Assessing Tourism Carrying Capacity Based on Visitors’ Experience Utility: A Case Study of Xian-Ren-Tai National Forest Park, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Methodological Framework
2.1.1. The Utility-Based Theoretical Framework of TCC
2.1.2. Choice Experiment Method
2.1.3. Random Utility Function and Conditional Logit Model
2.2. Data
2.2.1. Study Area
2.2.2. Survey Design
2.2.3. Data Collection
3. Results
3.1. Carrying Capacity of Individual Recreational Attributes
3.2. Carrying Capacity of the Recreational Attribute Sets
4. Discussion
4.1. The Interpretation of TCC Based on Visitors’ Experiences Utility
4.2. Policy Implications for Forest Park Management
4.3. Research Limitations and Further Studies
5. Conclusions
Funding
Data Availability Statement
Conflicts of Interest
References
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Environmental Status | Assessment Criterion |
---|---|
Best carrying capacity state | Q2, NU = Max |
Carrying capacity threshold | Q4, NU = 0 |
Low carrying capacity state | 0~Q1, NU > 0 |
Appropriate carrying capacity state | Q1~Q4, NU > 0 |
Unacceptable state | >Q4, NU < 0 |
Attribute | Attribute Description | Attribute Level | Type of Variable | Variable Name |
---|---|---|---|---|
Vegetation coverage | The vegetation coverage rate | 70% | 0, 1 | Forest * |
80% | 0, 1 | ForestBetter | ||
90% | 0, 1 | ForestBest | ||
Support facility | Elements including eco-lavatory, wood path, parking lot, service center, and special eateries and shops, each item earns 1 point | Inferior =1 | 0, 1 | Support * |
Medium = 2 | 0, 1 | SupportBetter | ||
Excellent = 3 | 0, 1 | SupportBest | ||
Garbage | No. of garbage cans distributed per 200 m | >10 | 0, 1 | Garbagemore |
3–10 | 0, 1 | Garbage * | ||
<3 | 0, 1 | GarbageLess | ||
Crowding | No. of people observed in a visible scope (per 100 m2) | <10 | 0, 1 | CrowdingBest |
20 | 0, 1 | Crowding * | ||
35 | 0, 1 | Crowdingmiddle | ||
50 | 0, 1 | Crowdingworse | ||
>60 | 0, 1 | Crowdingworst | ||
Traffic condition | Time spent traveling from city to park | Less convenient: >3 h | 0, 1 | Traffic * |
Partially convenient: 1–3 h | 0, 1 | TrafficBetter | ||
Convenient: <1 h | 0, 1 | TrafficBest | ||
Entrance Price | Admission fee | ¥30 *, ¥35, ¥40, ¥50, ¥80 | Continuous | Entrance Price |
Variable | Characteristics | N | % | Variable | Characteristics | N | % |
---|---|---|---|---|---|---|---|
Gender | Male | 179 | 54 | Marital status | Unmarried | 98 | 30 |
Female | 149 | 45 | Married (children = 0) | 22 | 7 | ||
Married (children > 0) | 208 | 63 | |||||
Age | 18–24 | 63 | 19 | Education | Junior high school | 30 | 9 |
25–40 | 113 | 34 | High school | 65 | 20 | ||
41–60 | 134 | 41 | Undergraduate | 220 | 67 | ||
61 or more | 18 | 5 | Graduate and above | 13 | 4 | ||
HH Income (per year; ¥’000) | ≤¥40 | 137 | 42 | Life satisfaction | Completely dissatisfied | 7 | 2 |
¥40–100 | 139 | 43 | Dissatisfied | 12 | 4 | ||
¥100–200 | 44 | 13 | Neither dissat. nor satis. | 90 | 27 | ||
