Impact of the Digital Economy in the High-Quality Development of Tourism—An Empirical Study of Xinjiang in China

Abstract

In the era of big data, the digital economy has become a key driving force for the high-quality development of tourism. Based on the annual panel data of 14 prefectures in Xinjiang from 2008 to 2018, this study proves the positive effect of the digital economy on the high-quality development of tourism. Through the construction of an evaluation index system for the high-quality development, a fixed effects model is used to investigate the relationship between them. Furthermore, mediating effect analysis is employed to study the mechanism. The robustness testing and heterogeneity analysis show the validity and rationality of the model. The results show that (1) The digital economy is an important driving force in the high-quality development of tourism in Xinjiang; (2) The digital economy promotes high-quality development by stimulating the upgrading of the tourism structure; (3) The impact of the digital economy on the high-quality development of tourism in different regions in Xinjiang presents great heterogeneity. The provincial capital presents a more significant effect.

1. Introduction

Xinjiang is an important strategic region for the development of tourism in China with its vast territory, unique geographical location, rich resources, and local ethnic custom. In recent years, the number of regional tourists has repeatedly reached new highs along with the steady progress in the stability and development of Xinjiang. Tourism has become an important pillar with the most potential as well as an important engine of high-quality economic development. However, tourism is not only an economic activity but also an effective carrier for people to communicate and interact. “The Fourteenth Five-Year Plan for National Economic and Social Development of the People’s Republic of China and the Outline of the Vision Goals for 2035” stated clearly that the tourism industry has shown new changes and characteristics. For instance, “Internet + tourism”, “smart tourism”, “red tourism”, and “cultural heritage tourism” have emerged as new forms of tourism. In the process of the high-quality development of tourism, fifth-generation mobile communication (5G), big data, and precise supervision are inevitable requirements. The proposal of the “Outline of the Fourteenth Five-Year Plan for the Development of Culture and Tourism in Xinjiang Uygur Autonomous Region” emphasizes that the high-quality development of tourism will run across the economic, social, cultural, and other fields in Xinjiang. The government proposed that tourism has become an important part of Xinjiang’s economy, and the high-quality development of the tourism industry has become an important way to improve people’s lives and well-being. Therefore, it is necessary to accelerate the transformation of Xinjiang from a big tourism province to a strong tourism province. In this process, digital technology and information technology not only improve the efficiency of the tourism industry and tourists’ experience but also give birth to new tourism consumption scenes and industrial chains. Whether digital technology can be used to improve the competitiveness of a region in the tourism market is the key to achieve the high-quality development of tourism in the region.

In terms of the research content, the digital economy is an Internet economy, an economic form under the rapid development of information technology and informatization, which can be divided into infrastructure and digital activities [1]; the former covers communications and Internet technologies, while the latter can be divided into platforms, digital solutions, digital content, and e-commerce. It is undeniable that although the digital economy is in its infancy in our country, it is the most active area of economic development that promotes the improvement of the total factor productivity and also plays an important role in stimulating investment, consumption, and employment, attracting the attention of scholars. In recent years, the depth and breadth of integration between the digital economy and various sectors of society have been expanding. By creating new business models constantly, it changed the economic structure of various industries in China; based on its own extensiveness, foundation, and technicality, it promotes the development of social economy [2,3,4]. In the existing literature, Han et al. used digital technology to examine the positive connection between ecotourism and sustainable development [5]. Lenia et al. studied the positive role of digital technology in urban development and creative tourism by analyzing the case of “Game city” [6]. Jennie et al. tested the positive role of social network technology in the tourism economy with online hotel transactions [7]. Guo et al. used the multi-phase difference in differences (DID) model and the propensity score matching difference in differences (PSM-DID) model to evaluate the impact of digital economy development on urban air quality [8]. Dan et al. used instrumental variables and smart city construction as a quasi-natural experiment and found that the digital economy can affect the high-quality green development of surrounding areas through spatial spill-over effects [9]. Min-Hyuk et al. found that the transformation of production, consumption, and distribution brought about by the digital economy has brought about adaptive social innovation [10]. Wang et al. found that the development of the digital economy has greatly improved the green innovation ability of cities [11]. These studies all came to a consistent conclusion that the digital economy can promote the development of related industries. However, there is little research on the empirical relationship between the digital economy and the high-quality development of tourism.

As for the high-quality development of tourism, Philip et al. studied the current situation of 53 small and medium-sized enterprises in southern England and concluded that the digital market is helpful to promote the development of the tourism industry [12]. Ankita et al. analyzed the factors that hindered the integration of tourism services and digital marketing in developing countries and provided suggestions for tourism development [13]. Gannon et al. pointed out that digital technology provides a good market basis for the sustainable development of tourism [14]. Chan et al. found that mobile technology plays a significant role in strengthening the direct relationship between infrastructure and sustainable tourism development [15]. Frank et al. found that the application of information technology plays an important role in promoting inter-organizational cooperation within a network of tourist destinations [16]. Zhao et al. found that per capita capital flow, star-rated hotels, fixed asset investment, employment in the tertiary industry, and other factors play an important role in the development of tourism [17]. Xu et al. found that the connection between industrial belts has become the most prominent problem for tourism [18]. Although these scholars have provided a good theoretical basis for studying the factors affecting the high-quality development of the tourism, the empirical research is still relatively insufficient.

