Research on the Development Potential of China’s Pro-Poor Tourism Industry Based on Geographical Nature Evaluation

Abstract

China has made considerable achievements in poverty alleviation and reduction, and pro-poor tourism is an important part of its poverty alleviation policy. To prevent policy investments from idling and becoming wasted, and to prevent poverty from returning to previously poverty-stricken areas, it is helpful to improve the continuity and adaptability of pro-poor tourism policies by assessing differentiated geographical capital. This study is based on the fundamentals of geographical nature: it divides geographical capital into resource endowments, market location, and spatial accessibility; tests the state of the three types of geographical capital by introducing Newton’s basic space gravity model; and comprehensively evaluates the tourism industry’s potential to develop. In addition, it uses data on China’s 560 pro-poor tourism villages for empirical research, and concludes that most of the pro-poor tourism villages show some potential for tourism development along with distinctive features of regional concentration. However, they are also restricted by many factors and require prolonged exploration and cultivation. China’s pro-poor tourism villages are mainly divided into three types: market, resource, and location advantage. The market advantage type should foster tourism product cultivation on the basis of market needs, deepen tourism product innovation, integrate with the industry chain of surrounding pro-poor villages, and form a regional clustering force. The resource advantage type should value market fragmentation and positioning, match the market positioning of surrounding tourism cities, utilize the marketing of surrounding tourism cities, and improve its own market popularity and reputation. The location advantage type may position itself as a tourism industry hub, and serve the surrounding scenic spots in order to achieve its own industry value. This study mainly analyzes and evaluates the development potential of the tourism poverty alleviation industry on the basis of geographical capital, and does this with the aim of improving the applicability of the tourism poverty alleviation industry’s pro-poor development strategy.

1. Introduction

Poverty elimination is “humanity’s common mission” and a crucial task facing developing countries [1]. Tourism has considerable effects on the social and economic development of poverty-stricken areas and increases the employment rate and income among impoverished populations; it has, therefore, become an important area for many countries and regions who aim to eliminate poverty and improve people’s livelihoods [2]. The effects of pro-poor tourism on poverty alleviation have been extensively validated and recognized. All countries promote the development of the pro-poor tourism industry and explore the coordination and integration of tourism development and poverty alleviation policies, and this has produced positive and effective achievements.

Over the past 40 years, since reform and ‘opening up’, more than 800 million Chinese people have lifted themselves out of poverty, accounting for over 70 percent of global poverty reduction. In 2020, China achieved the poverty reduction objective set out in the United Nations’ Sustainable Development Agenda 2030, a decade ahead of the projected deadline. China’s achievements in eliminating poverty have attracted global attention, and the country’s experience with poverty reduction has inspired serious discussions around the world [3]. Pro-poor tourism policy is a core part of China’s poverty alleviation strategy. The tourism industry has allowed for the elimination of poverty for over 10 percent of the population, and over 10 million people have lifted themselves out of poverty by working in tourism. Promoting pro-poor tourism resulted in a key breakthrough in China’s “poverty alleviation battle”, and is a main route for targeted poverty alleviation. Furthermore, it has significantly improved the effect of China’s poverty reduction policy [4]. As a country with extensive regional differences, China has identified 14 key development regions that require poverty alleviation, and has promoted poverty alleviation in accordance with their distinctive features [5,6].

Poverty problem and poverty alleviation research is cross-field, multidisciplinary, and comprehensive, and concerns major issues which should be solved by—all countries and regions in the world [7]. Both the emergence of poverty and the implementation of poverty alleviation policies are largely affected by geographical structure [8]. Such geographical structures are reflections of the nature of regional geography. To fundamentally analyze the causes of poverty and establish a basis for the implementation of poverty alleviation policies, it is necessary to analyze the geographical nature of this decisive structure. Compared with other industries, the tourism industry is more affected by climate conditions, living environment, cultural characteristics, location conditions, and other factors [5,9]. These factors, as the constituent elements of geographical nature, usually have obvious spatial characteristics. Therefore, the formulation and implementation of poverty alleviation policies led by the tourism industry need to be based on scientific evaluation and analysis of cognitive regional geographical nature [10]. Before formulating tourism poverty alleviation policies and entering the tourism industry development model, it is necessary to judge and recognize the differentiated geospatial capital, effectively improve the adaptability of tourism poverty alleviation policies, and ensure the sustainability of their policy-implementation effects [11].

Spatial poverty-concentration analysis found that a lack of/insufficient geographic capital causes spatial poverty traps and affects the implementation of poverty alleviation strategies [12,13]. Related studies of spatial poverty have mainly focused on three aspects. ① The first is the evaluation of geographic capital in poverty-stricken areas. Geographic capital research into spatial poverty seeks to endow economic, social, and spatial structural indicators with spatial geographical location attributes [14,15] and establish an aggregation of material, social, and human capital (this includes location conditions and natural environment conditions) [7,16]. Burke [17] and Bird [18] established an evaluation system that encompasses the economy, environment, and society, and used it to assess spatial poverty. The results show those research areas are disadvantaged in terms of ecological, economic, political, social, and other geographical capital. ② The second is the formation mechanism of concentrated geographical poverty. Studies have determined that spatial poverty traps are measured in accordance with a multidimensional scale that includes economy, environment, geographical location, infrastructure, natural endowment, society, and other geographical capital [19,20,21]. The non-volatility of spatial features at the regional level becomes the key reason for the existence of spatial poverty traps [22,23]. Levernier [24] and Rupasingha [25] found that American regional poverty is affected by changes in the poverty rate of neighboring counties, and identified that regional spatial location, economic development level, industry structure-adjustment features, and other factors result in concentrated poverty at the county level. ③ The third is the optimization of spatial policy for poverty reduction. Studies in this field have evaluated the implementation effects and problems of poverty reduction and anti-poverty policies. Diao et al. [26] found that agricultural policy had the strongest capacity to drive economic growth and poverty reduction in Ethiopia, and they showed that agricultural development is potentially imperative in decreasing poverty rates and increasing growth. Andrew and Shepherd [27] study of poverty alleviation projects found that poverty reduction projects must consider regional features, as the policy objective will otherwise be rendered ineffective. Mohanty and Ram [28] examined the links between poverty reduction and various fertility policies in Indian states. In recognizing the dynamic mechanisms that contribute to spatial poverty, studies have also put forward corresponding policy proposals. Palmer [29] discovered that agricultural growth is a determining factor in India’s rural spatial poverty, and irrigation is the main force contributing to agricultural growth; thus, He proposed that it is necessary to design poverty reduction strategies that target specific spatial elements. Narloch [30] combined geospatial and household data from Vietnam to investigate the relationship between environmental risks and poverty, and identified that land-use planning could be an important strategy to reduce the environmental burden on poor people.

