Adoption of renewable heating systems: An empirical test of the diffusion of innovation theory

Abstract

Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractThe implementation of heating technologies based on renewable resources is an important part of Italy's energy policy. Yet, despite efforts to promote the uptake of such technologies, their diffusion is still limited while heating systems based on fossil fuels are still predominant. Theory suggests that beliefs and attitudes of individual consumers play a crucial role in the diffusion of innovative products. However, empirical studies corroborating such observations are still thin on the ground. We use a Choice Experiment and a Latent Class-Random Parameter model to analyze preferences of households in the Veneto region (North-East Italy) for key features of ambient heating systems. We evaluate the coherence of the underlying preference structure using as criteria psychological constructs from the Theory of Diffusion of Innovation by Rogers. Our results broadly support this theory by providing evidence of segmentation of the population consistent with the individuals' propensity to adopt innovations. We found that preferences for heating systems and respondents' willingness to pay for their key features vary across segments. These results enabled us to generate maps that show how willingness to pay estimates vary across the region and can guide local policy design aimed at stimulating adoption of sustainable solutions.

Types of front of pack food labels: Do obese consumers care? Evidence from Northern Ireland

“…Previous studies using finite mixture of preference classes found that allowing for further heterogeneity within each preference class, by means of continuously varying random parameters, produced significant increases in model fit (Bujosa et al 2010, Greene and Hensher 2013, Campbell et al 2014, Boeri et al 2014, Farizo et al 2014, Yoo and Ready 2014, Franceschinis et al 2017. There is no a-priori strong rationale for negating this occurrence in our data.…”

“…To do so we specify choice probabilities using a latent class (LC) logit model, but a subset of taste coefficients, after testing, are also assumed to be continuosly random within preference classes. We name this a latent class random parameter logit model (LC-RPL) (amongst others Bujosa et al 2010, Franceschinis et al 2017 .…”

Households’ Preferences for a New ‘Climate-Friendly’ Heating System: Does Contribution to Reducing Greenhouse Gases Matter?

“…Several studies analyse awareness [12,13] and estimate citizens' willingness to pay (WTP) for the use of renewable energy sources (e.g., [14][15][16][17][18][19][20]). A number of studies also investigate homeowners' preferences for renewable domestic heating systems using the discrete choice experiment (DCE) approach [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35] or conjoint and variance analysis [36], and most of them suggest that whilst renewable energy adoption is notably valued by households, this value is not enough to counterbalance the importance of the economic factors while purchasing a new heating [24,25,27,29].…”

The Effects of Perceived Barriers on Innovation Resistance of Hydrogen-Electric Motorcycles

“…In the existing studies of innovation resistance theory, innovation resistance drew little attention from researchers in the field of consumer behaviors, with only a few researchers [5][6][7][8][9] engaging in relevant studies. Most researchers focused on the discussions of innovation influences [10][11][12][13][14][15], innovation diffusion [16][17][18][19] and the characteristics and behaviors, as well as the relationship between these two, among early adopters [20,21]. Dedehayir et al [22] suggested that understanding the consumers' willingness and unwillingness to adopt innovations were equally important.…”