In terms of research methods, how should people objectively evaluate the level of the high-quality development of tourism? Some scholars obtained the scores of the tourism development quality by establishing a series of evaluation index systems based on models, such as principal component analysis (PCA), analytic hierarchy process (AHP) and entropy weight method (EWM). Their work suggested that the economic development level, human resources, tourism development level, the tourist resorts, and market prospects can be used to measure the level of high-quality development of tourism [19,20,21,22]. Pha et al. evaluated the impact of digital technology on sustainable tourism development by establishing a model based on intelligent tourism technology [23]. Jiang et al. established dynamic capability theory model and found that information technology improves the competitiveness of tourism destinations through indirect effects [24]. Eleonora et al. processed panel data through hierarchical clustering, factor analysis and multi-dimensional scaling. The results show that digital technology in tourism is conductive to tourists and develops new tourism models [25]. Vincent et al. discovered that new technology mainly changed the booking intention of tourism consumers through trust and curiosity, and they proved that consumers’ attitude toward new technology affected their acceptance of hotels [26]. Based on the data of 35 major cities in China from 2015 to 2019, Yanyan Yao et al. used web crawler technology and the bootstrap sbm-gml model to obtain the fintech development index and green total factor productivity, respectively. They studied the intermediary role of industrial structure upgrading (UIS) and technological innovation (TI) in the green development effect of fintech [27]. Tinghui Li et al. investigated the impact of the economic cycle (recession and expansion) from 1990 to 2014 on the energy intensity of 16 emerging countries. With foreign direct investment as the regulating variable, they further analyzed the relationship between the economic cycle and energy intensity by using the impact mechanism [28]. The methods used in these references have played a great role in enriching the theoretical mechanism and research methods of this paper.

Although most of the existing literature on digital economy studies focuses on how the digital economy promotes the overall economic development, their findings do not suggest a logical relationship between the digital economy and the high-quality development of tourism. Therefore, it is necessary to evaluate the development level of the digital economy. An evaluation of the high-quality development level of tourism in Xinjiang is also conducted. The effect of the digital economy in the high-quality development of tourism is further investigated. The understanding of their relationship provides valuable information for the administrative agencies. It will accelerate the high-quality development of tourism in Xinjiang.

The contribution of this study is summarized as follows:

(1)

The digital economy is used as one of the important variables to explore its impact on tourism, which provides a new perspective of the research in this field.

(2)

The mechanism how the digital economy influences the high-quality development of tourism is investigated. The result reveals that the digital economy promotes the high-quality development of tourism by stimulating the transformation and upgrading of tourism in Xinjiang.

(3)

The heterogeneity of the impact of the digital economy in the high-quality development of tourism is explored based on 14 prefectures in Xinjiang. It makes sense from a macro perspective in order to narrow differences between the digital economy and the high-quality development of tourism in different regions of Xinjiang.

2. Materials and Methods

2.1. Methods

2.1.1. Entropy Weight Method

In order to measure the high-quality development level of the digital economy and the tourism comprehensively, it is necessary to properly determine the weight of various indicators so as to ensure the robustness, objectivity, and accuracy. In this study, the EWM is used to measure the weight of each indicator according to the variability of its original data objectively. Compared with AHP and the subjective assignment method, the EWM can avoid the interference of subjective factors effectively and reliably.

Firstly, in order to eliminate the error caused by different measurement units of each item, the original data are normalized as follows:

$$X{ }_{ij}=\frac{A_{ij}-\min \left(A_{1j},A_{2j},\dots A_{nj}\right)}{\max \left(A_{1j},A_{2j},\dots A_{nj}\right)-\min \left(A_{1j},A_{2j},\dots A_{nj}\right)}+0.01$$

(1)

where $A_{ij}$ (i = 1, 2, …, n, and j = 1, 2, …, m) represents the value of the j-th item of the i-th observation; $X_{ij}$ represents the standardized value of $A_{ij}$; max ($A_{1j}$, $A_{2j}$, …, $A_{nj}$) and min ($A_{1j}$, $A_{2j}$, …, $A_{nj}$) represent the respective maximum value and the minimum value of the j-th item among all observations. In order to avoid a zero value in this normalization, 0.01 is added as part of the equation.

Secondly, the entropy of each evaluation index is calculated. Initially, we compute the parameter, $P_{ij}$, the weight of the standardized value $x_{ij}$ in the continuous m observations as follows.

$$P_{ij}=\frac{x_{ij}}{{\sum }_{i=1}^m{x}_{ij}}$$

(2)

$$E_j=\frac{1}{\ln m}{\displaystyle \sum }_{i=1}^m{p}_{ij}\ln pij$$

(3)

where $E_j$ represents the entropy value corresponding to the j-th indicator.

Thirdly, the weight of each evaluation index is determined as follows.

$$d_j=1-E_j$$

(4)

$$w_j=\frac{d_j}{{\sum }_{j=1}^m{d}_j}$$

(5)

In Equation (4), $d_j$ represents the difference coefficient of the j-th indicator; in Equation (5), $w_j$ represents the weight of the j-th indicator.

2.1.2. Fixed Effects Model

The panel data are the repeated observation data of individuals at different time points on the cross section. Compared with the simple time series analysis, the sampling precision of the estimator can be increased due to the increase in the observed values, and more consistent and efficient estimators can be obtained. There are three models for panel data, namely, mixed model, fixed-effect model, and random-effect model. After the Houseman test, the fixed-effect model is selected to analyze the relationship between variables.

