Study on the Coordinated Development of Tourism Industry–Regional Economy–Ecological Environment in the Yili River Valley

Abstract

This study aims to clarify the relationship among the three systems of tourism industry, regional economy, and ecological environment in the Yili River Valley, which is essential for the sustainable development of the region. We explore the spatio-temporal evolution characteristics and influencing factors of the tourism–economy–ecosystem in the Yili River Valley using the center of gravity model, spatial mismatch index model, spatial variance model, and obstacle degree model, based on panel data from 2010 to 2019. The study shows that (1) the comprehensive development indices of the tourism industry, regional economy, and ecological environment in the Yili River Valley exhibit varying degrees of growth trends. Smaller increases are observed in ecological environment indices, while larger increases are found in regional economy and tourism industry indices. Both the regional economy and tourism industry indices share a strong correlation and similar development trends. (2) At the macro-regional scale, during the study period, the centers of gravity of the tourism industry, regional economy, and ecological environment in the Yili River Valley have consistently been separated from the spatial geometric center of the region. The degree of misalignment of the centers of gravity of the three systems as a whole has gradually reduced, indicating that the level of coordinated development of the region has continuously improved. (3) At the micro-regional scale, during the study period, most of the spatial misalignment indices of the Yili River Valley regions showed positive and negative fluctuations, and the types of misalignment varied to different degrees. However, the gap in spatial misalignment indices between different regions gradually narrowed, and the divergent characteristics of “east-west concentration, north-south dispersion” were gradually broken, with the overall indices showing a balanced development trend. (4) The spatial dislocation index of each region in the Yili River Valley is affected by multiple systems and factors, and the overall spatial dislocation factors are mainly the comprehensive utilization rate of general solid waste, exhaust gas emission, dust removal amount, etc., which mostly originate from the ecological environment system.

1. Introduction

According to the data published in the “Basic Situation of the Tourism Market in 2019”, China’s total tourism revenue in 2019 reached 6.63 trillion yuan, a 4.22-fold increase compared to 2010. Its economic output accounted for 14.88% of the gross domestic product (GDP). This indicates that China’s tourism industry has been rapidly developing in recent years, and the concept of mass tourism has become deeply rooted in people’s minds. Moreover, the development of the tourism industry often leads to improvements in regional economic development levels, and the results of economic development, in turn, provide a material conversion basis for the optimization of the ecological environment system [1]. However, the Yili River Valley is located in the less-developed areas of northwestern China, and the development status of each region varies, resulting in an increasingly apparent imbalance in the tourism industry, regional economy, and ecological environment system in each region of the area. This spatial dislocation phenomenon will inevitably restrict the long-term development of tourism in the region [2]. Therefore, how to coordinate the relationship between the tourism industry, regional economy, and ecological environment in the Yili River Valley, improve the development level of various regions in the Yili River Valley, consolidate the achievements of poverty alleviation, and promote the sustainable development of tourism in the less-developed areas of western China have become important topics that tourism scholars have paid widespread attention to and local governments have focused on.

The “spatial dislocation hypothesis” is essentially a theory that reflects spatial heterogeneity and can demonstrate imbalances in development between different regional systems [3]. The theory was first proposed in the 1960s by Kain in an article published in “ the Quarterly Journal of Economics”, initially used to analyze the work–life separation and employment of disadvantaged groups [4]. Later, with the development of the theory, scholars gradually began to study the spatial matching problem between employment and housing for residents of large cities [5,6]. By the beginning of the 21st century, the theory had matured and been applied to various fields, such as urban development, agriculture, ecology, tourism, and more [7,8,9,10,11,12]. Among them, domestic research on tourism based on spatial theory mainly focuses on spatial mismatch between tourism resources and tourism economy [13,14,15], spatial mismatch between tourism resources and ecological environment [16,17], spatial mismatch between scenic area income and the number of visitors [18,19], spatial mismatch between tourism industry and cultural industry [20], and other two between indicators and the spatial mismatch study between tourism, cultural industry, and economic development level, inbound tourism flow, tourist attractions, star-rated hotels, and three other indicators [21,22,23,24].

Throughout the domestic research on the three major systems of tourism industry–regional economy–ecological environment, it can be seen that the research content mostly focuses on calculating the level of system coupling and coordination [1,25,26,27,28,29,30], with fewer studies on the spatial mismatch between the systems. The constructed indicator system is mostly composed of a single indicator or a small number of indicators, and the scientific nature of the calculation results can be easily questioned. The research perspective focuses on the spatial and temporal evolution characteristics of the spatial dislocation of the tourism system, with fewer studies on the correlation characteristics, dispersal trends, and influencing factors among regions. The research scale focuses on a single province and city, with fewer studies on the spatial dislocation of tourism at the county and city levels. Moreover, the research area focuses on the central and eastern provinces and cities of China, which have developed economies and relatively good ecological environments, with less research on arid areas in the west.

In light of this, this paper focuses on the Yili River Valley, a less-developed area in western China, as its research subject. By referring to the relevant domestic and international literature, we aim to construct a system encompassing the tourism industry, regional economy, and ecological environment. This paper examines the mismatch or imbalance in the development process of the tourism industry–regional economy–ecological environment system in the Yili River Valley from both macro and micro perspectives. It also observes the spatial evolution and differentiation patterns of the spatial dislocation index in various regions of the Yili Valley during the study period. Lastly, by calculating the obstacle factors of the Yili River Valley from 2010 to 2019, we explore the main influencing factors of spatial dislocation in the Yili River Valley. This research is expected to provide a reference for relevant departments of the Yili River Valley to improve the imbalanced development of the tourism industry, regional economy, and ecological environment system, enhance regional coordinated development capacity, accelerate regional integration processes, and promote the sustainable development of the Yili River Valley. Simultaneously, it also holds significant reference value for other less-developed areas with tourism as the leading industry in achieving coordinated and sustainable regional development.

