Introduction

With the development of society, tourism has become one of the strongest and largest industries in the global economy, and the development of tourism plays an important role in promoting the national economy (Bazargani and Kiliç 2021). As a popular tourist city in the west, the Chengdu-Chongqing region has rich tourism resources, convenient transportation, and complete tourism facilities and services and has strong tourism development potential. According to the National Bureau of Statistics, in 2019, the international tourism foreign exchange revenue of the Chengdu-Chongqing region was US$4548.62 million, accounting for 3.4655% of China’s international tourism foreign exchange revenue; the number of international tourists was 7.12 million, accounting for 22.33% of China’s international tourist arrivals. In addition, on October 20, 2021, the Central Committee of the Communist Party of China and the State Council issued the Outline of the Construction Plan for the Twin-City Economic Circle in the Chengdu-Chongqing Region. The Outline calls for the Chengdu-Chongqing region to vigorously develop tourism, lead and create new market demand with high-quality supply, and create an international consumption destination rich in the characteristics of Ba Shu. China’s economic development has entered the stage of high-quality development, and the high-quality development of tourism industry is the fundamental requirement for the development of tourism industry in the twin-city economic circle of Chengdu-Chongqing region. Therefore, the construction of sustainable development of the ecosystem of Ba Shu cultural tourism industry is a major initiative to deeply explore Ba Shu cultural tourism resources, fully integrate into the national major regional development strategy, and vigorously promote the high-quality development of the cultural tourism economy in the twin-city economic circle of Chengdu-Chongqing region.

At present, there are few studies focusing on tourism competitiveness in Chengdu-Chongqing region. Most of the studies only take Sichuan or Chongqing as the research object (Qin 2019; Gu et al. 2019; Shi 2020; Deng et al. 2020), and the studies of Chengdu-Chongqing region are mostly explored from the perspectives of cultural industry, spatial structure, economic development, urban–rural development, transportation layout, and so on (Mengdie et al. 2014; Lei and Yonggang 2019; Cheng and Wang 2019; Li et al. 2020; Xiaobing 2020; Wu et al. 2021; Deng et al. 2021). Based on the niche theory, this study quantitatively analyzes the evolution of tourism competitiveness in Chengdu-Chongqing region and puts forward the corresponding promotion strategies, so as to perfect the tourism development strategy, promote the sustainable development of tourism industry, further promote the construction of Chengdu-Chongqing economic circle, and form an important growth pole of high-quality development in western China.

Literature review

With the increasing development of tourism and its great contribution to economic growth, tourism and related issues have attracted great attention. Especially for tourism competitiveness, scholars have conducted extensive research on this issue, with abundant research literature and diverse research views.

Factors influencing the competitiveness of the tourism industry

At the end of 1980s, foreign scholars introduced the concept of “competitiveness” in tourism research, and then WEF (WordEconomic Forum) and IMD (International Management Development Institute) constructed the international tourism competitiveness evaluation index system. After that, Porter (1990) created the diamond model of competitiveness analysis, which provided specific theoretical and practical guidance for tourism competitiveness research. Since then, the index system and measurement method of tourism destination competitiveness evaluation have become the key direction of research. Inspired by the diamond model, scholars have carried out case empirical evidence by constructing different competitiveness evaluation models. The consideration and framework construction of factors influencing tourism competitiveness have also moved from a single tourism resource, market demand, and regional environment to a rich variety. For example, Crouch and Ritchie (1994, 1995, 1999) constructed a conceptual model of sustainable destination tourism competitiveness from the perspectives of social welfare, social prosperity, and tourism development on the basis of the analytical framework of Porter’s competitiveness model. With the spread of information technology in the twenty-first century, human resources, technology, and management policies are included as important influencing factors of tourism competitiveness. Cimbaljevic et al. (2019) and Milicevic et al. (2020) found that information and communication technology is a key factor in determining the competitiveness of tourism destinations. Andrades and Dimanche (2019) believe that the training of tourism human resources and professionals is the key to the future improvement of tourism competitiveness. Kubickova (2019 and 2020) found that government actions such as corruption and tax cuts can also have an impact on the competitiveness of tourist destinations. Several studies have found that price competitiveness, the behavior of local residents, and tourist satisfaction can also have an impact on the competitiveness of tourist destinations (Perles-Ribes et al., 2021; Tse and Tung 2022; Stojanovic et al. 2021).

