Analysis on the tourism resource evaluation factors based on grey relational analysis – Taking Guizhou minority areas as an example

Abstract

Evaluation of tourism resources can help the government adjust policies and foster the development of tourism. As one of the ethnic areas, Guizhou has abundant tourism resources. In this study, five tourism resources in Guizhou, a minority area, including Huangguoshu Falls, Qianhu Hmong Village, Qingyan Ancient Town, Hailongtun Tusi Town and One Hundred Miles Azalea Park, were evaluated by using grey relational analysis theory (GRA). Through the establishment of the evaluation system, the appropriate evaluation indexes were selected and evaluated by the expert group to obtain index weight and specific index value. After dimensionless processing of the data, the relevancy coefficient and relevancy degree were calculated by grey relational analysis. It was found that the relevancy degree of the five tourism resources were 0.6907, 0.6329, 0.6421, 0.6129 and 0.6785 respectively, which indicated that the values of Huangguoshu Falls and One Hundred Miles Azalea Park were high and tourism value of Hailong Tusi Town was relatively low, and the results obtained were consistent with the actual situation.

Keywords

Grey relational analysis evaluation of tourism resource Guizhou indicator system tourism resource value

1. Introduction

Tourism is one of the fastest growing industries and contributes most to economic development at present [1, 2]. Tourism resources is the basis of tourism development. Through the evaluation of tourism resources, we can have a better understanding of tourism resources, determine whether they have the value of further development, and convert the potential value into economic value and social value [3]. In addition, the evaluation of tourism resources has a great role in the protection and sustainable development of resources. Most of the evaluation of tourism resources is based on the quality of tourist attractions [4]. There are many ways to evaluate tourism resources. Saiken et al. [5] evaluated Kazakh ethnic cultural tourism resources with fuzzy evaluation method to the impact of human factors on the evaluation. Zhao et al. [6] comprehensively evaluated and analyzed the wild plant resources in Guangxi Province using Entropy-Analytic Hierarchy Process (AHP) evaluation model and index weight model. It was found that although the level of sustainable development showed a slow upward trend, the overall level was still low, the comprehensive economic index was relatively stable, and the comprehensive social index showed a decreasing tendency after increasing. It provides some theoretical basis for promoting the development of wild plant resources in Guangxi province. Zeng et al. [7] evaluated the ecotourism resources of Xingkai Lake wetland by analytic hierarchy process and established an evaluation system which took ecological value, ecotourism resource value and resources development value as the main indicators. They found that the score of the ecotourism resource value of the Xingkai Lake wetland was 75.35, which was consistent with the status of the wetland. Wu et al. [8] evaluated the tourism resources in Xi’an, Shaanxi, China with AHP and fuzzy comprehensive evaluation method based on tourist perception, which provides a theoretical basis for the tourism development of Xi’an. Guizhou as a multi-ethnic-populated area has rich tourism resources. Evaluating the tourism resources in Guizhou has great values for the development and utilization of tourism resources in minority areas. In this study, grey relational analysis theory was used. The tourism resources in Guizhou, including Huangguoshu Falls, Qianhu Hmong Village, Qingyan Ancient Town, Hailongtun Tusi Town and One Hundred Miles Azalea Park, were evaluated through establishment of indicator system and expert group scoring.

2. Overview of tourism resources in Guizhou

Guizhou as one of the minority areas is a province with extremely rich tourism resources and high tourism values in China. The special karst landform in Guizhou is an unique natural scenery. The depression and waterfall on the ground and karst cave and underground river have high ornamental values. Animal and plant resources are also very rich. Besides natural landscape, Guizhou also has rich human landscape resources. As a multi-ethnic province, the multi-ethnic culture brings large influence to the architecture, diet, marriage custom and worship ceremony in Guizhou. The complex and special ethic culture been feature that attracts tourists. Guizhou is one of the birthplaces of ancient mankind, and many hominid sites have been found in Guizhou. It has revolutionary colors, for example, the famous historical events such as Zunyi Meeting and four times of crossing Chishui River. The red tourism resources is a part of the tourism resources. Some of the tourism resources in Guizhou are shown in Table 1.

