The Impacts of Tourism Development on Urban–Rural Integration: An Empirical Study Undertaken in the Yangtze River Delta Region

Abstract

A viable pathway towards achieving shared prosperity is made possible by the growth of tourism, which encourages the movement of urban and rural elements. This harmonious alignment of tourism development and urban–rural integration also helps to narrow the gap between urban and rural areas. This study uses a set of panel regression models to investigate whether tourism growth promotes urban–rural integration within 41 cities in the Yangtze River Delta Region of China from 2010 to 2020. The findings show that the effect of tourism development on urban–rural integration is significantly positive, displaying significant heterogeneity across various times and city sizes. Furthermore, tourism development exhibits a threshold effect and city-type heterogeneity concerning urban–rural integration. The effect demonstrates significant continuous growth along with the expansion of economic growth. However, the impact of tourism development on urban–rural integration demonstrates a distinct promotional threshold effect, and its positive effect appears to be weakened.

1. Introduction

Amidst the ongoing global trends of urbanization, the stark disparity between urban and rural areas has become increasingly conspicuous across various regions worldwide. In recent years, China has made notable progress in encouraging a new era of urbanization while effectively managing the harmonious growth of urban and rural areas. Nonetheless, there are still prominent problems such as the uneven allocation of public assets and the uncoordinated movement of urban and rural factors. Concurrently, propelled by the rapid expansion of the Chinese economy and the escalating demands within the tourism sector, the tourism industry has emerged as an increasingly vital contributor to the advancement of urban–rural development [1,2]. According to figures made public by the China Tourism Academy, the direct contribution of China’s tourism industry to the GDP in 2019 was 11.0%, with a complete contribution rate of 28.2%. This notable contribution is associated with the generation of 289 million employment opportunities. Consequently, tourism development has promoted urban–rural integration (URI) while driving rural economic development and raising farmers’ income levels [3]. On one hand, the dynamic influence of tourism has enhanced bilateral exchanges between urban and rural areas, embracing a variety of aspects like commodities, capital, information, and technology [4]. These exchanges have become more convenient and frequent. On the other hand, a growing number of rural regions have promoted the development of rural tourism by capitalizing on landscapes and cultural distinctiveness, thereby transforming these aspects into valuable tourism assets. This has not only provided farmers with novel income sources but has also improved the overall infrastructure of the locales [5]. Based on the aforementioned analysis, it is clear that the tourist sector plays a variety of roles in China’s process of integrating urban and rural areas. Thus, it is imperative to explore the relationship between tourism development and URI.

Numerous scholars have shown significant interest in the growing importance of tourism development within the context of URI. As a result, a substantial body of research has been conducted to explore the role of tourism development in bridging the gap between urban and rural regions [3,6]. Researchers have examined the connection between tourism development and urban–rural areas [7,8,9]. From the urban perspective, researchers have primarily focused on the economic implications, spatial revitalization, regional disparities, and resident perceptions of the urban area as influenced by the tourism industry [10,11,12]. For instance, Ma et al. [13] revealed that the rise in tourism significantly impacts China’s urban economic growth without exacerbating economic disparities among cities. From the rural perspective, studies have concentrated on the effects of tourism on increasing agricultural productivity, reducing poverty, and changing the spatial dynamics of rural areas [14,15,16]. According to Li et al. [17], social media marketing positively affects dining establishments’ performance. Overall, while the bulk of academics have concentrated on how tourism development may affect income equality between urban and rural areas, there appears to be less emphasis on thoroughly investigating the impact of tourism growth on URI as a whole. However, focusing solely on either urban or rural development neglects crucial information about the tourism industry’s intricate role in promoting URI. Furthermore, a thorough examination of the connections between the two is required in order to construct a strong institutional framework for integrated urban and rural development. Hence, it is imperative to conduct a thorough empirical analysis of the correlation between tourism development and URI.

To address the aforementioned shortcomings, this study utilizes panel regression models to assess the effects of tourism development on URI using 41 cities from the Yangtze River Delta Region (YRDR) in China as an empirical case. We take things a step further by analyzing the diverse impacts of tourism growth. Our study contributes to this field in two different ways. The inclusion of empirical data demonstrating the beneficial effects of tourism growth on URI theoretically contributes to the body of literature already in existence. Practically, this study can also offer recommendations for improving regional coordination and sustainable development in other developed regions around China.

2. Literature Review

2.1. The Impact of Tourism Development on the Urban Area and Rural Area

The impact of tourism development on a region can be comprehensively analyzed by considering both urban and rural areas [18]. Urban areas tend to benefit more from tourism development due to their superior infrastructure and greater visibility [18]. On the one hand, the tourism industry has the potential to boost economic growth, create employment opportunities, enhance urban landscapes and renewal efforts, foster cultural exchanges, and promote the sustainable growth of cities [13]. On the other hand, tourism can contribute to mitigating regional economic imbalances by optimizing resource allocation, adjusting the industrial structure, and encouraging investments [19]. As emphasized by Shin et al. [12], cultural tourism can significantly contribute to urban development. Furthermore, Liu et al. [19] demonstrated that the overall impact of the tourism sector on urban livability initially increases, but eventually decreases as tourism density rises. However, some scholars have argued that excessive tourism development may pose threats to urban livability [20]. With the high-quality improvement of tourism, a few scholars have emphasized that the tourism industry should not be overlooked in the process of URI.

