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Simulations of Pro-environmental Behavior in Social Networks in Six Countries
http://hdl.handle.net/10441/0002000029
http://hdl.handle.net/10441/000200002978834cb7-3ed1-400a-bf07-9da64a0d63f2
Item type | テクニカルレポート / Technical Report(1) | |||||||||||||||||||||||
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公開日 | 2023-10-23 | |||||||||||||||||||||||
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タイトル | Simulations of Pro-environmental Behavior in Social Networks in Six Countries | |||||||||||||||||||||||
言語 | en | |||||||||||||||||||||||
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言語 | eng | |||||||||||||||||||||||
キーワード | ||||||||||||||||||||||||
言語 | en | |||||||||||||||||||||||
主題Scheme | Other | |||||||||||||||||||||||
主題 | Carbon footprint | |||||||||||||||||||||||
キーワード | ||||||||||||||||||||||||
言語 | en | |||||||||||||||||||||||
主題Scheme | Other | |||||||||||||||||||||||
主題 | diffusion of environmental friendliness | |||||||||||||||||||||||
キーワード | ||||||||||||||||||||||||
言語 | en | |||||||||||||||||||||||
主題Scheme | Other | |||||||||||||||||||||||
主題 | DeGroot learning | |||||||||||||||||||||||
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言語 | en | |||||||||||||||||||||||
主題Scheme | Other | |||||||||||||||||||||||
主題 | free rider | |||||||||||||||||||||||
キーワード | ||||||||||||||||||||||||
言語 | en | |||||||||||||||||||||||
主題Scheme | Other | |||||||||||||||||||||||
主題 | degree centrality | |||||||||||||||||||||||
キーワード | ||||||||||||||||||||||||
言語 | en | |||||||||||||||||||||||
主題Scheme | Other | |||||||||||||||||||||||
主題 | international comparison | |||||||||||||||||||||||
資源タイプ | ||||||||||||||||||||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_18gh | |||||||||||||||||||||||
資源タイプ | technical report | |||||||||||||||||||||||
著者 |
京井, 尋佑
× 京井, 尋佑
× 内山, 愉太
× 森, 宏一郎
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内容記述タイプ | Abstract | |||||||||||||||||||||||
内容記述 | Pro-environmental behavior does not seem to diffuse sufficiently in Brazil, China, Germany, Japan, India, or the United States. When it comes to mitigating our carbon footprints, our pro-environmental behaviors are insufficient in any country. Based on the current distribution of carbon footprints and learning attitudes in social networks in the six countries, what will happen to the diffusion of pro-environmental behaviors in each country? What policy measures will be most effective in each country? This study aims to simulate the diffusion of pro-environmental behavior and to test the effectiveness of various policy measures in a dynamic social network model based on the settings of the six countries. To create a set of initial conditions in each country, the distribution of pro-environmental behaviors is generated based on carbon footprint data . The distribution of learning attitudes in social networks is estimated in each country, using data from responses in the World Values Survey. This study considers three policy measures: increasing the number of people pursuing best pro-environmental behavior practices (best practice promotion, or BPP), decreasing the number of free riders (free rider reduction, or FRR), and converting the learning patterns of people with high degrees of centrality into best practice (centrality-based best practice promotion, or CBPP). Three interesting findings were obtained. First, there are large differences in the estimated degrees of individual pro-environmental behavior and the proportions of learning patterns in the six countries. Second, FRR and BPP are generally effective in promoting pro-environmental behavior, but the choice of FRR or BPP depends on the initial proportion of free riders . Third, CBPP is the most effective policy of the three in all countries. Centrality in social networks must therefore be considered when implementing intervention policies. | |||||||||||||||||||||||
言語 | en | |||||||||||||||||||||||
引用 | ||||||||||||||||||||||||
内容記述タイプ | Other | |||||||||||||||||||||||
内容記述 | Discussion Paper, Series E, No. E-27, pp. 1-29 | |||||||||||||||||||||||
言語 | en | |||||||||||||||||||||||
書誌情報 |
en : Discussion Paper, Series E 号 No. E-27, p. 1-29, ページ数 29, 発行日 2023-09 |
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出版者 | ||||||||||||||||||||||||
出版者 | The Institute for Economic and Business Research Faculty of Economics, Shiga University | |||||||||||||||||||||||
言語 | en |