Journal of Resources and Ecology >
Analysis of Multiple Tourist Agents’ Symbiotic Relationship on the View of Tourist Enterprises Based on a Grey Correlation Model: A Case Study of Qinghai Lake, China
*First author: XIANG Cheng, E-mail:2575239630@qq.com
Received date: 2018-04-19
Accepted date: 2018-12-18
Online published: 2019-05-30
Supported by
National Natural Science Foundation of China (441550002)
Soft Science Research Projects of Science and Technology Office of Qinghai Province (2015-ZJ-608).
Copyright
Tourism symbiosis is a social phenomenon consisting of many complex factors, and the reciprocal cooperation among multiple tourist agents at tourist destinations is the crux of the sustainable development of tourism. This study is from the perspective of tourist enterprises, and introduces the Symbiosis Theory of genecology. A quantitative evaluation is used to analyze both the equilibrium state of the combined symbiotic behavior routes and the behavior patterns of tourist enterprises with local governments, community residents, tourists and tourist enterprises around Qinghai Lake. The findings reveal: (1) the symbiotic behavior routes of the multiple tourist agents “E→G-R-T-E” in the Qinghai Lake area are constituted of intense symbiotic indications, while the maximum dimensionality of symbiotic interest of “E→G-R-T-E” is still in the state of disequilibrium and dissymmetry; (2) the symbiotic model of multiple tourist agents “E→G-R-T-E” in the Qinghai Lake area is an asymmetrically positive symbiotic model. It is proposed that, by establishing symbiotic mechanisms for guidance, decisions, supervisory control and profit distribution, the participation mechanism for multiple agents “E-G-R-T” can be further standardized. Moreover, tourist enterprises should be regarded as the primary agents to optimize the symbiotic model for “E→G-R-T-E” through the reinforcement of integrative supply and the construction of integrative effect, and finally promote the integrative symbiotic model of symmetrical reciprocity of the E-R-G-T model “driven by scenic areas, responsive to community residents, affected by local governments and enjoyed by tourists.”
XIANG Cheng , TANG Zhongxia , LIU Menglin , SHAO Li . Analysis of Multiple Tourist Agents’ Symbiotic Relationship on the View of Tourist Enterprises Based on a Grey Correlation Model: A Case Study of Qinghai Lake, China[J]. Journal of Resources and Ecology, 2019 , 10(3) : 335 -344 . DOI: 10.5814/j.issn.1674-764X.2019.03.012
Fig. 1 Scenic spots’ distribution of the Qinghai Lake |
Table 1 The symbiotic indicator system for agents in the Qinghai Lake area |
Core agent | Units of symbiotic agents | Symbiotic factors |
---|---|---|
Tourist enterprises (E) | Tourist enterprises- governments (E-G) | Justice and equity (E-G1) |
Coordination and communication (E-G2) | ||
Guidance and support (E-G3) | ||
Mutually-beneficial cooperation (E-G4) | ||
Supervision and administration (E-G5) | ||
Tourist enterprises- residents (E-R) | Participation in operation (E-R1) | |
Cooperation and collaboration (E-R2) | ||
Trust and communication (E-R3) | ||
Harmony and progress (E-R4) | ||
Tourist enterprises- tourists (E-T) | Services recognition (E-T1) | |
Participation in tourism (E-T2) | ||
Ease of management (E-T3) | ||
Polite manner (E-T4) | ||
Living in harmony (E-T5) | ||
Tourist enterprises- tourist enterprises (E-E) | Fair competition (E-E1) | |
Mutually-beneficial cooperation (E-E2) | ||
Close contact (E-E3) | ||
Reaching a consensus (E-E4) | ||
Harmonious and friendly (E-E5) |
Table 2 Weight of symbiotic indicator system of multiple tourist agents in Qinghai Lake |
E-G | E-R | E-T | E-E | ||||
---|---|---|---|---|---|---|---|
WE-G=0.3154 Symbiotic factors weight | WE-R=0.2164 Symbiotic factors weight | WE-T=0.2193 Symbiotic factors weight | WE-E=0.2489 Symbiotic factors weight | ||||
E-G1 | 0.2213 | E-R1 | 0.2671 | E-T1 | 0.2077 | E-E1 | 0.2525 |
E-G2 | 0.2264 | E-R2 | 0.2567 | E-T2 | 0.1825 | E-E2 | 0.1535 |
E-G3 | 0.1665 | E-R3 | 0.2347 | E-T3 | 0.2121 | E-E3 | 0.2219 |
E-G4 | 0.1677 | E-R4 | 0.2415 | E-T4 | 0.2521 | E-E4 | 0.2220 |
E-G5 | 0.2181 | E-T5 | 0.1456 | E-E5 | 0.1801 |
Table 3 Correlation coefficient of symbiotic indicators’ factors of Qinghai Lake multiple agents |
E-G | E-R | E-T | E-E | ||||
---|---|---|---|---|---|---|---|
Symbiotic factors θ | Symbiotic factors θ | Symbiotic factors θ | Symbiotic factorsθ | ||||
E-G1 | 0.5584 | E-R1 | 0.6071 | E-T1 | 0.5541 | E-E1 | 0.5690 |
E-G2 | 0.5551 | E-R2 | 0.5716 | E-T2 | 0.6018 | E-E2 | 0.5775 |
E-G3 | 0.6214 | E-R3 | 0.5688 | E-T3 | 0.5829 | E-E3 | 0.5770 |
E-G4 | 0.5927 | E-R4 | 0.5840 | E-T4 | 0.5999 | E-E4 | 0.6020 |
E-G5 | 0.5753 | E-T5 | 0.6217 | E-E5 | 0.6413 |
Fig. 2 The medium and strong symbiotic factors of multiple tourist agents “E→G-R-T-E” of Qinghai Lake |
Table 4 Symbiotic correlation degrees of the unit of symbiotic agents “E→G-R-T-E” of Qinghai Lake |
Units of symbiotic agents | E-G | E-R | E-T | E-E |
---|---|---|---|---|
δ | 0.5777 | 0.5834 | 0.5902 | 0.5913 |
Fig. 3 The symbiotic behavior routes of correlative agents “E→G-R-T-E” in the Qinghai Lake area |
Table 5 Construction of the symbiotic behavior routes of correlative agents “E→G-R-T-E” in the Qinghai Lake area |
E-G | E-R | E-T | E-E | |
---|---|---|---|---|
Benefits of correlative agents “E→G-R-T-E” | G=a5˃a4˃a3˃a2˃a1 | R=a10˃a9˃a8˃a7˃a6 | T=a16˃a15˃a14˃a13˃a12˃a11 | E=a22˃a21˃a20˃a19˃a18˃a17 |
Benefits of Tourist Enterprises (E) | E=b5˃b4˃b3˃b2˃b1 | E=b10˃b9˃b8˃b7˃b6 | E=b16˃b15˃b14˃b13˃b12˃b11 | E=b22˃b21˃b20˃b19˃b18˃b17 |
Symbiotic routes combination | WE-G=W5˃W4˃W3˃W2˃W1 | WE-R=W10˃W9˃W8˃W7˃W6 | WE-T=W16˃W15˃W14˃ W13˃W12˃W11 | WE-E=W22˃W21˃W20˃ W19˃W18˃W17 |
Symbiotic routes combination of multiple-agents “E→G-R-T-E” in Nash equilibrium | WE→G-R-T-E=W5+W10+W16+W22 |
The authors have declared that no competing interests exist.
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