Nevertheless, in contrast to urban areas, rural areas have distinctive cultural legacies and ethnic tourism resources, such as ethnic communities, native festivals, and traditional performances, providing tourists with the opportunity to experience exotic cultures [7]. By enabling rural populations to participate in tourist-related activities, tourism can help to reduce poverty [21]. Additionally, rural tourism contributes to non-farming forms of income for rural households by utilizing the region’s great natural beauty and distinctive cultural features to draw tourists. This revitalizes the rural economy and encourages the growth of new businesses [22]. According to Mahadevan’s research, urbanization alone is insufficient to establish a clear link between tourism and poverty alleviation, whereas domestic tourism has a larger influence on poverty reduction than inbound tourism [23]. Wang et al. [24] found that rural tourism has a nonlinearly favorable impact on reducing poverty, demonstrating a double-threshold effect. However, there have been divergent views on how rural tourism development may affect rural regions [25,26,27]. Zhang [3] argued that tourism development exacerbates income inequality in rural areas. Shen et al. [28] investigated rural tourism development in China and revealed an imbalanced spatial development pattern, indicating that rapid rural tourism development frequently results in the erosion of rural characteristics. Dossouo et al. [25] concluded that tourism development exacerbates poverty. Furthermore, without the support of relevant planned initiatives, farmers face greater challenges in generating tourism income [29]. Overall, the existing research shows that tourism can affect the development of both urban and rural areas by affecting residents’ incomes. However, since the majority of these studies have focused on specific topics or viewpoints, it remains challenging to determine whether tourism effectively promotes URI.

2.2. Tourism Development and URI

While previous studies have primarily concentrated on assessing the impact of tourism on economic growth, there has been a growing interest in exploring how tourism can reduce the income disparity between urban and rural areas [30]. Due to the uneven distribution of tourism resources, as well as variations in tourism services, urban and rural areas have engaged in mutual borrowing and communication through the manner of tourism development. This has led to the breakdown of barriers, encompassing both psychological and material components, between urban and rural areas [31]. Consequently, substantial flows of goods, people, information, and capital have been generated, fostering the establishment of communication and interaction channels between urban and rural areas [32,33].

With the development of the economy, the tourism industry has the potential to play a crucial role in reducing regional income disparities by redistributing the benefits of economic growth from urban centers to less developed regions. Liu et al. [34] found that the tourism industry can contribute to narrowing the economic disparity between urban and rural regions in China. However, some academics argued that tourism exacerbates income inequality by leading to an unequal distribution of land and resources [35,36]. Specifically, tourism development may worsen wage disparities as it tends to concentrate attention in urban areas, promoting the growth of hotels, restaurants, entertainment venues, and other tourist facilities and services that primarily benefit urban locations, which results in a higher concentration of wealth and resources in urban areas compared to rural areas [37]. Rasoolimanesh et al. [38] found that there are prominent disparities in residents’ perceptions regarding the results of economic growth and community engagement in rural and urban contexts. In such cases, tourism development may expand the economic differences, which helps to shed light on how tourism may affect URI.

With respect to social development, tourism plays a significant role in dispersing economic benefits from urban regions to rural regions, thereby creating job chances for unskilled laborers [39]. Furthermore, due to the mobile nature of tourism consumption, it is widely believed that tourism promotes industrial integration, facilitates cultural exchange, and contributes to the equalization of public services [40]. The emergence of ecotourism, green tourism, and health tourism has also shifted the focus of environmental construction and protection from urban areas to rural areas [41]. Additionally, the principles and practices of URI are utilized to strengthen rural environmental management and preservation, advance the convergence of urban and rural environmental planning, and create a favorable environment for tourism and quality of life. This has emerged as a key element of urban–rural development, as it not only enhances inhabitants’ quality of life but also promotes sustainable growth and the peaceful coexistence of urban and rural regions [42].

Given that rural areas have an abundance of tourism resources, such as historical sites, folk culture, and traditional handicrafts, tourism usually provides employment opportunity for residents, which may promote URI [43]. These effects can be further amplified, particularly in industrialized areas where there is sufficient financial capacity to promote tourism in rural areas [44]. Zhang et al. [30] indicated that the role of tourism development in narrowing the income gap is stronger in the eastern region than in the western region in China due to the difference in the level of economic development. Blake et al. [45] concluded that the tourism industry provides less income to impoverished families, which can lead to income inequality. Consequently, considering the pronounced regional disparities in tourism benefits between urban and rural regions, the feasibility of job opportunities and improved social public offerings in rural regions may be limited. Thus, the magnitude of tourism’s effects on promoting URI may be higher in regions with an excessive degree of economic development in contrast to that of other cities.

The above literature review indicates that tourism development can affect the relationship between urban and rural regions. This study is supported scientifically by the existing studies. However, there are still some urgent problems that need to be solved. First, previous studies were predominantly based on qualitative research or focused on the effect of tourism on urban–rural disparity, overlooking the correlation between tourism development and URI [46,47]. In the current complex economic environment, the impact of tourism development on URI may be affected by several variables that exhibit a non-linear connection [37]. Second, few studies have focused on the threshold effects of tourism on URI. Furthermore, there has been little examination of the heterogeneity of tourism and URI across various periods and geographical areas. Third, most of the applicable literature from China depends on interprovincial data, neglecting the differences in economic and tourism development as well as the disparity between urban and rural regions [48]. By using panel data from 41 cities of the YRDR in China from 2010 to 2020, we creatively examine whether tourism may promote URI.

