A Conceptual Model Study of Tourism Resource Sharing in the Digital Economy

Abstract

The concept of “sharing” and the development of the digital economy have driven the transformation of resource allocation in the tourism industry to resource sharing. The article defines resource sharing in the tourism industry from a comprehensive perspective according to the systematic analysis of the concept of resource sharing and the background of the digital economy, which is an economic behavior of integrating, opening and sharing resources among members under the guidance of the government and relying on modern information technology such as the internet, with the sharing of usage rights as the main feature. Based on the dual inspiration of MICK resource classification theory and digital economy theory, the article constructs a conceptual model and measurement scale of resource sharing in the tourism industry from four dimensions: knowledge resource sharing, material resource sharing, information resource sharing and capital resource sharing. The panel data of 31 provinces (municipalities and autonomous regions) from 2016 to 2020 were analyzed mathematically and statistically. The analysis results showed that the weight of knowledge resources is the highest. Moreover, the eastern region had the highest level of resource sharing and the western region had the lowest level of resource sharing. Furthermore, the level of resource sharing in the past five years showed a trend of year-on-year improvement. Based on the scores, countermeasures are proposed in terms of enhancing the importance of information technology and strengthening basic support according to local conditions, which provide a reference for cities to improve the level of resource sharing.

1. Introduction

China is at the historical intersection of a new round of technological revolution and industrial change, with the digital economy as the representative of the economic form of radiation, the impact is deep, which provides a rare opportunity for China’s tourism industry to improve quality and efficiency, but also a serious challenge to the development of innovation in China’s tourism industry. Sharing is a people-centered socialist characteristic to promote people’s welfare, which is conducive to the fruits of modernization to benefit all people. As society changes and evolves, traditional production and management methods have long failed to meet the tourism industry’s strategic goal of gaining a competitive advantage and economic benefits. Joining the ranks of sharing and achieving inter-industry resource sharing using digital technology can effectively reduce production costs and gain economies of scale [1].

From the existing literature, the research on resource sharing is mainly theoretical studies on resource sharing and resource-sharing platform development [2]. Scholars have studied the conceptual connotation, content, mechanism, and path of resource sharing. Scholars have proposed different concepts of resource sharing from the perspectives of economics, sharing members, and the background of digitalization. Scenic resources, information resources, and human resources are all elements of resource sharing. In terms of mechanisms, scholars have studied human resource sharing mechanisms and education sharing mechanisms, etc. [3,4]. Studies have used empirical research to confirm the promotion effect of resource sharing on innovation performance and the negative effect of executive job satisfaction [5,6]. Other scholars have proposed relevant countermeasures on cultural resources, information resources, and human resource sharing [7]. The research methods mainly include structural equation analysis, hierarchical analysis, MB+ tree test method, and negative binomial regression model [8,9,10]. A few scholars have studied the conceptual model of resource sharing, for example, Benjamin L. Turner studied the conceptual model of soil resource allocation and proposed to group soil resources to form a biologically effective gradient [11]. Zhou Ping proposed a conceptual model of effective information resource sharing, including the effective sharing of specific information by a single organization or individual, the effective sharing of specific information by all organizations or individuals, and the effective sharing of information by all organizations or individuals to the effective sharing of information sharing system [12]. Dong Won Yi and other scholars studied the conceptual model of resource sharing in container terminals for improving the productivity of container terminals [13]. Regarding the research on resource sharing in the tourism industry, scholars have focused on the problems and countermeasures research of industrial resource sharing with specific tourism resources and specific regions. For example, scholars have studied the development status and path of information tourism resources [14,15], in addition to the problems and countermeasures in resource sharing in Yuanjia Village, Shanxi and other regions [16,17].

Although the existing studies are more extensive and have more diverse approaches, the studies on the connotation of the concept are based on a certain social context or research perspective and lack comprehensive definitions. There are fewer studies on the conceptual model of resource sharing in academia, fewer studies on the conceptual model of resource sharing in the tourism industry, and basically no scholars have studied resource sharing in the 31 provinces (cities and autonomous regions) in China. Therefore, the main contributions of the article are as follows. First, the conceptual connotation of resource sharing is refined from the functions, characteristics and goals of resource sharing, and a conceptual model of resource sharing is constructed according to China’s characterized national conditions and the development of the digital economy. Second, the evaluation index system of resource sharing is systematically constructed from the perspective of resource classification. Third, the index weights were determined using the entropy value method. Fourth, the average score of resource sharing in China in the past five years was analyzed by collecting relevant data from the 31 provinces (municipalities and autonomous regions) and calculating their factor scores. Fifth, countermeasures to promote the level of resource sharing in the tourism industry were proposed to improve the current situation of resource sharing in China’s tourism industry.

