研究目的
To analyze the social preferences of the detailed attributes of installing small-scale SPV power plants in South Korea and to quantitatively predict public acceptance of small-scale SPV power plants through simulation of virtual small-scale SPV power plants.
研究成果
The analysis shows that people considered the electricity bill, the operating body and the installation location to be more important than other attributes. The respondents prefer small-scale SPV power plants that are located in residential areas, have a large scale of installation, are operated by a private corporation and produce self-consumed electricity. The MWTP for these attributes are estimated to be KRW 4286/month, KRW 3712/kW, KRW 2885/month and KRW 3731/month, respectively. The results provide meaningful implications regarding the aspects of installation on which the government should focus.
研究不足
The study focuses on South Korea, and the results may not be directly applicable to other countries with different socio-economic and environmental contexts. The preference heterogeneity for all attributes suggests that the government should continue monitoring and try to change their attitude to potential opponents who do not like those attributes.
1：Experimental Design and Method Selection:
A choice experiment (CE) approach was used to analyze the social preferences for small-scale SPV power plant installation. The CE presents respondents with several product alternatives, consisting of attributes and levels related to the target goods, and then asks them to choose their preferred alternative among them.
2：Sample Selection and Data Sources:
The survey respondents were limited to the household owners and their spouses who have the actual burden of electricity bill payment and who are aged from 20 to 65 years. The sample of the survey consists of 600 South Korean households.
3：List of Experimental Equipment and Materials:
Not explicitly mentioned.
4：Experimental Procedures and Operational Workflow:
The actual fieldwork was conducted by a professional polling firm (Research Prime) for one month in June
5：Face-to-face surveys were conducted to ensure a better understanding of various attributes and to provide sufficient information to raise the response rates. Data Analysis Methods:
20 The collected SP data are analyzed using a discrete choice model (DCM) based on random utility models. A mixed logit model was used to reflect the heterogeneity of respondents’ preferences.
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