3. Research Data and Methods

3.1. Research Region

The Yangtze River Delta Region (YRDR) is located in the eastern part of China, totaling 41 cities. The YRDR is known for its rich cultural heritage, with numerous historical landmarks, traditional villages, and scenic natural attractions [49]. More specifically, the YRDR boasts 61 top-tier scenic spots that have achieved the prestigious AAAAA (5A) rating. Among these remarkable destinations are iconic sites like West Lake in Hangzhou, Huangshan Mountain in Huangshan, and the Classical Gardens in Suzhou. These renowned locations showcase the rich cultural and natural heritage of the region, attracting numerous visitors from both within China and around the world. Moreover, tourism in the YRDR has experienced a remarkable surge, witnessing an approximately 2.44-fold increase from 1.25 trillion yuan in 2010 to 3.06 trillion yuan in 2020. The substantial expansion of the tourism industry in the area highlights its appeal as a popular destination for both domestic and international travelers, contributing to its economic vitality and development. Thus, the YRDR has emerged as an exemplar of tourism development in China, demonstrating tourism’s remarkable potential. Recently, the YRDR has prioritized the pursuit of URI as a vital component of its developmental agenda [50]. By striving for equitable economic growth and endeavors to enhance the living standards of rural inhabitants, the region is dedicated to fostering a harmonious coexistence between urban and rural spheres.

3.2. Methods

3.2.1. Regression Model

We employed an empirical research approach using a panel regression model to analyze the impact of tourism development on URI, as represented by Equation (1)

$$lnur{d}_{it}={\alpha }_0+{\alpha }_1{td}_{it}+\alpha ln{X}_{it}+{\mu }_i+{\epsilon }_{it}$$

(1)

where ${tour}_{it}$ denotes tourism development; ${urd}_{it}$ represents the capacity of URI; $X_{it}$ is the control variable; ${\alpha }_0$ is a constant term; ${\alpha }_1$ is the estimated coefficient of tourism development; $\alpha$ is the coefficient of the control variable; ${\mu }_i$ is the individual constant effect; and ${\epsilon }_{it}$ is a random error term.

3.2.2. Threshold Model

Given the foregoing, it can be deduced that the impact of tourism growth on URI depends on the level of economic development in the area. Thus, the construction of a threshold effect model is considered on the basis of Equation (1)

$$\begin{array}{c}ln{urd}_{it}={{\alpha }_0+\beta }_1{td}_{it}\times I(PGDP\le Z_1)+{\beta }_2{td}_{it}I(Z_1<PGDP\\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}\le Z_2)+\cdots +{\beta }_m{td}_{it}\times I(PGDP>Z_m)+\alpha X_{it}+{\epsilon }_{it}\end{array}$$

(2)

where $I(\bullet )$ is an indicative function; ${\beta }_m$ represents the estimated coefficients of the core explanatory variables at different threshold levels; $Z_m$ is the threshold value; and $PGDP$ is the threshold variable (the level of economic development).

3.2.3. Variable Selection

(1)

Dependent variable. URI (uri), as an advanced stage in the development of the urban–rural system, encompasses the integration dynamics, integration process, and integration state. It signifies the convergence of various linkages between urban and rural domains, encompassing population mobility, facility connectivity, public service provision, and land space expansion, which manifests in the realms of population, space, economy, and society [51,52]. URI constitutes the physical spatial connection and social support network between urban and rural areas, adapting to the distinct stages of economic and social development within these regions. Therefore, we constructed an index system to measure the level of URI on the basis of urban–rural linkages. The process begins with sorting out the types of existing urban–rural linkages, and the URI evaluation index system is divided into four dimensions: population mobility, facility connectivity, public service provision, and land space expansion. The selection of indicators follows the principles of data availability, systematization, and representativeness, as shown in

Table 1. The index system of URI.

Dimension	Indicator	Calculation Method	Data Sources	Weights
Population	Spatial agglomeration	Rate of urbanization (%)	Data from the “statistical bulletin of national economic and social development of each city report”, 2010 to 2020.	0.096
Society	Education levels	The ratio of students to teachers in urban general secondary schools and in rural general secondary schools (%)	Data from the China Urban Construction Statistical Yearbook, 2011 to 2021.	0.073
	Medical levels	The ratio of the number of doctors per 1000 people in urban areas to the number of doctors per 1000 people in rural areas (%)	Data from the China Urban Construction Statistical Yearbook, 2011 to 2021.	0.138
Space	Traffic accessibility	The proportion of road mileage to land area (km/km2)	Data from the China City Statistical Yearbook, 2011 to 2021.	0.418
	Information accessibility	The number of subscribers with access to Internet broadband per 10,000 people (households/million people)	Data from the Zhejiang Statistical Yearbook, Jiangsu Statistical Yearbook, Anhui Statistical Yearbook, and Shanghai Statistical Yearbook, 2011 to 2021.	0.243
Economy	Income levels	The ratio of urban per capita disposable earnings to rural per capita disposable profits (%)	Data from the Zhejiang Statistical Yearbook, Jiangsu Statistical Yearbook, Anhui Statistical Yearbook, and Shanghai Statistical Yearbook, 2011 to 2021.	0.004
	Consumption levels	The ratio of urban per capita consumption expenditure to rural per capita consumption expenditure (%)	Data from the Zhejiang Statistical Yearbook, Jiangsu Statistical Yearbook, Anhui Statistical Yearbook, and Shanghai Statistical Yearbook, 2011 to 2021.	0.028

. Among them, the social dimension, educational level, and medical level are strong assurances for the coordinated development of urban and rural areas. Meanwhile, the entropy method was used to calculate index weights and evaluation indices; see reference [53] for the specific calculation procedure.