2. Materials and Methods

Through a literature review, we discovered that the relationship between the tourism industry, regional economy, and ecological environment has consistently been a hot topic in tourism research. This paper focuses on the Yili River Valley, a less-developed area in China, with the aim of exploring the imbalance of the tourism industry, regional economy, and ecological environment in the Yili River Valley and its influencing factors. The main research content revolves around three aspects: first, estimating the comprehensive development level of the three systems in the Yili River Valley; second, analyzing the spatial dislocation degree and spatio-temporal differences in the three systems from the macro and micro levels of the Yili River Valley; and third, exploring the obstacle factors affecting the spatial dislocation of the three systems in the Yili River Valley in order to provide a reference for the future coordinated development of the three systems in the region.

Therefore, this paper is based on the spatial dislocation theory and determines the tourism industry, social economy, and ecological environment as the three system index systems. Firstly, the entropy–TOPSIS model is employed to calculate the comprehensive development values of the three systems. Secondly, based on the calculation of the comprehensive development value of the three systems, the center of gravity model and spatial dislocation index model are utilized to determine the spatial dislocation degree of the three systems in the Yili River Valley. Finally, the obstacle degree model is used to explore the obstacle factors affecting the coordinated development of the three systems in the Yili River Valley. A discussion is then conducted according to the research conclusions. The article structure is shown in Figure 1.

2.1. Overview of the Study Area

The Yili River Valley (80°9′–84°56′ E, 42°14′–44°50′ N) is located in the western part of China’s Tian Shan Mountains, surrounded by mountains on three sides, and is the northern key to the ancient Silk Road, with a total area of 56,500 km² in the entire valley, involving ten administrative units, such as Yining, Khorgos City, Qabqar Siberian Autonomous County (hereafter, referred to as Chaxian), Xinyuan County, Huocheng, Zhaosu County, and other administrative units (the city of Kokoda City of Corps is not included) (Figure 2). The region’s climate is humid, precipitation is abundant, enjoying the “Western Wet Island”, “Jiangnan outside the Serbian”, “the hometown of the heavenly horse” reputation. As the largest valley area in Xinjiang, the valley has a total area of 37,600 square kilometers of mountains, 18,900 square kilometers of hills and plains, and a complete development of vertical zones of vegetation in the valley, with a large number of flora and fauna, creating many scenic tourist attractions in the Yili River Valley.

The Yili River Valley has colorful tourism resources, with 165 representative tourism resource monoliths, including 2 national 5A-level tourism scenic spots and 22 national 4A-level tourism scenic spots. The total number of tourists in Yili Prefecture for the whole year of 2019 was 59,724,000, a year-on-year increase of 45%, and the tourism revenue was 70.11 billion yuan, a year-on-year increase of 43.4%. They accounted for 28.31% and 19.3% of the total number of tourists and total tourism revenue in Xinjiang, respectively. It can be seen that the Yili River Valley is one of the regions with the most development potential in Xinjiang’s tourism industry.

2.2. Data Sources

As the tourism industry in all regions is in a non-conventional special period from 2020 to 2022, and considering the continuity, stability, and accessibility of data, this paper takes the Yili River Valley as the study area and selects 2010–2019 as the study period. The data used are statistical data, mainly derived from the relevant statistics of each region of the Yili River Valley in 2010–2019 and internet search. Specifically, X1–X3 and X6–X7 are obtained from the 2011–2020 “China Tourism Statistical Yearbook” and the official website of the Department of Culture and Tourism of the Xinjiang Uygur Autonomous Region (http://wlt.xinjiang.gov.cn/) (Accessed on 5 September 2023); X4–X5 are obtained through the 2011–2020 data on the number of people in the tourism industry, the number of people employed in the tertiary industry, tourism revenue, GDP in each region of the Yili River Valley, and recalculated; X8–X18 are obtained from the “ Statistical Yearbook of the Yili Kazakh Autonomous Prefecture”, “the Statistical Yearbook of China’s Regional Economy”, and “the Statistical Bulletin of the National Economy” and Social Development of Each Region, 2011–2020; and X19–X26 are obtained from the 2011–2020 “China Environmental Statistics Yearbook” and regional forestry bureaus. Missing data for individual years are supplemented by linear interpolation. Additionally, the coordinates of the geometric centroids of each region of the Yili River Valley are obtained from Baidu map (http://api.map.baidu.com/lbsapi/getpoint/index.html) (Accessed on 13 January 2024).

2.3. Indicator System

From the domestic tourism spatial mismatch literature, it can be seen that the system spatial mismatch that the system in n and time presents a mismatch, imbalance situation, can be regarded as anti-coupling. Therefore, we can draw on the coupling coordination research to construct a multi-system spatial mismatch indicator system. In order to guarantee the scientificity and rationality of the indicator system construction, this paper synthesizes the research of domestic scholars on tourism spatial dislocation [13,14,15,16,17,19] and tourism coupling coordination [25,26,27,28,29,30]. Combining with the actual situation of the Yili River Valley, it excludes some indicators that are not very relevant to the study, finds incomplete indicators, does not have the representative indicators, then retains 26 indicators, and constructs the spatial mismatch evaluation index system of the tourism industry–regional economy–ecological environment system by all the indicators according to the system they belong to and their nature (

Table 1. Evaluation index system of tourism industry, regional economy, and ecological environment.

Evaluation System	Index	Unit	Index Attribute	Weight	Reference
Tourism industry	Number of tourist attractions above level A X1	number	+	0.0327	[13]
	Number of travel agencies X2	number	+	0.0854	[14]
	Number of star-rated hotels X3	number	+	0.0697	[23]
	Share of tourism industry in the tertiary sector X4	%	+	0.0514	[15]
	Tourism revenue as a share of GDP X5	%	+	0.0396	[15]
	Tourism students X6	number	+	0.0319	[15]
	Tourism receipts X7	10 thousand	+	0.0459	[19]
Regional economy	Per capita GDP X8	100 M yuan	+	0.0281	[25]
	Local revenues X9	10 M yuan	+	0.0613	[25]
	Number of persons employed in the unit at the end of the year X10	10 thousand	+	0.0227	[27]
	fixed asset investment X11	10 M yuan	+	0.0333	[26]
	Average wages of persons on board X12	10 M yuan	+	0.0495	[27]
	Urban registered unemployment rate X13	%	−	0.0029	[27]
	Total sales of goods in society as a whole X14	10 M yuan	+	0.0562	[27]
	Number of beds in health-care facilities X15	number	+	0.0393	[28]
	Value added of primary industry X16	10 M yuan	−	0.0327	[28]
	Value added of secondary industry X17	10 M yuan	−	0.0355	[27]
	General public budget revenue X18	10 M yuan	+	0.0631	[25]
Ecological environment	General solid waste consolidation rate X19	%	+	0.0246	[16]
	Wastewater discharge X20	tonne	−	0.0102	[17]
	Exhaust emissions X21	tonne	−	0.0075	[29]
	Sulfur dioxide emissions X22	tonne	−	0.0102	[29]
	Fume emissions X23	tonne	−	0.0019	[29]
	Annual afforestation area X24	hectares	+	0.0260	[30]
	Sulphur dioxide removal X25	tonne	−	0.0801	[29]
	Soot removal X26	tonne	−	0.0578	[30]

