# Research on Ecological Compensation of National Parks Based on Tourism Concession Mechanism

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## Abstract

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^{4}yuan, the input cost of STIC was 140,696 × 10

^{4}yuan, the income after deducting tax from tourism tickets was 15,200 × 10

^{4}yuan, and the distribution ratio of back-feeding funds is 1:4.29 with the back-feeding funds provided to SNPA from STIC of 12,326.65 × 10

^{4}yuan. Through this paper, we know that landscape value monetization can provide ideas for quantitative accounting of the ecological compensation standard for national park tourism concession. In the future, this subject needs more theoretical and practical research on multiple long-term ecological compensation mechanisms.

## 1. Introduction

## 2. Study Area

## 3. Materials and Methods

#### 3.1. Data Sources

#### 3.2. Research Logic

#### 3.2.1. Calculating Landscape Use Value by TCIA

_{0}, C

_{1}], [C

_{1}, C

_{2}], …, [C

_{i}, C

_{i + 1}], …, [C

_{n−1}, C

_{n}], [C

_{n}, ∞]. The number of visitors per section is recorded as N

_{0}, N

_{1}, …N

_{i}, …N

_{n}, N = ${\sum}_{\mathrm{i}=0}^{\mathrm{n}}{\mathrm{N}}_{\mathrm{i}}$. If every tourist in the i-th section is willing to make a trip when the travel cost is C

_{i}, then the number of tourists who are willing to travel is N

_{i}and the tourists who are willing to pay a higher cost for travel can be calculated. When the travel cost is C

_{i}, the travel demand is M

_{i}= ${\sum}_{\mathrm{i}=0}^{\mathrm{n}}{\mathrm{N}}_{\mathrm{j}}$ and the travel probability is P

_{i}= M

_{i}/N. Assume that the tourist demand of N tourists is the same. When the travel cost is C

_{i}, the probability of a tourist traveling is P

_{i}; Q

_{i}= P

_{i}, Q

_{i}is the willing travel demand of each tourist when the price is C

_{i}. Second, Q

_{i}is the dependent variable and C

_{i}is the independent variable. Regression fitting is performed to obtain the tourist willingness and the demand curve of tourists, expressed as Q = Q (C). Third, the consumer surplus of each tourist is calculated as per Equation (3).

_{i}is the consumer surplus of each tourist in the i-th interval and C

_{i}is the lower limit of the travel cost of the i-th interval.

#### 3.2.2. Calculating Landscape Non-Use Value by CVM

_{i}represents the probability of the i-th payment value selected by the respondent and V

_{i}represents the i-th payment value selected by the respondent.

#### 3.2.3. Calculating the Input Value of the Enterprise from Statistical Data

## 4. Results

#### 4.1. Landscape Use Value

_{i}) are divided into 23 levels from 516 to 2, travel probabilities (P

_{i}) are divided into 23 levels from 100 to 0.39, and the corresponding Q

_{i}(for each tourist’s willingness to travel when the travel cost is C

_{i}) are from 1 to 0.0039.

_{i}) and willingness to travel (Q

_{i}) is shown in Figure 2. It can be discerned from the figure that the higher the tourist’s travel cost, the lower their willingness to travel, which is consistent with theoretical expectations.

_{i}and Qi, with C

_{i}as the independent variable and Q

_{i}as the dependent variable. The results show that the coefficient of determination (R

^{2}) is 0.78, p < 0.001. Furthermore, a logarithmic regression model is established: lnQ

_{i}= −0.0012C

_{i}+ 0.2639 (Equation (9)). The coefficient of determination (R

^{2}) of the logarithmic regression model is 0.99, p < 0.001 indicating that the model fits well.

#### 4.2. Landscape Non-Use Value

^{4}yuan.

#### 4.3. The Input Value of Concession Business, Travel Ticket Income Distribution Ratio, and Back-Feeding Fund Amount

^{4}yuan in 2018. According to Equation (2), the landscape use value and non-use value of the PPSNPS are summed, and the landscape value is 604,230.3 × 10

^{4}yuan. Thus, the ratio of enterprise input value and landscape value is 1:4.29. According to statistics, the scenic spot of PPSNPS in 2018 realized a total of 29,500 × 10

^{4}yuan in tourist tickets and paid a total of 14,300 × 10

^{4}yuan in taxes, so the profit was therefore 15,200 × 10

^{4}yuan. In accordance with the investment ratio of STIC and SNPA, in 2018, STIC can receive 2873.35 × 10

^{4}yuan and SNPA can receive 12,326.65 × 10

^{4}yuan. Then, the back-feeding funds in 2018 should total 12,326.65 × 10

^{4}yuan (Figure 3).

