Journal of Resources and Ecology ›› 2021, Vol. 12 ›› Issue (1): 80-90.DOI: 10.5814/j.issn.1674-764x.2021.01.008
• Resource Economy • Previous Articles Next Articles
Received:
2020-07-31
Accepted:
2020-09-22
Online:
2021-01-30
Published:
2021-03-30
Contact:
WEI Jianhua
Supported by:
WEI Jianhua. Value and Heterogeneity: Using a Choice Experiment to Evaluate the Coastal Recreational Environment[J]. Journal of Resources and Ecology, 2021, 12(1): 80-90.
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URL: http://www.jorae.cn/EN/10.5814/j.issn.1674-764x.2021.01.008
Attributes | Description | Level | Variable type | Variable names |
---|---|---|---|---|
Beach type | The material of beach | Cobblestone | Dummy variable | BT_Stone |
Gravel | Dummy variable | BT_Gravel | ||
Sand | Dummy variable | BT_Sand | ||
Beach garbage | The amount of garbage on the coastline in the view | < 2 pieces | Dummy variable | Garbage_low |
4-8 pieces | Dummy variable | Garbage_med | ||
> 10 pieces | Dummy variable | Garbage_high | ||
Beach crowding | Number of people in the view | 50, 100, 300, 500, 800 persons | Continuous variable | Crowding |
Water quality | Visibility depth of the water on the seaside | < 1 foot | Dummy variable | WaterQ_low |
2-3 feet | Dummy variable | WaterQ_med | ||
3-5 feet | Dummy variable | WaterQ_high | ||
Cost | Contribution fee to beach authority | 0, 10, 20, 50, 70, 100 yuan | Continuous variable | Cost |
Table 1 Specifications of the beach attribute variables
Attributes | Description | Level | Variable type | Variable names |
---|---|---|---|---|
Beach type | The material of beach | Cobblestone | Dummy variable | BT_Stone |
Gravel | Dummy variable | BT_Gravel | ||
Sand | Dummy variable | BT_Sand | ||
Beach garbage | The amount of garbage on the coastline in the view | < 2 pieces | Dummy variable | Garbage_low |
4-8 pieces | Dummy variable | Garbage_med | ||
> 10 pieces | Dummy variable | Garbage_high | ||
Beach crowding | Number of people in the view | 50, 100, 300, 500, 800 persons | Continuous variable | Crowding |
Water quality | Visibility depth of the water on the seaside | < 1 foot | Dummy variable | WaterQ_low |
2-3 feet | Dummy variable | WaterQ_med | ||
3-5 feet | Dummy variable | WaterQ_high | ||
Cost | Contribution fee to beach authority | 0, 10, 20, 50, 70, 100 yuan | Continuous variable | Cost |
Demographics | level | Percent (%) | Demographics | level | Percent (%) |
---|---|---|---|---|---|
Individual income | < 2000 yuan | 33.7 | Education background | Junior high school or below | 8.3 |
2000-2999 yuan | 14.0 | High school | |||
3000-3999 yuan | 17.1 | Technical school | 24.8 | ||
4000-4999 yuan | 10.5 | B.S. | 34.9 | ||
5000-5999 yuan | 11.1 | M.S. and PhD | 11.7 | ||
6000-6999 yuan | 5.1 | Residence | Dalian City (local) | 55.2 | |
> 7000 yuan | 8.6 | Other city of Liaoning Province (Non-local) | 17.8 | ||
Gender | Male Female | 49.2 50.8 | Other provinces of China (Non-local) | 27.0 | |
Sites (sample from) | Golden pebble Beach Xinghai Bay Fujiazhuang Park Xinghai Beach | 26.0 19.4 28.6 26.0 | |||
Age | 19-25 26-35 51-60 > 60 | 40.6 30.8 10.5 1.9 |
Appendix 1 Summary of the sample information
Demographics | level | Percent (%) | Demographics | level | Percent (%) |
---|---|---|---|---|---|