(2)

Core independent variable. Tourism development (td) performs a pivotal task in expediting the pace of URI. To assess tourism’s impact on URI, it is common in scholarly research to employ tourism depth indicators, which are selected based on empirical findings and sound scientific considerations [52,54]. Referring to Shan et al. [55], this study used the ratio of total tourism income to GDP to represent tourism development. Additionally, the ratio of tourist numbers to the whole population size was utilized as an alternative when conducting robustness tests. Tourism income is the economic output of tourism development. The tourism number is the number of tourists and can also be used to mirror the level of tourism development [56]. Thus, we made use of the ratio of tourist numbers to whole population size as an alternative when conducting robustness tests.

(3)

Threshold variable. We further assessed how economic expansion affected the development of the tourism industry and URI. Referring to the work of Gan et al. [52], we took the per capita GDP (pgdp) as the threshold variable.

(4)

Control variables. Following the previous studies on factors affecting URI, we controlled the influence of trade openness (open), regional investment (inve), government intervention (gov), technology innovation (tech), and industrial structure optimization (ind) [3].

4. Results

4.1. The Analysis Results of URI

4.1.1. The Evolutionary Characteristics of URI

From 2010 to 2020, the URI in the YRDR exhibited an initial upward trend followed by a subsequent decline, as illustrated in Figure 1. This pattern signifies the increasing emphasis placed on the advancement of URI. It is vital to prioritize the enhancement of infrastructure, including the institution of efficient transportation systems and robust communication networks, to foster stronger connections between urban and rural regions. The degree of URI in Shanghai exhibited considerable fluctuations; however, Shanghai also demonstrated the most rapid rate of advancement. During the period from 2010 to 2012, the level of URI in Zhejiang was lower than that in Jiangsu. However, it surpassed Jiangsu after 2012 and grew to be second to Shanghai in terms of the integration progress. The level of URI in Anhui province consistently remained lower than that in Shanghai, Jiangsu, and Zhejiang provinces. It can be viewed that the differences in the level of URI in the YRDR are still significant.

4.1.2. Spatial Characteristics of the URI

Based on the classification of the overall level of URI in the YRDR, we divided the urban development indices of 2010, 2015, and 2020 into five grades by using the method of natural breaks (Figure 2). In 2010, a spatial pattern of high integration was evident in Shanghai, Suzhou, Wuxi, and Tongling. Conversely, Suzhou, Bozhou, Fuyang, Chuzhou, Yangzhou, Luan, and Anqing exhibited a spatial pattern of low integration. These areas are predominantly located in the southern regions of Anhui and Jiangsu. In 2015, the level of URI had become more balanced in the north–south direction. A high-grade development zone of URI had emerged, with Shanghai as the central hub and which included Suzhou, Wuxi, Jiaxing, and Hangzhou. The development of the Shanghai metropolitan region has performed a favorable function, facilitating the drift of urban sources into the surrounding rural areas. Additionally, it has promoted the transfer and concentration of industries to new towns through initiatives such as industrial restructuring and urban spatial adjustment. In 2020, cities with a higher degree of urbanization were primarily concentrated along the urban belt of Hefei, Wuhu, and Maanshan. Notably, a striking spatial pattern with large-grade fluctuations was found around the periphery areas of the central cities, which was characterized by significant grade changes. In general, the region where URI development was more advanced shifted i from Shanghai as the central hub to Hefei, Wuhu, and Maanshan, showcasing a distinct agglomeration effect. Consequently, the government should allocate relatively more attention and resources to ordinary cities to foster their development.

4.2. The Impacts of Tourism Development on URI

4.2.1. Descriptive Analysis and Panel Stationarity Test

All variables in this study underwent a logarithmic transformation to solve the heteroscedasticity issue and guarantee the reliability of the empirical findings. The VIF of all variables is below 5, while the correlation coefficients between independent variables are below 0.8 (as shown in

Table 2. Descriptive statistics and validity tests.

Variable	Mean	Std. Dev.	Min.	Max.	Skewness	Kurtosis	VIF
uri	0.246	0.095	0.029	0.517	0.279	2.688	—
td	0.187	0.175	0.029	1.067	2.907	12.225	1.06
lnopen	29.38	31.56	1.364	201.037	2.081	8.068	1.58
lninve	0.757	0.26	0.001	1.468	0.251	2.695	1.53
lngov	1.729	1.028	0.262	14.576	4.774	55.658	1.50
lntech	0.36	0.236	0.021	2.14	2.327	13.231	1.39
lnind	0.438	0.085	0.233	0.731	0.315	3.706	1.05
lnpgdp	10.954	0.622	9.112	12.201	−0.474	2.789	2.41

and

Table 3. Correlation matrix.

	uri	td	lnopen	lninve	lngov	lntech	lnind	lnpgdp
uri	—
td	0.120 **	—
lnopen	0.478 ***	0.001	—
lninve	0.275 ***	0.183 ***	−0.534 ***	—
lngov	−0.558 ***	0.080 *	−0.350 ***	0.273 ***	—
lntech	0.577 ***	−0.075 *	0.249 ***	−0.056	−0.501 ***	—
lnind	0.146 ***	−0.053	0.182 ***	−0.139 ***	−0.178 ***	0.082 *	—
lnpgdp	0.764 ***	0.054	0.513 ***	−0.370 ***	−0.609 ***	0.560 ***	0.175 ***	—

Note: *, **, and *** represent 10%, 5%, and 1% levels, respectively.

