1. Introduction
Ecosystems are the foundation for human survival and development, providing the environmental conditions and material support necessary for human existence. The benefits that humans derive from the natural environment are defined as ecosystem services (ES) [
1]. The basic ideas behind ES germinated in the late 1960s. The term "ecosystem services" was coined in 1982 by ecological scientist Walter Westman, bringing the concept into wider use [
2]. In 1997, ecological economists Robert Costanza et al. published a landmark paper describing a methodology for valuing ecosystem service functions and estimating the annual economic value of the world's ecosystem services to be
$33 trillion [
3]. This research has led to the recognition that public environmental resources, such as clean water and biological resources, are limited and valuable, and has made people aware of the importance of the public goods provided by the ecological environment [
4]. The Millennium Ecosystem Assessment, conducted in 2005, systematically studied the relationship between ES and human well-being and focused on the assessment of ecosystem service functions. The project classified ES into four categories: provisioning, regulating, cultural, and supporting services, and this classification system has since become widely used in environmental science, economics, and policy.
Cultural ecosystem service (CES) refers to the non-material well-being that humans obtain from ecosystems, including aesthetic inspiration, cultural identity, sense of home, and spiritual experiences [
1]. Cultural ecosystem services (CESs) are directly experienced and subjectively valued by people who benefit from them [
5]. They are more closely related to human well-being [
6,
7] and the ecosystem's sustainability [
8]. However, it is difficult to identify and evaluate CESs, since the value of these intangible benefits depends not only on the physical landscape and infrastructure but also on public demand and social culture [
9]. Because of this challenge, the evaluation of CESs has become a hot topic in recent years. The evaluation methods are generally divided into value accounting [
10,
11,
12,
13], land use matrix method [
14,
15,
16], participatory method [
17,
18], and model simulation [
19,
20,
21]. Currently, most evaluations of CESs focus on assessing the overall CES from the perspective of service supply and demand or synthesizing the overall results through simple evaluations of each service category.
Some studies focus on the evaluation of a particular type of CESs, mostly recreation service [
22,
23,
24] and aesthetic service [
25,
26,
27], which are easier to quantify. Very little of the literature deals with tourism service, even though tourism is a significant contributor to ecosystem services. A very important reason is that there is some controversy about whether the tourism service belongs to cultural services. Some authoritative institutional reports that serve as the basis of research provide relevant elaborations on tourism. The Millennium Ecosystem Assessment (MEA) report uses the term "recreation and ecotourism" as an example to illustrate the classification of cultural services [
1] (p.7). The Economics of Ecosystems and Biodiversity (TEEB) report clearly lists “tourism” as a category under cultural services when describing the classification of ES [
28] (p.4). Although the two reports classify tourism as a cultural service, the term "ecotourism" is predominantly used throughout the text, suggesting that only tourism closely related to the natural environment is recognized. Moreover, many statements consider tourism as an industry that depends on ES or describe it as a beneficiary of ES. As Josep Pueyo-Ros has stated in his paper, tourism is treated in a "schizophrenic" manner [
29], being considered on the one hand as a cultural ecosystem service, and on the other hand as a "nature-based consumptive industry". In the SEEA (System of Environmental Economic Accounting) report, the services that benefit visitors/tourists are classified as recreation-related services, and tourism is not directly mentioned [
30]. To support the SEEA revision, the European Environment Agency (EEA) has published the Common International Classification of Ecosystem Services (CICES). The classification of ES in this report is more systematic and complex. Although tourism is not directly mentioned in the category of cultural services, some of the elaborations in the report are instructive as to whether tourism can be considered as a cultural service. The report regards cultural services as "the environmental settings, locations or situations" that can involve "individual species, habitats, and whole ecosystems", which is a more specific and detailed definition [
31] (p.10). According to this definition, especially for tourism cities, visitations are the most prominent and dominant setting of the city. In other words, tourism can exist as a cultural service for tourism-oriented cities. It also states that "The settings can be semi-natural as well as natural settings (i.e., can include cultural landscapes) providing they are dependent on in-situ living processes " [
31] (p.10). This indicates that the report no longer emphasizes only completely natural environments, but that semi-natural environments, managed ecosystems and even cultural landscapes can provide cultural services. Therefore, tourism does not need to be limited to whether it is nature-based or not. For cities like Liyang that are striving to develop all-for-one tourism, all kinds of tourism attractions should be included in the evaluation of tourism service.