). Among them, the tourism industry, under the requirements of high-quality development of tourism [30], selects three aspects to characterize the tourism reception capacity (X1–X4, X6), tourism market scale (X7), and tourism economic efficiency (X5); regional economy is a concept covering a wide range of content; the number of regional economic growth does not fully reflect the meaning of the regional economy; and the economic structure and the construction of social economy are also important embodiments of regional economy. So, the construction of the regional economy is selected from the total economic scale (X8–X9, X11, X14, X18), the economic structure (X12, X13, X16, X17), and the social and economic construction (X10, X15); ecological environment, under the requirements of “green water and green mountains are the gold and silver mountains”, is characterized by the “pressure-state-state” model [26]; and three aspects of environmental burden (X20, X23), ecological endowment (X24), and environmental governance results (X19, X25–X26) are selected.

2.4. Research Methods

2.4.1. Entropy Weight–TOPSIS Model

Entropy weight method is an objective method to assign weights to indicators according to the variation degree of each indicator. Compared with subjective weighting method, entropy weight method can fully represent the information contained in indicators and has higher reliability and accuracy [31]. As a comprehensive distance evaluation method, TOPSIS model has strong objectivity and rationality [32]. Therefore, in order to obtain more accurate and objective results, this study adopts the combination of entropy weight method and TOPSIS method. The entropy weight method is used to determine the X1–X26 index weights. On the basis of determining the index weights, TOPSIS model is used to evaluate and compare the development levels of the three systems of tourism industry, regional economy, and ecological environment in Yili River Valley. The specific formula is referred to [23].

2.4.2. Center of Gravity Model

The spatial and temporal changes in the center of gravity can somehow reflect the spatial distribution and movement trajectory of the research elements at different points in time, and from the geometric point of view, spatial dislocation refers to the separation of the geometric center of gravity of two elements [13]. In the paper, we pick up the coordinate data of the geometric center of gravity points in each region of the Yili River Valley through Baidu map and bring the comprehensive development index of the three systems of tourism industry, regional economy, and ecological environment into the center of gravity model, so as to derive the coordinates of the center of gravity of the three systems during ten years. After using ArcGIS10.2 visualization, the macro spatial mismatch of tourism industry, regional economy, and ecological environment in Yili River Valley can be shown more intuitively. The calculation formula is as follows:

$$\overline{x}=\frac{{\sum }_{i=1}^n{M}_i{x}_i}{{\sum }_{i=1}^n{M}_i},\overline{y}=\frac{{\sum }_{i=1}^n{M}_i{y}_i}{{\sum }_{i=1}^n{M}_i},$$

(1)

In the above formula, $M_i$ refers to the calculated index value of a factor (tourism industry, regional economy, ecological environment) of the $i$ city in Yili River Valley, and $x_i$, $y_i$ refers to the longitude and latitude coordinates of the $i$ city, respectively.

2.4.3. Spatial Mismatch Index

Using the panel data of tourism industry–regional economy–ecological environment, comprehensive development index can quantitatively calculate the spatial misalignment index. The traditional spatial dislocation index is mainly used to calculate the degree of dislocation of the region as a whole and does not reflect the specific situation of positive and negative dislocation in each region [21]. In order to more clearly analyze the differences in the degree of dislocation in each region of the Yili River Valley, to explore the main dislocation areas, and to discover the key points, the paper introduces the secondary regional spatial misalignment index proposed by Li Lingyan and Weng Gangmin in their study [21] to calculate the spatial misalignment index of tourism industry–regional economy–ecological environment in each region of the Yili River Valley at the micro level. The specific formula is as follows:

$${SMI}_i=\frac{1}{E}\left\{\left[\left(\frac{T_i}{T}+\frac{P_i}{p}\right)/2\right]\times E-E_i\right\}\times 100,$$

(2)

where ${SMI}_i$ is the spatial mismatch index of a county or city in the Yili River Valley, $i$ indicates the number of secondary regions included in the overall region, which takes the value of 10 in this paper, $T$ indicates the total mismatch index of the tourism industry in the Yili River Valley, $P$ indicates the total mismatch index of the regional economy, and $E$ indicates the total mismatch index of the ecological environment. $T_i$, $P_i$, and $E_i$ indicate the comprehensive mismatch indices of tourism, economy, and ecology of the regions, respectively.

2.4.4. Spatial Variance Model

The spatial variance function, also known as the semi-variogram, is an effective means of resolving spatial variability patterns and structural analysis [33]. In this paper, the spatial dislocation index of the Yili River Valley during the study period is assigned as a spatial variable to the geometric centroid of each region, and the data are fitted with the help of Gaussian, spherical, linear, and exponential models in the spatial variance function module of geostatistical software GS⁺9.0. This paper applies this model to reveal the law of spatial variation in the spatial pattern of the tourism industry, regional economy, and ecological environment of the Yili River Valley with the following formula:

$$\gamma \left(k\right)=\frac{1}{2N\left(k\right)}{{\sum }_{i=1}^{N\left(k\right)}\left[Y\left(x_i\right)-Y\left(x_i+k\right)\right]}^2,$$

(3)

where $\mathsf{\gamma }\left(k\right)$ is the semi-variate function value; $Y\left(x_i\right)$ and $Y(x_i+k)$ are the spatial mismatch values of tourism industry–regional economy–ecological environment on the spatial units $x_i$ and $x_i+k$, respectively, for $Y\left(x\right)$; $N\left(k\right)$ is the sample size of the separation distance k.