The fixed-effect model is defined as

$$y_{it}={\beta }_0+{\beta }_1{x}_{it}+u_i+{\delta }_t+{\epsilon }_{it}$$

(6)

where i (i = 1, 2, …, n) represents different observations and t (t = 1, 2, …, T) represents different time points; $x_{it}$ is the explanatory variable representing the value of observation i at time point t, and $y_{it}$ is the corresponding explained variable; ${\beta }_0$ represents the intercept, which does not change by cross-section over time; ${\beta }_1$ is the regression coefficient of the explanatory variable; $u_i$ and ${\delta }_t$ represent the time invariant individual effect and time control effect, respectively; ${\epsilon }_{it}$ represents the random disturbance term.

Based on the FEM, a basic model is constructed as follows to analyze the relationship between the high-quality development level of tourism and the digital economy:

$$Hq{d}_{it}={\alpha }_0+{\alpha }_{1}Di{g}_{it}+{\alpha }_c{Z}_{it}+u_i+{\delta }_t+{\epsilon }_{it}$$

(7)

where $Di{g}_{it}$ is the development level of the digital economy of observation i at time point t$; Hq{d}_{it}$ is the high-quality development level of tourism corresponding to $Di{g}_{it}$; $Z_{it}$ represents a series of control variables; $u_i$, which does not change with time, indicates the individual fixed effect that only relates to observation i; ${\delta }_t$ represents the time fixed effect, ${\epsilon }_{it}$ represents the random disturbance term.

2.1.3. Mediating-Effect Model

Considering the influence of an independent variable on a dependent variable, if the independent variable affects the dependent variable by affecting a new variable, the new variable is called the intermediary variable. Referring to the intermediary effect test procedure and method, this paper constructs the following equations and steps: (1) Empirical analysis is carried out with the high-quality development of the tourism industry as the explained variable and the digital economy as the explained variable. (2) Take the intermediary variable as the explained variable and the digital economy as the explained variable to carry out empirical analysis. (3) The digital economy and intermediary variables are included in the empirical model for regression analysis. The transmission-effect model is as follows, If the coefficients ${\alpha }_1$ and ${\beta }_1$ are both significant and ${\gamma }_1$ is smaller or significantly lower than ${\alpha }_1$, it indicates the existence of a mediating effect.

Step 1: Build the impact model of the development of the digital economy on the high-quality development of tourism:

$$Hq{d}_{it}={\alpha }_0+{\alpha }_1*Di{g}_{it}+u_i+{\delta }_t+{\epsilon }_{it}$$

(8)

Step 2: Build the impact model of the development of the digital economy on intermediary variables:

$$mec{h}_{it}={\beta }_0+{\beta }_1*Di{g}_{it}+u_i+{\delta }_t+{\epsilon }_{it}$$

(9)

Step 3: Build the impact model including the digital development and intermediary variables:

$$Hq{d}_{it}={\gamma }_0+{\gamma }_1*\mathrm{D}ig+{\gamma }_2*mec{h}_{it}+u_i+{\delta }_t+{\epsilon }_{it}$$

(10)

where $mec{h}_{it}$ represents the intermediary variable corresponding the development level of the digital economy of the observation i at time point t, representing the industrial structure of the observation i at the time point.

2.2. Variables and Data Sources

The digital economy, as a motivated technology, can effectively promote the sustainable reforming of tourism. In the context of development driven by innovation, technological progress can improve the utilization efficiency of tourism resources, and the conversion rate of pollutants through technological progress increases to improve the environmental quality. This can realize resource allocation and the generation of new requirements in tourism. In respect of social outcomes, tourism enterprises use digital technology to target specific customers and scientifically analyze customer needs to optimize the production and marketing process of tourism products and improve the quality of tourism services. Taking digital technology as the driving force of innovation, deepening the “Internet + tourism” and promoting the development of smart tourism help improve the popularity of scenic spots. All in all, the digital economy is supposed to be one of the important indicators for this paper. In order to describe the digital economy, the following data such as the number of mobile phone users, the number of fixed Internet broadband access users, the postal and telecommunications services, the proportion of education spending in total GDP(GDP is the final outcome of the production activities of all permanent residents of a country (or region) in a certain period), the number of college students in every group of 10,000 people, the software revenue in tertiary industries, and the income of tourism products in the tertiary industry are measured. As for control variables, on the premise of avoiding endogeneity and pseudo regression of variables, the research reflects the unique regional characteristics of Xinjiang and chooses government regulation, industrial efficiency, the overall economic development level, and transportation infrastructure to analyze the impact of the digital economy on the high-quality development of tourism.

To describe the high-quality tourism development, the following information such as the number of days with second-class or above air quality, the public green space per capita, the number of scenic spots of 3A-level and above, the total fixed assets of accommodation and catering, the passenger capacity, the number of guest rooms (or beds) of the accommodation enterprises above a designated size and the number of employees in the accommodation and catering enterprises, the number of inbound tourists, and the number of domestic tourists is selected.