2. Connotation and Development of the Concept of Resource Sharing in the Digital Economy

The term “sharing” originally means to be shared, which means that the right to use or know about an object or information is shared with other people. The term “resource sharing” was first introduced by Bétourné and other scholars in 1970 [18], and then it was widely mentioned in the field of computing. In 1979, Kent, an American librarian, first defined the concept of resource sharing and pointed out that “resource sharing” is a reciprocal peer relationship from the perspective of resource sharing membership, that is, each member owns something that can be used by other members, and each member is willing to share the thing with other members [19]. Based on an economic perspective, Marshall proposed that resource sharing is a manifestation of agglomeration externality, and as a social phenomenon, it emphasizes the group behavior of reallocating valuable resources with interest as the center [20]. The research on resource sharing in China began in 1985 with the study of the Internet of Computer Things. Then the research on library resource sharing reached a white hot stage. With the development and presentation of the concept of sharing, industrial development has a new innovative path. Industrial cooperation has become a new direction of resource sharing, and collaborative innovation resource sharing has emerged, which means that under the role of government guidance and mechanism arrangement, the enthusiasm of each participating body is fully mobilized to promote the deep cooperation of different fields and industries, and then realize the integration, opening and sharing of resources [21]. With the rapid development and growth of digital industries, the way and content of resource sharing has been substantially subverted. Resource sharing in the digital economy era emphasizes relying on the internet to break the phenomenon of resource silos, achieve coordination, interoperability, dissemination and sharing of information resources, and improve the efficiency of resource utilization [22]. The definition of the concept of resource sharing by scholars is listed in Table 1.

The concept of resource sharing was initially developed from the construction of library resource networks, and most of the existing research results have focused on the sharing of library intelligence resources and archival information resources. The tourism industry is a typical service industry, and its industry characteristics and attributes, production and operation methods, inputs and outputs are different from those of libraries in the public welfare category. The use of information technology tools such as cloud technology, the Internet of Things, big data, and artificial intelligence in the digital economy has challenged the existing level of the tourism industry. Considering China’s national conditions and the research results of existing scholars, this article defines the concept of resource sharing in the tourism industry. It is an economic behavior that realizes the integration, opening and sharing of resources among members under the guidance of the government and relying on modern information technology means such as the Internet, with the sharing of usage rights as the main feature.

The connotation of resource sharing in the tourism industry under the background of the digital economy mainly contains four points. ① Economy, resource sharing is an economic behavior centered on benefits. The external economy and the extension of the industrial value chain are the external motivation for resource sharing in the tourism industry. The sharing of industrial resources can reduce industrial costs, form industrial competitive advantages, and pursue greater value space. ② Sharedness, which emphasizes the cooperation and sharing of each participating subject. Each interest subject shares and exchanges, allocates and uses, absorbs and creates resources such as materials, information, capital and knowledge to achieve the maximum win-win situation for individual and organizational interests based on the bond of benefit sharing. ③ Technically, resource sharing emphasizes the sharing and co-construction of resources with the support of technology. Resource sharing in the tourism industry under the background of the digital economy needs to rely on typical Internet technology means to innovate and optimize the way of allocating tourism resources and realize the great improvement of tourism industry efficiency. ④ Dominance. China’s characteristic national conditions determine that the realization of resource sharing requires government policy guidance and mechanism roles. The government’s adoption of a reasonable and effective regulatory mechanism is of great significance to the benign development of the tourism industry. It is inevitable to establish a government-led and market-collaborative governance mechanism in the development of the industry.

3. Conceptual Model of Resource Sharing in the Tourism Industry

3.1. Classification System of Tourism Resources

Clarifying the classification system of resources is necessary for clarifying the constitutive dimensions of resource sharing. Traditional resource theory takes a variety of classification approaches, and Table 2 lists different classification views of resources.

Scholars classify resources from multiple perspectives, such as the form, nature, function and characteristics of resources, which have certain rationality and provide a reference value for the classification of tourism industry resources. However, with the development of the economy and the change of times, the traditional resource classification no longer meets the requirements of modern society for resource classification. If classified according to the resource form, the tourism industry includes both tangible resources such as ornamental landscapes as well as institutions, and intangible resources such as knowledge and culture. Institutions, knowledge, and cultural resources are unified as knowledge resources according to the resource function, and there is a classification crossover. Resource integration activities require that tourism industry resource classification should not only abstract the functional characteristics of different resources to facilitate the search, and it also requires covering all tourism industry resource types. Scholars such as Zhao Daozhi proposed the MICK resource classification based on resource functions in strict accordance with the principles of form, purpose, and connotation, which integrated the concepts of resources and capabilities and emphasized the functionality of resources [28]. There are many types of tourism industry resources and classification criteria; moreover, each type corresponds to its corresponding function. The article draws on the MICK resource quadratic method to build a tourism industry resource classification system strictly in accordance with the classification principles of connotation principle over purpose principle and purpose principle over form principle (e.g., patented technology in the form of information belongs to knowledge resources according to connotation) to divide the tourism industry resources into tourism industry material resources, information resources, capital resources, knowledge resources.