## 5. Discussion and Conclusions

#### 5.1. Discussion

#### 5.2. Conclusions

- (1)
- This study constructed a long-term ecological compensation mechanism under the concession model of tourism back-feeding communities in PPSNPS. It is an effective technology to quantitatively evaluate the ecological compensation standard using the ecological compensation fund allocation ratio based on the input cost of the national park tourism concession enterprise and landscape value. The long-term ecological compensation scheme constructed in this paper clarifies that the SNPA and the STIC are the main bodies of ecological compensation. The calculation results show that the landscape value of PPSNPS in 2018 was 604,230.3 × 10
^{4}yuan, the input cost of STIC was 140,696 × 10^{4}yuan, and the income after deducting tax from tourism tickets was 15,200 × 10^{4}yuan. Thus, the allocation ratio of ecological compensation funds is 1:4.29, and the ecological compensation fund provided to SNPA from STIC is 12,326.65 × 10^{4}yuan. This study provides an idea for the construction of a long-term ecological compensation mechanism for national park tourism concession. - (2)
- TCIA and CVM are effective tools for the monetization and accounting of the national park tourism landscape value, and they can provide effective technologies for the distribution of the ecological compensation funds for the national park tourism concession.
- (3)
- Concession is an effective form for market participation in ecological compensation in national parks. The long-term ecological compensation mechanism in national parks cannot be limited to a single method and a single source. Multiple compensation methods should be encouraged, and multiple market entities and communities should participate. In the future, the construction of multiple long-term ecological compensation mechanisms for nature reserves should be further explored.

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 3.**Travel ticket distribution ratio and back-feeding fund amount in PPSNPS. (

**a**) the orange color represents the landscape use-value, the blue sector represents the landscape non use-value, the green color represents enterprise input cost and the distribution ratio represents the ratio of enterprise input value and landscape value, which is 1:4.29. (

**b**) the purple one represents the concession income and the red sector represents the back-feeding fund, both of them are calculated from the distribution ratio for the travel ticket profit.

Serial Number | [C_{i}, C_{i + 1}] | N_{i} | M_{i} | P_{i}/% | Q_{i} |
---|---|---|---|---|---|

1 | 0–50 | 6 | 516 | 100 | 1 |

2 | 50–100 | 9 | 510 | 98.84 | 0.9884 |

3 | 100–200 | 15 | 501 | 97.09 | 0.9709 |

4 | 200–300 | 22 | 486 | 94.19 | 0.9419 |

5 | 300–400 | 31 | 464 | 89.92 | 0.8992 |

6 | 400–500 | 34 | 433 | 83.91 | 0.8391 |

7 | 500–600 | 27 | 399 | 77.33 | 0.7733 |

8 | 600–700 | 29 | 372 | 72.09 | 0.7209 |

9 | 700–800 | 33 | 343 | 66.47 | 0.6647 |

10 | 800–900 | 51 | 310 | 60.08 | 0.6008 |

11 | 900–1000 | 42 | 259 | 50.19 | 0.5019 |

12 | 1000–1200 | 43 | 217 | 42.05 | 0.4205 |

13 | 1200–1400 | 34 | 174 | 33.72 | 0.3372 |

14 | 1400–1600 | 28 | 140 | 27.13 | 0.2713 |

15 | 1600–1800 | 23 | 112 | 21.71 | 0.2171 |

16 | 1800–2000 | 26 | 89 | 17.25 | 0.1725 |

17 | 2000–2500 | 29 | 63 | 12.21 | 0.1221 |

18 | 2500–3000 | 17 | 34 | 6.59 | 0.0659 |

19 | 3000–3500 | 9 | 17 | 3.29 | 0.0329 |

20 | 3500–4000 | 2 | 8 | 1.55 | 0.0155 |

21 | 4000–4500 | 3 | 6 | 1.16 | 0.0116 |

22 | 4500–5000 | 1 | 3 | 0.58 | 0.0058 |

23 | 5000~ | 2 | 2 | 0.39 | 0.0039 |

Serial Number | Payment Amount (Yuan) | Absolute Frequency (Person-Time) | Relative Frequency (%) |
---|---|---|---|

1 | 2.5 | 9 | 3.36 |

2 | 7.5 | 27 | 10.07 |

3 | 15 | 48 | 17.91 |

4 | 25 | 34 | 12.69 |

5 | 35 | 10 | 3.73 |

6 | 45 | 25 | 9.33 |

7 | 55 | 12 | 4.48 |

8 | 65 | 5 | 1.87 |

9 | 75 | 9 | 3.36 |

10 | 85 | 7 | 2.61 |

11 | 95 | 37 | 13.81 |

12 | 110 | 11 | 4.10 |

13 | 130 | 6 | 2.24 |

14 | 150 | 4 | 1.49 |

15 | 170 | 4 | 1.49 |

16 | 190 | 9 | 3.36 |

17 | 250 | 11 | 4.10 |

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## Share and Cite

**MDPI and ACS Style**

Rao, D.; Wang, J.; Liu, M.; Ma, N.; Li, Z.; Bai, Y.
Research on Ecological Compensation of National Parks Based on Tourism Concession Mechanism. *Sustainability* **2022**, *14*, 6463.
https://doi.org/10.3390/su14116463

**AMA Style**

Rao D, Wang J, Liu M, Ma N, Li Z, Bai Y.
Research on Ecological Compensation of National Parks Based on Tourism Concession Mechanism. *Sustainability*. 2022; 14(11):6463.
https://doi.org/10.3390/su14116463

**Chicago/Turabian Style**

Rao, Didi, Jiaran Wang, Moucheng Liu, Nan Ma, Zhidong Li, and Yunxiao Bai.
2022. "Research on Ecological Compensation of National Parks Based on Tourism Concession Mechanism" *Sustainability* 14, no. 11: 6463.
https://doi.org/10.3390/su14116463