 2)
How to correct consumer misperceptions and support efficient energy-saving behaviours?
Given the above, directing consumers towards certain heuristics may be effective in helping them estimate the energy usage of different appliances more accurately. In fact, a study has found that simply telling people that “large appliances that primarily heat or cool things use a lot more energy than people think” improved understanding and estimates of energy use (Marghetis et al., 2019). More broadly, feedback is a powerful behavioural tool for improving energy awareness and reducing energy consumption of households (Karlin et al., 2015). Thanks to smart technologies, such as in-home displays, it is now relatively easy to provide consumers with detailed and timely information on their energy usage at home, which can help them learn about their usage and override reliance on the ineffective mental shortcuts.
One caveat is that feedback primarily encourages curtailment actions, such as turning off lights or adjusting the thermostat, rather than energy efficiency measures like buying more efficient appliances (Schley & DeKay, 2015). Curtailment actions are also generally preferred by consumers, but potentially less impactful compared to energy efficiency measures (Lesic et al., 2018; Schley & DeKay, 2015). A reason for this preference likely lies in the larger complexity of the energy efficiency measures, which require effort and/or monetary costs instead of making small adjustments to day-to-day behaviours (Attari et al., 2010).
Therefore, effective interventions to support household energy-saving behaviours must go beyond correcting misperceptions; they should also address other aspects of behaviour, such as preferences or habits, while considering the cognitive mechanisms behind them. This is exactly what behavioural science helps with – diagnosing the cognitive biases that shape consumer perceptions of energy use in order to design interventions that effectively shift behaviours and lead to sustained energy savings. By integrating behavioural insights into energy policies and initiatives, more effective and lasting changes in household energy consumption ca be achieved.
REFERENCES
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