3.2. Constitutive Dimensions of Resource Sharing in the Digital Economy

Resource sharing in the context of the digital economy is a complex multidimensional abstract variable. Due to the late introduction of resource sharing, there are few research results on the constitutive dimensions of resource sharing in academia. Studies have been conducted to classify the constitutive dimensions of resource sharing from different theoretical perspectives and division criteria; however, the academic community has not yet reached a unified understanding of the constitutive dimensions of resource sharing. Although scholars did not put forward the concept of resource sharing in the tourism industry in the early stage, their research contents have long covered the factors of resource sharing in the tourism industry, such as tourism attraction resources, infrastructure, information resources, knowledge resources, platform sharing, and sharing economy. In order to break the administrative barriers and distance restrictions, scholars first explored the sharing of tourism attraction resources and talent resources and realized resource sharing by unified planning of scenic spots and building a talent resource-sharing platform [29,30,31]. In order to respond to the changes in the market environment to form a good competitive advantage, scholars proposed the need to share knowledge resources among enterprises sharing knowledge resources among organizations [32,33]. In order to cope with the impact of the big data era on tourism, scholars propose to strengthen industry integration and realize information resource sharing among all parties [17,34]. Based on the perspective of enterprise innovation, resource dependency theory suggests that resource sharing includes the sharing of tangible and intangible resources. Information sharing capability among enterprises is divided into information sharing extension, breadth and intensity [35]. Sharing frequency, resource output and input in the context of open innovation all belong to the category of resource sharing [36]. From the industrial perspective, in addition to the above-mentioned material resources, information resources, knowledge resources and industry-specific resources, financial resources also belong to the scope of industrial resource sharing [37]. From a sociological perspective, the Marxist theory of “sharing” considers that resource sharing includes three dimensions of natural resources, material products and immaterial products sharing [38]. Benefit sharing, service sharing and opportunity sharing are three key dimensions to realize the theory of shared development [39].

Integrating the above literature studies, the conceptual model of resource sharing in the digital economy is systematically constructed (Figure 1). Resource sharing in the digital economy is a multidimensional variable that contains four dimensions material resource sharing, information resource sharing, capital resource sharing, and knowledge resource sharing.

Among the tourism industry resources, material resources are the most basic because of the strong dependence of the tourism industry on resources, which are the material guarantee and development cornerstone of tourism industry innovation and development [40]. While most material resources are exclusive and not public goods, many tangible material resources are also shared because tourism is exotic, integrated and driven. Material resource sharing refers to the sharing of tourism resources in physical form that the tourism industry enjoys in order to achieve the complete operation and development of the tourism industry. Material resources are mainly divided into public infrastructure resources and inter-industry resources [41]. As the development of the digital economy continues to accelerate, the asymmetry of information resources in the hands of tourism-related subjects caused by the digital divide has seriously hindered the healthy development of the tourism industry. The essence of information resource sharing is to satisfy the information needs of each using subject by coordinating the distribution of information resources among tourists and tourism enterprises, and to play the maximum utility of information resources [42] Digital transformation of the tourism industry has become an important push to adapt to the development of the times. It’s also the key to building the competitiveness of the industry in the new era. Since the concept of “sharing” was put forward in 2015, it has long penetrated into all aspects of economic life, and the sharing of capital resources has greatly improved production efficiency. The sharing of capital resources means that enterprises or governments with idle capital resources temporarily transfer the right to use their funds to the demand side, so as to realize the circulation of capital elements in the industry and promote the sustainable development of the tourism industry. As an important national strategic resource, knowledge resources provide the basic support for industrial production activities and are given the historical status of “the first resource” [43]. In the new era, expanding the content of knowledge resource sharing, innovating the mode of knowledge resource sharing, and satisfying the urgent demand for knowledge resources in the industry have become important research contents of China’s knowledge resource management and research. The essence of knowledge resource sharing is the optimal allocation of knowledge resources, which means the recombination and allocation of knowledge resources within a certain range in a certain environment to achieve greater social and economic values of knowledge resources [44].