As an effective means of poverty alleviation, poverty alleviation tourism has been widely recognized by the tourism industry, and its poverty alleviation effect has become an important research hotspot in the tourism industry. In the 1950s, the World Bank started focusing on the influence of geographical factors on poverty and the implementation of relevant strategies [31,32]. Poverty alleviation tourism is dominated by government organizations, relying on policy tilt and government support [33], linking stakeholders to guide social residents in poor areas to participate in tourism activities [34,35], introducing tourism to drive socio-economic growth, and creating direct or indirect employment opportunities for residents to reap benefits [36,37]. On the contrary, in the process of research, some scholars have proposed that there are limitations to poverty alleviation tourism, and the continuous expansion of tourism can not effectively improve poverty [38,39] and may even exclude poor residents from tourism industries, resulting in power inequality and marginalization [40,41]. Therefore, the poverty alleviation effect of tourism is complex. The development of tourism can make poor areas get rid of poverty and become rich, but may also make them fall into a poverty trap [42]. ‘Multiplier effects’ and ‘leakage effects’ coexist [43]. The possible reason for this is that the difference between the actual implementation of regional poverty alleviation policies and policy formulation will lead to unfair distribution of benefits [44], resulting in the reduced effectiveness of poverty alleviation [45]. We also found that research on poverty alleviation tourism mainly focuses on two aspects. ➀ The first is constructing the research framework of the relationship between tourism and poverty alleviation. By exploring the internal mechanism and path-dependence of tourism poverty alleviation [46], the measurement model of poverty and tourism is constructed from different levels such as geography and tourism scope [41] (Medina-Munoz et al., 2016); the tourism value chain is introduced [47,48], and power empowerment [49], capacity of resources [50], and other factors enrich the theoretical framework to scientifically analyze the relationship between tourism and poverty alleviation. ② the second is the effectiveness of tourism poverty alleviation. Researchers mainly focus on poverty-stricken areas in developing countries in Asia and Africa. Through case or empirical analysis, it is shown that the level of economic development makes the effectiveness of tourism poverty alleviation have a certain threshold [51]. Tourism models such as voluntary tourism [52], agricultural tourism [53], and creative tourism [54] can inject new development momentum into tourism poverty alleviation, and coordinating the interests of stakeholders such as government–community–enterprise [55,56] can also promote the realization of sustainable development for poverty reduction.

In addition, tourism industry development depends considerably on geographical and natural resources. Development strategies should be established based on the recognition of regional geographic capital to consider the tourism industry as the core driving force of regional poverty reduction. Exploring the spatial layout of poverty-stricken areas with the help of GIS [5] is important for effectively identifying the impact of spatial poverty. Geographical space studies have become an important branch of studies on pro-poor tourism [57]. Some studies have analyzed and measured the influence of the tourism industry’s development on poverty’s spatial patterns. Steven D [58] used geographic-weighted regression to analyze the spatial changes and influences resulting from American rural pro-poor tourism. Liu et al. [59] analyzed the influence of the tourism industry on urban–rural space structure and identified that tourism is favorable for narrowing China’s urban–rural gap and changing poverty’s spatial pattern. Studies have analyzed the different influences of the progressive reduction of spatial distance through the tourism economy on the implementation effect of poverty alleviation policies, using geographical spatial analysis of poverty to analyze the time and spatial features of pro-poor tourism regions [60,61]. Zhu et al. [62] used pro-poor tourism pilot villages as a study case and analyzed the spatial distribution features of villages in which tourism policy was mainly emphasized. Rogerson J M [11] took adventurous tourism as a poverty alleviation development strategy and enabled it to become an advantageous industry, encouraging economic development based on South Africa’s excellent geographical location and unique natural landscape.

In general, the study on the combination of pro-poor tourism and geographic space mainly focuses on the driving effect of tourism industry development on the change in geographic spatial patterns. On the contrary, there are relatively few studies on the influence of geographic capital on pro-poor tourism policy. Most of the relevant studies follow the analysis paradigm of human geographic space, selecting factors such as natural resource endowment, spatial accessibility, and spatial location for analysis. Additionally, these studies judge the development ability of the tourism industry based on the advantages and disadvantages of single-factor- or multiple-factor-weighted comprehensive value. However, the geographical nature of the pro-poor tourism industry should place more emphasis on the study of the structured situation of a space’s geographical elements as well as on local geographical elements’ complementary advantages—fostering strengths and circumventing weaknesses, so as to establish the focus and implementation path of tourism industry poverty alleviation policy, and more effectively guiding the integration of the tourism industry and local natural and social environment, so as to effectively realize the policy effectiveness of poverty alleviation.

To address the research gap in existing studies, this paper conducts an empirical study on the data of 560 poverty alleviation tourism villages in China, and measures the geographical capital value of each poverty alleviation village. We classified poverty alleviation tourism villages based on this value and put forward targeted industrial development policies. The research objectives of this paper are as follows: ① Establishing a theoretical framework of geographical nature. We define the geographical capital depending on the development of the tourism industry in poverty alleviation regions into three dimensions—resource endowment, market development potential, and space accessibility—and we analyze the structural relationship within the system. ② Newton’s basic spatial gravity model is introduced to establish the measurement model of resource endowment, market development potential, and space accessibility. We calculate the geographical capital status of each poverty alleviation village and classify the tourism poverty alleviation villages’ types according to the geographical capital status and distribution characteristics. ③ By analyzing the geographical nature of pro-poor tourism villages, we can understand the advantages of pro-poor tourism industry development, identify the core factors that restrict tourism, and then put forward a pro-poor tourism strategy that is suitable for regional geographical characteristics, so as to improve the applicability and effectiveness of the poverty alleviation strategy. In short, this study establishes a systematic cognition of geographic capital in poverty-stricken areas, and combines regional geographic capital analysis with poverty alleviation strategy formulation, so as to provide support for the formulation of accurate and effective poverty alleviation measures.

