Figure S1 Sampling method in this study: we used two-stage random sampling. (First we selected the l...
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Figure S1 Sampling method in this study: we used two-stage random sampling. (First we selected the locations and then we selected households from the Basic Resident Registry in cooperation with the local governments of the selected locations). Selection of households. Sample.

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Population

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Population

Figure S1 Sampling method in this study: we used two-stage random sampling. (First we selected the locations and then we selected households from the Basic Resident Registry in cooperation with the local governments of the selected locations).

Selection of households

Sample

●Prefecture ▲City ■Town

Basic Resident Register

Selection of locations

Whole Japan

Population

●Prefecture ▲City ■Town

Basic Resident Register

Number of locations for the survey

147 locations x 14 households

→The number of households selected for each location was adjusted so that the total number of households was 2000.

●Prefecture ▲City ■Town

Basic Resident Register

Selected: 180 locations

Locations of respondents: 147 locations

Locations

Surveyed (Households)


Population

FigureS2 Relationship between the number of sampled points and population in each prefecture; the locations selected for this survey reflect the population distribution in Japan as there is a good correlation between the results.

Tokyo

Number of selected locations

Osaka

Aichi

Saitama

Hyogo

Fukuoka

Kanagawa

Hokkaido

Chiba

Population


Table s1 procedures used for the pretest and main test

Table S1 Procedures used for the pretest and main test


Population

表1

表1

Table S2Comparison of calculation results for weighting factors: (a) Conditional logit model, (b) Random parameter logit model (the figures in brackets in the table are the estimated values of the standard deviation)


Table s3 correlation matrix for weighting factors

Table S3Correlation matrix for weighting factors

**: Significant at the 1% level, *: Significant at the 5% level

The non-correlation test is performed to verify the hypothesis that there is no correlation between the two variables. If the result is determined to be significant, the hypothesis will be rejected and, statistically, this means that “there is a correlation between the two variables”.


Population

Figure S3Frequency distribution of weighting factors for social assets WF1 (JPY/JPY10,000) and statistical values

Comparison chart

Probability

Frequency

Data value

Normal distribution

Fit


Population

Figure S4Frequency distribution of weighting factors for primary production WF1 (JPY/kgDW) and statistical values

Comparison chart

Probability

Frequency

Data value

Normal distribution

Fit


Population

Figure S5Frequency distribution of weighting factors for biodiversity WF1 (JPY/EINES) and statistical values

Comparison chart

Probability

Frequency

Data value

Normal distribution

Fit


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