¥200 or more | 8 | 2 | Satisfied | 127 | 39 | ||
Completely satisfied | 92 | 28 |
Attributes | Attribute Levels | Coeff. | S.D. | z-Statistics | Net Utility/ RMB Yuan |
---|---|---|---|---|---|
Vegetation coverage | Forest * | −1.034 | - | - | −39.315 |
Forest Better | 0.5201 | 0.183 | 2.85 | 19.801 | |
Forest Best | 0.513 | 0.221 | 2.32 | 19.514 | |
Support facility | Support * | −0.813 | - | - | −30.921 |
SupportBetter | 0.265 | 0.246 | 1.08 | 10.085 | |
SupportBest | 0.548 | 0.288 | 1.9 | 20.835 | |
Garbage | Garbagemore | −1.567 | 0.287 | −5.46 | −59.576 |
Garbage * | 1.468 | - | - | 55.815 | |
GarbageLess | 0.098 | 0.202 | 0.49 | 3.761 | |
Crowding | CrowdingBest | 0.400 | 0.228 | 1.75 | 15.220 |
Crowding * | 1.819 | - | - | 69.148 | |
Crowdingmiddle | −0.834 | 0.241 | −1.38 | −31.711 | |
Crowdingworse | −0.723 | 0.306 | −2.36 | −27.487 | |
Crowdingworst | −0.662 | 0.287 | −2.31 | −25.170 | |
Traffic condition | Traffic * | −1.211 | - | - | −46.035 |
TrafficLess | 0.287 | 0.184 | 1.55 | 10.919 | |
TrafficLeast | 0.924 | 0.251 | 3.68 | 35.116 | |
Entrance price | Entrance Price | −0.0263 | 0.007 | −3.82 | - |
Log-likelihood | −383.461 | ||||
McFadden Pseudo R2 | 0.154 | ||||
Number of observations | 1312 | ||||
Prob > chi2 | 0 |
Alternative | Vegetation Coverage | Support Facility | Garbage | Crowding | Traffic Condition | Net Utility |
---|---|---|---|---|---|---|
Alternative-1 | 70% | Inferior | 3–10 pieces/200 m | 35 persons/100 m2 | 1–3 h | −35.212 |
Alternative-2 | 90% | Inferior | <3 pieces/200 m | 50 persons/100 m2 | 1–3 h | −24.212 |
Alternative-3 | 80% | Inferior | >10 pieces/200 m | 50 persons/100 m2 | >3 h | −144.218 |
Alternative-4 | 80% | Inferior | <3 pieces/200 m | 35 persons/100 m2 | <1 h | −3.954 |
Alternative-5 | 70% | Excellent | 3–10 pieces/200 m | 50 persons/100 m2 | <1 h | 44.965 |
Alternative-6 | 70% | Inferior | 3–10 pieces/200 m | >60 persons/100 m2 | 1–3 h | −28.672 |
Alternative-7 | 90% | Inferior | <3 pieces/200 m | 35 persons/100 m2 | >3 h | 7.668 |
Alternative-8 | 80% | Medium | <3 pieces/200 m | 35 persons/100 m2 | 1–3 h | 12.854 |
Alternative-9 | 70% | Medium | >10 pieces/200 m | 20 persons/100 m2 | 1–3 h | −8.739 |
Alternative-10 | 70% | Medium | <3 pieces/200 m | <10 persons/100 m2 | >3 h | −56.283 |
Alternative-11 | 80% | Medium | 3–10 pieces/200 m | >60 persons/100 m2 | <1 h | 95.646 |
Alternative-12 | 90% | Excellent | <3 pieces/200 m | >60 persons/100 m2 | 1–3 h | 29.860 |
Alternative-13 | 70% | Excellent | >10 pieces/200 m | 35 persons/100 m2 | 1–3 h | −98.848 |
Alternative-14 | 70% | Medium | <3 pieces/200 m | >60 persons/100 m2 | 1–3 h | −39.719 |
Alternative-15 | 80% | Medium | 3–10 pieces/200 m | 20 persons/100 m2 | >3 h | 108.813 |
Alternative-16 | 80% | Excellent | >10 pieces/200 m | 20 persons/100 m2 | <1 h | 67.509 |
Alternative-17 | 80% | Excellent | 3–10 pieces/200 m | <10 persons/100 m2 | 1–3 h | 122.590 |
Alternative-18 | 70% | Medium | 3–10 pieces/200 m | 20 persons/100 m2 | 1–3 h | −46.936 |