With the rapid development and wide application of digital technologies such as big data, artificial intelligence, cloud computing, Internet of things, and mobile Internet, the process of the digital industry and industrial digitalization continues to advance, and the digital economy plays a huge role in upgrading the industrial structure. As we can see, the higher the development level of the digital economy, the higher the information utilization, which accelerates not only the flow of information but also the integration of information and technology. This promotes the development and transformation of new technologies, which greatly promote the transformation and upgrading of the industrial structure. The transformation and upgrading of the industrial structure will continue to optimize the service quality of tourism-related industries and provide tourists with a better sense of experience and satisfaction. Accelerating the development of the digital economy and effectively promoting the upgrading of related industrial structures drive the high-quality development of the tourism.

From a governmental administration point of view, the Xinjiang Uygur Autonomous Region has 14 prefectures that are a combination of four prefecture-level cities, five autonomous prefectures, and five normal prefectures. The four prefecture-level cities include Urumqi city, Karamay city, Turpan city and Hami city, and the five autonomous prefectures are Changji Hui Autonomous Prefecture, Bortala Mongolian Autonomous Prefecture, Bayingolin Mongolian Autonomous Prefecture, Ili Kazak Autonomous Prefecture, and Kizilsu Kirgiz Prefecture while the other five normal prefectures are Kashgar Prefecture, Hotan Prefecture, Aksu Prefecture, Altay Prefecture, and Tacheng Prefecture. The annual panel data are the data of 14 prefectures in Xinjiang from 2008 to 2018.

All data were derived from the Statistics Yearbook (Xinjiang) tourism Statistics Yearbook and statistical bulletins on the website of the Culture and Tourism Department of the Xinjiang Uygur Autonomous Region (https://www.xinjiang.gov.cn (accessed on 1 December 2020)) spanning 11 years from 2008 to 2018.

3. Results

3.1. Theoretical Analysis and Research Hypothesis

The high-quality development of tourism is a kind of quality and benefit-oriented economic development integrating new development concepts, which is broader and has higher quality than traditional tourism. The high-quality development of tourism covers the two dimensions of fundamentals and social results, which is an organic unity of “process” and “result”. In terms of fundamentals, environmental quality and tourism resources are its main connotations. In the social aspect, tourism service quality and tourism attraction are its important performance measures. In this paper, we analyzed the impact of the digital economy on the high-quality development of tourism from two dimensions: fundamentals and social outcomes.

3.1.1. The “Process Mechanism” of the Digital Economy Affecting the High-Quality Development of Tourism

In respect of environmental quality, with the integrated development of the digital economy and tourism industry, digital technology, as a general technology, can effectively promote the sustainable reform of the tourism industry. In the context of development driven by innovation, technological progress can improve the utilization efficiency of tourism resources, and the conversion rate of pollutants through technological progress increases to improve the environmental quality. In addition, digital technology can improve the transparency of environmental information and facilitate the public to participate in the supervision. At the same time, digital technology can effectively improve environmental regulations and achieve precise supervision of pollution emissions. Therefore, environmental quality lays the foundation for the high-quality development of tourism.

In respect of tourism resources, the digital economy can realize resource allocation and the generation of new requirements in tourism, forming new value propositions and creating new resource combinations. In the process of tourism development, tourism enterprises can more effectively grasp the preferences of tourism consumers through digital technology and realize the effective allocation of resources such as scenic spots, accommodation, catering, and passenger volume. Tourism resources form an endogenous driving force for the high-quality development of tourism.

3.1.2. The “Result Mechanism” of the Digital Economy Affecting the High-Quality Development of Tourism

The digital economy can improve the quality of tourism service. Tourism enterprises use digital technology to target specific customers and scientifically analyze customer needs to optimize the production and marketing process of tourism products and improve the quality of tourism services. As a derivative of the application of digital technology in the tourism industry, “smart tourism” has completely changed the traditional single tourism form. “Smart tourism” not only promotes the spread of traditional culture and the construction of tourist attractions and cities but also establishes better personalized demand services in the information interaction platform so that tourists can obtain information through multiple channels. This study mainly reflects the quality of tourism services by the number of employees in the accommodation and catering industry. Tourism service quality is the endogenous condition for the high-quality development of tourism.

The integration of the digital economy and traditional tourism can effectively improve tourism attraction. Taking digital technology as the driving force of innovation, deepening the “Internet + tourism”, and promoting the development of smart tourism all help improve the popularity of scenic spots. Xinjiang not only has unique natural scenery and a cultural landscape but also has profound cultural relics and heritage. In this context, tourism enterprises take cultural and tourism integration as the main engine, promote “cultural and tourism +”, concentrate on building the brand of “Xinjiang is a good place,” and attract tourists from all over the world, which is the sustainable condition for the high-quality development of the tourism industry. The mechanism is shown in Figure 1.

Based on the above theoretical analysis, the following hypothesis is proposed:

Hypothesis: 

The development of the digital economy has a positive impact on the high-quality development of tourism.

3.2. Evaluation Index System for the High-Quality Development of the Digital Economy and Tourism

At present, scholars usually refine the connotation and formation elements of the digital economy when evaluating the development level of the digital economy and select appropriate evaluation indicators and methods from the perspective of statistical measurement, such as AHP and SEM, to evaluate the development level of the digital economy in a region. After referral to relevant literature and systematic calculation and comparison, EWM was selected to establish the evaluation system. The development level of the digital economy in Xinjiang from 2008 to 2018 was measured based on the digital infrastructure, digital talents, and digital ecology.