Research methodology of tourism competitiveness

In terms of research methods, statistical analysis, analysis of variance, factor analysis, cluster analysis, regression modeling, and structural equation modeling are frequently used as measures by foreign scholars. For example, Campón-Cerro et al. (2017) constructed structural equation model to analyze the data of 464 rural tourists traveling in Spain. Kubickova and Li (2017) used the time series analysis method to study the role of government in tourism competitiveness on the basis of the life cycle model for tourism areas. Algieri et al. (2018) used dynamic panel data model to explore the driving factors of competitive advantage in tourism services of 28 EU countries during 2000–2013. Lopes et al. (2018) evaluated the competitiveness of 8 tourism areas in northern Portugal by using the Tourism Competitiveness Index. Salinas Fernandez et al. (2020) constructed a new Tourism Competitiveness Composite Index (TTCI-DP) and used this index to rank the 80 tourism countries that attract the majority of international tourists. Croes et al. (2020) combined the theory of tourism competitiveness with the theory of human development and put forward the theoretical hypothesis of tourism competitiveness based on the dynamic framework. This hypothesis is based on the recursive relationship between tourism competitiveness and human development. Kubickova and Martin (2020) established a conceptual model to increase government participation and destination competitiveness on the basis of tourism area life cycle (TALC). Škrinjarić (2021a, b) applied Grey Systems Theory to evaluate the efficiency of sustainable tourism in European countries. Gao et al. (2021) constructed an evaluation framework for sustainable development of tourism cities based on the SDGs (sustainable development goals) and Tourism Competitiveness Index, formed a technical evaluation system of sustainable development of tourism cities, and evaluated the sustainable development level of 221 tourism cities in China in 2018. Altinay and Kozak (2021) proposed a model, called the butterfly competitiveness model, to capture the edge of chaos of the tourism industry, the butterfly effects of COVID-19, cosmology, bifurcation events and behaviors, and health and safety-driven self-organization for destination competitiveness. On the basis of previous studies, Milutinovic et al. (2021) puts forward an evaluation model of tourism destination competitiveness based on competitive performance from the perspective of stakeholders and measures destination competitiveness from the perspective of supply side. Garcia-Almeida and Gartner (2021) present a model of intangible cultural heritage from a knowledge-based view that studies its role in destination competitiveness. Gryshchenko et al. (2022) proposed the estimation method of green tourism potential based on ecological and tourism regional competitiveness and constructed the green tourism potential matrix of Ukraine in 2019 and 2020.

Strategies to improve tourism competitiveness

In terms of promotion strategies, the existing literature puts forward suggestions from different perspectives. For example, from the perspective of the government, it is suggested that policymakers should develop a comprehensive tourism policy focusing on product and service development, national branding, and SME development (Khan et al. 2020), pay attention to travel pricing policies (du Plessis and Saayman 2018; Moreno-Izquierdo et al. 2020; Stojanovic et al. 2021), and create a favorable entrepreneurial environment for entrepreneurs (Komppula, 2014). From the perspective of the environment, it is suggested that decision makers should implement effective environmental management and certain environmental marketing activities (Pulido-Fernández et al. 2019). From the perspective of marketing, it is recommended that marketing organizations adapt their marketing strategies to different market segments (Almeida-Santana and Moreno-Gil 2019). From the perspective of sustainable development, it is suggested that tourism planning should adopt a more collective and far-sighted approach based on a number of guidelines (Peng and Tzeng 2012; Bernal Escoto et al. 2019). From the perspective of product diversification, it advocates the type of strategic choice for the development of destination tourism products should be based on the intensification, centralization and diversification of tourism products (Benur and Bramwell 2015). From the perspective of innovation, it is argued that cooperation, enterprise scale, and market competition are conducive to improve the innovation ability of tourism enterprises and further improve the competitiveness of tourism (Divisekera and Nguyen 2018). From a global perspective, it is suggested that decision makers should pay attention to improve the relationship between tourism performance and tourism competitiveness (Bazargani and Kilic 2021). Mtapuri et al. (2021) believe that destination managers and tourism enterprises have the opportunity to adopt sustainable tourism practices, and use of local resources in a strategic manner, in order to maximize the increase in its economic relations, ultimately for the growth of tourism opportunities, and could improve the competitiveness of the destination, while protecting the environment and its carrying capacity. Bertolini et al. (2021) further discusses strategy making in an organizational realm marked by power relations and how their consequences affect society as a whole. There is a need for further research on the impact of strategy-making on power relations and how its consequences affect the organizational sphere.

In summary, studies on tourism competitiveness are increasingly well developed, but their research areas are mostly in popular tourism areas (or developed countries), and less in developing countries. Moreover, there are shortcomings in the theoretical application of the existing studies. Based on this, this paper constructs an index system based on ecological niche theory from an ecological perspective, takes the Chengdu-Chongqing region of China as an example, calculates the ecological niche value of the competitiveness of urban tourism industry, and studies the competitiveness and spatial pattern of urban tourism in the Chengdu-Chongqing region from 2010–2019.

Theoretical approach

Tourism ecological niche

Niche was first proposed by Johnson in 1910, but he did not give a specific concept. Grinell (1917, 1924) first gave the definition of a niche — the last unit of distribution occupied by exactly one species or subspecies, later called a spatial niche. Elton (1927) explained niche in terms of the relationship between food and natural enemies, which was later defined as a functional niche. Hutchinson (1957) proposed the multidimensional hypervolume model of ecological niche, which explained the concept of ecological niche from the effects of various factors on organisms in the environment. The above three niche definitions are considered to be the most representative niche concepts. Although there are still controversies in the academic world on the definition issues after this, the basic connotation has been included in the above three definitions. Referring to Hutchinson’s multidimensional hypervolume niche, this paper defined the niche as the position of a population in an ecosystem and its functional relationship and role with related populations in time and space.

With the development of niche theory, niche theory has been gradually applied to tourism development. Tourism niche is the status, function, and relative relationship with other tourism resources of scenic spots in the process of regional tourism development in a certain period, which studies the role of scenic spots in the development of regional tourism (Xiang, 2009a).