Kriging (Kriging) interpolation is a simulation of spatial modeling and interpolation of stochastic processes based on the spatial variance model. The formula is as follows [34]:

$$Y\left(x_0\right)={\sum }_{i=1}^n{\lambda }_{i}Y\left(x_i\right),$$

(4)

where $Y\left(x_0\right)$ is the unknown point; $Y\left(x_i\right)$ is the known sample point; ${\lambda }_i$ is the weight of the $i$ sample point on the unknown point; and $n$ is the number of known points.

2.4.5. Obstacle Degree Model

In order to further reveal the main factors restricting the coordinated development level of tourism resources, regional economy, and ecological environment in various regions of the Yili River Valley, this study draws on the studies of scholars such as Peng Fei and Han Zenglin [34], calculating the weight value of X1–X26 indicators, introducing the obstacle degree model to measure the obstacle degree of each indicator to various regions of the Yili River Valley, and identifying the key influencing factors. The formula is as follows:

$$A_i=w_i{d}_i/{\sum }_{i=1}^n{w}_i{d}_i\times 100\%,$$

(5)

where $A_i$ is the degree of influence of the $i$ indicator on spatial dislocation; $w_i$ is the weight of the $i$ indicator; and $d_i$ represents the normalized value of the $i$ indicator.

3. Results

3.1. Analysis of Comprehensive Index of Tourism Industry–Regional Economy–Ecological Environment in the Yili River Valley

After establishing the evaluation index system of the tourism industry–regional economy–ecological environment, the entropy value method was used to calculate the panel data weights of the three system indices in the Yili River Valley. And then, the TOPSIS model was used to calculate the mean value of the comprehensive indices of the tourism industry, regional economy, and ecological environment.

Firstly, it can be seen from Figure 3 that there are certain differences in the development levels and characteristics of the three subsystems of the Yili River Valley due to various reasons such as location conditions, development history, resource status, and national strategy. From the overall characteristics of the three systems, the development level of the three systems is low, the maximum value is not more than 0.3, and the comprehensive index value of some subsystems is less than 0.15 in some years. In addition, the development level of ecological environment is obviously higher than that of regional economy and tourism industry, and the comprehensive index of tourism industry is always lower than that of regional economy.

Secondly, from the perspective of the evolution of the three systems, the average value of the comprehensive index of regional economy, ecological environment, and tourism industry in the Yili River Valley during 2010–2019 showed a general trend of fluctuation and rise. The comprehensive index of regional economy increased from 0.112 in 2010 to 0.275 in 2019, with an increase rate of 145.54%. This shows that after 10 years of development, the regional economy of the Yili River Valley achieved rapid development. The comprehensive development index of ecological environment increased from 0.203 in 2010 to 0.234 in 2019. Ecological environment is a basic system with little elasticity of change, and the continuous optimization of ecological environment is mainly due to the implementation of China’s long-term environmental protection policies. The development index of the tourism system changed from 0.109 in 2010 to 0.230 in 2019, with an increase of 111.01%. The development curve of the tourism industry and regional economy has a strong similarity. With the support and promotion of regional economy, the development of the tourism industry shows a significant rise.

3.2. Analysis of Overall Spatial Mismatch of Tourism Industry–Regional Economy–Ecological Environment in Yili River Valley

The comprehensive development index of tourism industry–regional economy–ecological environment in the Yili River Valley was imported into the formula of the center of gravity model. The latitude and longitude coordinates of the center of gravity of the tourism industry, regional economy, and ecological environment in the Yili River Valley from 2010 to 2019 were calculated. ArcGIS10.2 was used for visualization to obtain the ten-year trajectory of the migration of the center of gravity of the tourism industry, regional economy, and ecological environment in the Yili River Valley (Figure 4).

Observation of Figure 4 reveals that the regional economic and ecological centers of gravity of the Yili River Valley during the study period are located in Yining County. The center of gravity of the tourism industry is also located in Yining County except for 2015 when it is located in Chaxian, but the three have been showing a mismatch. This paper cites the spatial center analysis model proposed by Bao, X.P. et al. [35] in their research. It is calculated that the spatial geometric center of gravity of the Yili River Valley is located in Gongliu County (81.53° E, 43.68° N), which is separated from the center of gravity of tourism industry, regional economy, and ecological environment of the Yili River Valley. The center of gravity of the tourism industry, regional economy, and ecological environment in the Yili River Valley all develops to the northwest, and the center of gravity of the tourism industry evolves in latitude and longitude with a larger magnitude. With the passage of time, the three constantly deviate from the center of gravity of the spatial geometry of the Yili River Valley, resulting in a deepening of the trend of non-equilibrium development, and this spatial non-equilibrium phenomenon is due to the location conditions of the counties and cities, the endowment of tourism resources, and the speed of socio-economic development not being the same, not being synchronized.

However, it is worth noting that the distance between the centers of gravity of the tourism industry–regional economy–ecological environment in the Yili River Valley shows a dislocation trend of first increasing and then decreasing. Specifically, before 2014, the distribution of the centers of gravity of the three systems in the Yili River Valley did not have any regularity and were far away. The reason for this is that in the early stage of development, the People’s Government of Yili Kazak Autonomous Prefecture was still in the stage of strengthening investment in tourism infrastructure and expanding the scale of the tourism market in the Yili River Valley, neglecting the development of the ecological environment, which intensified the spatial mismatch between the tourism industry, the regional economy, and the ecological environment. In 2014, after the “scientific development concept as a guide, set up the goal of ecological civilization construction” was put forward in the “Yili Prefecture Ecological Environmental Protection Master Plan”, the People’s Government of Yili Kazak Autonomous Prefecture actively created a national ecological civilization demonstration county. The spatial constraints were based on the resource carrying capacity, environmental capacity, and the ecological red line, linking the capacity and the red line with the planning industry, establishing a system for approving the total amount of industries, and rationally determining the structure and scale of industries. This series of goals and measures made the development level of the three systems of tourism industry, regional economy, and ecological environment in the Yili River Valley improve unprecedentedly in the middle and late periods of the study, and the center of gravity distance of the three systems showed a gradually decreasing trend.