Total factor productivity is considered by the academic community. However, it is obviously not enough to only use a single dimension as the evaluation index for the development of tourism. Therefore, more and more scholars tend to measure the high-quality development level of a region through a multi-dimensional method, which is composed of four secondary indicators, the quality of the tourism environment, the quality of tourism resources, the quality of tourism services, and tourism attraction, to measure the high-quality development level of tourism in Xinjiang. We made use of the annual data available in 14 prefectures in Xinjiang from 2008 to 2018 and the high-quality development level of tourism, denoted Hqd in the formulas in Section 2. To assess the quality of the tourism environment, two third-level indexes, the days with air quality above grade 2, and the public green space per capita were used. Tourism resources are the core products of tourism. The quality of tourism resources is the most important factor affecting the quality of tourism development. The third-level indexes are defined to assess the quality of tourism resources, which include the number of scenic spots of 3A-level and above, the total fixed assets of accommodation and catering, and the passenger capacity. The quality of tourism services is also an important factor affecting the quality of development, including mainly accommodation conditions and service capacity. The measurement indicators for the quality of tourism services are the number of guest rooms (or beds) provided by the accommodation enterprises of a certain size and the number of employees in the accommodation and catering enterprises. In addition, tourism attraction is the most intuitive reflection of the quality of tourism development, and the number of tourists who visit a region directly reveals the attraction. The tourists can be either inbound tourists or domestic tourists.

Table 1. High-quality development index system of the digital economy and tourism in 14 prefectures of Xinjiang.

Primary Index	Secondary Index	Tertiary Index	Index Attribute
Digital economy	Digital infrastructure	Mobile phone users (10,000 households)	+
		Fixed Internet broadband access users (10,000 households)	+
		Total amount of post and telecommunications business (10,000 yuan)	+
	Digital talents	Education expenditure as a percentage of the GDP	+
		Number of college students per 10,000 people	+
	Digital ecology	Ratio of software business income to tertiary industry	+
		Ratio of software product income to tertiary industry	+
Tourism high quality development index	Environmental quality	Number of days above Class II air quality	+
		Per capital park green space area	+
	Tourism resources	Number of scenic spots of 3A-level and above	+
		Total fixed assets of accommodation and catering	+
		Passenger volume	+
	Tourism service quality	Number of beds in guest rooms of the accommodation enterprise	+
		Number of employees in the accommodation and catering industry	+
	Tourism attraction	Inbound tourists	+
		Domestic tourist arrivals	+

Note: The “index attribute” indicates if the impact of an indicator is positive (marked by “+”) or negative (marked by “−”).

summarizes the evaluation indicators for their development level.

3.3. Multicollinearity Test of Explanatory Variables

The digital economy is used as one of the most important explanatory variables to explain the high-quality development of tourism. In order to comprehensively analyze it, it is also necessary to set control variables that may have an impact on the high-quality development of tourism, such as government regulation, industrial efficiency, the overall economic development level, and transportation infrastructure, to control the possible nonlinear impact of other variables. Among them, the government regulation is expressed by the proportion of fiscal revenue in GDP in a year, the industrial efficiency is expressed by the total factor productivity of tourism, the overall economic development level is expressed by the GDP, and the transportation infrastructure is expressed by the number of vehicles in a year. Before the benchmark regression, the correlation analysis and multiple collinearity test are conducted for the explanatory variables. In the correlation analysis of the explanatory variables, the correlation between the digital economy and the control variables is very low. The variance inflation factor (VIF) values that are far less than 10 are shown in

Table 2. Variance expansion factors of explanatory variables.

Variable	Digital Economy	Economic Development	Industrial Efficiency	Government Regulation	Transportation Infrastructure
VIF	2.770	1.480	1.010	1.160	2.040
1/VIF	0.361	0.678	0.986	0.866	0.490

, which indicates that there is no correlation and collinearity between the explanatory variables.

3.4. Unit Root Test and Cointegration Test

Before the regression of panel data, in order to avoid pseudo regression and ensure the effectiveness of the estimation results, the stationarity of the series should be tested, and the most commonly used method to test the stationarity of data is the unit root test. After the use of the Kao test to conduct the panel unit root test, it was found that the original data of traffic facilities were unstable but were stable after first-order difference. Since the economic significance of the variable after the first-order difference was not the same as that of the original variable, and the cointegration was used to test whether the original sequence can be used for regression. The Kao test of panel data was selected for the cointegration test. As we can see in

Table 3. Kao test for cointegration.

Test	Statistic	p-Value
Modified Dickey–Fuller	3.1058	0.0009
Dickey–Fuller	4.5180	0.0000
Augmented Dickey–Fuller	4.3170	0.0000
Unadjusted Modified Dickey–Fuller	3.0212	0.0013
Unadjusted Dickey–Fuller	4.3229	0.0000

, the p values were all less than 0.001, so the original hypothesis should be rejected. There was a long-term cointegration relationship between variables.

3.5. Empirical Analysis Results

Combined with the Hausmann test results in Section 2.1.2, we chose the fixed-effect model to regress the relationship between the digital economy and the high-quality development of tourism. As presented in

Table 4. Baseline regression results.

Variable	Tourism High Quality Development Index
	OLS	Fe
Digital economy	0.912 *** (42.78)	0.830 *** (28.43)
Government regulation	−0.005 ** (−1.40)	−0.014 ** (−2.15)
Economic development level	0.022 ** (1.52)	−0.011 (−0.18)
Industrial efficiency	−0.013 * (−0.98)	−0.000 (−0.05)
Transportation infrastructure	0.031 * (1.57)	0.118 (1.26)
Cons	−0.499 * (−1.53)	−1.118 (−1.52)
Fixed Prefecture and year	NO	YES
N	154	154

Note: 1. Figures in parentheses are the t statistics. 2. The “*”, “**”, and “***” denote the significance levels at 0.1, 0.05, and 0.01, respectively.