Evaluation model

Tourism niche ecostate-ecorole model

Niche ecostate-ecorole theory is the basis of evaluating urban tourism competitiveness. According to the principle of niche ecostate-ecorole, tourism niche also includes “state” and “potential.” The “state” means the state of the tourist destination (the number of resources, infrastructure, the number of tourists, the level of economic development), which stands for the location of the tourist destination in the region and the interaction with the surrounding environment. The term “potential” refers to the impact and dominance of a tourist destination on its system, such as productivity and growth rate (Zhu 1997).

Combined with the state and potential of the tourism niche, the comprehensive niche value of the tourism destination is calculated as the basis for judging the competitiveness of urban tourism. The calculation formula is as follows (Xiang 2009b).

$$N_i=\frac{S_i+A_iP_i}{\sum\limits_{i=i}^n\left(S_j+A_jP_j\right)}i,j=1,2,3,\dots,n$$
(1)

In this formula, \(N_{i}\) is the niche value of tourist destination \(i\); \(S_{i}\) and \(P_{i}\) are the state value and potential value of tourist destination \(i\), respectively; \({S}_{j}\) and \({P}_{j}\) are the state value and potential value of tourist destination \(j\), respectively; \({A}_{i}\) and \(A_{j}\) are dimension conversion factors; and n is the number of regions. \(S_{i} + A_{i} P_{i}\) can be regarded as the absolute tourism niche of city \(i\); its ratio to the sum of absolute tourism niches of other regions is the relative tourism niche of region \(i\), namely the tourism niche of region i.

After the “state” and “potential” values of each index are calculated, the niche of each dimension of the region can be calculated. Then calculate the urban comprehensive niche.

The calculation formula of dimensional niche is as follows.

$$M_{t} = \frac{{\sum\limits_{i = 1}^{n} {N_{i} W_{i} } }}{{\sum\limits_{i = 1}^{n} {W_{i} } }} \, i = 1,2,3,...n;$$
(2)

Among them, \({M}_{i}\) is the comprehensive niche of tourist destinations; \({N}_{i}\) is the niche of each indicator factor. \(W_{i}\) represents the weight of indicators, reflecting the impact of each evaluation index factor on the niche of tourism destination.

Tourism niche expansion model

In the regional tourism system, the expansion of tourism niche means that on the basis of realistic conditions, in order to consolidate or improve its status and role in the regional tourism system, tourism destinations continue to expand their niche space so as to enhance their adaptability and competitiveness. It is generally manifested in two aspects:

  1. (1)

    Generalization expansion: The development of tourist destinations is relatively mature, and the available resources in the region are reduced, in order to break through the bottleneck of development and form “omnivorous” or “extensive.”

  2. (2)

    Enhanced expansion: The development of tourism destination is weak, and the development ability limits the utilization of various resources. In order to enhance its development ability and expand it, it can be manifested as mining potential niches or introducing new niches (Chen and Yan 2019).

The “state” and “potential” of the tourism ecological niche will increase or decrease with the continuous development of the tourism site, thus bringing about the expansion or reduction of the tourism ecological niche. In order to better reflect the expansion degree of tourism city niche in the region, the ratio of “state” and “potential” of tourism city niche can be used to reflect (He et al. 2019).

$$T = \frac{P}{S}$$
(3)

\(T\) represents the degree of niche expansion of tourism cities in a specific study area, P represents the potential of tourism niche, and S represents the state of niche. S is the standardized data of each index, and the value of its average growth amount is used as the measurement index of “potential.”

T > 0; it indicates that the tourism niche is in the expansion state: the greater the \(T\), the greater the expansion speed; therefore, the influence of the city is gradually increasing. \(T < 0\), it means that the tourism niche is compressed. The smaller \(T\) is, the greater the compression speed is, which means that the development of tourism cities is hindered and the influence is gradually weakened. T = 0; the tourism niche does not change, and the influence of tourism cities does not change.

Tourism niche breadth model

Tourism niche breadth refers to the sum of all niche conditions in a tourist destination or the degree of utilization of all tourism niche conditions (tourism resources, tourism market, tourism environment, etc.). The higher the width of the ecotone, the more positions and roles the tourism site occupies in each resource dimension of the region’s tourism system (Huang 2001).

This study refers to the tourism niche breadth model proposed by Xiang (2012) and uses the specific formula as follows.

$$N_{i} = \frac{{\left( {\sum\limits_{j = 1}^{m} {p_{j} r_{j} } } \right)}}{{\mathop {_{{\sum\limits_{i = 1}^{n} {\left( {\sum\limits_{j = 1}^{m} {p_{j} r_{j} } } \right)} }} }\nolimits_{i} }}$$
(4)

In this formula, \(N_{i}\) denotes the width of tourism niche of destination \(i(N_{i} \in [0,1])\). When \(N_{i} = 0\), the width of tourism niche is the smallest. When, \({N}_{i}=1\) the width of tourism niche is the largest.

r represents the weight of tourism niche evaluation index, which is obtained by entropy method. p represents the score of tourism niche evaluation index. \(j\) represents the tourism niche evaluation index number, \(j = 1,2,3,......,m\). i represents the number of tourist destinations, \(i=\mathrm{1,2},3,\dots \dots ,n\).

The larger the width of tourism niche is, the greater the role of the research object in the tourism system is, and the stronger the tourism competitiveness is. On the contrary, the smaller the width of tourism niche is, the smaller the role it plays in the tourism system is, and the smaller the tourism competitiveness is, and the development is limited, so it is necessary to develop new tourism niche.