2. Geographic Nature Recognition for the Development of the Pro-Poor Tourism Industry

Regional natural geographical elements play a determining and fundamental role in tourism industry development and affect the product features and market structure of the tourism industry. Furthermore, poverty and poverty-reduction governance also depend considerably on natural geographical structures [63]. It is, therefore, only the recognition of natural geographical structures that can enable radical interpretations of the factors that cause poverty and explorations and establish effective routes for poverty elimination.

The natural geographical structure is a reflection of the geographical nature of the region. Krugman, the representative of new economic geography, put forward geographical nature theory [64]: Firstly, natural endowment is the resource condition that determines the basic productive forces as well as the basis for the survival and development of human society. Secondly is market value, which affects the ability of resource value transformation and interaction and determines the agglomeration choice of population and capital. On the basis of Krugman’s dualistic geographical nature theory, follow-up researchers put forward a third factor, which corresponds to the third industrial revolution—the information revolution—with the conditions of scientific and technological facilities and human resources [65]. Researchers extracted the characteristics of the three geographical natures and analyzed their evolution. Then, based on the main ideas of modeling to construct the three geographical nature of region evolution mode, the model of regional evolution under the three geographical natures was constructed. It was found that the first geographical nature dominated the spatial distribution of population in agricultural society, the second geographical nature guided economic and population spatial distribution from decentralization to agglomeration, and the third geographical nature began to guide new agglomeration characterized by “Planar Development”. Nowadays, according to geographical nature theory, researchers refer to the structural evaluation of geographical resources [66,67], analyze the characteristics of regional geographic spatial differentiation, and trace the root causes of regional economic or social differences.

In drawing on Krugman’s understanding of geographic nature as a two-element construct, this study considers the pro-poor tourism industry’s features, analyzes and sorts out the geographical features of poverty alleviation villages, and constructs a framework system that can be used to evaluate the tourism industry development potential of poverty alleviation villages. We divide geographic nature into three basic dimensions (Figure 1).

① The first is resource endowment. The tourism industry strongly depends on natural resource endowment. Basic tourism resources, geographic conditions, and climate conditions are fundamental conditions that affect the development of the tourism industry and determine the features and direction of its survival and development. ② The second is market location. Market location determines the achievement capability of the tourism industry’s economic benefits. In addition, most of the efforts to promote tourism industry development through poverty alleviation villages have just started and are at the stage of industry cultivation and market development, and accordingly, no stable and effective market spatial structure has been formed. The market’s natural location, therefore, highlights the basic potential and spatial structure of the poverty alleviation villages’ market region. ③ the third is accessibility, which reflects the capability of tourists to access locations and promote visits by using modern technology. Most poverty alleviation villages border economic development regions and geographically remote areas. Accessibility is, therefore, a key problem that restricts the development of the tourism industry and limits its development potential.

In referring to analyses of the geographic nature of pro-poor tourism villages, this study highlights the advantages of tourism industry development, recognizes the core factors that restrict the tourism industry, evaluates the tourism industry development potential of poverty alleviation villages, and proposes effective strategies and measures that can be used to promote tourism industry development through poverty alleviation villages that improve poverty alleviation and reduction efforts.

3. Research Method and Data Source

3.1. Evaluation Model for Tourism Industry Development Potential Based on the Three Elements of Geographic Nature

Based on the recognition of natural geographic elements that affect poverty alleviation through tourism industry development, we comprehensively research the three proposed elements of geographic nature and construct an evaluation model to determine the development potential of pro-poor tourism. This study is based on Newton’s basic space gravity model [8,68], and decomposes this model into three dimensions, which match the three spatial geographic nature elements. The three parts are resource endowment, market location, and accessibility. Considering the tourism industry’s characteristics, this study made some changes in the variables and parameters under the precondition of maintaining the construct of the basic spatial gravity model (Figure 2). The three types of basic dimensions are as follows:

$$T_{jk}=K{A}_j{M}_j^{n}exp(-\beta {\gamma }_j),$$

(1)

where $T_{jk}$ is the comprehensive development potential of the poverty alleviation Village j; $A_j$ is the tourism resource endowment of the poverty alleviation Village j, which reflects the development potential of tourism resources and the tourism product supply level of the poverty alleviation villages; $M_j^n$ is the development potential at Market n of the poverty alleviation village j; ${\gamma }_j$ is the spatial accessibility of the poverty alleviation village j; $\beta$ is the spatial damping coefficient and the defined decay speed of spatial interaction; and $\beta$ is the non-negative spatial damping coefficient. As in previous studies, $\beta$ was set to 0.0046 [69], and K was the normalizing factor.

(1) Evaluation method to determine tourism resource endowment

Tourism resource development in pro-poor tourism villages in China has just begun. Tourism resource endowments have mainly highlighted the potential for tourism resource development in poverty alleviation villages and analyzed the tourism resource endowment and development potentials in different regions. This study mainly evaluated what attracted resource endowments using two steps:

Step 1: Evaluate basic tourism resource endowments. This study used tourism resource endowment as the basic evaluation index system (

Table 1. Evaluation Index System for Basic Tourism Resource Endowment.

Level I Indicator	Specific Indicator	Calculation Method	Data Source
Location Condition	Shortest distance to the town	Calculate the shortest distance from the village to the county	Obtain the county location from the national basic geographical data set and calculate the distance
	Shortest distance to the scenic spot	Calculate the shortest distance from the village to tourist scenic spots above 3A level	Obtain the coordinates of national 3A, 4A, and 5A scenic spots through AMAP POI
Resource Endowment	Surrounding tourism resource	Calculate the weight index of the scenic spots within 5 km of the village	Obtain national important tourism resource data through AMAP POI and provide weighted calculations per grade of the scenic spot: 10 points for 5A scenic spots, 8 points for 4A scenic spots, 6 points for 3A scenic spots, and 2 points for other scenic spots
	Vegetation abundance	Calculate the normalizing vegetation index	Obtain the normalizing vegetation index through the resources and environment platform of the Chinese Academy of Sciences
	Water resource abundance	Calculate the weighted average value of the distance to rivers	Analyze and calculate distance based on national basic geographic data and weighted calculations per river grade

), which was divided into two dimensions: location condition and resource state. The entropy-weight method was used to calculate the information entropy for each indicator to weigh each index and measure the basic value of the tourism resource endowment of each poverty alleviation village.