3.3. Spatial Mismatch Analysis of Tourism Industry–Regional Economy–Ecological Environment in Regions of Yili River Valley

In order to quantify the spatial dislocation degree of tourism industry–regional economy–ecological environment in each region of Yili River Valley, this paper introduces the micro-spatial dislocation model to calculate the spatial dislocation index of tourism economy and ecological environment system. The time cross-section data of 2010, 2013, 2016, and 2019 were selected (

Table 2. Regional spatial dislocation index of tourism industry–regional economy–ecological environment in Yili River Valley.

City	2010	Misdirection	2013	Misdirection	2016	Misdirection	2019	Misdirection	Change in Direction
Yining City	−0.197	−	−2.125	−	−1.149	−	2.024	+	negative → positive
Horgos City	*		*		3.729	+	−4.062	−	positive → negative
Yining County	2.293	+	−3.764	−	0.081	+	3.444	+	positive and negative fluctuations
Qabqar Siberian Autonomous County	4.670	+	−0.375	−	−1.465	−	1.134	+	positive and negative fluctuations
Huocheng County	3.709	+	−4.600	−	1.225	+	0.049	+	positive and negative fluctuations
Gongliu County	4.749	+	−0.524	−	−3.876	−	1.242	+	positive and negative fluctuations
Xinyuan County	2.814	+	4.970	+	0.361	+	−1.851	−	positive → negative
Zhaosu County	2.945	+	−1.659	−	2.296	+	−0.999	−	positive and negative fluctuations
Tekes County	2.638	+	−1.455	−	−0.446	−	0.192	+	positive and negative fluctuations
Nilek County	4.580	+	−1.684	−	0.046	+	−0.330	−	positive and negative fluctuations

* The city of Horgos has been established since 2015 with no data available prior to that date.

), and ArcGIS 10.2 was used for visual analysis.

3.3.1. Spatial Dislocation Direction

Based on previous experience, according to the positive and negative spatial dislocation index, it can be divided into positive dislocation zone and negative dislocation zone [13,14]. Positive dislocation indicates that the predicted value of economic indicators is higher than the actual value, and compared with the growth of tourism industry and ecological environment level, the regional economic level still has large room for improvement. Negative dislocation indicates that the predicted value of economic indicators is lower than the actual value, compared with the rapid improvement of regional economic development level, the levels of tourism industry and ecological environment are still relatively backward.

Combined with the actual situation of the Yili River Valley, the region with absolute value of spatial dislocation index greater than 3.39 is identified as a high dislocation region; the region with absolute value of spatial dislocation index between 2.27 and 3.39 is identified as a high dislocation region; and the region with absolute value of spatial dislocation index between 1.16 and 2.27 is identified as a low dislocation region. The region with the absolute value of spatial dislocation index between 0.046 and 1.159 is considered a low dislocation region.

As can be seen from Table 2, during the study period, most of the spatial dislocation indices in the Yili River Valley are positive and negative, and the regions with fundamental changes can be divided into three types. The first type was that the spatial dislocation indices changed from positive to negative, and the relationship between tourism industry, regional economy, and ecological environment changed from a relatively backward to relatively advanced development of regional economy. For example, the dislocation degree of Horgos City and Xinyuan County has always been in the high dislocation zone and has changed from positive high dislocation to negative high dislocation, indicating that the development coordination of its tourism industry, regional economy, and ecological environment is poor. The dislocation degree of Xinyuan County has gradually shifted from positive high dislocation zone to positive low dislocation zone. It shows that the development of tourism industry, regional economy, and ecological environment in this region has a harmonious trend. The second type is that the spatial dislocation index changes from negative to positive, and the relationship between tourism industry, regional economy, and ecological environment changes from a relatively advanced development of regional economy to relatively backward development. For example, Yining City’s dislocation degree changes from negative to low dislocation zone to positive to low dislocation zone. It shows that the spatial dislocation of tourism industry, regional economy, and ecological environment has not changed significantly. Dislocation and the third type is the space index fluctuation change in counties and cities, including Yining County, Huocheng County, Gongliu County, Tex County of “positive and negative and positive” transformation of the mode, Zhaosu County, and Nyalek County of “positive and negative to positive, negative” shift pattern. The space of the seven counties and cities is in misalignment, and the fluctuated is decreasing. This shows that the development and change in tourism industry, regional economy, and ecological environment are complicated, but in general, the development of the three is changing to a harmonious state.

3.3.2. Spacetime Evolution Analysis of Spatial Dislocation

During the study period, the spatial dislocation of tourism resources, regional economy, and ecological environment has always existed in the Yili River Valley, and the spatial dislocation pattern of each region has evolved frequently (Figure 5). The spatial dislocation index of Khorgos City continued to rise and gradually moved toward the negative high dislocation zone, indicating that the development speed of its social economy, ecological environment, and tourism industry was quite different. This was mainly caused by the enhancement of local tourism organization capacity and the increase in the number of tourists with the establishment of Khorgos Port City in 2015, coupled with the support of economic development and infrastructure construction. The tourism industry has maintained a high growth momentum. However, the city’s tourism climate comfort and greening continue to be low, and the difference in development speed between systems is increasing. The spatial dislocation index of Chaxian, Nielek County, Huocheng County, Zhaosu County, and Tekes County has continued to decline, indicating that the gap between the development speed of social economy, ecological environment, and tourism industry has narrowed. The spatial dislocation index of Yining County, Xinyuan County, and Yining City increased first and then decreased, while the spatial dislocation index of Gongliu County decreased first and then increased.

On the whole, from 2010 to 2019, the number of high dislocation zones decreased year by year, from four high dislocation zones in 2010 to one high dislocation zone in 2019. Meanwhile, the number of low dislocation zones increased year by year, from one low dislocation zone in 2010 to six low dislocation zones in 2019. Finally, the spatial dislocation in the Yili Valley gradually evolved into a low dislocation zone. The gradual migration of the high dislocation area to the west indicates that in the early development process, each region actively promoted the rapid development of the tourism industry system and the regional economic system and ignored the protection of the ecological environment system to a certain extent, resulting in the deepening of the dislocation situation of the three systems. Later, the coordinated development of the industrial system was emphasized, and the benefits of the tourism industry–regional economy–ecological environment system improved simultaneously. The dislocation situation of the three major systems has improved, which further confirms the conclusion of the previous stage.