Niche overlap model

Niche overlap refers to the phenomenon that two or more species with similar niches share or compete for common resources while living in the same space. If the tourism industry development route of the two cities is similar, the tourism niche of the two cities will overlap. If the development of tourism industry in the two cities is completely consistent, the tourism niches of the two cities will completely overlap. If the development characteristics of tourism industry in the two cities are only partially consistent, then the niche of tourism industry in the two cities is partially overlapping. The higher the niche overlap of tourism industry in each province, the more common resources needed between each other, and the competition is fiercer (Xiang 2009a, b; Yang 1992).

In order to ensure the reliability of the results, “Pinka” model was used to calculate the niche overlap values of 16 tourist cities in Chengdu-Chongqing region. The specific calculation formula is as follows (Pianka 1973; Li et al. 2006).

$$\alpha_{ij} = \frac{{\sum\limits_{a = 1}^{n} {P_{ia} \cdot P_{ja} } }}{{\sqrt {P_{ia}^{2} \cdot P_{ja}^{2} } }}$$
(5)

Among them, \(\alpha_{ij}\) indicates the niche overlap of tourism industry in \(i\) city and \(j\) city. \({P}_{ia}\) and \(P_{ja}\) represent the ecological niche values of i city and j city in the evaluation index ɑ respectively. α = 1, 2, 3, …, n; n represents the number of evaluation indicators.

Because the 4 travel dimensions are independent of each other, alpha deposition method is used (Cody 1974).

$${a}_{ij}^{p}=\prod_{K=1}^{N}{a}_{ij}\left({A}_{K}\right)$$
(6)

\(\alpha_{ij} (A_{K} )\) represents the ecological niche overlap values of \(i\) city and \(j\) city in the dimension \(K\). \({a}_{ij}^{p}\) represents the combined ecological niche overlap value of \(i\) city and j city. \(K\) = 1, 2, 3, …, N; N represents the number of evaluation indicators.

The formula for calculating the integrated overlap of tourism eco-locations (Peng and Yan 2015) is as follows:

$$d_i=\frac{\sum\limits_{j=2}^ma_{ij}^p}{m-1}$$
(7)

Among them, \({d}_{i}\) represents the combined overlap of tourism ecological niches in city \(i\), \(\alpha_{ij}^{p}\) represents the combined ecological niche overlap value of i city and \(j\) city, j  = 2, 3, …, m − 1, and \(j\) represents the number of cities.

Construction of evaluation index system and data source

Evaluation index system

Regional tourism competitiveness is the result of many factors, so the construction of tourism competitiveness evaluation index system needs to take account of the tourism resources, ecological environment, and social and economic factors. Based on the comprehensive reference of the existing research on the competitiveness of tourism industry (Sánchez and López 2015; Hanafiah and Zulkifly 2019; Li and Du 2021; Martinez et al. 2021; Tleuberdinova et al. 2022), this paper constructs an index evaluation system of tourism industry competitiveness with 26 indicators from four dimensions, including tourism resources, tourism market, social economy, and ecological environment.

Data source and processing

The data of this paper comes from Sichuan Statistical Yearbook (2010 ~ 2020), Chongqing Statistical Yearbook (2010 ~ 2020), China Statistical Yearbook (2010 ~ 2015), Chongqing Tourism Bulletin (2010 ~ 2019), and statistical bulletin of some provinces and cities in Sichuan (description: “statistical yearbook” editing and publishing rules for the previous year’s data in the next year’s statistical yearbook; statistical bulletin shows the data of the year). It can be seen from Table 1 that the competitiveness evaluation indexes of tourism industry are all positive indexes. In order to eliminate the influence of data dimension and unit, this paper adopts the “normalization” method to standardize the data, and the specific formula is as follows:

Table 1 Evaluation index system of tourism competitiveness
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$${X}_{i}^{*}=\frac{{X}_{i}-{X}_{\mathrm{min}}}{{X}_{\mathrm{max}}-{X}_{\mathrm{min}}}$$
(7)

Determination of evaluation index weight

Entropy method can be used to determine the discrete degree of an index. The greater the dispersion of the index is, the greater the impact of the index on the comprehensive evaluation. In multi-index decision-making problems, the greater the variation of an index, the greater the information provided by the index, the greater the evaluation effect of the scheme, and the greater the weight of the index (Zhang et al. 2011; Zhu et al. 2014; Luo 2018; Gu et al. 2019). We can use this tool to calculate the index weight.

The steps of index weight determined by entropy method are as follows.

  1. (1)

    Standardized treatment of indicators

Positive indexes

$$r_{ij} = \frac{{x_{ij} - x_{i}^{\min } }}{{x_{i}^{\max } - x_{i}^{\min } }}$$
(8)

Negative indicators

$${r}_{ij}=\frac{{x}_{i}^{max}-{x}_{ij}}{{x}_{i}^{max}-{x}_{i}^{min}}$$
(9)

For convenience, remember the standardized data as \(r_{ij}\).

  1. (2)

    Considering that the result of entropy method may be 0, non-negative translation (the value of 0 plus 0.00001) is used.