Step 2: Adjust the tourism resource endowment values. The first form of adjustment was based on climate factors. Climate has a strong effect on the tourist industry, and restricts trends in tourism industry development in poverty alleviation villages. This study adopted the year-round appropriate tourist visit days of the poverty alleviation villages’ regions as the evaluation indicator [70,71] and adopted climate factors to revise the tourism resource endowment of the poverty alleviation villages. The second form of adjustment was based on terrain factors. Most of the poverty alleviation villages are located in remote areas with harsh environments, so the terrain factors considerably limit the development of the tourism industry and have irregular and unpredictable influences on tourism resource endowment [72,73]. For example, regions with high altitudes and rough terrain may cultivate excellent mountain tourism resources, while regions with low altitudes and flat surfaces may cultivate good wetland tourism resources. However, such influences are hard to reflect in the grade distribution of tourism resources. Therefore, this study adopted terrain factors to assess the tourism resource endowments of poverty alleviation villages with a specific formula, as follows:

$$A_j=A_j^{\prime }\times {(W_j)}_{std}\times (1+L_j)$$

(2)

$$L_j=\{\begin{array}{l}0.2\begin{array}{c}\end{array}\begin{array}{cc}\begin{array}{cc}& \begin{array}{cc}{(S_j)}_{std}+& {(H_j)}_{std}>0.6\end{array}\end{array}& \end{array}\\ 0\begin{array}{cc}\begin{array}{c}\end{array}Others& \end{array}\end{array}$$

(3)

where $A_j$ is the tourism resource endowment of poverty alleviation village j; $A_j^{\prime }$ is the basic resource endowment of poverty alleviation village j; $W_j$ is the climate adjustment coefficient; $L_j$ is the terrain adjustment coefficient; and $W_j$ adopts the year-round appropriate tourist visit days of poverty alleviation villages’ regions as the evaluation indicator. The subscript std indicates the standard value. The terrain adjustment coefficient ($L_j$) is calculated by the adopted elevation ($H_j$) and slope ($S_j$) as the evaluation indicators (Formula (3)).

(2) Evaluation method for market development potential

The tourism industry of poverty alleviation villages has not formed a stable and effective market spatial structure, so the market development potential assessments focused on evaluating ideal market potential and analyzing hierarchical structures determining the market potential of the poverty alleviation villages.

In this regard, this method takes the pro-poor tourism villages as the core and divides the market potential into three circles based on the distance from the tourist market to the poverty alleviation village. Furthermore, it divides the three-market circle structure into half-day tours (40 km), 1-day tours (80 km), and 2-day tours (160 km) [74,75]. The evaluation indicators for the market circle potential were the per capita gross domestic product (GDP) and the total population. The specific formula is as follows:

$$M_j^n={(P_j^n{C}_j^n)}^{\alpha },$$

(4)

where the three market circles are marked as Circle 1, Circle 2, and Circle 3, respectively, and Circle 1 is a half-day tour, Circle 2 is a 1-day tour (80 km), and Circle 3 is a 2-day tour (160 km); $P_j^n$ is the population of the potential market circle n and reflects the population base of the target market circle; $C_j^n$ is the per capita GDP of potential market circle n and reflects the economic foundation of the target market; and $\alpha$ is the travel probability parameter, which reflects the capability of the potential market to generate travel needs. In a previous study, the parameter was set to 0.64 [69], and the value of n was 1, 2, and 3.

Additionally, weighted aggregation was used to determine the market potential of the three circles and to calculate the comprehensive market development potential value of pro-poor tourism villages. The specific calculation formula is as follows:

$$T{M}_j^{}={\lambda }_1\times M_j^1+{\lambda }_2{M}_j^2+{\lambda }_3\times M_j^3,$$

(5)

where $T{M}_j^{}$ is the comprehensive market development potential of pro-poor tourism village j, $M_j^1$ is the development potential of the pro-poor tourism village at Circle 1, $M_j^2$ is the development potential of the pro-poor tourism village at Circle 2, and $M_j^3$ is the development potential of the pro-poor tourism village at Circle 3. The weight coefficient of each market circle was defined as the rate of average outlays per tourist per day for different market types. The value of the average outlays per tourist per day was based on the China Tourism Statistics. The weight coefficient ${\lambda }_2$ of the 1-day tour was 1, the weight coefficient ${\lambda }_1$ of the half-day tour was 0.5, and the weight coefficient ${\lambda }_3$ of the 2-day tour was 3.4.

(3) Evaluation method for accessibility

Accessibility was used to test the time spent reaching a poverty alleviation village from any point in the region (point i is the center point of each grid in the vector map). It indicates the convenience of reaching the poverty alleviation village from anywhere within the region, and is favorable for clarifying the relationship between the poverty alleviation village and the location of the traffic network. The region’s accessibility based on the traffic network was calculated. The cost distance method was used to calculate the accessibility from each scenic spot in the region to the poverty alleviation village. The calculation progress is as follows [76,77]: a 1 km × 1 km grid was used to rasterize the original vector map, and the different speeds of various road types according to the driving speeds of different road networks based on national laws were set. Subsequently, the speed intervals for accessibility of different land utilization types were set based on China’s land utilization classification data (

Table 2. Speed Calculation Based on Accessibility Distance; Cost–Distance, km/h.

Linear Road Type	High Railway	Normal Railway	Expressway	National Road	Provincial Road	County Road	Town Road
Speed	250	120	100	80	60	40	30
Land Utilization Type	Cultivated land	Woodland	Grassland	Water area	Construction land	Unused land
Speed	5	3	4	1	10	3

).