3.3. Evaluation Index System Construction and Empirical Analysis

3.3.1. Indicator System Construction and Data Sources

The construction of a scientific and reasonable evaluation index system of tourism industry resource sharing is an important basis for judging the impact mechanism of tourism industry resource sharing on industrial innovation. Based on the above conceptual model and guided by the principles of scientificalness, comprehensiveness, typicality and accessibility, the evaluation index system is divided into a target layer, criterion layer and indicator layer (Table 3).

Construction of Material Resource Sharing Index System

Material resources of the tourism industry refer to the material form resources held by the tourism industry to provide products or services for tourists, which are mainly divided into public infrastructure resources and material resources of the tourism industry [41], and the article follows this viewpoint to analyze the sharing of material resources of the tourism industry. Referring mainly to the relevant studies by Nan Lan [41] and Wang Zhao-feng [45], three indicators are selected: railway mileage, road mileage, and the number of A-class scenic spots. Among them, railroad mileage and highway mileage are important indicators of public transportation infrastructure of the tourism industry, and the number of A-class scenic spots, as the evaluation index of industrial material resources, directly reflects the reception capacity of the tourism industry.

Construction of Information Resource Sharing Index System

Information resource sharing is a complex capacity system involving multiple subjects, dimensions and elements, which directly responds to the capacity of destination resource sharing and laterally responds to the level of destination digital infrastructure. Referring to the relevant literature [46,47], the digital application level is selected as the basic measure of information resource sharing. Internet penetration rate represents the level of digital technology application at the individual level and social level, which can laterally reflect the scale, content and level of digital supply in the destination tourism industry.

Construction of Capital Resource Sharing Index System

The sources of funds for tourism industry development are mainly divided into three aspects. One is the government’s cultural and tourism business fee set up to support the development of the tourism industry, but the use of this fund includes cultural undertakings such as libraries in addition to tourism, which is not representative of the capital investment in the tourism industry. Second is the capital of the tourism industry, and the article integrates the practices of many scholars such as Huang Mei and selects the fixed assets of star-rated hotels to measure industrial funds [48]. Third is the urban economic factor, and scholars point out that the cities that benefit the most from tourism and develop rapidly are not the cities with tourism as a pillar industry, but rather the cities with a large and diverse economic base, reflecting the influence of the city economy on the tourism industry capital. The article quantifies this as the ratio of tertiary sector income to GDP, drawing on the research of Hua Fei-Fei and other scholars [49].

Construction of Knowledge Resource Sharing Index System

Knowledge resource sharing emphasizes the creation, dissemination, absorption, integration and reuse of knowledge within the industry. The transmission process of knowledge resource sharing includes two parts, the creation of knowledge from knowledge providers and the absorption and application of knowledge by knowledge receivers. Accordingly, knowledge resource sharing can be divided into knowledge creation and knowledge absorption. The knowledge creation process mainly considers human cost and material cost, which are measured by the full-time equivalent of research and development (R&D) personnel and the number of students enrolled in higher education institutions, respectively. Knowledge absorption is measured by the knowledge outcomes created by knowledge providers, quantified as the number of patents granted [50].

Data Sources and Research Methods

The article aims to study the level of resource sharing in the tourism industry, and the level of tourism development in the 31 provinces and cities is taken as the object of investigation considering the availability and reliability of the analyzed data. The article collected relevant data from the 31 provinces for a total of five years from 2016 to 2020, and the data selected for the article were obtained from the China Statistical Yearbook and the China Statistical Yearbook of Culture, Heritage and Tourism. The principle of factor analysis is a statistical analysis method of clustering multiple variables into a few composite variables in a dimensionality reduction manner to obtain more information and determine the number of dimensions with as little loss of information as possible. Since the index system constructed in the article is relatively clear and all statistical data are available, the factor analysis method is adopted to make a comprehensive evaluation and dimensional division of resource sharing.

3.3.2. Factor Analysis

The SPSS 26.0 statistical software was used to conduct exploratory factor analysis on the tourism industry resource sharing scale. Factors were extracted by principal component analysis and rotated by the orthogonal greatness method, and the rotated factor matrix was output (Table 4). The feasibility experiment of factor analysis was conducted on the data before formal analysis, and the KMO value of 0.686 was obtained, which was greater than 0.6, indicating that the overlapping information among the variables was fair and suitable for factor analysis. The Bartlett test observation value of significance 0.000 was less than 0.05, indicating that the original hypothesis should be rejected and the variables were significantly correlated and suitable for factor analysis. The results showed that four common factors could be extracted from the tourism industry resource-sharing index system, and the factor loadings of each index are greater than 0.60, and the overall variance explanation rate reaches 82.320%. The above results indicated that the tourism industry resource-sharing index system was well constructed.