  2. (3)

    Weight \(\beta_{i}\) determination.\({F}_{ij}\) is defined as the proportion of the \({\overline{S} }_{ij}\) index value; \(\overline{{S_{ij} }}\) is the average value of the \(j\) index of \(i\) city, then \(F_{ij} = \frac{{\overline{{S_{ij} }} }}{{\sum\limits_{i = 1}^{n} {\overline{{S_{ij} }} } }}\). Let \(E_{ij}\) be the entropy value of the index ofj; there is \(E_{ij} = - K\sum\limits_{j = 1}^{n} {F_{ij} *\ln F_{ij} }\)(where \(K = \frac{1}{\ln n}\)) and the weight of each index is \(W_{ij} = \frac{{(1 - E_{ij} )}}{{\sum\limits_{j = 1}^{n} {E_{ij} } }}\); construct weighted vector , \(W={\left({W}_{1},{W}_{2},\dots ,{W}_{n}\right)}^{T}\) that is \(\beta_{i}\) value. The ecological factor weight coefficient \(\beta_{i}\) indicates the influence degree of this factor on the niche of urban tourism competitiveness.

Empirical results and analysis

Evaluation of urban tourism competitiveness and spatial patterns

In order to show the temporal changes of tourism industry competitiveness in Chengdu-Chongqing region, this paper divides 2010–2019 into two stages to study the ecological niches of tourism industry competitiveness. In the study, “state” refers to the standardized data of each evaluation index, and “potential” refers to the standardized annual growth value of each evaluation index, and the dimension conversion factor A is 1. According to Eq. (1), the annual ecological niche values of different indicators in each city (N) are calculated. According to Eq. (2) and Table 1, the comprehensive ecological niche of each city (M) is calculated by using the annual ecological niche value obtained by Formula (1). Then, the mean values of different dimensions of ecological niche of each city during 2010–2015 and 2015–2019 were calculated and arranged respectively, as shown in Table 2. In order to visually study the trends of the comprehensive ecological status values of each city in different periods, this paper draws a stage trend of tourism competitiveness of cities in the Chengdu-Chongqing region (Fig. 1).

Table 2 Dimensions of urban tourism competitiveness and comprehensive niche ranking
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Fig. 1
figure 1

The stage changing trend chart of tourism competitiveness in Chengdu-Chongqing metropolitan area

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Through Table 2 and Fig. 1, we find that compared with the comprehensive ecological position of the tourism industry competitiveness of cities in the Chengdu-Chongqing metropolitan area from 2010–2015, the comprehensive ecological position has improved overall from 2015 to 2019, but the comprehensive ranking of each city has not changed much. Among them, Ya’an City had the largest change in the composite ecological ranking during this decade, rising from 16 to 10th place, mainly due to the large improvement in resource competitiveness of Ya’an City. Chongqing and Chengdu have clear advantages in all dimensions, especially Chongqing. The competitiveness of the tourism industry is reflected in all dimensions except for the two core cities of Chongqing and Chengdu. On the resource dimension, Leshan, Nanchong, and Mianyang have a clear advantage, mainly due to their rich mountain sports tourism resources and the “celebrity effect.” In the market dimension, Leshan is way ahead. As a national historical and cultural city, Leshan, relying on its rich tourism resources, attaches great importance to the development of tourism and constantly creates high-quality tourism routes, capturing a large market share. In terms of social economy, Mianyang City performs more prominently. Mianyang is the second largest city in Sichuan with a GDP of over 300 billion RMB. Its strong economic advantages and convenient transportation have steadily increased its overall competitiveness amidst the fierce competition from various cities. On the environmental dimension, the environmental competitiveness of most cities has significantly decreased, which indicates that the environmental quality problem in the development process has become a common obstacle to the tourism development of cities in the Chengdu-Chongqing metropolitan area, and the cities need to pay more attention to green development and accelerate the construction of ecological civilization.

With the help of Jenks’ classification method, this study classified the dimensional and comprehensive competitiveness of urban tourism in the Chengdu-Chongqing region from 2010 to 2015 and 2015 to 2019 into five levels, low, low, medium, high, and high, and used ARCGIS to map the evolution of the two-stage spatial pattern of tourism competitiveness of each region in the Chengdu-Chongqing region (Fig. 2).

Fig. 2
figure 2figure 2

Two-stage spatial pattern evolution of tourism competitiveness in Chengdu-Chongqing metropolitan area

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As can be seen from Fig. 2, the Chengdu-Chongqing metropolitan area has different advantages and disadvantages in all dimensions of tourism competitiveness. Overall, the eastern region, where Chongqing is located, has clear advantages in all areas. Chengdu has strong advantages at the socio-economic level and at the market level. The central region is at a disadvantage in all dimensions of tourism competitiveness. The northern region excels in the socio-economic dimension and its overall tourism competitiveness is in good shape. The southern region, on the other hand, is less competitive in the resource dimension and the market dimension, but its socio-economic development has progressed in recent years. Currently, the Chengdu-Chongqing metropolitan area exhibits a clear core city-driven pattern. As the core cities, Chongqing and Chengdu play the role of radiation drive. A core city is a city that plays a pivotal role in a regional city cluster and has a high level of economic, cultural, and social developments. Core cities are the most competitive cities in the region and occupy the most resources. Therefore, while using their own resources, environment, and economic advantages to develop tourism, core cities should promote regional linkage development, strengthen cooperation with neighboring cities, give full play to the role of core cities, and realize regional integrated development. Most of the remaining cities are not very competitive on their own. In order to better attract tourists, the shortcomings of each region should be compensated and the advantages of each region should be given full play. For example, the central region should take advantage of its location connecting Chongqing and Chengdu to reasonably plan tourism routes between the two core cities. Besides, the central region should adopt the strategy of ecological location expansion, update the management mode, develop tourist attractions with local characteristics, and adopt a linked tourism development strategy to achieve regional development. At the same time, the southern and northern regions should strengthen tourism marketing, take advantage of socio-economic and resource advantages, segment the market, and lead the market with points to integrate brand characteristics and improve tourism competitiveness.