Based on the above driving speeds according to different road types, the travel time along a given road network in a target region was calculated, and the grid was endowed with the corresponding time–cost value. Subsequently, the shortest weighted distance versus cost for the cost raster of the road network was analyzed, and the accessibility value from each scenic spot in the region to the poverty alleviation village was calculated [78]. The larger the value of weighted distance, the lower the value of accessibility and vice versa. Furthermore, the average value of poverty alleviation village accessibility was calculated for all the specified regions’ grids to reflect the accessibility of each village. The specific formulas are as follows:

$$A_i=\min (M_j{T}_{ij})$$

(6)

$$S_j={\displaystyle \sum _{i=1}^n\frac{A_i}{n_j}},$$

(7)

where point i is the center point of each grid in the vector map; j is the number of the poverty village; T_ij is the travel time from any point i to the poverty alleviation village j via the shortest route along the current traffic network; M_j is the weight; Ai is the accessibility from point i to village j; S_j is the accessibility of the poverty alleviation village j; and n is the total number of grids. The smaller the value of S_j, the more convenient it is to access the villages from any point.

3.2. Data Source

The data on national pro-poor tourism pilot villages were collected from the websites for the State Council Leading Group Office of Poverty Alleviation and Development (www.cpad.gov.cn, 15 July 2021)) and the original China National Tourism Administration (www.cnta.gov.cn, 15 July 2021). In 2015, the State Council Leading Group Office of Poverty Alleviation and Development and the original China National Tourism Administration jointly selected 560 national pro-poor tourism villages from all provinces. These villages are the experimental fields for China’s pro-poor tourism work and the barometer to determine the effects of the poverty alleviation strategy through the tourism industry. This study used these villages as the study samples.

The research team employed geographic coding according to villages’ names through an internet map (map.baidu.com, 15 July 2021), obtained the coordinates of the administrative villages, placed them into the fundamental geographical database after coordinate correction, and adopted Asia Lambert Conformal Conic for projection. Scenic spot data came from the official website for the Ministry of Culture and Tourism of the People’s Republic of China. The POI of the key villages of the poverty alleviation tourism project and important surrounding scenic spots were obtained using the Baidu coordinate-picking system, and the Internet data coordinates were corrected using GeoSharp software. The administrative regions, water bodies, river networks, and road data were mainly from the China National Fundamental Geographic Information Database. The latest vector data provided by Google Maps were also considered. The slope and elevation data came from the grid’s remote sensor data at 30 m, as provided by the National Administration of Surveying, Mapping, and Geo-information. The traffic network data were based on the land traffic network data at the end of 2016, and the rural road data were based on the Baidu Map, which was used to generate traffic data at all levels including high-speed rail, rail, expressway, and national, provincial, county, and rural roads (Figure 2). The data on China’s different administrative regions and government locations came from the National Earth System Science Data. The majority of the data quantification was done using the QGIS software platform.

4. Research Results

4.1. Research Results for Tourism Resource Endowment

Using Formulas (2) and (3), the resource endowment values of pro-poor tourism villages were calculated; the results are shown in

Table 3. Resource Endowment Value.

	Location Condition	Resource Condition	Basic Resource Endowment	Comprehensive Resource Endowment
Mean Value	25.91	10.22	39.68	14.98
Num	559.00	559.00	559.00	559.00
Min	7.31	2.08	23.81	11.04
Max	28.34	28.67	65.97	32.60
Range	21.04	26.59	42.16	21.56
Standard Deviation	2.24	2.30	8.07	5.25
Coefficient of Variation	8.63%	22.48%	20.33%	35.06%

and Figure 3 and Figure 4. From the basic tourism resource endowment values, these villages were divided into five types using the natural fractionation method, with the five types accounting for 10.02%, 32.02%, 24.33%, 17.89%, and 15.74%, respectively. The results showed that the fundamental tourism resources of pro-poor tourism villages are mostly poor, and the fundamental resource development level of 71.37% of the villages is below average. With adjustments based on terrain and climate factors, the basic resource endowment values showed a significant rise (accounting for 9.66%, 19.86%, 32.56%, 24.37%, and 13.55%, respectively), and the ratio of samples reaching Levels 4 and 5 increased by 9.29%. Therefore, the tourism resources of pro-poor tourism villages show excellent development potential and can be optimized and significantly increased in subsequent resource development.

The basic resource endowment value of China’s pro-poor tourism villages showed a significant geographical clustering effect (Figure 3). The regions with relatively good tourism fundamental endowment values were mainly concentrated in the regions between the Yellow and Yangtze River basins and spatially concentrated in the Shandong, Shaanxi, and Shanxi provinces. The adjusted resource endowment values have significantly changed and have been significantly raised in the southwest mountainous areas and southeast coastal areas, where they have shown relatively good resource development potential. Taking the Hu Huanyong line [79] as the dividing line, the tourism resource endowment of poverty alleviation villages in the west and north is relatively poor, which also indicates the difficulty of development (Figure 4).

4.2. Research Results of Market Development Potential

Formulas (4) and (5) were used to calculate the comprehensive market development potential values of the pro-poor tourism villages, and the specific test results are shown in the comprehensive market index in Figure 5.

The comprehensive market development potential of China’s pro-poor tourism villages has three features. First, the comprehensive market development potential index of pro-poor tourism villages is generally low. There are relatively few pro-poor tourism villages with market superiority—they only account for about 9 percent of the total, and are mainly distributed in the Guangdong, Shandong, and Zhejiang provinces, predominantly in eastern coastal areas. Second, the comprehensive market development values of poverty alleviation villages in Central China are average, and the market development potential of poverty alleviation villages at the common boundary of provinces is relatively good. Third, pro-poor tourism villages in the region to the west of the Hu Huanyong line have relatively low market development potential.

The market structure type in Figure 5 indicates the market circle structure of each poverty alleviation village. The specific type analysis of sample points is as follows: First, the average value (${\overline{\mathrm{m}}}_{\mathrm{n}}$, is 1, 2, 3) and variance (${\delta }_{\mathrm{n}}$, n is 1, 2, 3) of the index of the three market circles of each sample village were respectively calculated; if each market circle’s index was higher than ${\overline{\mathrm{m}}}_{\mathrm{n}}+{\delta }_{\mathrm{n}}$, the market circle was regarded as playing a powerful role and was marked as 1; if the value of the market circle’s index was between ${\overline{\mathrm{m}}}_{\mathrm{n}}+{\delta }_{\mathrm{n}}$ and ${\overline{\mathrm{m}}}_{\mathrm{n}}-{\delta }_{\mathrm{n}}$, then the market circle was regarded as playing a medium role; if each market circle’s index was lower than ${\overline{\mathrm{m}}}_{\mathrm{n}}-{\delta }_{\mathrm{n}}$, the market circle was regarded as playing a weak role and was marked as 0. Second, on the basis of these calculations, the three-market circle indices of each sample village were classified and combined. The various types of villages were marked with different colors on the map (Figure 5).