3.3.3. Spatio-Temporal Differentiation Characteristics of Spatial Dislocation

The spatial variance model can detect the spatial differentiation characteristics of the spatial misalignment index in the Yili River Valley. The four-time cross-section spatial misalignment indices of 2010, 2013, 2016, and 2019 were assigned as spatial variables to the geometric centroids of each county and city, and the data were fit with the help of the Gaussian, spherical, linear, and exponential models in the spatial variance function module of geostatistical software GS⁺9.0. It was found that the fit was optimal when the sampling step length was in the interval of 5.09–6.64 km, and the model with the best fit was selected for fitting. The fitting parameters were obtained (

Table 3. Fitting parameters of spatial dislocation variation function of tourism industry–regional economy–ecological environment in Yili River Valley.

Year	Range/km	Nugget	Sill	Nugget Coefficient	Fitting Model	Determination Coefficient
2010	9.336	1.904	2.111	0.098	Exponential	0.884
2013	42.088	2.110	8.229	0.744	Gaussian	0.690
2016	23.016	1.266	1.296	0.023	Linear	0.934
2019	16.771	0.485	0.499	0.971	Linear	0.947

).

As can be seen from Table 3, in general, the four-year variance range showed a fluctuating trend of rising and then falling. The results show that the spatial effect of the overall spatial mismatch index of the Yili River Valley region is constantly changing, and the trickle-down effect of the high spatial mismatch region on the surrounding areas first rises and then falls and eventually shows a gradually equalized development trend. The overall fluctuating downward trend of the nugget value and the abutment value indicates that the spatial mismatch spatial divergence of each region of the Yili River Valley has continued to diminish. The spatial variation values in 2010 and 2016 were relatively small, and the spatial dislocation heterogeneity of the tourism industry–regional economy–ecological environment in the Yili River Valley caused by random factors accounted for 9.3% and 2.8% of the total spatial heterogeneity, respectively. The results show that the structure of the spatial dislocation of the tourism industry–regional economy–ecological environment in the study area has strong spatial correlation. The characteristics of the spatial heterogeneity are regular and do not vary greatly because of the large changes due to the influence of random factors. It was relatively large in 2013 and 2019. It shows that most of the variations in the spatial dislocation structure of the Yili River Valley are acted on by random factors, and the influence is significant. However, the overall fluctuating climbing trend indicates that the structured divergence caused by spatial autocorrelation gradually weakened during the evolution of tourism industry–regional economy–ecological environment spatial mismatch, while the spatial variance caused by stochastic components became more and more significant. In terms of the optimal model fitted by the spatial variance function, the four-year spatial variance model keeps changing. In 2010, the spatial pattern presented an exponential model with clustered distribution; in 2013, it presented a Gaussian model; and in 2016 and 2019, it presented a linear model with random spatial pattern. The fitting coefficients of the model generally show an upward trend and gradually reach a good fitting degree. The results show that the evolution of the spatial dislocation divergence of the tourism industry–regional economy–ecological environment in the Yili River Valley shows better continuity and stability characteristics, and the spatial self-organization is increasing year by year.

Spatial heterogeneity is the implied premise of spatial interpolation, and it is the non-uniform spatial distribution of elements that requires spatial interpolation; spatial correlation is the basis of spatial interpolation, and the lack of such correlation makes spatial interpolation a mathematical game [33]. According to the analysis results of the variation function, the ordinary Kriging interpolation method in ArcGIS10.2 software is used to draw the spatial distribution of the spatial mismatch of tourism industry–regional economy–ecological environment in the Yili River Valley. As seen in Figure 6, the spatial dislocation pattern of tourism industry–regional economy–ecological environment in the region shows a certain pattern of regularity and continuity and the overall spatial evolution pattern of east > central > western, accompanied by the obvious trend of transferring the high- and low-value areas of spatial dislocation.

Specifically, in 2010, the “peak” core area centered on Chaxian and Nilek County in the high-value spatial dislocation area showed a decreasing trend to the surrounding areas. The “trough” core area centered on Khorgos City and Zhaosu County in the low-value spatial dislocation area showed an increasing trend to the surrounding areas, indicating that in the early stage, the “peak” core area in the low-value spatial dislocation area showed an increasing trend to the surrounding areas. The spatial differentiation pattern of the overall spatial dislocation index in the Yili Valley has shown the characteristics of “east-west convergence, north-south dispersion”. In 2013, the high-value region of spatial dislocation was divided into three “trough” core regions centered on Chaxian, Tokuzliu County, and Nilek County, indicating that at this stage, the spatial differentiation trend of the overall spatial dislocation index of the Yili Valley changed significantly, and the high–low-value region developed from a centralized point-like distribution to a multi-point and multi-core equilibrium. Compared with the previous period, the low-value region of spatial dislocation spreads in the north–south direction and gradually forms the sub-core of the high-value region. In 2016, the spatial dislocation high-value area further spread and formed a “peak” core and sub-core area centered on Xinyuan County, Horgos City, and Yining County, while the spatial dislocation low-value area had a certain trend of southward movement and formed a “trough” core area centered on Tex County. In 2019, the high-value area of spatial dislocation formed a “peak” core area centered on Khorgos City, Chaxian, Zhaosu County, and Tekes County and a “trough” core area centered on Nilek County and Xinyuan County. Looking at the overall differentiation trend of spatial dislocation in the past 10 years, the high-value area of spatial dislocation index gradually diffused and differentiated from an obviously convex “mountain” core area to a relatively flat “mountain” core area and sub-core area. The low-value area of spatial dislocation index gradually evolved from two relatively flat “trough” core areas to a relatively depressed “trough” core area and sub-core area. The isocontour density increased to a certain extent, indicating that the spatial dislocation index gap between the regions of the Yili River Valley gradually decreased, the overall disequilibrium gradually weakened, the differentiation characteristics of “east-west convergence, north-south dispersion” were gradually broken, and the overall development trend was balanced.