). These results show that the variables do not significantly exhibit multicollinearity, which could affect the results. The results given in Table 1 show that the mean value of uri is 0.246, with a standard deviation of 0.095. Similarly, the mean value of td is 0.187, with a standard deviation of 0.175. The observed differences between the means of these variables are not substantial. The remaining variables’ means and distributions are also within acceptable bounds. The results, as presented in

Table 4. Unit root tests of variables.

Variable	LLC Test	IPS Test	Fisher−ADF Test	PP Test
uri	−4.274 ***	−2.638 ***	−7.274 ***	169.306 ***
td	−2.315 **	−2.105 **	−5.454 ***	217.639 ***
lnopen	−5.233 ***	−1.769 **	−5.948 ***	1393.397 ***
lninve	−8.810 ***	−3.397 ***	−5.324 ***	779.423 ***
lngov	−54.111 ***	−11.039 ***	−4.124 ***	529.452 ***
lntech	−3.506 ***	−1.941 **	−2.256 ***	453.392 ***
lnind	−31.827 ***	−6.241 ***	−6.624 ***	438.026 ***
lnpgdp	−3.100 ***	−1.844 ***	−1.404 *	194.246 ***

Note: *, **, and *** represent 10%, 5%, and 1% levels, respectively.

, indicate that all variables pass all of the unit root tests. This implies that the panel data is steady, ensuring the validity and precision of the analysis.

4.2.2. Panel Stationarity Test

(1)

Benchmark regression

Columns (1) to (6) in

Table 5. Regression results.

Variable	(1)	(2)	(3)	(4)	(5)	(6)
td	0.318 *** (7.92)	0.285 *** (7.37)	0.242 *** (6.08)	0.280 *** (7.70)	0.270 *** (9.05)	0.269 *** (8.97)
lnopen		−0.001 *** (−6.39)	−0.001 * (−6.58)	−0.001 *** (−7.40)	−0.0009 *** (−6.82)	−0.0001 ** (−6.80)
lninve			0.077 ** (3.67)	0.090 *** (4.73)	0.058 *** (3.66)	0.059 *** (3.68)
lngov				−0.028 *** (−9.49)	−0.011 *** (−4.20)	−0.011 * (−4.22)
lntech					0.200 *** (14.02)	0.200 *** (14.00)
lnind						−0.015 (−0.48)
_cons	0.186	0.227	0.177	0.210	0.126	0.057
sigma_u	0.090	0.112	0.122	0.113	0.095	0.096
sigma_e	0.057	0.054	0.053	0.048	0.039	0.039

Note: The t-statistics for the coefficients are reported in parentheses; *, **, and *** represent 10%, 5%, and 1% levels, respectively.

display the findings from the stepwise regression models. The estimated coefficients of tourism development on URI are positive and statistically significant, as shown in column (1) of Table 5, without taking control factors into account. The estimated value and significance of tourism development remain largely unchanged as more control variables are added in columns (2)–(5). This finding further supports the notion that tourism development exerts a positive function on URI.

Regarding the effects of control variables on the URI, two control variables (invest and tech) have a favorable impact on URI. On one hand, there is a positive and statistically significant correlation between investment level and URI. A one percent increase in investment leads to a 0.059% increase in the URI. This increase in investment helps boost the level of infrastructure construction, supporting the parity between public services such as healthcare and education in urban and rural regions, and encouraging agricultural modernization in the YRDR. On the other hand, the estimated coefficient of tourism development on URI is positive and significant at the level of 1%. A one percent increase in technological innovation raises the URI by 0.200%.

(2)

Threshold effect test

The per capita GDP was included as a threshold variable to investigate the threshold effect of economic development on the association between tourism development and URI. The bootstrap method was employed to identify this effect, and the results are presented in

Table 6. Results of threshold effect significance test for entire samples.

Threshold Variable	Number	F Value	p-Value	Threshold Critical
				1%	5%	10%
td	Single	91.13	0.040	50.879	35.678	28.534
lnpgdp	Single	99.61	0.000	48.221	38.791	33.541
	Double	98.71	0.010	43.626	32.463	25.7

and

Table 7. Threshold regression results for entire samples.

Variables	(1)	(2)
td ≤ 0.528	0.436 *** (10.740)	—
td > 0.528	0.270 *** (9.380)	—
lnpgdp ≤ 11.042	—	0.183 *** (6.380)
11.042 < lnpgdp ≤ 11.795	—	0.375 *** (12.470)
lnpgdp > 11.795	—	0.713 *** (6.080)
lnopen	−0.001 *** (−6.840)	−0.001 *** (−4.550)
lnfund	0.035 *** (2.220)	0.063 *** (4.380)
lngov	−0.028 *** (−4.770)	−0.012 *** (−4.810)
lntech	0.189 *** (13.660)	0.168 *** (12.730)
lnind	−0.013 (−0.420)	0.027 (0.357)
_cons	0.130 *** (7.110)	0.108 *** (6.080)
R2	0.612	0.662
F statistics	91.13	98.71

Note: The t-statistics for the coefficients are reported in parentheses; *** represent 1% levels.