Alternative-19 | 90% | Medium | >10 pieces/200 m | <10 persons/100 m2 | <1 h | 20.359 |
Alternative-20 | 70% | Inferior | <3 pieces/200 m | 20 persons/100 m2 | <1 h | 37.789 |
Alternative-21 | 80% | Medium | <3 pieces/200 m | 50 persons/100 m2 | 1–3 h | 17.079 |
Alternative-22 | 90% | Excellent | <3 pieces/200 m | <10 persons/100 m2 | >3 h | 13.296 |
Alternative-23 | 90% | Medium | 3–10 pieces/200 m | 20 persons/100 m2 | 1–3 h | 165.482 |
Alternative-24 | 80% | Inferior | 3–10 pieces/200 m | <10 persons/100 m2 | 1–3 h | 70.834 |
Alternative-25 | 80% | Inferior | <3 pieces/200 m | >60 persons/100 m2 | 1–3 h | −21.610 |
Alternative-26 | 80% | Excellent | >10 pieces/200 m | 20 persons/100 m2 | 1–3 h | 61.126 |
Alternative-27 | 70% | Medium | >10 pieces/200 m | 35 persons/100 m2 | >3 h | −166.553 |
Status quo | 70% | Inferior | 3–10 pieces/200 m | 20 persons/100 m2 | >3 h | 8.692 |
Alternative | TCC Status | TCC Characteristic | Alternative | TCC Status | TCC Characteristic |
---|---|---|---|---|---|
Alternative-1 | Unacceptable state | Alternative-15 | Appropriate state | ||
Alternative-2 | Unacceptable state | Alternative-16 | Appropriate state | ||
Alternative-3 | Unacceptable state | Alternative-17 | Appropriate state | ||
Alternative-4 | Unacceptable state | Carrying capacity threshold | Alternative-18 | Unacceptable state | |
Alternative-5 | Appropriate state | Alternative-19 | Low state | ||
Alternative-6 | Unacceptable state | Alternative-20 | Appropriate state | ||
Alternative-7 | Low state | Close to threshold | Alternative-21 | Low state | |
Alternative-8 | Low state | Alternative-22 | Low state | ||
Alternative-9 | Unacceptable state | Alternative-23 | Appropriate state | Best carrying capacity state | |
Alternative-10 | Unacceptable state | Alternative-24 | Appropriate state | ||
Alternative-11 | Appropriate state | Alternative-25 | Unacceptable state | ||
Alternative-12 | Low state | Alternative-26 | Appropriate state | ||
Alternative-13 | Unacceptable state | Alternative-27 | Unacceptable state | Lowest carrying capacity state | |
Alternative-14 | Unacceptable state | Status quo | Low state | Close to threshold |
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Kang, N. Assessing Tourism Carrying Capacity Based on Visitors’ Experience Utility: A Case Study of Xian-Ren-Tai National Forest Park, China. Forests 2023, 14, 1694. https://doi.org/10.3390/f14091694
Kang N. Assessing Tourism Carrying Capacity Based on Visitors’ Experience Utility: A Case Study of Xian-Ren-Tai National Forest Park, China. Forests. 2023; 14(9):1694. https://doi.org/10.3390/f14091694
Chicago/Turabian StyleKang, Nannan. 2023. "Assessing Tourism Carrying Capacity Based on Visitors’ Experience Utility: A Case Study of Xian-Ren-Tai National Forest Park, China" Forests 14, no. 9: 1694. https://doi.org/10.3390/f14091694
APA StyleKang, N. (2023). Assessing Tourism Carrying Capacity Based on Visitors’ Experience Utility: A Case Study of Xian-Ren-Tai National Forest Park, China. Forests, 14(9), 1694. https://doi.org/10.3390/f14091694