Leading the pack or lagging behind? Validating a simple measure to prospectively identify adopter categories for low emission technologies

Adopting low emission technologies will be fundamental to mitigating climate change, yet many consumers have yet to do so. Rogers' (2003) diffusion of innovations model, and its categorisation of consumers to motivationally distinct adopter categories defined by how fast an innovation is adopted, would appear to be a useful tool for addressing this challenge, allowing low emission technology adoption strategies to be tailored to consumers in different adopter categories. Preventing this potential application, however, is the retrospective means by which adopter category classification traditionally occurs. The purpose of this research was therefore to evaluate a prospective method for determining adopter category: asking consumers to self-identify the low emission technology adopter category to which they belong. Across two Australian samples (combined n = 2645), we found that current and planned adoption patterns for three low emission technologies (electric vehicles, electric space heating, electric/solar water heating) were generally consistent with those theorised by Rogers, even after controlling for potential barriers to adoption (e.g., financial resources, length of time residing in one's home, adoption costs). The one exception was for innovators vs. early adopters, where no consistent adoption differences were observed. Notwithstanding this exception, self-identified adopter category represents a valid and expeditious means for prospectively classifying a consumer's adopter category, allowing for the development of low emission technology adoption strategies that are tailored to the motivational profile of each adopter category.