China’s pro-poor tourism market circle structure has three features. First, the pro-poor tourism villages with relatively poor development potential across all three market circles account for a considerable proportion (56.71 percent), and regions to the west of the Hu Huanyong line account for 32 percent. Second, pro-poor tourism villages with relatively good development potential in all three market circles account for 25 percent and are mainly concentrated in the Guangdong, Shandong, and Zhejiang provinces. Third, the development potential of medium- and long-distance markets is better than that of short-distance markets. The development potential of long-distance markets in 70 percent of poverty alleviation villages is superior to short-distance markets. The poverty alleviation market should further value the development of medium- and long-distance markets, effectively raise the industry’s added value, and construct the tourism market framework in accordance with long-to-short-distance markets.

4.3. Research Results for Accessibility

Formulas (6) and (7) were used to calculate the accessibility values of the pro-poor tourism villages, and the specific results are shown in Figure 6. The calculation results for accessibility indicated that the accessibility of China’s pro-poor tourism villages has a relatively strong regional difference (Figure 6). First, villages with accessibility values between 0–1 h and 1–2 h account for 7.74 percent and 18.67% of all villages, respectively. These areas, mainly in the eastern region, have a relatively complete road network infrastructure, especially around the main traffic lines with high-speed rail. Second, villages with accessibility values between 2–4 h and 4–12 h account for 23.40 percent and 26.66 percent, respectively, and are mainly distributed throughout China’s middle area. Villages with accessibility values over 12 h account for 23.53 percent, and are mainly distributed in the northern regions and west of the Hu Huanyong line.

4.4. Research Results for Comprehensive Development Potential

Using Formula (1), the tourism resource endowment value, market development potential value, and accessibility value were comprehensively calculated, and the comprehensive development potential value of the pro-poor tourism villages was calculated (the research results are shown in Figure 7). The distribution of the development potential of China’s pro-poor tourism villages has the following distinctive regional features:

First, there are few poverty alleviation villages with relatively high development potential (red points) across all three market circles. These villages are mainly distributed in the Shandong, Guangdong, and Zhejiang provinces and the regions at the common boundary of the Shaanxi and Shanxi provinces along the Yellow River.

Second, pro-poor tourism villages located at the boundary of the junction between Central and Western China also show relatively good development potential (yellow points). Within this region, the development potential of the first-circle market of the pro-poor tourism villages is higher than the development potential of the second and third market circles, indicating that such poverty alleviation villages should depend on local tourism markets to cultivate short-distance tourism markets.

Third, the regions to the west and north of the Hu Huanyong line show relatively low development potential (green and blue points). Deserving of attention is the development potential of long-distance markets, which is higher than that of short-distance markets. Therefore, such poverty alleviation villages should bolster medium- and long-distance markets with more economic value, cultivate accommodation, catering, and other tourism products, and attract more overnight tourists.

4.5. Summary

The development potential of China’s pro-poor tourism villages has distinctive regional differences and relative geographical concentrations. Specifically, it has the following features: First, the pro-poor tourism villages in Shandong province, on the edge of Shanxi province, and at the common boundary between the Guangdong and Fujian provinces show excellent development potential and a relatively good development foundation in terms of resource endowment, market development potential, and accessibility. As such, they can effectively support the development of the tourism industry. Second, the pro-poor tourism villages in the mountainous areas of Central China have relatively good tourism endowment cultivation potential. However, the region’s market development potential and accessibility are relatively poor. Third, in the regions to the west and north of the Hu Huanyong line, the development potential of pro-poor tourism villages is pending urgent improvement, and it takes a relatively long time to construct and improve the tourism development foundation. Meanwhile, the market development potential of the pro-poor tourism villages mainly lies in the medium- and long-distance markets. Therefore, such pro-poor tourism villages should emphasize attracting more overnight tourists and achieving greater tourism market value.

5. Development Strategy for China’s Pro-Poor Tourism Villages

5.1. Strategic Model

The state of the geographical nature of capital determines the development potential of the tourism industry, and affects development prospects and modes as well. This study divides the natural geographical elements into comprehensive resource endowment, market development potential, and accessibility, and proposes strategies; it then provides recommendations for tourism industry development through poverty alleviation villages that draw on various combinations of the three dimensions (Figure 8).

Two development types on the upper-right and lower-left corners of Figure 8 are marked; #S1 is excellent comprehensive development potential, while #S6 is relatively weak development potential. The #S1 type is superior in terms of comprehensive endowment, market development potential, and accessibility, and also shows excellent tourism industry development potential. Tourism can become the core route for the area to eliminate poverty and prosper, and can also bolster the pillar-oriented industry of the regional economic system. The indicator values for the three dimensions of the #S6 type are relatively poor, meaning its tourism development is seriously restricted and requires a prolonged period to explore and cultivate tourism; accordingly, the tourism industry should be regarded as an auxiliary industry and not be taken as the core driving force for boosting the region’s economy.

The two development types on the upper-left and lower-right corners of Figure 8 are, respectively, based on resource cultivation (#S2 and #S3) and market development (#S4 and #S5).

First, the pro-poor tourism villages of the resource cultivation development route (#S2 and #S3) have relatively good market extraction potential and can effectively market tourism resources. Market advantages become important pillars for the development of the tourism industry in poverty alleviation villages of this kind. These villages should take the recognition of market needs as the cutting point, lead tourism resource cultivation based on demand, and promote the exertion of market advantages. However, they are also confronted by the problem of relatively weak accessibility, which further restricts the capability of market advantage conversion. In the resource cultivation process, it is necessary to promote an innovative resource development model, enhance infrastructure construction, weaken tourists’ perceptions of distance with novel tourism products, and promote the capability of market advantage conversion.

Second, pro-poor tourism villages of the market development route (#S4 and #S5) have relatively good resource endowment, which lays the foundation for industry development. Owing to the lack of market development conditions, resource advantages are hard to convert effectively. Pro-poor tourism villages should, therefore, place their development focus on enhancing market management and improving the popularity and reputation of poverty alleviation villages. Similarly, if these villages also face the problem of poor accessibility, pro-poor tourism should avoid prioritizing nearby development, engage in market fragmentation and positioning, recognize target markets with better value, prioritize the development of overnight and holiday tour markets, and optimize their resource conversion route.