Individual income | < 2000 yuan | 33.7 | Education background | Junior high school or below | 8.3 |
2000-2999 yuan | 14.0 | High school | |||
3000-3999 yuan | 17.1 | Technical school | 24.8 | ||
4000-4999 yuan | 10.5 | B.S. | 34.9 | ||
5000-5999 yuan | 11.1 | M.S. and PhD | 11.7 | ||
6000-6999 yuan | 5.1 | Residence | Dalian City (local) | 55.2 | |
> 7000 yuan | 8.6 | Other city of Liaoning Province (Non-local) | 17.8 | ||
Gender | Male Female | 49.2 50.8 | Other provinces of China (Non-local) | 27.0 | |
Sites (sample from) | Golden pebble Beach Xinghai Bay Fujiazhuang Park Xinghai Beach | 26.0 19.4 28.6 26.0 | |||
Age | 19-25 26-35 51-60 > 60 | 40.6 30.8 10.5 1.9 |
Variables | Model-1 (CL) | Model-2 (HCL) | Model-3 (RPL) | |||||
---|---|---|---|---|---|---|---|---|
Coef. | P>z | Coef. | P>z | Coef. | P>z (for Coef.) | Coef.SD. | P>z (for Coef.SD.) | |
BT_Gravel | -0.264 | 0.033 | -0.221 | 0.176 | -0.352 | 0.095 | 0.102 | 0.879 |
BT_Sand | 0.067 | 0.656 | 0.037 | 0.751 | -0.201 | 0.564 | 2.071 | 0.066 |
Garbage_med | 0.497 | 0.000 | 0.376 | 0.053 | 0.899 | 0.014 | 1.403 | 0.049 |
Garbage_low | 0.695 | 0.000 | 0.506 | 0.045 | 1.436 | 0.004 | 0.153 | 0.806 |
Crowding | -0.002 | 0.000 | -0.001 | 0.039 | -0.002 | 0.000 | 0.003 | 0.016 |
WaterQ_med | 0.202 | 0.182 | 0.089 | 0.465 | 0.264 | 0.319 | -1.257 | 0.110 |
WaterQ_high | 0.695 | 0.001 | 0.457 | 0.063 | 0.828 | 0.053 | -2.894 | 0.038 |
Cost | -0.016 | 0.000 | -0.011 | 0.027 | -0.020 | 0.000 | - | - |
Age | - | - | 0.019 | 0.766 | - | - | - | - |
Gender | - | - | -0.030 | 0.853 | - | - | - | - |
Education | - | - | 0.033 | 0.625 | - | - | - | - |
Income | - | - | 0.086 | 0.005 | - | - | - | - |
Address | - | - | -0.068 | 0.479 | - | - | - | - |
No. params. | - | 8.000 | - | 13.000 | - | 15.000 | - | - |
LR | - | 231.320 | - | 10.110 | - | 12.360 | - | - |
Prob > chi2 | - | 0.000 | - | 0.072 | - | 0.089 | - | - |
Log likelihood | - | -576.470 | - | -561.410 | - | -560.290 | - | - |
AIC | - | 1168.940 | - | 1148.820 | - | 1150.580 | - | - |
Table 2 Parameter estimates under the CL, HCL and RPL models
Variables | Model-1 (CL) | Model-2 (HCL) | Model-3 (RPL) | |||||
---|---|---|---|---|---|---|---|---|
Coef. | P>z | Coef. | P>z | Coef. | P>z (for Coef.) | Coef.SD. | P>z (for Coef.SD.) | |
BT_Gravel | -0.264 | 0.033 | -0.221 | 0.176 | -0.352 | 0.095 | 0.102 | 0.879 |
BT_Sand | 0.067 | 0.656 | 0.037 | 0.751 | -0.201 | 0.564 | 2.071 | 0.066 |
Garbage_med | 0.497 | 0.000 | 0.376 | 0.053 | 0.899 | 0.014 | 1.403 | 0.049 |
Garbage_low | 0.695 | 0.000 | 0.506 | 0.045 | 1.436 | 0.004 | 0.153 | 0.806 |
Crowding | -0.002 | 0.000 | -0.001 | 0.039 | -0.002 | 0.000 | 0.003 | 0.016 |
WaterQ_med | 0.202 | 0.182 | 0.089 | 0.465 | 0.264 | 0.319 | -1.257 | 0.110 |
WaterQ_high | 0.695 | 0.001 | 0.457 | 0.063 | 0.828 | 0.053 | -2.894 | 0.038 |
Cost | -0.016 | 0.000 | -0.011 | 0.027 | -0.020 | 0.000 | - | - |
Age | - | - | 0.019 | 0.766 | - | - | - | - |
Gender | - | - | -0.030 | 0.853 | - | - | - | - |
Education | - | - | 0.033 | 0.625 | - | - | - | - |
Income | - | - | 0.086 | 0.005 | - | - | - | - |
Address | - | - | -0.068 | 0.479 | - | - | - | - |
No. params. | - | 8.000 | - | 13.000 | - | 15.000 | - | - |
LR | - | 231.320 | - | 10.110 | - | 12.360 | - | - |
Prob > chi2 | - | 0.000 | - | 0.072 | - | 0.089 | - | - |