3.3.3. Factor Score Evaluation

Determination of Index Weights

① Data standardization. In order to avoid result bias, the data were normalized before using the entropy method to calculate the index weights, and the processing was as follows

$x_{aij}^{\prime }=\frac{x_{aij}-min \left(x_{aij}\right)}{\mathit{max}\left(x_{aij}\right)-min \left(x_{aij}\right)}$

Note: $x_{aij}^{\prime }$ is the standardized value; $x_{aij}$ is the original data of j indicators in province and city i in year a; $\mathit{max}\left(x_{aij}\right)$ is the maximum value of j indicators; $min \left(x_{aij}\right)$ is the minimum value of j indicators.

② The share of the jth indicator in the indicator in province and city i

$p_{aij}=\frac{x_{aij}^{\prime }}{{\sum }_{i=1}^m{x}_{aij}^{\prime }}(0<p_{aij}<1;i=1,2\dots n;j=1,2\dots m)$

③ Calculate the information entropy value of the jth indicator

$e_j=-\ln {\left(n\right)}^{-1}\sum _{i=1}^n{p}_{aij}\ln \left(p_{aij}\right)$

④ Calculate the weight of evaluation indicators

$w_j=\frac{1-e_j}{{\sum }_1^m(1-e_j)} \left((0\le W_{\mathrm{j}}\le 1\right)$

Calculate the weight of the resource-sharing evaluation index system according to the above steps (Table 5). The knowledge resource sharing factor has the largest weight, indicating that the better the regional knowledge creation and absorption, the higher the level of tourism industry resource sharing. Second, is the material resource factor, which is reflected in the regional public basic resources and industrial material basic resources, occupying a larger proportion. Third, is the financial factor, the larger the regional tourism industry funds, the higher the level of urban economic development, and the higher the level of sharing of tourism industry resources. The fourth is the information technology factor, which occupies the smallest proportion. Though China reached the development level of global leadership in information infrastructure at the end of 2020, the results of the study show that China’s digital divide problem is more obvious.

Calculation of Composite Score

The composite scoring formula is used to calculate the annual resource-sharing score according to the weights of resource-sharing evaluation indexes (Figure 2). Then we calculate the national average annual resource-sharing score and standard deviation based on the total annual resource-sharing score (Table 6).

Looking at the average scores of each province in the past five years (Figure 2), the overall resource-sharing level is higher in Shandong, Guangdong, Jiangsu and Zhejiang, which are located in the central region. The lowest is in Ningxia, Tibet, Qinghai and Hainan, which are located in the western region. It can be seen that the stronger the overall competitiveness of higher education regions, the higher the level of regional resource sharing. In terms of time level, the resource-sharing level improves year by year, with the greatest improvement from 2019 to 2020. However, the resource sharing level in the Beijing region in the past five years has shown a continuous decrease since 2016, hitting the bottom in 2018, and rebounding slightly in 2019 to 2020, but still lower than the resource sharing level in 2016. Guangdong, Shandong and Jiangsu ranked among the top three in the country in terms of resource sharing level for four consecutive years from 2017 to 2020. Tibet, Ningxia, Qinghai and Hainan ranked at the bottom of the country in terms of resource sharing level for five consecutive years, and the spatial pattern is relatively stable. Four cities in Tibet, Shanxi, Hainan, and Tianjin have had more stable resource-sharing levels for five years than the remaining 27 cities, and four cities in Shandong, Guangdong, Zhejiang, and Beijing have experienced greater changes in resource-sharing in the last five years. Beijing has had the largest change in resource sharing level in the last five years, from first place in the country in resource sharing level in 2016 to a lower than the national average score in resource sharing level in 2018.

4. Conclusions and Discussion

The vulnerability of the tourism industry indicates that once the environment on which it depends changes, the industry needs to take timely measures within the industry to respond to the challenges brought by the increasingly changing external environment, and the content of resource sharing in the tourism industry has evolved with the changing times. Therefore, this study explores the conceptual model and measurement scale of resource sharing in the context of the digital economy, adding the target layer of information resource sharing compared with existing studies. It analyzes the resource-sharing situation in each province based on relevant data from 31 provinces and proposes the path to promote resource sharing. Theoretically, it enriches the conceptual model of resource sharing, and practically, it provides practical reference suggestions for provinces to enhance the innovative development of the tourism industry and integrate the types of resources.

4.1. Conclusions

① Resource sharing in the tourism industry contains four dimensions.

Tourism industry resource sharing is a complex multi-dimensional abstract variable. The results of both theoretical and empirical analysis show that tourism industry resource sharing includes four dimensions, which are tourism industry knowledge resource sharing, tourism industry material resource sharing, tourism industry capital resource sharing and tourism industry information resource sharing. This conclusion fills the gap in the conceptual model of resource sharing in the tourism industry by systematically proposing a conceptual model of resource sharing based on MICK resource classification theory in the context of the digital economy from an industrial perspective.