Table 1
Some tourism resources of Guizhou

National 5A tourist attractions	Huangguoshu Waterfall, Loong Palace and One Hundred Miles Azalea Park
National 4A tourist attractions	Tianhe Tan, Qingyan Ancient Town, Zhijin Cave, Mount Fanjing, Nanjiang Valley, Libozhang River, Xijiang Hmong Village, Mount Yuntai, Lou Shan Pass, Mount Shuangru, Yushe Forest, Yelang Ancient Spring and Feilong Village
National Key Scenic Sites	Hongfeng Lake, Malinghe Valley, Shiqian hot spring, Jiulong Cave, Ziyun Getu River, Pingtang and Yanhe Wujiang One Hundred Miles Gallery
National forest park	Chishui Zhuhai National Forest Park, Mount Fenghuang, Huangping Wuyang River, Duyun Qingyun Lake, Zheng’an Jiudao water forest park, Bijie Forest and Xishui
National geological park	Guanling Fossil National Heopark, Mount Wumeng, Chishui Danxia, Sinan Wujiang Karst and Suiyang Shuanghe Cave
National Nature Reserve	Mount Leigong, Chishui Suoluo Nature Reserve, Weining Caohai, Yanhe Mayang River, Xishui mid-subtropical-broad-leaved evergreen forest and Maolan Karst Forest
Major historical and cultural sites protected at the national level	Site of Zunyi Meeting, Shiqian Wanshou Palace, Congjiang Zengchong Tower, former site of crossing Chishui the fourth times, former site of Zhenyuan Heping Village, Fuquan Ming Dynasty City Wall, Historic Site of Anshun Ningu and Anshun Fuwen Temple
National intangible cultural heritages	The Leishan Miao manufacturing technique of reed-pipe wind instrument, Danzhai Shiqiao ancient paper-making technique, Nayong Gushanzhu dance, Sinan Huadeng Opera, Shiqian puppet show, Zhenning Bronze Drum, and Renhuai Maotai brewing technology

3. Grey relational analysis

Grey relational analysis can be used to find out the relationship between different elements based on the correlation between reference sequence and comparison sequence [9] and find out factors that influence target value. The correlation represents the influence degree between elements and objects. The larger the correlation, the larger the influence; the smaller the correlation, the smaller the influence [10]. The main procedures of grey relational analysis are shown below.

(1)
The behavioral characteristics of the system were analyzed. Sequence of dependent variables was taken as the reference sequence, and sequence of independent variables was taken as the comparative sequence. Reference sequence was supposed as $x_{0}=\{{x_{0}(k)|k=1,2,\cdots,n}\}$ and the comparative sequence as $x_{i}=\{{x_{i}(k)|k=1,2,\cdots,n}\}$ , where $x_{0},x_{i}\in x(i=1,2,\cdots m)$ .
(2)
As the units of different elements in the system were different, the original data needed to be processed by dimensionless method, i.e., initialization. Dimensionless data could be obtained by dividing the original data at the back by the first data in the same sequence.
(3)
The relevancy coefficient was calculated. The expression of the relevancy coefficient of $x_{0}(k)$ and $x_{0}(k)$ was:

$\displaystyle\zeta_{i}(k)=\frac{\mathop{\min}\limits_{i}\mathop{\min}\limits_{% k}|x_{0}(k)-x_{i}(k)|+\rho\mathop{\max}\limits_{i}\mathop{\max}\limits_{k}|x_{% 0}(k)-x_{i}(k)|}{|x_{0}(k)-x_{i}(k)|+\rho\mathop{\max}\limits_{i}\mathop{\max}% \limits_{k}|x_{0}(k)-x_{i}(k)|}.$ (1) $\displaystyle\Delta_{i}(k)=|x_{0}(k)-x_{i}(k)|,\text{ then}$ $\displaystyle\zeta_{i}(k)=\frac{\mathop{\min}\limits_{i}\mathop{\min}\limits_{% k}\Delta_{i}(k)+\rho\mathop{\max}\limits_{i}\mathop{\max\Delta_{i}(k)}\limits_% {k}}{\Delta_{i}(k)+\rho\mathop{\max}\limits_{i}\mathop{\max\Delta_{i}(k)}% \limits_{k}},$ (2)

where $\rho\in(0,\infty)$ is an identification coefficient, 0.5 generally.
(4)
The relevancy degree was calculated using the follow equation:

$\displaystyle r_{i}=\frac{1}{n}\sum\limits_{k=1}^{n}{\zeta_{i}(k),k=1,2,\cdots% ,n}.$ (3)
(5)
The obtained relevancy degrees were ranked, and the main and secondary factors of target changes were combined with the actual condition for analysis.

4. Grey relational analysis based Guizhou tourism resources evaluation

4.1 Selection of evaluation indicators

The tourism resources in the minority areas were evaluated according to Tourism Resources Classification, Investigation and Evaluation of People’s Republic of China (GB/T18972-2003). The evaluation system is shown in Fig. 1.

Figure 1.

The tourism resources evaluation system.

The evaluation of tourism resources is mainly carried out from perspectives of the value of resource elements, the influence of resources and the added value. The value of resource elements mainly refers to the value of the evaluated object as a tourist resource.