At present, there is not a complete theoretical framework or evaluation system for tourism service. Evaluations related to tourism service are often from the perspective of the tourism industry, focusing on tourism performance [
32,
33,
34], tourist behavior preference [
35,
36,
37], tourism resource potential [
38,
39,
40], tourism service quality [
41,
42,
43], and tourism service economic valuation [
44,
45,
46]. The evaluation methods mainly include monetary approaches [
44,
47], questionnaire and interview surveys [
36], evaluation by constructing an indicator system [
32,
33,
48], model simulation [
49,
50], and social media data mining [
51,
52]. Although monetary quantification is popular and convenient, it is always subjective and difficult to capture non-use values, such as existence or bequest values, which are often important components of the total economic value [
53]. Questionnaire and interview surveys are more conventional and are prone to random errors with small sample data. The model simulation approach draws mainly on the Recreation module of the InVEST model and the SolVES model. However, the InVEST model often cannot accurately reflect the actual situation of the study area. This is because the geotagged photos used in the "Recreation and Tourism" tool come only from the Flickr website, which is not universally used in all countries around the world, and the database only covers the period from 2005 to 2017. The SolVES model can create a statistical model between social survey data and natural environmental variables, but the model's single environmental parameter setting will cause different landscape types to use the same environmental variables, which ultimately leads to inaccurate results [
54].
As tourism is an important driving force for integrated urban-rural development and an important platform for external communication, China has vigorously developed the tourism industry since the reform and opening up in the 1980s, becoming the largest domestic tourism market and one of the world's leading tourism economies. In 2015, the National Tourism Administration first proposed the concept of "all-for-one tourism". Since then, local governments across the country have been exploring ways to integrate tourism with various industries and utilize existing tourism resources to promote regional development [
55,
56]. As a typical city that relies on its natural resources to develop all-for-one tourism, Liyang's top priority is to ensure a good ecological environment, so it is necessary to evaluate ES by taking tourism service as the dominant type of cultural service. Taking Liyang as an example, this paper constructed a tourism service evaluation system from the perspective of service supply and tourist demand. Based on the evaluation results, tourism service improvement suggestions were proposed from the perspective of enhancing the city's ecosystem services, providing policy references and planning guidelines for the city's future development. The research also provided a case study for enriching the evaluation of cultural ecosystem services.
4. Discussion
4.1. Practical Implications for Future Tourism Development
In order to promote the coordinated development of ecological environment and tourism in Liyang, it is necessary to take measures from the perspective of improving ecosystem services. Through the comprehensive evaluation and analysis, the following suggestions are proposed for the city’s future tourism development.
(1) For developed scenic spots and attractions, such as the hotspot areas shown in the previous analysis, a large number of online reviews have already been generated. This paper used social media data mining and sentiment analysis to obtain word clouds of tourist sentiment tendencies. The positive word clouds reflect the advantages that should be carried forward. The negative word clouds reflect the dissatisfaction of tourists, which needs to be targeted for improvement and enhancement. First, the tour routes within the scenic areas need to be more reasonable and flexible. Second, the transport capacity within the scenic areas needs to be expanded, especially during the peak season when there are large crowds, to eliminate long waiting times and crowded queues for tourists. In addition, the high fees charged by scenic spots are also a prominent issue, especially for the national 5A-level Tianmu Lake and Nanshan Bamboo Sea. The business model of seeking high profits from ticket sales and transport fees should be changed as soon as possible because tourists will not return. The excellent tourism resources should be fully utilized to develop advanced services and related industry chain, providing tourists with a variety of affordable and high-quality tourism experiences. This will in turn attract a continuous stream of tourists, creating a virtuous cycle and promoting the development of the whole city.
(2) As analyzed in the previous section, the cold spots of tourism service are located in the southwest of the city, where there are good mountain and forest landscapes, as well as large areas of farmland and ponds. It is therefore necessary to carry out mountain restoration and farmland system restoration. At the same time, tourism should be combined with the local industries such as the pumped storage power station, the cement factory, and shrimp farming. It is a good opportunity to develop new tourism projects with a beautiful ecological environment and unique characteristics.
(3) Rural tourism is a development approach that is highly integrated with new urbanization and all-for-one tourism. Since 2013, Liyang has been committed to creating a rural pattern of an “ecological home and leisure paradise”, through the development model of “rural areas as tourism destinations”. At present, it has more than 20 villages with national or provincial honors. However, these well-developed villages are small in scale and scattered in distribution, failing to form a clustering effect. In the future, it will be necessary to make greater efforts to build rural tourism destinations that are highly integrated with ecology, production, and life. It is also important to create a rural tour route that connects the villages, which will become an important aspect of all-for-one tourism.