5.2. Analysis of Specific Strategies

This study engaged in specific strategy analysis based on the sample data of poverty alleviation villages. Figure 8 shows a scatter thermogram, whose data was drawn from the comprehensive resource endowment value (Axis X), market development potential value (Axis Y), and accessibility value (thermal value). In referring to this figure’s scattered thermal distribution, this study proposes a tourism industry development policy for pro-poor tourism villages that considers the three dimensions.

The distribution of points that correspond to China’s pro-poor tourism villages is mainly concentrated in the middle of the coordinate axis. Sample points of the #S1 type with excellent comprehensive development potential and #S6 type with relatively weak development potential are relatively few. Most of China’s pro-poor tourism villages, therefore, show some tourism industry development potential, but still face many restrictive factors; it will take time to overcome. The distribution in Figure 9 was then projected into the geographic space, as shown in Figure 10. The sample point distribution of pro-poor tourism villages is divided into three types and shows significant geographical regularities, as follows:

First, the sample points of the market advantage type (Part T1 in Figure 9 and red sample points in Figure 10) are distributed in the coordinate area according to the above-average market development potential and below-average resource endowment, accounting for about 20 percent of all villages and showing a relatively good accessibility value. Poverty alleviation villages of this type are mainly concentrated in the eastern and southeastern coastal regions with relatively good market conditions and accessibility. Villages of this kind should serve local tourism market needs, deepen tourism product innovation, and form industry integration with surrounding poverty alleviation villages. In addition, they should also gradually become the core developent area of the tourism industry, by enhancing the development of the tourism industry.

Second, the sample points of the resource advantage type (part T2 in Figure 9 and green points in Figure 10) are distributed in the coordinate region. They show below-average market development potential, medium resource endowment (accounting for about 70 percent), and relatively poor accessibility. Villages of this kind are mainly concentrated in the Qinling Mountains area in Central China, the Loess Plateau at the junction of the Shanxi and Shaanxi provinces, and the Yunnan–Guizhou Plateau. They have good accessibility and resource development potential, but relatively weak market development potential. They should emphasize market fragmentation and positioning and explore local market potential. Their development strategies should depend on the market positioning of surrounding tourism cities, utilize the marketing of these cities to improve their market popularity and reputation, and convert excellent tourism industry development conditions into market value.

Third, the sample points of the accessibility advantage type (part T3 in Figure 9 and yellow points in Figure 10) are distributed in the coordinate area with relatively poor development potential and medium resource endowment, and account for about 10 percent. These villages are mainly distributed along the borders of each province and along the main forms of railway transportation. In particular, they are more concentrated at the junction of the Shanxi and Henan provinces and along some railway lines, including the Beijing–Kowloon, Beijing–Guangzhou, and Lanzhou–Xinjiang lines. The resource and market conditions of these villages do not have relative advantages; the subsequent development of the tourism industry should, therefore, focus on characteristic accommodations and catering and be positioned as the tourism industry hubs that serve surrounding scenic spots and achieve tourist industry value.

Most of China’s poverty alleviation villages are located along the edge of regions with harsh natural environments and poor economic and social development. The accessibility of poverty alleviation villages is, basically, poor, and has become a bottleneck that restricts tourism industry development. In order to improve tourism industry development, poverty alleviation villages should focus on constructing traffic infrastructure and connecting themselves to surrounding tourism cities.

6. Discussion and Conclusions

6.1. Discussion

A “Spatial Poverty Trap” is caused by the adverse impact of geographical capital disadvantages on the poor population’s production and lifestyle in the region. This adverse impact makes the poor population’s income stay at a low level for a long time and fall into a state of persistent poverty, which is called a “Spatial Poverty Trap” [80]. The quality of geographic capital is often regarded as a prerequisite for determining the spatial distribution of poverty [81]. Compared with the poverty spatial distribution, geographical capital is also an important determinant of the spatial distribution of the tourism industry, affecting regions’ development mode and industrial viability [9,82]. Therefore, the tourism industry is regarded as a core poverty alleviation industry in a region, and its industrial development strategy will be more determined and influenced by regional geographic capital. In order to improve the accuracy and implementation of the tourism poverty alleviation policy, the government should evaluate and recognize the differentiated geospatial capital before formulating the tourism poverty alleviation policy and importing the tourism industry development mode so as to effectively improve the sustainability and adaptability of the tourism poverty alleviation policy.

As a geographical nature framework, the natural geographical structure integrates multiple geographical elements systematically and organically, which reflects the comprehensive geographical capital situation of tourism poverty alleviation villages and relatively weakens the decisive role of single elements [83]. Then, considering that the tourism poverty alleviation in the village of the tourism industry is just starting, it has not yet been able to form a certain scale of industry [46,84]. We fully consider the influence of natural geographical structure on the development potential of tourism poverty alleviation villages, evaluating the basic potential of the development of the tourism poverty alleviation village rather than all kinds of tourism industry development data reflecting its reality (e.g., tourists quantity and tourism income). Based on the research conclusions of this article, we divided the geographical nature of tourism poverty alleviation villages into three dimensions according to the expanded geographical nature theory of Krugman [66,67]. The first nature is resource endowment, which is the resource dependence of the tourism industry and the un-changeable indicator element. The second nature is market value, which mainly reflects the market transformation ability of the tourism industry, and expounds the geospatial relationship between tourism source market and tourism poverty alleviation village. The third nature is spatial accessibility, which reflects the influence of scientific and technological capabilities on geographical space. We classify the tourism poverty alleviation villages from different combinations of three dimensions, and then propose targeted industrial development policies [68].

In the study and evaluation of the first nature, tourism resource endowment, the resource endowment value of tourism poverty alleviation villages presents a geographical clustering effect. At the same time, climate and terrain factors were used to modify the initial resource endowment values to improve the possibility of discovering high-quality tourism resources in tourism poverty alleviation villages. According to our research results, the comprehensive resource endowment index, when adjusted by climate and terrain factors, changed significantly [5,85]. The resource endowment values increased significantly in the Chinese southwest mountainous areas and southeast coastal areas, which show good potential for resource development.