(1)

Ornamental and recreational values: whether an object is worth watching and pleasant in the process of tourism is evaluated.

(2)

Historical, scientific, cultural and artistic values: whether an object is historic, scientific, cultural and artistic is evaluated.

(3)

Rare or peculiar degree: whether an object has rare species or whether a landscape is special was evaluated.

(4)

Scale, abundance and probability: whether the evaluation object has a large scale, the landscape is harmonious and unified, and the interaction between nature and humanity is obvious is evaluated.

(5)

Completeness: whether the evaluated object is intact or not destroyed is evaluated.

Resource influence includes two aspects:

(1)

Popularity and influence: whether an object is well-known worldwide or nationwide is evaluated.

(2)

Suitable period or scope of use: whether an object has a long tour date or can be visited by most tourists is evaluated.

Added value is about the environmental aspects of tourism resources, that is, tourism protection and environmental safety. It refers to whether the evaluated object is under protection, without being polluted and destructed. This indicator includes positive and negative scores, negative score for being protection and negative score for being polluted and damaged.

Twenty staffs who engaged in the tourism research field and the tourism industry were selected to form an expert group to judge the importance of each indicator in the tourism resources evaluation system. The comprehensive weight of each indicator was obtained by Yaaph 0.5.3, weight calculation and consistency test (Fig. 1).

4.2 Scoring process

The scoring standards of tourism resources described in Tourism Resources Classification, Investigation and Evaluation of People’s Republic of China. Environmental protection and safety in the item of added value could be positive or negative. The tourism resources in the minority areas were scored by the expert group. Five tourism resources were selected, and they were Huanggguoshu Waterfall (A ${}_{1}$ ), Qianhu Hmong Village (A ${}_{2}$ ), Qingyan Ancient Town (A ${}_{3}$ ), Hailongtun Tusi Town (A ${}_{4}$ ) and One Hundred Miles Azalea Park (A ${}_{5}$ ).

Table 2
Values of indicators of tourism resources

Indicator	Standard	A ${}_{1}$	A ${}_{2}$	A ${}_{3}$	A ${}_{4}$	A ${}_{5}$
X ${}_{1}$	30	27	24	22	17	26
X ${}_{2}$	25	20	22	18	17	16
X ${}_{3}$	15	13	10	8	7	9
X ${}_{4}$	10	8	8	7	6	8
X ${}_{5}$	5	4	3	3	3	3
X ${}_{6}$	10	9	7	7	6	7
X ${}_{7}$	5	3	4	4	4	2
X ${}_{8}$	$+$ / $-$	$-$ 5	$-$ 5	$-$ 4	$-$ 3	$-$ 4

The obtained data were processed by dimensionless, and the results are shown in Table 3.

Table 3

The dimensionless processing of data

Indicator	Standard	A ${}_{1}$	A ${}_{2}$	A ${}_{3}$	A ${}_{4}$	A ${}_{5}$
X ${}_{1}$	1	1	1	1	1	1
X ${}_{2}$	0.83	0.74	0.92	0.82	1.00	0.62
X ${}_{3}$	0.50	0.48	0.42	0.36	0.41	0.35
X ${}_{4}$	0.33	0.30	0.33	0.32	0.35	0.31
X ${}_{5}$	0.17	0.15	0.13	0.14	0.18	0.12
X ${}_{6}$	0.33	0.33	0.29	0.32	0.35	0.27
X ${}_{7}$	0.17	0.11	0.17	0.18	0.24	0.08
X ${}_{8}$	0.00	$-$ 0.19	$-$ 0.21	$-$ 0.18	$-$ 0.18	$-$ 0.15

According to the obtained dimensionless data, the relevancy coefficient was calculated using Eq. (2), and the calculation results are shown in Table 4.

Table 4

Value of relevancy coefficient

Indicator	A ${}_{1}$	A ${}_{2}$	A ${}_{3}$	A ${}_{4}$	A ${}_{5}$
$\zeta_{i}(1)$	1	1	1	1	1
$\zeta_{i}(2)$	0.87	0.73	0.62	0.62	086
$\zeta_{i}(3)$	0.62	0.59	0.32	0.53	0.59
$\zeta_{i}(4)$	0.43	0.33	0.41	0.29	0.29
$\zeta_{i}(5)$	0.29	0.48	0.39	0.13	0.51
$\zeta_{i}(6)$	0.46	0.59	0.62	0.36	0.49
$\zeta_{i}(7)$	0.78	0.62	0.49	0.59	0.62
$\zeta_{i}(8)$	0.29	0.12	0.19	0.23	0.34

The relevancy degree of the tourism resources was calculated using Eq. (3) according to the relevancy coefficient. The calculation results were A ${}_{1}$ $=$ 0.6907, A ${}_{2}$ $=$ 0.6329, A ${}_{3}$ $=$ 0.6421, A ${}_{4}$ $=$ 0.612 and A ${}_{5}$ $=$ 0.6785.