Measuring of urban tourism eco-location expansion rate

Through the expansion of niche, we can see the cities that are developing rapidly or stagnant at present. The higher the value of niche expansion is, the better the development of the city is. On the contrary, the development prospect is not optimistic. Through the calculation of Formula (3), the degree of niche expansion in the analysis table is obtained. It can be seen that the tourism industry in Chengdu-Chongqing metropolitan area has shown a sustained growth trend in the past 10 years (T value is mostly greater than 0), and only in a certain year or a few years (less than 3 years), the development is hindered (T value is less than 0). Among them, Mianyang City, Yibin City, Guang’an City, and Ziyang City have more blocked years, indicating that the development of tourism industry in the above regions is weaker than that in other regions. The tourism niche of Chengdu, Neijiang, Dazhou, and Chongqing continued to expand (T > 0).

Combined with the systematic clustering method of SPSS 26.0 software, 16 cities were classified (Fig. 3). According to the ranking of comprehensive niche expansion value, they were divided into four categories. The first category was two cities with high niche expansion rate: Dazhou and Ya’an. The second category is ten cities with medium niche expansion rate: Zigong, Suining, Leshan, Luzhou, Nanchong, Chongqing, Meishan, Chongqing, Neijiang, and Yibin. The third type of ecological expansion rate is low in three cities: Deyang, Guang’an, and Ziyang. The fourth category is the bottom city of niche expansion rate: Mianyang. In recent years, the niche of the two cities in the first category has continued to expand. Ya’an has rich tourism resources and convenient transportation in Dazhou. The two cities make full use of their own advantages, and the tourism industry has developed rapidly. The niche expansion rate is in the forefront. The tourism competitiveness of Chongqing and Chengdu in the second type of cities is relatively high. At present, the niche is still in the state of expansion. However, due to the long development time and the weak attraction of new tourism resources, the degree of expansion and development is not as good as that of other cities that are still in the state of development. The development is initially stagnant, and the expansion value is more regular. Compared with the comprehensive niche value, it is in a relatively stable stage of development, and it is difficult for the tourism market to develop rapidly again. The second kind of other cities such as Zigong, Suining and other cities’ tourism development and expansion is also stable and not prominent, but because of its tourism foundation is far less than Chongqing, Chengdu, its tourism niche competitiveness is not prominent. In the second category, Neijiang City has a poor development foundation and its niche competitiveness is far lower than that of Chongqing and Chengdu. However, Neijiang City has focused on project construction and brand building, and its tourism development has continued to improve in the past decade. The city’s cultural and tourism development has delivered a solid answer and showed a gratifying trend. The third category of Mianyang tourism niche in recent 5 years, many times in a state of compression, belongs to the prospect of not optimistic region (Tables 3 and 4).

Fig. 3
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2015–2019 cluster analysis of niche expansion rate of tourism industry in Chengdu-Chongqing metropolitan area (the rescaled distance clustering combination)

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Table 3 Niche expansion rate and ranking of 16 cities in Chengdu-Chongqing metropolitan area from 2015 to 2019
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Table 4 Annual ecological expansion rate and ranking of 16 cities in the Chengdu-Chongqing metropolitan area
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Measuring the width of urban tourism eco-location

Using the index system constructed in Table 1 and the collected data, the factor ecological position of each city was measured according to Eq. (1). Then, the width of the ecological niche of each city per year was measured according to Eq. (4) (Table 5).

Table 5 Niche width and ranking of each dimension of 16 cities in Chengdu-Chongqing metropolitan area in each year
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By observing the change of niche breadth in each region, it can be seen that the niche breadth of Chongqing (0.4587) and Chengdu (0.2447) was significantly wider than that of other regions from 2010 to 2014. The niche breadth of Leshan (0.0450), Mianyang (0.0330), Nanchong (0.0316), Yibin (0.0233), Guang’an (0.0216), Deyang (0.0208), and Luzhou (0.0207) was higher (the niche value was greater than 0.02), and the niche breadth of Dazhou (0.0184), Suining (0.0165) was lower. However, after several years of development, in 2019, the niche breadth of Chengdu (0.2537) and Chongqing (0.4598) was still significantly ahead of that of other regions. The niche breadth of Dazhou (0.0244) was at a medium level of development, while that of Deyang (0.0172) became narrower, indicating that Dazhou City plays a smaller and less competitive role in the tourism system in the Chengdu-Chongqing metropolitan area, which is well developed, while Deyang City is the opposite. Considering its niche expansion, it is found that the tourism niche of Dazhou City continues to expand (T value has been greater than 0). In contrast, the tourism niche of Deyang City in recent years is still in the expansion state, but the expansion state is not obvious. It is not prominent in the Chengdu-Chongqing metropolitan area, or even lower than the average value, which is consistent with the narrowing of niche breadth (Table 6).