② The weights of each dimension of resource sharing are, in descending order, knowledge resource sharing > material resource sharing > capital resource sharing > information resource sharing.

The results of the factor score calculation for the last five years of statistics from the provinces show that the ranking order of each factor is knowledge resource sharing (57.44), material resource sharing (25.1), capital resource sharing (14.27), and information resource sharing (3.19). Knowledge resource sharing has the largest proportion, reflecting that knowledge resource is the first productive force to promote the development and progress of the tourism industry. The digital economy has built an intelligent world in which everything is connected and instantaneously synchronized, which provides rich forms of knowledge resources and knowledge service platforms and enhances the efficiency and total amount of knowledge resource transfer and absorption. As the key element and core resource of resource sharing, the amount of its transfer and absorption directly affects the degree of resource sharing. Material resources share a larger proportion, and material resources are the premise and basis for promoting the innovation development of the tourism industry. Systematic integration and sharing of material resources of the tourism industry can not only stimulate the market vitality and increase the development momentum of the tourism industry but also promote the quality and efficiency of the tourism industry and promote the growth of the tourism economy. The low proportion of financial resources indicates that the level of regional economic development can, to a certain extent, improve the level of resource sharing in the tourism industry and promote the development of the tourism industry. There is a large gap between the information technology resource sharing and other factors in comparison, which is different from the conclusion that the contribution of information technology to China’s tourism market is high as proposed by scholars such as Sun Yuanyuan [51], which on the one hand indicates that the digital economy era has put forward higher requirements for the level of digital technology application, and on the other hand reflects that the tourism industry still does not pay enough attention to the application of digital technology in the context of the digital economy, and the digital divide is prominent.

③ The national resource sharing level in descending order is the eastern region > the central region > the western region.

According to the development of economic development level and resource sharing level in the provinces, the regional differences in resource sharing are divided into eastern, central and western regions, and the analysis is carried out from these three regions. The eastern region includes 12 provinces, including Beijing, Tianjin, Hebei, Liaoning, Shanghai, Jiangsu, Zhejiang, Fujian, Guangdong, Shandong, Hainan, and Guangxi; the central region includes 9 provinces and regions, including Henan, Hubei, Hunan, Anhui, Jiangxi, Shaanxi, Jilin, Inner Mongolia, and Heilongjiang; the western region includes 10 provinces and regions, including Sichuan, Shaanxi, Chongqing, Yunnan, Guizhou, Xinjiang, Gansu, Ningxia, Qinghai, and Tibet. The study found that the level of resource sharing in the national tourism industry showed a status quo of high in the east, low in the west and middle in the center, which was consistent with the development trend of China’s economic development level. The fact that the western region lags behind the central and eastern regions in terms of the level of resource sharing was an inevitable result, which was determined by the combination of the constituent dimensions of resource sharing. First of all, the level of education development in the eastern and central regions far exceeds that in the western region. Secondly, the level of economic development in the western region consistently lags behind that in the eastern and central regions. Thirdly, the western region lags behind the other two regions in terms of the number of tourist attractions, accessibility, and other material resources. Lastly, the internet industry in the eastern and central regions has developed more strongly than that in the western region, and the level of regional information technology sharing is higher.

④ The level of resource sharing in the national tourism industry has increased year by year in the past five years.

The results of the analysis of data from 31 provinces in the past five years show that, on the whole, the level of resource sharing in the national tourism industry has shown a year-on-year increase in the five years from 2016 to 2020. The main manifestations are as follows. First, 30 provinces except Beijing have the lowest resource-sharing score in 2016. Second, twenty-nine provinces except Beijing, Jilin and Qinghai have the highest resource-sharing score in 2020. Third, except Beijing, Tianjin, Shanxi, Heilongjiang, Guangxi, Hainan, Shanxi, Gansu and Qinghai, the remaining twenty-one provinces have increasingly higher resource-sharing scores from 2016 to 2020. Fourth, the resource-sharing scores from 2019 to 2020 have the largest increase. From 2016 to 2019, China’s tourism scenery, capital investment, knowledge absorption, and information penetration increased steadily, which is an important reason for the year-on-year increase in the level of resource sharing in China’s tourism industry.

