Spatial and Temporal Characteristics of PV Adoption in the UK and Their Implications for the Smart Grid

Snape, J. Richard

doi:10.3390/en9030210

Cited by 32 publications

(18 citation statements)

References 18 publications

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“…Our results corroborate previous studies that emphasized the influencing role of the interpersonal communication and social interactions in the innovation adoption process [17,20,22,45,52,58,61,62,64]. Additionally, our study revealed that this influencing role was stronger than the influencing role of the installers (with an increasing tendency) while nearing to the final decision along the purchasing process.…”

Section: Discussionsupporting

confidence: 91%

Communication and Household Adoption of Heating Products in Hungary

Munkácsi

Mahapatra

2019

Energies

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Existing studies of heating products have analyzed the adoption of energy-efficient heating technologies from diverse micro and macroeconomic aspects, such as diffusion of innovation, willingness to pay, business models, energy pricing, etc., but the analysis from a marketing management approach based on end customer insight is still lacking. Understanding the decision-making process of end customers, and the influence of social environment at the diverse stages of the purchase process leads to a focused market strategy, thereby contributes toward overcoming the multi-level segmentation challenge faced by the manufacturers of heating products. In this context, a two-step exploratory research was conducted in December 2013 with end customers of the residential heat market in Hungary. The end customers were found to be active decision-makers engaged in deliberate planning in the purchase of heating products. They start searching for information by turning mainly to online information sources and they actively integrate their social network in all stages of the decision-making process, which means that the role of the installer is relatively less influential along the whole purchasing process. Identified influencing communication channels at the diverse stages of the purchase process may support manufacturers to develop a user-centric marketing strategy by optimizing the communication instruments in their marketing mix by, for instance, including direct end customer communication via online channels and by de-emphasizing offline communication channels.

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Section: Discussionsupporting

confidence: 91%

Communication and Household Adoption of Heating Products in Hungary

Munkácsi

Mahapatra

2019

Energies

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“…Based on diffusion data for every zip code in California, United States (US), they showed that the installation of a system in a district increased the probability of additional installations in the same district. Subsequent spatial statistical analyses have been conducted for other countries, including Seki et al (2013Seki et al ( , 2014, who considered diffusion data for every prefecture and municipality in Japan, and Richter (2013) and Snape (2016), who investigated every postal code in the United Kingdom (UK).…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Neighborhood influences on the diffusion of residential photovoltaic systems in Kyoto City, Japan

Kosugi

Shimoda

Tashiro³

2019

Environ Econ Policy Stud

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This study investigates the factors influencing the diffusion of residential photovoltaic systems. Factors examined are related to social attributes, such as population structure and living environment within neighborhoods and those close by, together with a neighbor effect revealed as a positive spatial dependency of the diffusion. To examine these factors simultaneously, the study applies a spatial econometric analysis, taking advantage of the availability of cumulative data on installed residential photovoltaic systems and census-based social attributes in about 4000 census blocks in Kyoto City, which include 1.47 million people. Results include: (1) an observed neighbor effect, especially between census blocks within a radius of 1000 m; (2) evidence that diffusion is positively influenced in a census block by lower population density and higher number of household members, as well as by lower ratios of detached houses and lower population densities in nearby census blocks; and (3) indication that diffusion is positively influenced by a higher proportion of young people through various mechanisms. To further facilitate the diffusion, implementing non-economic measures designed in light of the observed neighborhood influences is recommended, in addition to conventional economic support measures.

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“…After the standard normalization, the values of six indicators are obtained and the Grey incidence decision method is applied to generate the clean energy development index score. Among them, data of the power transmission line [36], the proportion of renewable energy generation, and annual utilization hours of renewable energy equipment come from the China Electric Power Yearbook [37] Table 2 contains the regional energy poverty scores in China. From Table 2, the increase of the minimum energy poverty value indicates that there is an improvement in the region facing serious energy poverty.…”

Section: Panel Data Model For Influence Factors Of Energy Povertymentioning

confidence: 99%

Energy Poverty in China: A Dynamic Analysis Based on a Hybrid Panel Data Decision Model

Wang

Yuan

et al. 2017

Energies

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Abstract:Renewable energy can help to tackle energy poverty issues of the availability of modern energy services and the sustainability of energy supply. Based on the concept of the Energy Development Index, published by International Energy Agency, this paper builds the clean energy development index and applies the Grey incidence decision method to analyze regional energy poverty issues in China. A model using panel data investigates the influencing factors that are governing energy poverty alleviation and the relationship between energy poverty and social development. The improved index system not only considers the access to modern energy services, but also addresses the cleanliness of energy supply and the transition to clean energy consumption for cooking. The results indicate that due to insufficient clean energy development, China's Northeast and West regions have experienced increasing energy poverty problems, while energy poverty in the Southwest region has improved considerably because of its renewable energy development. Urbanization, affordability, and renewable energy development can increase access to modern energy services, contributing to energy poverty alleviation. However, the role of rural household consumption levels in energy poverty alleviation should be considered in rural energy policy.

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Spatial and Temporal Characteristics of PV Adoption in the UK and Their Implications for the Smart Grid

Cited by 32 publications

References 18 publications

Communication and Household Adoption of Heating Products in Hungary

Communication and Household Adoption of Heating Products in Hungary

Neighborhood influences on the diffusion of residential photovoltaic systems in Kyoto City, Japan

Energy Poverty in China: A Dynamic Analysis Based on a Hybrid Panel Data Decision Model

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