, on the one hand, the coefficient value of the digital economy on the high-quality development of tourism in the second column of Table 4 is 0.912, the third column is 0.830, and they are both significant. The results indicate that the coefficient of the digital economy as one of the important variables is significantly positively related to the high-quality development of tourism at the significance level of 1%. The reason is that the digital economy makes it possible to transform the traditional development mode of tourism into new forms, which conforms to the digital economy’s characteristics of innovation, efficiency, and openness. At the same time, the digital transformation brought about by the digital economy has promoted the quality and efficiency of tourism. They will all promote the high-quality development of tourism. On the other hand, among the other four variables, government regulation and industrial efficiency have not significantly promoted the high-quality development of the tourism industry. That is because the government’s work in promoting the high-quality development of the tourism industry is not fully implemented. Although the industrial efficiency is constantly improving, increasing the investment blindly has not brought about a better sense of experience for consumers. The traffic congestion and garbage littering also reduce the quality of the tourism. Therefore, while developing the tourism industry, it is unwise to ignore the experience and satisfaction of tourists. Finally, from the perspective of the economic development level and transportation infrastructure, it can be concluded that with the development of economic level and the popularization of automobiles, people’s living standards have greatly improved and more and more attention has been paid to entertainment and leisure life, which prove that there is a large market development space for China’s tourism industry. All of these promote the high-quality development of tourism. The demand and supply aspects should cooperate with each other; only in this way can the dividends of the high-quality development of the tourism industry be truly realized in the daily life of every citizen. The comparison with the OLS model indicates that compared with other control variables, the digital economy, as one of the most important explanatory variables for the high-quality development of tourism, has greatly promoted the high-quality development of tourism. In the table, “Fe” represents the fixed-effect model, “OLS” represents ordinary least square method, “YES” and “NO” on the row of “Fixed Prefecture and year” indicate whether the model is fixed in state and time, and N represents the number of observations.

3.6. Analysis of the Mediation Effect

The reason why the industrial structure is chosen as the intermediary variable to study the impact mechanism of the digital economy in the high-quality development of the tourism industry is that with the rapid development and wide application of digital technologies such as big data, artificial intelligence, cloud computing, Internet of things, and mobile Internet, the process of the digital industry and industrial digitalization continues to advance, and the digital economy plays a huge role in upgrading the industrial structure. Liu Yang et al. found that the promotion of industrial structure upgrading by the digital economy is reflected in both the direct effect and indirect effect [29]. The direct effect is that the application of digital technology constantly generates new industries and new formats, and digital technology enables the upgrading and transformation of traditional industries. Indirect effects are the use and allocation of human capital, scientific and technological innovation, and other resource elements that promote the upgrading of the industrial structure.

Taking the industrial structure as an intermediary variable, the regression analysis results are shown in

Table 5. Results of mediating effect analysis.

Var	Tourism High Quality Development Index
	Baseline	Mech	Hqd
Dig	0.830 *** (28.43)	0.409 ** (2.86)	0.499 *** (2.86)
mech			0.234 *** (2.86)
N	154	154	154
R2	0.917	0.901	0.912

Note: 1. Figures in parentheses are the t statistics. 2. The “**”, and “***” denote the significance levels at 0.05, and 0.01, respectively.

. From the first column in the table, it can be seen that the coefficient value of the digital economy with respect to the high-quality development of the tourism industry is 0.830, and it has passed the significance test. It shows that the development of the digital economy can significantly promote the high-quality development of the tourism industry. The coefficient value of the digital economy with respect to the industrial structure in the second column of Table 5 is 0.409, and it has passed the significance test, indicating that the digital economy can significantly promote the upgrading of the industrial structure. The third column is the regression result of incorporating both the digital economy and intermediary variables into the empirical model. It can be seen that the regression coefficient value of the digital economy is 0.499. Compared with 0.830 in the first column, the coefficient value is slightly smaller, but the innovation of the digital economy is indicated. The coefficient is considered positive and has passed the significance test, indicating that the intermediary effect of the industrial structure exists significantly, that is, the digital economy can significantly improve the industrial structure and ultimately accelerate the high-quality development of the tourism industry.

In order to ensure the reliability of the tourism industry as an intermediary effect, we further chose the bootstrap sampling method for testing. The bootstrap sampling test refers to whether the 95% confidence interval of the product term ($\gamma *\beta$)of regression coefficient $\alpha$ and regression coefficient $\beta$ includes the number 0. If the 95% confidence interval does not include the number 0, it indicates that it has an intermediary effect; if the 95% confidence interval includes the number 0, it means that there is no intermediary effect. The test results are shown in

Table 6. Bootstrap results.

Variable	Observed Coef.	Bootstrap Std. Err.	Z	p > |Z|	Normal-Based [95% Conf. Interval]
r(ind_eff)	0.1068	0.0262	4.07	0.000	0.0554	0.1583
r(dir_eff)	0.2887	0.1134	2.54	0.011	0.0663	0.5111

below. The p value is far less than 0.05, which indicates that we should reject the zero hypothesis and affirm the conclusion that the digital economy promotes the high-quality development of tourism by promoting the transformation and upgrading of tourism.