4.2. Discussion

Based on the above research results, the following measures should be focused on in order to enhance the level of resource sharing in the tourism industry:

First, enhance the importance of information technology and adapt to the requirements of the digital economy era. As a new productivity and production orientation in the era of the digital economy, informatization has become a pioneering force to lead innovation and drive development. Information technology has long penetrated into all walks of life, and the integration of the tourism industry and information industry is deepening. It is urgent to use information technology to expand the direction of tourism development and enhance the efficiency of tourism development from the point of view of the weighting ratio of resource sharing level. First of all, play the leading role of the government, vigorously pay attention to, support, encourage and help information technology to promote the development of the regional tourism industry. Vigorously develop and pay attention to the application of information technology in all aspects of the tourism industry to enhance the efficiency of resource allocation in the more developed areas of information technology. For regions and cities with lower levels of information technology development, governments at all levels and in all areas need to further give policy and resource elements. At the same time, establish a scientific research platform to increase the investment in the new generation of information technology and provide strong technical support for the development of the tourism industry. Secondly, the region should accelerate the establishment of a tourism industry information platform, promote intelligent management of information, and use information technology to achieve timely, timely accurate, dynamic management of tourism information, and enhance the level of tourism industry information. Establish a regional tourism database and build a data platform to break the difficulties of data silos, privacy leakage, and duplication of facilities, which can collect, standardize, clarify, store, manage, analyze, mine and present data [52]. Enhance the scope and depth of digital technology applications, improve the efficiency of all-factor combinations, realize de-platforming and de-centralization, and improve the scale efficiency of the tourism industry. Again, tourism enterprises should accelerate the construction of information technology infrastructure, realize digital production, operation and management, and improve tourism service efficiency. Reach cooperation with Travelport, Travelocity, Expedia, Ctrip, Qunar, Tuniu and other well-known online travel service providers to achieve precise marketing by targeting target customers with the help of platform resources. In addition, vigorously study and penetrate the digital economy era digital to technology to shorten the service process, improve the quality of product supply, and build a shared resource system for tourism.

Second, strengthen basic support in accordance with local conditions, and bring in talents to stimulate economic vitality in China, which as a large country with a large population, has been adopting a rough economic development approach for many years. There is a serious imbalance in economic, educational and technological relations between regions. Therefore, it is imperative to strengthen regional basic support according to local conditions and narrow the gap between economic, educational and technological development. First, government departments should fully grasp their role as guides in resource sharing in the tourism industry, grasp and promote regional resource-sharing elements in a reasonable and orderly manner according to the development status and conditions of their provinces, and formulate relevant policies to improve the level of resource sharing. For example, Beijing is rich in capital resources but low in material resource sharing, so it can make use of capital advantages to increase tourism industry investment and develop Beijing’s proprietary tourism brands such as “Forbidden City” to effectively drive the development of the regional tourism industry. Zhejiang and Jiangsu, where the level of information resources sharing is at the leading level nationwide, can make full use of the internet to spread fast and wide audience characteristics of marketing regional tourism characteristics. Secondly, constantly cultivate high levels of talent in the tourism industry, and promote the flow of high-level talent to the western region. Tourism-related departments formulate talent demand plans according to the requirements of the times and establish tourism discipline research centers. Cultivate emerging talents with new-age information technology literacy, digital communication literacy, statistical analysis literacy, and philosophical and social science literacy. Integrate internet technology to build a platform for nurturing and employing talents, using internet technology as a fulcrum to expand the practice system of tourism nurturing. Use technology as a support to share the current situation of talent resources and build a perfect talent service platform. The western region is not attractive enough for talent due to economic development and other factors, and the degree of internationalization, marketization and regionalization of industrial talents is not high. Enhancing market openness, revitalizing talent introduction methods, strengthening talent introduction efforts, and improving talent welfare treatment can effectively break the current dilemma. Finally, grasp the tourism dividend and realize the common construction and sharing of the tourism economy. Seize the opportunity of the end of the epidemic residents’ high demand for tourism, based on regional tourism characteristics, vigorously develop the tourism economy and promote regional economic growth. Improve the tourism benefit distribution mechanism, explore the benefit distribution pattern of tourism participating subjects, realize the development of the regional tourism economy virtuous cycle, and enhance the width of tourism funds and resources sharing.

Author Contributions

Conceptualization, X.C. and X.L.; methodology, X.L.; software, X.L.; validation, X.C. and X.L.; formal analysis, X.L.; investigation, X.C. and X.L.; resources, X.C.; data curation, X.L.; writing—original draft preparation, X.L.; writing—review and editing, X.C.; visualization, X.L.; supervision, X.C.; project administration, X.C.; funding acquisition, X.C. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

The research did not involve human or animal subjects.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data in this article were obtained from the official website of the National Bureau of Statistics (http://www.stats.gov.cn/), the Ministry of Culture and Tourism of the People’s Republic of Chinese (http://www.mct.gov.cn/) as well as the websites of provincial (cities and autonomous regions) governments or tourism bureaus.