In the study of the second nature, a market’s development potential, we consider that the tourism industry of poverty-stricken villages has just started to develop, and its tourist source market is still in the cultivation stage [81,86]. Therefore, the study divides three market circles according to the spatial distance, and analyzes the industrial development potential of different market circles by using the measurement method of virtual markets rather than set a specific target customer market. The research results show a new view that 70% of poverty alleviation villages in China have a remote market value better than the near market value. Most poverty alleviation villages should incline to develop the middle and remote market, effectively improve the added value of the industry, and adopt the way from far to near to carry out the spatial structure of the tourism market.

In the study on the third nature, space accessibility, our research results confirmed previous studies [87,88]. The accessibility of tourism poverty alleviation villages in the central and eastern regions is better, with an average arrival time of 1.69 h and 1.99 h, respectively. The average arrival time of tourism poverty alleviation villages in the northeast region is 5.12 h. Additionally, the accessibility of tourism poverty alleviation villages in the western region was the worst, with an average time of 13.47 h. In general, the spatial accessibility of China’s tourism poverty alleviation villages is relatively poor, which has also become an important factor to limit the development of its tourism industry.

In the study of the comprehensive development potential of tourism poverty alleviation villages, we introduce the Newton gravity model to comprehensively evaluate the above three dimensions. Additionally, on the basis of comprehensive evaluation, we classify the tourism poverty alleviation villages—focusing on mining the development advantages of each type—and design a high-quality development path. Our research results also confirmed the previous relevant studies: ① In the region to the west and north of the Hu Line, the development potential of poverty alleviation tourism villages still needs to be improved; it will take a long time to build and improve the development foundation of the tourism industry. We propose, then, that this type of village should pay more attention to the development of the middle and remote markets rather than the near market. ② For the tourism poverty alleviation villages with relatively good accessibility, such as the tourism poverty alleviation villages in the border areas of some provinces and regions, we propose these villages should be developed with the core characteristic of accommodation and catering, locate themselves in the transit and reception areas of tourism, and serve the surrounding tourist attractions to achieve industrial value. ③ For the tourism poverty alleviation villages in the central mountainous area with relatively superior resource endowment, more attention should be paid to cultivating tourism resources and tourism products with high market value should be found and built. ④ For poverty alleviation villages in the east and southeast with relatively superior market conditions, they should deepen the innovation of tourism products and integrate the industrial chain with the surrounding tourism industry, forming regional cluster synergy, so as to improve the development ability of the tourism industry.

The innovation of this paper is to regard the study of geographical nature as a systematic and comprehensive system and place emphasis on the combined utility and interaction of various geographical elements rather than emphasizing the advantages and disadvantages of individual elements. Additionally, we pay more attention to the identification of the development advantages of tourism poverty alleviation villages, and formulate distinctive development strategies for different types of tourism poverty alleviation villages. At the same time, in the evaluation of resource endowment and market development potential, we select a new evaluation model that is more suitable for the development status of tourism poverty alleviation villages. Based on this innovative research model, we also obtain new research findings and explore new potential points for the development of tourism poverty alleviation villages. This study aims to serve the formulation of tourism poverty alleviation policy and enhance the persistence and sustainability of tourism poverty alleviation policy, so as to fundamentally explore its survival and modes of effective industrial development.

6.2. Conclusions

By the basic theory of geographical nature, this paper divides geographical capital into three dimensions: resource endowment, market development potential, and space accessibility. Newton’s basic spatial gravity model is introduced, which is divided into three modules for respectively measuring the indices of three dimensions and comprehensively evaluating the development potential of the tourism industry. This study uses the data of 560 tourism poverty alleviation villages in China to conduct empirical research, and analyzes and evaluates the comprehensive potential of tourism industry development for poverty alleviation villages. Most of Chinese tourism poverty alleviation villages show a certain potential for the development of the tourism industry, show distinct regional concentration characteristics, and face many constraints, which need a long time for exploration and cultivation. The study divides tourism poverty alleviation villages into three types, and puts forward development strategy suggestions:

① Market advantage type. These villages are mainly located in the eastern and southeastern coastal areas. The tourism resources of this type of village are unattractive and make it difficult to form good industrial competitiveness. These villages should serve the local tourism market demand, deepen innovation of tourism products, and integrate the industrial chain with the surrounding poverty alleviation villages to form a regional cluster force, so as to improve the development capacity of the tourism industry.

② Resource advantage type. These villages are mainly concentrated in the central mountainous area. These villages also present poor space accessibility, and their market development potential is weak. These villages should pay attention to market segmentation positioning, and mine the local market potential. They should be attached to the surrounding tourism city market positioning so that the superior tourism industry development conditions can be quickly transformed into market value.

③ Space accessibility advantage type. These villages are mainly distributed at the junction of the first ladder and the second ladder in mainland China, which are concentrated in the provincial edge of the Shanxi and Henan provinces. Since the resource conditions and market conditions of these type villages do not show relative advantages, the industrial value is realized by serving the surrounding tourist attractions in the subsequent development of the tourism industry.

The poverty alleviation tourism policy has taken root in the Chinese mainland, fulfilling a historical mission of poverty alleviation and producing certain positive effects. However, the poverty alleviation policy system has been running for a certain period of time and urgently needs to be adjusted and updated. China’s poverty alleviation policy has entered the development stage of targeted poverty alleviation, attaching importance to the consolidation of poverty alleviation effects and the sustainability of poverty alleviation strategies [68,87]. This paper considers the geographic capital of poverty alleviation strategies as the core index of tourism development potential evaluation and analyzes the development path and policy needs of tourism poverty alleviation villages from the perspective of geographical nature analysis. It has scientific-guiding significance for optimizing the strategy of rural tourism poverty alleviation villages, rationally allocating tourism policy resources, and promoting the sustainable development of rural tourism.

Due to the wide distribution of tourism poverty alleviation villages in China, their geographical capital differences are strong. We put all poverty alleviation villages on a national scale for comparative analysis. In a follow-up study, we will further enhance the pertinence and effectiveness of the research by choosing the different types of typical geographic clusters of tourism poverty alleviation villages for field research and case studies. In the future research, we will further carry out thematic research on promoting the sustainable development of local rural tourism and the implementation effect of poverty alleviation policies.