. The single- and double-threshold F values for economic development both passed the significance test, with estimated values of 11.042 and 11.795, respectively. After logarithmic conversion, the values were calculated to be 68,816.093 yuan and 128,476.517 yuan. The coefficient of tourism development on URI was 0.183 when the first criterion was not met; between the first and second thresholds, it rose to 0.375 (Figure 3). When the second threshold was exceeded, the coefficient kept increasing until it reached 0.713. These findings demonstrate that as the economic development level continues to rise, the promotional impact of tourism development on URI shows a slight tendency to rise.

However, when testing the threshold effect, it was found that the extent of the effect of tourism development on URI was also controlled by the interval. This finding highlights an overlooked aspect in many studies where the core explanatory variable itself acts as a threshold variable. Based on the threshold effect, this study further employs a panel threshold model to examine the nonlinear impact of tourism development on URI. While the double-threshold test failed, the single-threshold test for tourism development had an F value of 91.13, which was statistically significant at the 5% level (Table 6). The estimated single-threshold coefficient was 0.528 (Table 7 and Figure 4). In other words, when tourism development surpassed 0.528, the influence coefficient of tourism development on URI decreased from 0.436 to 0.270, indicating a 38.073% reduction in the positive impact. As a labor-intensive industry, tourism can provide more employment opportunities for residents and contribute to the public infrastructure in urban–rural areas. Additionally, the tourist sector can also improve the YRDR’s industrial structure and lessen its overdependence on primary and secondary industries because it is a service sector with significant industrial costs added. However, there is a risk of the Dutch disease effect and resource curse occurring due to an influx of outside capital and labor into the tourism business when tourism receipts (% of GDP) exceed 52.5% [57]. At this stage, tourism development reaches a threshold, making further developments increasingly challenging and diminishing the gains already achieved. Therefore, the timely development of innovative tourism products is crucial to avoid negative impacts on URI. Additionally, large-scale tourism activities may lead to environmental damage, the overuse of resources, and socio-cultural conflicts. These issues may mitigate the beneficial effects of tourism development on URI.

4.3. Heterogeneity Analysis

4.3.1. Regression Results

Referring to the “Notice on Adjusting the Standard of City Size Division”, issued by the State Council of China, municipalities directly under the central government, provincial capitals, sub-provincial cities, and larger cities are classified as high-grade cities, while other cities are classified as general cities; high-grade cities include Shanghai, Nanjing, Wuxi, Suzhou, Hangzhou, Ningbo, and Hefei. In both types of cities, the impact of tourism development on URI is positive and statistically significant, as shown in columns (1) and (4) of

Table 8. Regression results and threshold regression results for diverse sub-samples.

Variables	General City			High−Grade City
	(1)	(2)	(3)	(4)	(5)
td	0.256 *** 8.68	—	—	1.043 ***	—
				(3.85)
lnopen	−0.001 ***	−0.001 ***	−0.001 ***	−0.001 ***	−0.001 ***
	(−3.59)	−2.92)	(−3.66)	(−3.59)	(−3.33)
lninve	0.058 ***	0.059 ***	0.037 **	−0.160 *	−0.118 ***
	(3.51)	3.86)	(2.25)	(−1.88)	−1.59)
lngov	−0.009 ***	−0.009 ***	−0.010 ***	−0.151 *	−0.116
	(−3.37)	(−3.75)	(−3.93)	(−1.68)	−1.44)
lntech	0.227 ***	0.189 ***	0.214 ***	0.081 *	0.088 ** 2.42)
	(12.43)	(10.61)	(12.07)	(1.98)
lnind	0.001	0.01	0.004	(−0.01	0.071
	(4.38)	(0.31)	(0.01)	(−0.14)	1.09)
lnpgdp ≤ 11.031	—	0.183 ***	—	—	—
		6.23
lnpgdp > 11.031	—	0.358 ***	—	—	—
		11.53
td ≤ 0.528	—	—	0.411 ***	—	—
			10.16
td > 0.528	—	—	0.261 ***	—	—
			9.22
lnpgdp ≤ 11.719	—	—	—	—	0.767 ***
					3.08
lnpgdp > 11.719	—	—	—	—	1.063 ***
					4.41
_cons	0.091	0.094	0.092	0.441	0.347
sigma_u	0.077	0.06	0.074	0.069	0.058
sigma_e	0.038	0.036	0.037	0.042	0.037
R2	0.583	0.6379	0.6162	0.669	0.742
F statistics	77.84	83.82	76.38	21.61	25.98

Note: The t-statistics for the coefficients are reported in parentheses; *, **, and *** represent 10%, 5%, and 1% levels, respectively.

. Specifically, a 1% rise in tourism development contributes to a 0.256% and 1.043% increase in URI for high-grade cities and general-grade cities, respectively. Furthermore, the estimated coefficients of tourism development are higher in high-grade cities compared to general-grade cities. This suggests the need for a further transformation of cities to high-grade cities to improve their economic growth and URD. For general cities, the relatively smaller positive impact of tourism development on URI can be attributed to factors such as a smaller population size, slower economic development, smaller market size, insufficient capital investment, and relatively lower attractiveness. In conclusion, the findings highlight the importance of promoting cities’ transformation into high-grade cities, particularly for enhancing economic development and urban–rural construction. General-grade cities may require additional attention and support to overcome challenges related to their size and economic development.

4.3.2. Threshold Test

There is no threshold effect for tourism development (td) in high-grade cities (

Table 9. Results of threshold effect significance test for diverse sub-samples.

