Now showing 1 - 5 of 5
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A Framework to Measure Regional Disparities in Battery Electric Vehicle Diffusion in Ireland

2021-08, Mukherjee, Sanghamitra

This work studies the role of socio-economic and geospatial factors in shaping battery electric vehicle adoption for the case study of Ireland. It provides new insights on the level and timing of likely adoption at scale using a Bass diffusion model combined with a spatial model. The Bass model demonstrates that a country like Ireland may experience peak sales between 2025 and 2030 given current trends, reaching overall uptake levels that are not commensurate with current policy goals, whilst also potentially creating gulfs in regional take-up. The key conclusion from the spatial analysis is that location matters for uptake, through various channels that help or hinder adoption such as resources, information, and policy. Additional investment in public charging infrastructure facilities may also be needed as gaps in coverage exist, especially in rural areas to the West and South-West of the country. Although Ireland enjoys good network coverage overall, this study suggests that more charge points may be needed in some counties and Dublin city and suburbia where the number of charge points is currently disproportionate to a minimum network coverage comparable with the land area, population size, number of private vehicle owners, and travel behaviour. As the urgency for climate action intensifies in the coming decade, our spatio-temporal approach to studying uptake will not only help meet Ireland’s socio-ecological vision for the future, but also provide insights and strategies for comparable countries that are similarly placed in terms of electric vehicle adoption.

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Attitudes to Renewable Energy Technologies: Driving Change in Early Adopter Markets

2020-09, Mukherjee, Sanghamitra, Meles, Tensay, Ryan, L. (Lisa B.), Healy, Séin, Mooney, Robert, Sharpe, Lindsay, Hayes, Paul

This paper explores the motivations behind the adoption of key renewable energy technologies in an early adopter market. Notwithstanding their social benefits, uptake of electric vehicles, heat pumps, and solar photovoltaic panels remains low, necessitating targeted measures to address this. We conducted a comprehensive survey of a nationally representative sample of Irish households and analysed this rich dataset using pairwise group comparisons and a factor analysis combined with a logit regression model. We found fundamental differences between adopters and non-adopters. Current adopters tend to be younger, more educated, of higher socio-economic status, and more likely to live in newer buildings of generous size than non-adopters. Environmental attitudes are an insufficient predictor of uptake - whilst non-adopters self-report as being more sustainable, adopters believe that their own decisions impact climate change. Importantly, social processes will be instrumental in future uptake. Word-of-mouth recommendation will matter greatly in communicating the use and benefits of technologies as evident from the significantly larger social networks that current adopters enjoy. Using these insights, policy incentives can be designed according to public preferences.

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Preferences for Renewable Home Heating: A Choice Experiment Study of Heat Pump System in Ireland

2019-06-29, Meles, Tensay, Ryan, L. (Lisa B.), Mukherjee, Sanghamitra

Renewable sources of home heating like heat pump systems are expected to play a vital role in mitigating the adverse effects of carbon-intensive heating systems. Compared to conventional heating systems, heat pump systems are more energy efficient, have low maintenance and operational costs and provide reliable and environmentally friendly home heating. Despite those advantages, the uptake of heat pumps has been low among the Irish population and little is known about the factors that affect their adoption. This paper uses a discrete choice experiment approach to investigate preferences for heat pumps in the residential sector based on nationally representative household survey data from Ireland. We analyse the choice data using a mixed logit model and estimate the marginal willingness to pay for bill savings, environmentally sustainable, installation hassles and increase in home comfort using both models in preferences space and in willingness to pay (WTP) space. Our results show that upfront cost, bill savings, environmental sustainability and installation hassle significantly influence household uptake of heat pumps. The estimated results also reveal the presence of heterogeneous preferences. Furthermore, the results show that households are willing to pay for heat pumps; however, the values might not be large enough to cover the higher upfront costs of, for example, a ground source heat pump. Overall, the study highlights that policy makers should consider the various financial and non-financial factors that influence adoption and heterogeneity in preferences in designing policy intervention aimed at increasing the uptake of heat pumps.

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Factors influencing early electric vehicle adoption in Ireland

2018-08-31, Ryan, L. (Lisa B.), Mukherjee, Sanghamitra

The objective of this work is to analyse the key determinants of electric vehicle uptake amongst early adopters. Transport accounts for about a quarter of Europe’s total greenhouse gas emissions and has not achieved similar reductions in emissions as other sectors. However, there is an opportunity to achieve lower emissions through the widespread use of electric vehicles. Due to the rising awareness of the link between emissions and global warming, the European Union has set serious targets for renewable energy and greenhouse gas emissions that member states must achieve by 2020 and 2030. Although considerable progress has been made in reaching targets, efforts in the transport sector have been lagging in many countries, with a significant boost required in electric vehicle roll-out if transport-specific targets are to be met. One reason for this lack of progress is possibly an incomplete understanding of the motivations behind consumer uptake, which in turn, hampers policy design to encourage adoption. Here, for the first time, the case study of Ireland is used to analyse socio-demographic and neighbourhood characteristics such as charging infrastructure, dealers and other EV adopters, to identify the key determinants of electric vehicle adoption in the early phase of technology diffusion. From our exploratory data analysis, social class which represents whether the population consists of skilled, semi-skilled or unskilled workers, appears to be the principal factor affecting EV uptake in Ireland. This variable may proxy for income effects, implying that the average wealth of a neighbourhood matters for EV ownership. There also appears to be clustering in EV adopters, possibly due to unobserved peer effects. The OLS model performs poorly for our dataset. Our future work will help determine the significant predictors of adoption based on a spatial econometric approach that explicitly models relationships between agents in the model such that the restrictive assumptions of OLS models can be relaxed to allow for interdependence between individual actors.

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Boosting Renewable Energy Technology Uptake in Ireland: A Machine Learning Approach

2020-09, Mukherjee, Sanghamitra

This study explores the impact of socio-demographic, behavioural, and built-environment characteristics on residential renewable energy technology adoption. It provides new insights on factors influencing uptake using nearest neighbour and random forest machine learning models at a granular spatial scale. Being computationally inexpensive and having good classification performance, these models serve as useful baseline prediction tools. Data is sourced from an Irish survey of consumer perceptions of three key technologies – electric vehicles, solar photovoltaic panels, and heat pumps – and general attitudes towards sustainability, innovation, risk, and time. We demonstrate that utility bills, residence period, attitudes to sustainability, satisfaction with household heating, and perceptions of hassle have the biggest influence on current uptake. Urban areas, typically having better access to information and resources, are likely to see the biggest uptake first. Additionally, compatibility of household infrastructure, technical interest, and social approval are the most important predictors of potential uptake. These results may inform policy in other early adopter markets as well. Overall, policy makers must be cognisant of the stage of adoption their country is currently at. Accordingly, a holistic approach to tackling low adoption must include measures that not only enhance adoption capabilities via rebates and financial measures, but also support the opportunity and intent to purchase such technologies.