The final evaluation result was A ${}_{1}$ $>$ A ${}_{5}$ $>$ A ${}_{3}$ $>$ A ${}_{2}$ $>$ A ${}_{4}$ , i.e., Huangguoshu Waterfall $>$ One Hundred Miles Azalea Park $>$ Qingyan Ancient Town $>$ Qianhu Hmong Village and Hailongtun Tusi Town. Therefore the tourism resource values of Huangguoshu Waterfall and One Hundred Miles Azalea Park were high, and the tourism resource value of Hailongtun Tusi Town was low.

5. Discussion

Grey relational analysis is simple in calculation; therefore it has a large advantage in information system processing and can analyze the degree of relevancy between evaluation objects. It has been applied in many fields, for example, the development and utilization of mineral resources [11], the main factors affecting the driving force of carbon dioxide emissions [12], the main factors affecting the financial expenditure for tourism development [13], the related factors affecting the competitiveness of urban tourism and tourism revenue [14, 15].

In this paper, the tourism resources of Guizhou Province were evaluated by grey relational analysis. Five tourism resources, Huangguoshu Waterfalls, Qianhu Hmong Village, Qingyan Ancient Town, Hailongtun Tusi Town and One Hundred Miles Azalea Park were taken as the evaluation objects. In the establishment of evaluation indicator system, the evaluation method described in Tourism Resources Classification, Investigation and Evaluation of People’s Republic of China was used, i.e., obtaining indicator weight and the concrete index value by expert group scoring. After the dimensionless processing of the data, the relevancy coefficient and relevancy degree of the tourism resources were calculated by grey relational analysis. The results showed that Huangguoshu Waterfalls had the largest relevancy degree, followed by One Hundred Miles Azalea Park, Qingyan Ancient Town, Qianhu Hmong Village and Hailong Tusi Town. It indicated that the tourism resource values of Huangguoshu Waterfall and One Hundred Miles Azalea Park were high, and the tourism resource value of Hailongtun Tusi Town was low.

Huangguoshu Waterfalls is a national 5A scenic spot. It has been ranked as the largest waterfall group in the world by the Guinness headquarters. It has been recorded in the Guinness World Records and has a history of 50,000 years. It has extremely high ornamental value. It also has high historical and cultural values because of the praise of ancient literati. In the long process of development and construction, Huangguoshu Waterfall as a tourist resource has been deeply developed, and environmental protection has also received sufficient attentions. Therefore, Huangguoshu Waterfall is of great values.

One Hundred Miles Azalea Park which covers about 125 square kilometers is also one of the national 5A scenic spots. It is the largest natural Azalea garden in the world and also a summer resort. Besides Azalea, it has more than one hundred of animals and plants, including clouded leopard and Taxus chinensis. Moreover it has a patriotism education base, and some minorities such as the Miao and Yi minorities inhabit in the One Hundred Miles Azalea Park. Since the establishment of the management committee of One Hundred Miles Azalea Park in 2007, the environmental protection and development has gained good development. It indicates that One Hundred Miles Azalea Park also has high values.

Hailongtun Tusi Town is a Tusi castle served in the period from Song dynasty to Ming dynasty in Longyan, Zunyi, Guizhou, China. It is a provincial cultural relic protection site. Its ornamental and recreational value is lower than the natural scenic spots such as Huanggguoshu Waterfall and One Hundred Miles Azalea Park, but it is of high values to the study of military affairs and politics in the Middle Ages. Overall it has low popularity and influence, small scale and general tourism value.

6. Conclusion

Evaluation of tourism resources is of great values to the development and utilization of tourism resources. In this study, five tourism resources in Guizhou minority areas were evaluated using grey relational analysis, the indicator values of the evaluation system were obtained through scoring of expert group, and the relevancy coefficient and degree were calculated. It was found that the tourism values of Huangguoshu Waterfall and One Hundred Miles Azalea Park were high, and that of Hailongtun Tusi Town was low, which were consistent with the actual conditions.

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Analysis on the tourism resource evaluation factors based on grey relational analysis – Taking Guizhou minority areas as an example

Abstract

Keywords

1. Introduction

2. Overview of tourism resources in Guizhou

Table 1 Some tourism resources of Guizhou

4.1 Selection of evaluation indicators

Table 2 Values of indicators of tourism resources

6. Conclusion

References

Table 1
Some tourism resources of Guizhou

Table 2
Values of indicators of tourism resources