City Type	Threshold Variable	Number	Threshold Value	p-Value	F Value	Threshold Critical
						1%	5%	10%
Ordinary cities	td	Single	0.528	0.080	31.370	57.651	38.509	29.66
	lnpgdp	Single	11.031	0.006	67.070	55.017	37.514	30.916
High-grade cities	lnpgdp	Single	11.719	0.040	18.780	25.505	17.797	14.743

). For general cities, tourism development and economic development’s single-threshold F values both passed the significance test; the threshold values were 0.528 and 11.031, respectively. However, when tourism development is utilized as the threshold variable, as compared to the full sample, the general city’s tourism development has a smaller effect on promoting URI. Specifically, the estimated coefficient of tourism development on URI was 0.411 when the initial threshold of tourism development was not attained. Once it exceeded the first threshold value, the coefficient fell to 0.261. This is most likely due to the inequitable distribution of regional resources in general cities. On the one hand, the gap between urban and rural areas would expand due to slow tourism growth in certain regions and rapid growth in others, and thus tourism’s role in fostering URI would increasingly deteriorate. On the other hand, the excessive development of tourism may cause damage to the local environment, affecting the ecological balance and environmental quality. The promotion effect of tourism development on URI continuously increases as the level of economic development grows, which is consistent with the full-sample threshold results. The growth of tourism can revitalize local rural communities’ economies, raise their economic standing, improve farmers’ quality of life, and increase their capacity for development. For high-grade cities, when the level of economic development was low (lnpgdp ≤ 11.719, where lnpgdp = 11.719 corresponds to an actual per capita GDP of 122,361.82 yuan), the estimated coefficient of tourism development was 0.767. The coefficient of tourism development was 1.063 when the level of economic growth was high (lnpgdp > 11.719), passing the significance test at the 1% level as well. This indicates the significance of the positive impacts of the tourism industry on URI over time.

4.3.3. Effect of Tourism Development on URI at Different Stages

In 2014, the “Opinions on Further Promoting the Reform of the Household Registration System”, introduced by the State Council of China, was a crucial turning point for URI. To minimize distinctions between agricultural and non-agricultural household registrations and combine them under a single-resident household registration, the document recommended the creation of a unified urban–rural household registration system. The policy regarding household registration migration was generally relaxed and expanded, except for in a few major cities and provincial capitals. These adjustments allowed for increased mobility and facilitated the flow of people between urban and rural regions, fostering greater integration.

To examine the effects of tourism development on URI development, the period of 2010–2020 was divided into two phases as per the aforementioned classification. The two phases were set as 2010–2014 and 2015–2020, respectively. The calculated coefficients of tourism development are all positive and statistically significant, as shown in columns (1) to (2) in

Table 10. Effect of tourism development on URI in different periods.

	(1)	(2)
	2010–2014	2015–2020
td	0.330 ** (8.87)	0.104 ** (2.10)
lnopen	−0.001 ** (−2.49)	−0.0006 *** (−3.82)
lninve	0.079 *** (5.73)	−0.020 (−0.88)
lngov	−0.003 (−1.88)	−0.022 *** (−3.93)
lntech	0.169 *** (6.15)	0.135 *** (6.87)
lnind	0.020 (0.76)	0.035 (0.76)
cons	0.057 *** (3.22)	0.261 *** (8.10)
sigma_u	0.094	0.069
sigma_e	0.017	0.035
R−squared	0.614	0.495
Model	FE	FE

Note: The t-statistics for the coefficients are reported in parentheses; **, and *** represent 5%, and 1% levels, respectively.

, suggesting that the tourism sector exerts a positive effect on URI over the course of the two sub-periods. In particular, a 1% increase in tourism development is linked to increases in the URI of the two sub-periods of 0.330% and 0.104%. The growing impact of tourism development suggests that governments at all levels in the YRDR are paying greater attention to the development of tourism infrastructure, road networks, landscape construction, and promotion in the context of URI. This emphasis supports the URI objectives and emphasizes the importance of tourism in forging stronger linkages between urban and rural communities.

4.3.4. Robustness Tests

By using the ratio of tourists to the entire population as the independent variable in place of the percentage of tourism revenue in GDP, we conducted robustness checks to confirm the validity of our findings. The system GMM (Generalized Method of Moments) can address endogeneity issues, control fixed effects and the heterogeneity of panel data, and solve these endpoint issues by introducing appropriate instrumental variables to avoid bias in estimates [58]. Furthermore, this study uses the system GMM for robustness checks, as presented in

Table 11. Regression results and robustness test results.

Variable	FE		System GMM
	(1)	(2)	(3)
L. lnurd	—	—	0.826 *** (25.22)
lntist	0.001 *** (8.11)	—	—
td	—	0.368 *** (12.79)	0.100 ** (2.67)
lnopen	−0.0008 (−6.16)	−0.0009 *** (−7.67)	0.001 *** (3.00)
lninve	0.091 *** (5.82)	0.047 *** (3.09)	0.013 (0.42)
lngov	−0.009 *** (−3.44)	−0.002 (−0.89)	−0.138 *** (−2.29)
lntech	1.902 *** (13.02)	0.130 *** (5.90)	0.138 *** (3.42)
lnind	−0.011 (−0.34)	−0.003 (−0.12)	0.477 *** (6.61)
_cons	0.129 *** (6.61)	0.121 *** (6.84)	—
sigma_u	0.080	0.114	—
sigma_e	0.040	0.034	—
R2	0.566	0.565	—
AR(1)	—	—	0.016
AR(2)	—	—	0.696
Hansen	—	—	0.594

Note: The t-statistics for the coefficients are reported in parentheses; **, and *** represent 5%, and 1% levels, respectively.