By analyzing the current situation and observing the comprehensive data from 2015 to 2019, the following conclusions can be drawn. (1) From 2015 to mid-2019, the comprehensive tourism niche breadth of Chongqing and Chengdu is much higher than the average value of 0.02 in the selected cities, which is a city with a high tourism niche breadth. Chongqing’s tourism comprehensive niche breadth accounts for 45.98% of the whole region; Chongqing’s tourism comprehensive niche breadth accounts for 25.37% of the whole region. It can be seen that Chongqing and Chengdu are in the core position in the tourism development of the Chengdu-Chongqing metropolitan area and play an indispensable role in the whole region. But Chengdu still has a certain gap with Chongqing. (2) The tourism comprehensive niche breadth of Luzhou, Mianyang, Leshan, Nanchong, Yibin, and Guang’an is slightly higher than the average value of urban tourism comprehensive niche breadth, which is higher than the average value of 6.2%, 66.0%, 76.2%, 58.0%, 10.5%, and 1.2%, respectively, and belongs to the city with higher tourism niche breadth (Table 5). (3) The comprehensive tourism niche breadth of Zigong, Deyang, Suining, Neijiang, Meishan, Dazhou, Ya’an, and Ziyang are all lower than the average value of the comprehensive tourism niche breadth of the selected cities, which belongs to the cities with low tourism niche breadth in recent years. It can be seen that the development of these cities is just so-so due to various reasons.

Table 6 Ecological position width and ranking of 16 cities in the Chengdu-Chongqing region in each dimension from 2015 to 2019
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Measuring the overlap of urban tourism eco-locations

According to the evaluation index system constructed in Table 1 and the obtained data, firstly, the mean value of ecological position of different indicators in each city is calculated according to Formula (1). Then, the overlapping values of tourism ecological position of 16 cities in Chengdu-Chongqing region under 4 dimensions of tourism resources, tourism market, socio-economy, and ecological environment were calculated separately according to Eq. (5). Since the 4 dimensions are independent of each other, the product alpha method (Eq. (6)) is used to obtain the tourism ecological niche overlap matrix of the 16 cities (Table 7). In order to better show the overlap characteristics among cities, this paper calculates the comprehensive overlap degree of tourism ecological niche of each city in the Chengdu-Chongqing region through Eq. (7) (Table 8).

Table 7 Integrated niche overlap matrix of tourism competitiveness in Chengdu-Chongqing metropolitan area
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Table 8 Comprehensive overlap of tourism eco-locations in 16 cities in the Chengdu-Chongqing region
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Phase 1: 2010–2015

Through Table 7, we can find that the overlap degree of tourism eco-location among 16 cities in Chengdu-Chongqing region is higher than 0.6 or even higher than 0.8, which indicates that the overlap degree of tourism eco-location among cities in Chengdu-Chongqing region are at a high level and the competition pressure among them is high. In addition, the overlap degree of ecological position among 59 groups of cities is higher than 0.8, among which Nanchong and Mianyang have the highest ecological position overlap degree. Through Fig. 2, it can be seen that Nanchong and Mianyang are adjacent to each other and have high overlap in tourism resources, markets, socio-economics, and environment.

Phase 2: 2015–2019

Through Table 7, we can find that the overlap of tourism eco-location among 16 cities in the Chengdu-Chongqing region is higher than 0.6 or even higher than 0.9, which means that the overlap of tourism eco-location among cities in the Chengdu-Chongqing region is at a higher level and the competition pressure between them has increased. In addition, 92 groups of cities have an ecological position overlap higher than 0.8, and 13 groups of cities have an ecological position overlap higher than 0.9. Among them, Chengdu and Leshan have the highest ecological position overlap group.

Comparing the overlap of urban ecological position in the two phases of 2010–2015 and 2015–2019, we can see that the overlap of ecological position among 16 cities in Chengdu-Chongqing region is gradually increasing and the competition is becoming more intense. Most cities are in a state of “high overlap.” The development among cities tends to be homogeneous. Besides, the tourism competition in most city groups shows a “low to high” variation. Only 26 city groups show a “high to low” variation in tourism competition.

As can be seen from Table 8, half of the cities’ rankings in terms of comprehensive overlap of ecological niches decreased, only two cities’ rankings remained unchanged (Luzhou and Ziyang), and the remaining cities’ rankings in terms of comprehensive overlap of ecological niches increased. In addition, almost all cities are facing severe competitive pressure as their ecological location overlap increases.

Conclusion and strategies

Conclusion

Tourism economy is an important “assistant” of modern economy with high-quality development, and is a new type of industry with great growth potential. The study of tourism competitiveness of cities in Chengdu-Chongqing region is conducive to helping government departments in Chengdu-Chongqing region to better formulate development strategies and achieve high-quality development and helping tourism enterprises to better identify development projects and achieve innovative development. Based on the niche theory, this paper constructs a tourism competitiveness evaluation index system from four aspects, tourism resources, tourism market, social economy, and ecological environment; measures the tourism competitiveness of cities in Chengdu-Chongqing region with the niche ecostate-ecorole model, niche width model, and niche expansion model; and measures the influence degree among cities in Chengdu-Chongqing region with the ecological niche overlap model. The results found that:

  • From 2010 to 2019, the tourism eco-location values of most cities in the Chengdu-Chongqing region show an upward trend and gradually increase their competitive advantages.