4.2. Methodological Advantages
As there has been controversy over whether the tourism service belongs to cultural services, few articles have studied tourism from the perspective of ecosystem services. Through reviewing literature and authoritative reports, this paper argues that tourism service should be treated as a cultural service for tourism-oriented cities. Taking Liyang, a typical all-for-one tourism city in China, as an example, a tourism service evaluation indicator system was established from three aspects: the quality of tourism resources, the comprehensiveness of tourism service facilities, and tourist satisfaction. This study expands the boundary of cultural services and enriches the research cases of ecosystem service evaluation.
In terms of analyzing tourist satisfaction, this paper used the Octopus tool to collect big data of tourist check-in photos and comments from tourism websites and used ROST CM for text mining to identify tourists’ sentiment tendencies. When analyzing the hotspot areas, the big data for tourism reviews is segmented and processed to generate positive and negative word clouds, based on which the corresponding improvement suggestions were proposed. Instead of traditional questionnaires, the big data analysis method can collect multi-source data of larger volume, which is not only cost-effective, but also avoids the subjective bias caused by small sample size.
4.3. Limitations and Future Research Directions
Given the data availability, this study selected 7 indicators to develop the basic evaluation system, some other indicators should be further considered to improve the research framework. For example, the landscape aesthetic quality should also be included in the scope of tourism resource quality. Each aspect of tourism services, such as dining, accommodation, recreation and medical services, should be specified with indicators. In addition, when measuring tourism accessibility, not only objective accessibility should be considered, but also perceived accessibility, which emphasizes the ease of access to activities, should be considered [
67].
Although big data analysis is more objective than questionnaires, there is still a sample representation issue. In general, social media users tend to be younger, more educated, and urban residents [
68,
69], which may lead to an overestimation of the perceptions of certain groups. In contrast, questionnaires and interviews have the advantage of being able to collect demographic information. Future research should organically combine conventional and innovative social survey methods for spatial and non-spatial data collection.
5. Conclusions
With many advantages, such as good economic benefits, low resource consumption, and low environmental impact, tourism is an important industry of the national economy and an important channel for expanding employment [
70]. As a cross-regional activity, tourism plays a crucial role in promoting economic development, human well-being, and cultural awareness. At present, there is still no unified understanding of tourism service in ES research, and no evaluation method system for tourism service has been formed. This paper advocates that tourism service should be considered as a cultural service, at least for tourism cities. Liyang in China was taken as an example to evaluate tourism service using technical methods such as GIS spatial analysis, social media data mining and sentiment analysis. The research results show the following conclusions:
(1) The areas with higher tourism service are distributed in the north-western edge and the east of the city, while the areas with lower tourism service are mainly distributed in the north-eastern and south-western parts of the city. The hotspot areas are located in Wawushan Scenic Area and Bieqiao Village in the northern part of the city, Caoshan Resort in the west, Tianmu Lake and Nanshan Bamboo Sea in the south, and the central area of the city. The cold spot areas are concentrated in the southwest.
(2) The hotspot areas should focus on improving the tour routes, the transport capacity, and excess charges. The cold spot areas should work on ecological restoration, and meanwhile, create new tourism attractions by combining the local industries. Besides, rural tourism needs further development in the future.
(3) This paper has made a preliminary attempt to evaluate tourism service, and the research framework should be further improved by carefully considering indicators from other aspects and by adopting an integrated multi-method approach to data collection.
Figure 1.
Location of the study area and distribution of tourism resources.
Figure 1.
Location of the study area and distribution of tourism resources.
Figure 2.
Landscape area loss index at different granularities.
Figure 2.
Landscape area loss index at different granularities.
Figure 3.
Landscape indexes at different granularities.
Figure 3.
Landscape indexes at different granularities.
Figure 4.
Evaluation grid network.
Figure 4.
Evaluation grid network.
Figure 5.
Quality of Tourism Resource Evaluation. (a) Density; (b) Reputation; (c) Popularity.
Figure 5.
Quality of Tourism Resource Evaluation. (a) Density; (b) Reputation; (c) Popularity.
Figure 6.
Distribution of tourism service facilities. (a) Tourism service POI; (b) Road network.
Figure 6.
Distribution of tourism service facilities. (a) Tourism service POI; (b) Road network.
Figure 7.
Evaluation of the comprehensiveness of tourism service facilities. (a) Tourism service POI density; (b) Transport accessibility.
Figure 7.
Evaluation of the comprehensiveness of tourism service facilities. (a) Tourism service POI density; (b) Transport accessibility.
Figure 8.
Evaluation of tourist satisfaction. (a) Number of check-in photos at attractions; (b) Sentiment orientation of tourist reviews.