4. Discussion

4.1. Heterogeneity Analysis

Due to the different resource endowment of a region and different development stages, obvious heterogeneity is presented in the regional distribution of both the development of the digital economy and the high-quality development of tourism. There may also be regional differences in the degree of impact the digital economy has on the high-quality development of tourism. Considering mainly the different geographical locations, overall economic development levels, ethnic composition, and tourism transportation of various prefectures in Xinjiang, the 14 prefectures of Xinjiang are grouped into four large tourism areas as a reference [30]: The provincial capital circle, northern Xinjiang, southern Xinjiang, and eastern Xinjiang. The provincial capital circle includes the Urumqi and Changji Hui Autonomous regions. The Northern Xinjiang tourism area includes Karamay, the Ili Kazak Autonomous region, Tacheng, Altay, and the Bortala Mongolian Autonomous region. The southern Xinjiang tourism area covers the Bayingolin Mongolian Autonomous region, Aksu Prefecture, Kizilsu Kirgiz, Kashgar, and Hotan. Eastern Xinjiang includes Hami and Turpan. The level of the four parts is presented by using the sum of the high-quality development data of the digital economy and tourism industry of prefectures from 2008 to 2018 included in the four parts.

Table 7. Differences in the development indicators in four areas.

Tourism High Quality Development Index
Region	Mean 1.691 0.507 0.534 0.312	Median	Standard deviation
Capital circle		1.291	1.187
Northern Xinjiang		0.429	0.354
Southern Xinjiang		0.365	0.459
East Xinjiang		0.264	0.192
Digital economy
Capital circle	1.209 0.504 0.533 0.311	0.711	1.255
Northern Xinjiang		0.424	0.389
Southern Xinjiang		0.395	0.491
East Xinjiang		0.293	0.214

compares the values of the indicator about the digital economy and the indicator about tourism high-quality development in the four tourism areas. The differences demonstrate that the values of the indexes for the provincial capital circle tourism area are much higher than those in the other three tourism areas. Its high-quality tourism development index and digital economy development level are nearly three times that of the eastern Xinjiang tourism area, and more than twice that of northern and southern Xinjiang tourism areas, showing the advantage as the first-mover. This result lays a foundation for the regional heterogeneity test in understanding the impact of the digital economy on the high-quality development of tourism.

Table 8. Regional heterogeneity test of the impact of the digital economy on the high-quality development of tourism.

Variable	Capital Circle	Northern Xinjiang	Southern Xinjiang	East Xinjiang
Dig	0.863 *** (22.90) 0.233 ** (2.49)	0.818 *** (26.09) 0.095 ** (5.12)	0.843 *** (27.79) 0.085 ** (4.33)	0.873 ** (15.79) 0.040 ** (2.45)
Cons
T	11	11	11	11
N	2	5	5	2

Note: 1. Figures in parentheses are the t statistics. 2. The “**” and “***” denote the significance levels at 0.05 and 0.01, respectively.

shows regional heterogeneity in terms of the impact the digital economy has on the high-quality development of tourism. The result illustrates that the digital economy development in all four tourism areas has a significant effect on the high-quality development of tourism. The digital economy in the provincial capital circle tourism area has the strongest promotion effect on the high-quality development of tourism. The Urumqi and Changji Hui Autonomous regions have attracted many tourists with their relatively convenient transportation condition and development level. It cannot be ignored that the development level of the digital economy in these two regions is far ahead, which is because of the foundation for the high-quality development of the tourism industry. Although the development level of the digital economy and the high-quality development of the tourism industry in Eastern Xinjiang are not as good as those in other regions, the digital economy in eastern Xinjiang promotes the high-quality development of the tourism to a large extent. Although the natural resource advantages of Turpan and Hami are not as good as those in other areas, policies such as making the digital economy larger and stronger, building a competitive advantage, are leading the rapid development of tourism in Turpan and Hami. It has provided a good example for several other regions.

4.2. Robustness Check

In fact, there are many methods that can be used to test the robustness. Replacing the digital economy of manufacturing labor productivity, new indicators are chosen to measure the high-quality development level of the digital economy and tourism to ensure the validity and reliability of the proposed models. Firstly, tourism revenue is used as an index to measure the level of high-quality tourism development, which increases the intuitiveness in selecting the explained variables and reduces the deviation of the results caused by artificial calculation methods. As shown in

Table 9. Robustness test results.

Variable	Tourism High Quality Development Index
	Tourism Income	Tourism High Quality Development Index
Dig	0.347 *** (2.62)
Dig2		0.263 *** (2.22)
L.dig			0.880 *** (16.41)
N	154	154	154
R2	0.917	0.912	0.635

Note: 1. Figures in parentheses are the t statistics. 2. The “***” denotes a significance level of 0.01.

, as one of the most important explanatory variables, the digital economy is significantly positive. Secondly, the sum of the number of mobile users, the number of Internet users, and the income of post and telecommunications in the 14 prefectures in Xinjiang from 2008 to 2018 is used to count and estimate the scale of the digital economy in a certain region. In this case, the parameter Dig2 is used to represent the development level of the digital economy as shown in Table 9. The result shows that at the significance level of 1%, the digital economy plays a significantly positive role in promoting the high-quality development of tourism. Thirdly, the potential endogenous variables caused by some non-observable factors and the lag period of the digital economy are used as the core variable to test the promotion effect of the digital economy on the high-quality development of the tourism. In this case, the parameter L.dig is used to represent the lag level of the digital economy. As shown in Table 9, the results reveal that the digital economy lags by one time period, which proves that the early tendency of the digital economy will have a certain causal effect on the current state of the high-quality development of tourism. All of the results demonstrate that the fixed-effect model is reasonable and effective to study the relationship between the digital economy and high-quality development of tourism.