  • The tourism ecological position values of the core cities in the Chengdu-Chongqing region (Chengdu and Chongqing) remain stable, while the tourism ecological values of the remaining cities change significantly. In addition, the ecological position values of the central cities are significantly lower than those of the cities in the peripheral areas.

  • During 2010–2019, the overlap of tourism ecological position of cities in Chengdu-Chongqing region is high, and the overlap of tourism ecological position of most of the cities shows a “low to high” change feature. This indicates that the degree of tourism homogenization in Chengdu-Chongqing region is high.

Enhancement strategies

Based on these conclusions, the article proposes the following recommendations from the perspectives of ecological niche separation, ecological niche expansion, ecological niche generalization, and specialization.

Strategy of niche separation

In studying the competitiveness of regional tourism industry, due to the limited tourism resources, similar geographical location, overlapping source markets, and intense competition in tourism industry, the ecological location separation strategy can effectively avoid vicious competition and can be misplaced to develop and avoid shortcomings. Within the Chengdu-Chongqing metropolitan area, Nanchong and Mianyang are spatially adjacent to each other, with high overlap of ecological locations and fierce competition. Low-level repeated development in the region should be avoided to reduce the overlap of ecological environment. Mianyang can take advantage of its socio-economic and environmental strengths; play its important strategic advantage as the hinterland of the “Western Triangle” of Chengdu, Chongqing, and Xi’an and the pivot city of the “Belt and Road” and the Yangtze River Economic Belt; and promote its profound history and culture. Nanchong’s unique tourism resources Nanchong gives full play to its unique tourism resources and promotes traditional folk cultures such as the Great Puppet of Northern Sichuan and Bayu Dance. The two places form a staggered development to avoid homogeneous competition.

Strategy of niche expansion

Expanding urban niche can release the potential of urban tourism development. Under the condition of existing tourism resources, the competitiveness of urban tourism can be improved by developing new tourism resources, innovating tourism products, updating tourism service forms and facilities, and updating management mode. For example, Deyang has basically formed a relatively perfect tourism industry system by vigorously promoting tourism projects, establishing brand image, expanding the tourism market, and enhancing tourism services. For cities with low ecological width, such as Zigong, Deyang, Suining, Neijiang, Meishan, Dazhou, Ya’an, and Ziyang, they can learn from the development model of Deyang, strengthen their own tourism infrastructure and tourism reception service facilities, and continuously optimize and improve their own tourism development environment. Zigong can launch related cultural products with salt history, dinosaurs, and colored lanterns as the core, create high-quality Sichuan opera, promote salt dishes, and promote Zigong city to leap from a large city with tourism resources to a strong city with tourism economy. Suining City can promote the commercialization of cultural tourism projects, promote cultural creation and display, increase the protection and promotion of Song porcelain and other non-heritage resources, and implement cultural “going out.” Neijiang City can fully develop its rich humanistic landscape, protect its unique natural scenery, and promote the integrated development of cultural tourism. Meishan City promotes the promotion and sales of pickle city products and carries out special catering and cultural creativity around Dongpo culture. Dazhou City relies on its rich historical resources, red background, and special products such as lantern-shaded beef and Dongliu mash to promote the overall development of tourism industry. Ya’an, featuring the only ecological tourism city in the Chengdu-Chongqing Economic Zone, relies on the rich cultural heritage of the Han Dynasty to build a cultural brand according to local conditions. Ziyang, as the “double gateway” connecting Chengdu in the west and Chongqing in the east, should further develop short-distance tourism to attract tourists from the surrounding area and give full play to its influence as the hometown of talents in the past generations.

Strategies of niche generalization and specialization

In the case of limited or saturated regional tourism resources, we can strengthen the tourism advantages to form competitive advantages, take advantage of the niche of a certain aspect to form specialization, or relax the choice of expansion of tourism destination development mode and adopt diversified tourism development strategy to form generalization. Chongqing and Chengdu that have significant niche advantages, whose tourism industry development has been relatively mature, should adopt the strategy of generalization and expansion, improve all aspects of the tourism industry as far as possible, and form a complete tourism system to develop in all directions. Other cities with relatively low niches and intensive expansion strategies should adopt to maintain development, tap more tourism resources as much as possible, find new breakthroughs, and attract tourists by strengthening and expanding a regional feature to form a unique advantage of the city. For example, Luzhou pays attention to the integration of tourism and culture in its development, strengthens the creation of famous cultural tourism towns in Sichuan Province, and enhances the protection and utilization of culture such as the ancient architectural complex of Yao Ba. Leshan relies on famous places such as Leshan Buddha to form characteristic advantages and strengthen the construction of the four business cards of “famous mountain, famous Buddha, famous number, and famous person.” Yibin can take advantage of its economic development, promote its rich tourism resources, enhance traditional scenic spots such as Xingwen Shihai and Lizhuang Ancient Town, and promote the construction of an “international ecological garden city.” Guang’an can take advantage of its “key red tourism area” resource environment and “Chongqing 1-h economic circle” traffic conditions to attract tourists from the surrounding areas.