3.4. Influence Factors of Spatial and Temporal Evolution of Spatial Dislocation Index in Yili River Valley

The three system indicators of tourism industry–regional economy–ecological environment in the Yili River Valley were brought into the barrier degree model. The barrier factors for each indicator in each region of the Yili River Valley were calculated, and the top four barrier factors for each region in the study period were screened. The results are shown in

Table 4. Top 4 obstacle factors of spatial dislocation index in Yili River Valley from 2010 to 2019.

City	Barrier Factors 2010				Barrier Factors 2013				Barrier Factors 2016				Barrier Factors 2016
	1	2	3	4	1	2	3	4	1	2	3	4	1	2	3	4
Yining City	X3	X6	X9	X2	X25	X9	X3	X14	X2	X3	X14	X12	X25	X12	X14	X26
Horgos City	0	0	0	0	0	0	0	0	X18	X9	X20	X22	X9	X4	X18	X8
Yining County	X24	X4	X10	X6	X11	X4	X10	X16	X5	X26	X25	X4	X5	X26	X4	X8
Qabqar Siberian Autonomous County	X24	X20	X19	X21	X24	X11	X19	X9	X26	X16	X22	X23	X26	X16	X22	X20
Huocheng County	X24	X19	X20	X10	X16	X18	X17	X10	X1	X20	X21	X22	X16	X26	X1	X14
Gongliu County	X24	X19	X20	X22	X13	X19	X20	X21	X5	X22	X21	X23	X5	X19	X16	X22
Xinyuan County	X24	X19	X3	X6	X4	X24	X26	X17	X3	X16	X14	X25	X17	X14	X3	X16
Zhaosu County	X19	X20	X22	X21	X19	X20	X22	X21	X1	X26	X5	X19	X1	X26	X8	X16
Tekes County	X24	X19	X20	X13	X20	X21	X26	X13	X19	X26	X1	X20	X26	X5	X26	X20
Nilek County	X19	X22	X21	X23	X11	X19	X21	X17	X1	X20	X22	X21	X1	X8	X20	X22

.

First, from the spatial dislocation influencing factors of each region in the Yili River Valley, 43.7% of the influencing factors in Yining County originated from the tourism industry system; 75% of the influencing factors in Chaxian; 75% of the influencing factors in Gongliu County; 68.8% of the influencing factors in Zhaosu County; 75% of the influencing factors in Tex County; 68.8% of the influencing factors in Nilek County originated from the ecological environment system; 43.7% of the influencing factors in Yining City; 62.5% of the influencing factors in Khorgos City; 43.7% of the influencing factors in Huocheng County and Xinyuan County; and 37.5% of the influencing factors originated from the regional economic system. In summary, a total of five counties and cities have spatial dislocation influencing factors focused on the ecological environment system, one county focused on the tourism industry system, and four counties and cities focused on the regional economic system.

Secondly, except for X7 and X15, the remaining 24 indicators are all factors affecting the spatial dislocation of provinces (cities). During the study period, these 24 indicators appeared 152 times in total, meaning that the average occurrence of each indicator was 6.3 times. In this paper, indicators with more than 6.3 times of occurrence were identified as the main influencing factor of the overall regional spatial dislocation. Looking at the overall spatial dislocation influencing factors from 2010 to 2019, we can see that X19, X24, X20, and X21 as the top four obstacle factors appeared seven, six, four, and three times, respectively, in 2010. In 2013, X11, X19, X20, and X21 appeared three, three, two, and four times, respectively, as the top four obstacle factors. In 2016, X22, X1, X20, and X26 appeared as the top four obstacle factors five, four, four, and four times, respectively. In 2019, X26, X16, X1, and X8 appeared seven, five, three, and four times, respectively, as the top four obstacle factors. Among them, the comprehensive utilization rate of general solid waste X19, exhaust gas emission X21, dust removal X26, three influencing factors, appear most frequently in the overall spatial dislocation influencing factors. X26 occurred 11 times in total, accounting for 7.24% of the total number of influencing factors; X19 and X21 occurred 10 times, respectively, accounting for 6.57% of the total number of influencing factors; the three indicators occurred 31 times in total, accounting for 20.39% of the total number of influencing factors and were the main influencing factors of the overall regional spatial dislocation in the Yili River Valley. Wastewater discharge X20 occurred nine times, sulfur dioxide discharge X22 and annual afforestation area X24 occurred eight times, respectively, accounting for 5.92%, 5.26%, and 5.26% of the total influencing factors, respectively, belonging to the secondary influencing factors. The number of travel agencies X2, the number of star-rated hotels X3, the number of beds of medical and health institutions X15, and other influencing factors appeared no more than five times at the highest and only appeared as the main influencing factors of the overall regional spatial dislocation in the Yili River Valley within a certain period of time.

In summary, it is concluded that the main influencing factors of spatial dislocation in the Yili Valley system are the comprehensive utilization rate of general solid waste, exhaust gas discharge, dust removal amount, wastewater discharge, sulfur dioxide discharge, and annual afforestation area, which mostly originate from the ecological environment system. In order to reduce the spatial dislocation in the development of tourism industry, regional economy, and ecological environment system and improve the ability of regional coordinated development, we must focus on the ecological environment system and take ecological environment protection as the first priority.

4. Conclusions

Starting from the perspective of spatial dislocation of tourism industry–regional economy–ecological environment, this paper uses a gravity center model and spatial dislocation model to analyze the spatial dislocation of tourism industry–regional economy–ecological environment system in the Yili River Valley and its various regions from both macro and micro levels. The spatial and temporal evolution, agglomeration characteristics, and influencing factors of spatial dislocation of the three major systems in the study area were explored by using the spatial geographic visualization method and obstacle degree model. The main conclusions are as follows:

First, although the comprehensive development index of tourism industry, regional economy, and ecological environment did not exceed 0.3, the three systems showed varying degrees of growth. Among them, the comprehensive development index of ecological environment is significantly higher than that of regional economy and tourism industry. As the ecological environment is the basic system, the increase rate is relatively small, and the comprehensive development index of tourism industry is always lower than that of regional economy. However, regional economy and tourism industry have the largest growth rate, the development trend of the two is consistent, and they have a strong correlation.