Log likelihood | - | -576.470 | - | -561.410 | - | -560.290 | - | - |
AIC | - | 1168.940 | - | 1148.820 | - | 1150.580 | - | - |
Variable | MWTP | 90% confidence interval |
---|---|---|
BT_Stone | 27.20 | - |
BT_Gravel | -17.30 | (-34.351, -0.249) |
BT_Sand | -9.90 | - |
Garbage_high | -114.72 | - |
Garbage_med | 44.17 | (14.555, 73.794) |
Garbage_low | 70.55 | (29.891, 111.247) |
WaterQ_low | -53.68 | - |
WaterQ_med | 12.98 | - |
WaterQ_high | 40.69 | (6.060, 75.345) |
Crowding | -0.12 | (-0.167, -0.072) |
Table 3 MWTP estimates under RPL models
Variable | MWTP | 90% confidence interval |
---|---|---|
BT_Stone | 27.20 | - |
BT_Gravel | -17.30 | (-34.351, -0.249) |
BT_Sand | -9.90 | - |
Garbage_high | -114.72 | - |
Garbage_med | 44.17 | (14.555, 73.794) |
Garbage_low | 70.55 | (29.891, 111.247) |
WaterQ_low | -53.68 | - |
WaterQ_med | 12.98 | - |
WaterQ_high | 40.69 | (6.060, 75.345) |
Crowding | -0.12 | (-0.167, -0.072) |
Groups | Garbage_med | Water Q_high | Crowding | Number of obs. | Number of respondents |
---|---|---|---|---|---|
Location | 13.96 | 13.47 | -0.17** | 1044 | 348 |
Non Location | 85.51 | 89.63 | -0.03 | 846 | 282 |
male | 49.82* | 15.57 | -0.13** | 930 | 310 |
female | 6.25 | 61.09** | -0.10** | 960 | 320 |
Income ≥ 5000 yuan | 50.37* | 141.64* | -0.17** | 468 | 156 |
Income < 5000 yuan | 39.54** | 59.37** | -0.08** | 1422 | 474 |
Edu ≤ high school | -73.59 | 612.88 | -1.55** | 540 | 180 |
Edu > high school | 51.76** | 30.58 | -0.10** | 1350 | 450 |
Site 1: Gold pebble Beach | 47.60 | 26.48 | 0.02 | 492 | 164 |
Site 2: Xinghai Bay | 188.49** | 225.20* | -0.02 | 366 | 122 |
Site 3: Fujiazhuang Park | 42.42 | -38.75** | -0.18** | 540 | 180 |
Site 4: Xinghai Beach | 15.52 | 194.79** | -0.15** | 492 | 164 |
Sunbathing | 39.10** | 23.64 | -0.04 | 390 | 130 |
Swimming, boating | 52.80 | 59.83* | -0.13** | 582 | 194 |
Beach walk | 11.69 | 46.32** | -0.13** | 564 | 188 |
Barbecue, camping | 144.92 | -223.37 | -0.20** | 198 | 66 |
All samples | 44.17**(8.88, 79.47) | 40.69*(15.57, 81.98) | -0.12**(-0.18, -0.06) | 1890 | 630 |
Table 4 MWTP for the random variables by groups under the RPL
Groups | Garbage_med | Water Q_high | Crowding | Number of obs. | Number of respondents |
---|---|---|---|---|---|
Location | 13.96 | 13.47 | -0.17** | 1044 | 348 |
Non Location | 85.51 | 89.63 | -0.03 | 846 | 282 |
male | 49.82* | 15.57 | -0.13** | 930 | 310 |
female | 6.25 | 61.09** | -0.10** | 960 | 320 |
Income ≥ 5000 yuan | 50.37* | 141.64* | -0.17** | 468 | 156 |
Income < 5000 yuan | 39.54** | 59.37** | -0.08** | 1422 | 474 |
Edu ≤ high school | -73.59 | 612.88 | -1.55** | 540 | 180 |
Edu > high school | 51.76** | 30.58 | -0.10** | 1350 | 450 |
Site 1: Gold pebble Beach | 47.60 | 26.48 | 0.02 | 492 | 164 |
Site 2: Xinghai Bay | 188.49** | 225.20* | -0.02 | 366 | 122 |
Site 3: Fujiazhuang Park | 42.42 | -38.75** | -0.18** | 540 | 180 |
Site 4: Xinghai Beach | 15.52 | 194.79** | -0.15** | 492 | 164 |
Sunbathing | 39.10** | 23.64 | -0.04 | 390 | 130 |
Swimming, boating | 52.80 | 59.83* | -0.13** | 582 | 194 |
Beach walk | 11.69 | 46.32** | -0.13** | 564 | 188 |
Barbecue, camping | 144.92 | -223.37 | -0.20** | 198 | 66 |
All samples | 44.17**(8.88, 79.47) | 40.69*(15.57, 81.98) | -0.12**(-0.18, -0.06) | 1890 | 630 |
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