Figure 8.
Evaluation of tourist satisfaction. (a) Number of check-in photos at attractions; (b) Sentiment orientation of tourist reviews.
Figure 9.
Comprehensive evaluation of tourism service.
Figure 9.
Comprehensive evaluation of tourism service.
Figure 10.
Hot-cold spot analysis.
Figure 10.
Hot-cold spot analysis.
Figure 12.
Word clouds of hotpot areas. 1 indicates Wawushan Scenic Area, 2 indicates Caoshan Resort, 3 contains the attractions of the central city, 4 mainly covers Tianmu Lake, 5 mainly covers Nanshan Bamboo Sea Scenic Area, 6 indicates cold spot area in Tianmu Lake Town, 7 indicates the cold spot area in Shezhu Town.
Figure 12.
Word clouds of hotpot areas. 1 indicates Wawushan Scenic Area, 2 indicates Caoshan Resort, 3 contains the attractions of the central city, 4 mainly covers Tianmu Lake, 5 mainly covers Nanshan Bamboo Sea Scenic Area, 6 indicates cold spot area in Tianmu Lake Town, 7 indicates the cold spot area in Shezhu Town.
Figure 13.
Aerial photos and proposed programs of cold spot area in Tianmu Lake Town.
Figure 13.
Aerial photos and proposed programs of cold spot area in Tianmu Lake Town.
Figure 14.
Aerial photos and proposed programs of cold spot area in Shezhu Town.
Figure 14.
Aerial photos and proposed programs of cold spot area in Shezhu Town.
Table 1.
Basic data.
Category |
Data |
Data Source |
Location data |
Tourism resources |
Baidu Maps |
POIs of tourism service facilities |
Road network |
OpenStreetMap |
Big data for tourism reviews |
Number of check-in photos at attractions |
Ctrip (www.ctrip.com), |
Tourism review texts |
Mafengwo (www.mafengwo.cn), |
Popularity ratings of attractions |
Tongcheng Travel (www.ly.com) |
Table 2.
Evaluation indicator system for tourism service
Table 2.
Evaluation indicator system for tourism service
Target |
Indexes |
Weight |
Factors |
Weight |
Tourism service |
Quality of tourism resource |
0.2427 |
Density |
0.0953 |
Fame |
0.0749 |
Popularity |
0.0725 |
Comprehensiveness of tourism service facilities |
0.581 |
Tourism service POI density |
0.063 |
Transport accessibility |
0.518 |
Tourist satisfaction |
0.1763 |
Number of check-in photos at attractions |
0.085 |
Sentiment orientation of tourist reviews |
0.0913 |
Table 3.
Speed and time cost values for different road levels.
Table 3.
Speed and time cost values for different road levels.
Road levels |
Motorway |
Level 1 |
Level 2 |
Level 3 |
Level 4 |
Pedestrian |
Other |
Speed () |
100 |
80 |
60 |
40 |
20 |
10 |
5 |
Time cost value () |
0.6 |
0.75 |
1 |
1.5 |
3 |
6 |
12 |
Table 4.
Statistics of the area proportion of tourism service by different levels.
Table 4.
Statistics of the area proportion of tourism service by different levels.
Area Proportion (%) |
Lower level |
Low level |
Medium level |
High level |
Higher level |
Whole city |
4.07 |
21.28 |
47.08 |
24.72 |
2.85 |
City divisions |
Zhuze Town |
0.00 |
4.59 |
67.34 |
22.39 |
5.68 |
Shangxing Town |
1.80 |
21.69 |
53.05 |
17.70 |
5.76 |
Nandu Town |
0.65 |
19.46 |
77.20 |
2.68 |
0.00 |
Shezhu Town |
20.24 |
58.33 |
19.49 |
1.94 |
0.00 |
Bieqiao Town |
0.18 |
33.15 |
55.00 |
9.42 |
2.24 |
Shanghuang Town |
4.07 |
12.44 |
49.79 |
33.48 |
0.21 |
Daitou Town |
0.91 |
11.74 |
39.25 |
48.09 |
0.00 |
Kunlun Subdistrict |
0.00 |
11.64 |
58.98 |
29.38 |
0.00 |
Licheng Subdistrict |
0.00 |
0.10 |
8.15 |
88.18 |
3.57 |
Guxian Subdistrict |
0.00 |
2.84 |
43.69 |
52.06 |
1.42 |
Tianmu Lake Town |
5.37 |
20.85 |
42.56 |
27.13 |
4.10 |
Daibu Town |
0.07 |
6.61 |
36.24 |
52.42 |
4.66 |