Second, at the macro-regional scale, the center of gravity of tourism industry, regional economy, and ecological environment in the Yili River Valley from 2010 to 2019 all developed to the northwest. The longitude and latitude of the center of gravity of tourism industry changed greatly and were always separated from the spatial geometric center of gravity of the region. The center of gravity of the three systems had obvious dislocation, but on the whole, the degree of dislocation gradually narrowed. This shows that the development trend of the region is good, and the ability of regional coordinated development is constantly improving.

Third, at the micro-regional scale, most of the spatial dislocation indices of each region in the Yili River Valley during 2010–2019 showed positive and negative fluctuations, with different degrees of dislocation types, frequent evolution of spatial dislocation patterns in each region, and the spatial dislocation differentiation of each region changing in stages. But, the differentiation of “east-west convergence, north-south dispersion” is gradually broken. The overall dislocation situation improved slightly, and the overall index showed a balanced development trend.

Fourth, the spatial dislocation index of each region in the Yili River Valley is the result of coupling effects of many factors. The overall spatial dislocation factors are mainly the comprehensive utilization rate of general solid waste, exhaust gas discharge, dust removal, wastewater discharge, sulfur dioxide discharge, and annual afforestation area, which are mostly derived from the ecological environment system.

5. Discussion

This paper takes the Yili River Valley, an underdeveloped region in western China, as the research object and discusses the spatial mismatch of tourism industry–regional economy–ecological environment and the influencing factors, which is a favorable supplement to the existing research system on the imbalance of the development of tourism industry–regional economy–ecological environment in the regions of the Yili River Valley. It is also an important reference for other underdeveloped regions in China where tourism is the dominant industry to achieve coordinated and sustainable development in the region. The results of the study reveal three main points:

First, compared with “the 12th Five-Year Plan”, “the 13th Five-Year Plan” emphasizes the five concepts of “innovation, coordination, green, openness, and sharing” [36], and China has put forward higher requirements for macro-control of the development environment. In this context, “system-wide coordination” is an inevitable step for the development of each region in China [37]. The steady growth of tourism industry–regional economy–ecological environment in this study is in line with this trend.

Secondly, the ecological basis and economic level of each region are very different, resulting in different levels of economic, ecological, and tourism growth in different regions. To some extent, this can reflect the differences in the scale of investment and the emphasis on regional development among different regions [38]. Therefore, the relationship between tourism industry, regional economy, and ecological environment in different regions of the Yili River Valley is not a simple linear relationship, and the synchronization and dislocation between them coexist, showing certain spatial differences. This is consistent with the research conclusions of previous scholars [2,13]. At present, the economy of the Yili River Valley is dominated by extensive growth, and the connotative high-quality development model driven by technical efficiency has not yet formed, the resource allocation efficiency of tourism industry is not high, and the awareness of ecological environment protection is insufficient. Among them, the high dislocation area is mainly distributed in the central city, the border port, the tourism industry, and the relatively high development level of ecological environment area. It is staggered with low dislocation, and the linkage of regional development is not high. The “siphon” phenomenon of economic development advantage area to its surrounding tourism industry advantage area and ecological environment advantage area is obvious. In order to promote the balanced and coordinated development of various regions in the Yili River Valley and improve the level of regional development, the relevant parts should make full use of the development advantages of the highly positive dislocation area, give full play to its radiating role, promote the development of the surrounding negative dislocation area, and deepen regional cooperation, taking the optimization road of “taking the line with the point, expanding the surface with the line, combining the point with the surface, and making multidimensional efforts” and promoting the coordinated development of various regions. At the same time, all regions should also pay attention to the exploration of potential tourist source markets and strive to improve the level of local economic development and the ability to guarantee basic service facilities, so as to build a better living environment for hosts and tourists and a better overall tourism development pattern.

Third, the Yili River Valley regional spatial dislocation index is affected by multi-systems and multi-factors. Although there is no similar to Qinghai, Inner Mongolia, Anhui, Turpan, and other regions with the development of tourism and the economy, the ecological environment, on the contrary, has a negative development trend [39]. But, the factors affecting the overall spatial dislocation and the research results of other scholars [33] all come from the ecological environment system. The strategy of giving priority to ecotourism should be implemented in tourism development. Ecotourism aims at protecting natural resources and the environment and promoting the coordinated development of regional society. In order to achieve sound development of ecotourism, it is necessary to link all departments and participate in the whole society. The government needs to establish an ecological economy, ecological system, ecological environment, ecological culture, eco-space, and eco-habitat “six-in-one” ecological civilization tourism model [40]. This is to formulate and improve all kinds of laws and regulations, from the institutional level to guide the enterprises to low emissions, the tourist attractions of the environmental carrying capacity and the ecological capacity limit, the public, and the tourists. And this leads to civilized tourism, mainly developing cultural tourism, agricultural tourism, wine tourism, and other projects, and ultimately realizes green tourism, low-carbon tourism, smart tourism, and ecotourism in the whole region. In order to realize the sustainable development of tourism industry, regional economy, and ecological environment, the tourism industry in the Yili River Valley needs to implement the strategy of giving priority to ecotourism.

However, this paper also has some shortcomings. First, due to the availability of data, this paper selects a total of 26 indicators from three dimensions: tourism industry, regional economy, and ecological environment. The indicators include multiple indicators of tourism, economy, and ecology that are strongly related to the tourism industry as much as possible to build the system. The selection of indicators is reasonable and reflects the scientificity. However, due to the limited availability of indicators and due to the lack of county data disclosure, the year is not complete enough to further explore. Therefore, future studies should obtain important primary county data through long-term observation and investigation and further explore the factors affecting the dynamic evolution characteristics of tourism spatial dislocation in the Yili River Valley in a longer time series. Secondly, this paper only analyzes the main social and economic factors affecting the spatial dislocation of tourism industry, regional economy, and ecological environment in the Yili River Valley. In the future, it is necessary to further explore the physical geography and other factors of the spatial dislocation of tourism industry, regional economy, and ecological environment in the Yili River Valley, so as to make the research more realistic and practical.