5. Conclusions

5.1. Conclusions

Based on the data from 14 prefectures in Xinjiang, it is proposed that the digital economy significantly influences high-quality tourism. The fixed-effect model was used to study the relationship between the digital economy and the high-quality development of tourism. The level of the digital economy and high-quality development of the tourism level of 14 prefectures in Xinjiang were analyzed by EWM. The digital economy level that affects the high-quality development of tourism was analyzed empirically. The first findings are summarized as follows: the level of the digital economy and the high-quality development of tourism in Xinjiang show a steady upward trend and their coefficient is significantly positive. Furthermore, the mechanism of how the digital economy promotes the high-quality development of tourism was analyzed. The digital economy can promote the high-quality development of tourism by stimulating the upgrading of the industrial structure. The higher the development level of the digital economy, the higher the degree of digitalization, which will undoubtedly improve the high-quality development of the tourism industry. Last but not least, the heterogeneity analysis and robustness test ensure the reliability and validity of the model, and the results confirm that the digital economy is the key driving force for the high-quality development of tourism. Among the four tourism circles, the digital economy has played a very good role in promoting the high-quality development of the tourism industry. Among them, the capital tourism circle has the most significant regression coefficient. The Urumqi and Changji Hui Autonomous regions, with their economic and geographical advantages, have better played the role of the digital economy in promoting the high-quality development of tourism followed by Hami and Turpan. These two prefectures make use of their unique natural resources and the strength of government to vigorously develop the digital economy, which has greatly promoted the high-quality development of the tourism industry.

5.2. Suggestions

Obviously, the digital economy plays an important role in promoting the high-quality development of tourism. How can we make good use of the digital economy and the rich tourism resources in Xinjiang to promote the high-quality development of Xinjiang’s tourism? There are three ways to start.

Firstly, it is critical to make good use of the important conclusion of this paper, that is, to use the digital economy to promote the high-quality development of the tourism industry. The user traffic obtained from both online and offline channels should be fully explored to then put more energy into the research and development of tourism products; therefore, users will be stimulated to have more diversified travel motivations. By increasing the repurchase rate of products, optimizing and upgrading products and services, the enterprises in the tourism can act in line with the current changes in tourism needs and avoid the accumulation of homogeneous products. Big data, artificial intelligence, and other technologies should be used to efficiently recommend personalized tourism products to users, which are distinctive, connotative, and warm. Secondly, tourism is an experience-based economy. The enterprises in this sector should cultivate professional tourism talents to formulate tourism products and deeply explore the tourism characteristics of the scenic spots to make sure their tourism products are more transparent in a down-to-earth manner. As a result, the actual experiences of tourists exceed their expectations. At present, online travel platforms provide a large number of high-quality travel strategies to attract users and use this as a marketing opportunity to recommend relevant travel products to influence users’ consumption decisions. The high user stickiness can be taken advantage of to expand their platforms. All in all, it is imperative to speed up the level of tourism informatization, to improve the quality of tourism public services, and strengthen tourism management capabilities.

Secondly, the digital economy should be used to promote the upgrading of the tourism structure alone. There are two main ways: one is to directly generate new industries and format the industries or empower traditional tourism to accelerate its transformation. The other is to indirectly affect the critical elements of human capital, scientific and technological innovation by changing their usages and configurations. Therefore, tourism can comprehensively use 5G technology, Internet of Things technology, and artificial intelligence technology to provide technical support for the intelligent management of scenic spots and to gradually form a tourism cloud platform, enabling high-quality services. Otherwise, the digital economy can be used to improve the efficiency of tourism. In traditional tourism, production and consumption are usually out of synchronization. The data generated cannot be stored, and large differences exist among the elements of tourism. It is difficult to achieve economies of scale, resulting in the low efficiency of tourism. However, with the deepening of the application of the digital economy in tourism, the digital economy can be used to empower the production, dissemination, and consumption processes of tourism and improve the industrial efficiency of tourism gradually. Therefore, tourism can change the extensive growth mode that relies on resources and markets in the supply-side structural reform focusing on technology innovation and the continuous integration of technology flow, material flow, capital flow, and talent flow.

Finally, the regional heterogeneity analysis reveals that there is a serious regional development imbalance. Therefore, strengthening the infrastructure construction for the digital economy to promote the development of the digital economy is essential. The tourism areas in the south and north of Xinjiang have the same level of high-quality development and digital economy, and the digital economy has promoted the high-quality development of tourism to a certain extent in the two regions. The digital economy should be developed vigorously while developing the economy and improving infrastructure to promote the high-quality development of tourism. In addition, data sharing is necessary to call on all regions to pay attention to the role of the digital economy in promoting the high-quality development of tourism. It is easy to collect store and exchange information and to tap the deep value of digital resources with the digital economy. The development strategy should be reasonably planned to improve the supervision system of the digital economy, and preventive measures should be taken, so as to actively promote the high-quality development of tourism.