. The results indicate that tourism development can promote URI, which is consistent with the findings from Table 11. The coefficient of tourism development on URI is 0.001, which is positive and statistically significant at the level of 1%. Due to the anomalous data caused by the outbreak of the COVID-19 pandemic, we used the panel data of 2010–2019 to analyze the regression results. The results remained consistent with those in Table 5, further affirming the robustness of our findings. Additionally, the system GMM results demonstrate that tourism development can promote URI, as indicated in column (3), and is statistically significant at the 1% level. The AR test findings support the hypothesis that first-order series are correlated and second-order series are not correlated, aligning with the established conclusion. The validity of the instrumental variable selection is demonstrated by the Hansen test’s p-values, which are all more than 0.100, demonstrating consistency with the established results. Consequently, we can certainly state that the outcomes shown in Table 11 are reliable.

5. Discussion

The tourism industry is transforming, moving from a resource-centric approach to one that emphasizes coordinated and integrated development [3]. Specifically, the objective of tourism development extends beyond the mere expansion of the industry’s scale, focusing on accelerating the process of URI. However, empirical research on the specific effect of tourism development on URI remains limited. Given this practical background and theoretical gap, it is essential to explore the correlation between tourism development and URI. To investigate whether tourism development can support URI, a panel regression model was used with case studies of 41 cities from the YRDR.

Through empirical analysis, this research provides evidence that tourism development can promote the process of URI. An increasing amount of research has shown that improving the efficiency of how tourism components are distributed can help urban–rural development, create employment opportunities, and promote economic and cultural exchanges between urban and rural regions [59,60]. Therefore, it is crucial to recognize that tourism development has emerged as one of the main forces in URI.

The diversity of cities in the YRDR benefits from the growth of tourism in terms of boosting URI. However, the magnitude of this effect is stronger in high-grade cities such as Shanghai, Ningbo, Nanjing, and Suzhou. These high-grade cities possess more resources and advantages, which provide better support and opportunities for tourism development, thus enhancing the impact of tourism on URI. This result is constant with Zhu et al.’s research [61]. Furthermore, the benefits of tourism growth in high-grade cities are greater than those in ordinary cities, mainly because high-grade cities tend to prioritize rural tourism products in the context of URI [62]. Over time, the tourism industry’s contribution to the promotion of URI has grown in the YRDR, as urban and rural regions leverage tourism development to share resources and complement each other’s strengths [63].

This study makes the following contributions to the literature: Firstly, it is among the pioneering studies that are empirically examining the impact of tourism development on URI. By providing empirical evidence, this study is helping to develop the body of research that highlights the positive correlation between the tourism industry and URI. Tourism development can promote urban–rural integration mainly by promoting economic development, providing employment opportunities, optimizing the use of resources, and achieving cultural exchange [34]. Secondly, this study emphasizes the significance of urban agglomerations as special tourist destinations. It recognizes that tourism not only promotes URI within individual cities, but also strengthens cooperation among different cities within an urban agglomeration. By considering the threshold effect, this research sheds new light on how to facilitate the process of URI in urban agglomerations through collaborative tourism development. Tourism development can accelerate the process of urban–rural integration by strengthening regional cooperation and coordinated development. Thirdly, this study contributes to theoretical perspectives by establishing a dataset and model framework that can advance our understanding of the topic. Although the information is unique to the YRDR, the analytical framework and methodology employed in this study can be generalized and applied to other urban agglomerations worldwide, offering valuable insights for further research.

6. Conclusions

To examine the effect of tourism development on URI, we used panel data from 41 cities in the YRDR of China from 2010 to 2020. We found that tourism development has positive effects on URI in the YRDR. There are great variations in the effect of tourism development on URI across specific stages and types of cities. The influence of tourism development becomes weaker over time in the YRDR. Moreover, high-grade cities receive a larger beneficial impact from tourism development than ordinary cities. Tourism development tends to contribute to URI more when tourism receipts are below the threshold of 52.8% of the GDP. The results seem to suggest that cities that benefit more from tourism do so at the higher end than at the upper end of their GDP per capita growth distribution. Along with economic development increases, its impact continues to grow. For high-grade cities and ordinary cities, there is a threshold effect on the proportion of tourism revenue to the GDP. However, under the threshold of tourism development, for high-grade cities, tourism development has no significant effect on URI. For ordinary cities, the estimated coefficient of tourism on URI decreases when tourism development exceeds the first threshold values.

Furthermore, several implications can be drawn for authorities and enterprises involved in URI. Firstly, cities located in the YRDR should prioritize capital investment in rural tourism and incorporate tourism urbanization into the infrastructure construction of both urban and rural regions. Secondly, the agricultural industry chain can be expanded by utilizing underutilized land resources and encouraging the construction of infrastructure to support the six tourism-related aspects of “food, lodging, transportation, attractions, shopping, and entertainment”, which aim to promote the fusion of agriculture and tourism. Thirdly, the mechanism of URI should be formed by the flow of logistics, human resources, information, and capital between urban and rural regions to achieve a provincial coordinated and equitable allocation of resources in the YRDR. To be more specific, Shanghai should make the most of its advantages in economic growth and tourism resources to take the lead in promoting URI in other cities. Small cities such as Zhoushan, Huangshan, Wuhu, and Shaoxing should continue consolidating their important roles in tourism development and implement comprehensive marketing strategies.