Conflicts of Interest

The authors declare no conflict of interest.

Footnotes

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Figures and Tables

Figure 1. Conceptual model of resource sharing.

Figure 2. Resource sharing scores of 31 provinces (municipalities and autonomous regions) from 2016 to 2020.

Table 1

Definition of the concept of resource sharing by domestic and foreign scholars.

Author (Year)	Research Perspective	Concept Definition
Kent (1979) [19]	Membership	A reciprocal companionship, that is, a companionship in which each member owns something that can be used by other members and each member is willing to share that thing with other members
Qi Yong, et al.(2013) [21]	Economics	Under the role of government guidance and mechanism arrangement, the government fully mobilizes the enthusiasm of each participating subject to promote deep cooperation in different fields and industries, and then realize the integration, integration, opening and sharing of resources
Marshall (2018) [20]	Industrial cooperation	As a social phenomenon, emphasizing that it is a group behavior of reallocating valuable resources centered on interests
Li Ruo-chi(2021) [22]	Digital economy	Relying on the Internet to break the phenomenon of resource silos, coordinate, interoperate, disseminate and share information resources, and improve the efficiency of resource utilization

Table 2

Resource classification perspective.

Scholars	Basis of Classification	Classification Viewpoint
Amit and Schoemaker(1993) [23]	Resourcecharacteristics	Productive resources, instrumental resources
Grant (1991); [24]Wilson (2002) [25]	Nature ofresources	Financial resources, physical resources, technological resources, goodwill resources, human resources, and organizational resources
Galbreath (2005) [26];Hall (1992) [27]	Resource form	Resource form Tangible resources, intangible resources
Zhao Daozhi,Sun Jianyong(2007) [28]	ResourceFunction	MICK resources: material resources, information resources, financial resources, knowledge resources

Table 3

Tourism industry resource sharing evaluation index system.

Target Level	Criteria Level	Indicator Level	Unit	Nature
Materialresourcessharing	Public infrastructure	M1: Railway mileage	km	Positive
		M2: Road mileage	km	Positive
	Industrial material resources	M3: A-class scenic spots	pcs	Positive
Informationresourcessharing	Digital application level	I1: Internet penetration rate	%	Positive
Capitalresourcessharing	Industrial capital	F1: Fixed assets of star-ratedhotels million	ten thousand yuan	Positive
	Urban economy	F2: Tertiary industry income to GDP ratio	%	Positive
Knowledgeresource sharing	Knowledgecreation	K1: R&D personnel full-timeequivalent	person/year	Positive
		K2: Number of undergraduatestudents	person	Positive
	Knowledgeabsorption	K3: Number of patents granted	pcs	Positive

Note: Internet penetration rate = Internet broadband access users (10,000 households)/resident population (10,000 people); tertiary industry income to GDP ratio = tertiary industry value-added (billion yuan)/gross regional product (billion yuan).

Table 4

Rotated factor load matrix.

Dimension	Indicator Layer	FactorLoadings	Explained Total Variance	Cumulative %
Knowledge resourcesharing	K1: R&D personnel full-time equivalent	0.930	26.827%	26.827%
	K2: Number of undergraduate students	0.675
	K3: Number of patents granted	0.876
Materialresourcessharing	M1: Railway mileage	0.804	26.182%	53.009%
	M2: Road mileage	0.814
	M3: Star-rated scenic spots	0.736
Capitalresources sharing	F1: Fixed assets of star-rated hotels million	0.849	16.661%	69.669%
	F2: Tertiary industry income to GDP ratio	0.799
Informationresourcessharing	I1: Internet penetration rate	0.922	12.651%	82.320%

Factor extraction method: principal component analysis. Factor rotation method: orthogonal rotation method with kaiser criterion. KMO = 0.686. Sig. = 0.000. Percentage of variance explained by the four factors cumulatively = 82.320%.

Table 5

Weighting and ranking of the indicator system.

Dimension	Indicator Layer	WeightingFactor	Total Weighting	Ranking
Knowledgeresourcesharing	K1: R&D personnel full-time equivalent	22.78%	57.44%	1
	K2: Number of undergraduate students	7.81%
	K3: Number of patents granted	26.85%
Materialresourcessharing	M1: Railway mileage	7.47%	25.1%	2
	M2: Road mileage	7.25%
	M3: Star-rated scenic spots	10.38%
Capitalresourcessharing	F1: Fixed assets of star-rated hotels million	13.56%0.71%	14.27%	3
	F2: Tertiary industry income to GDP ratio
Informationresourcessharing	I1: Internet penetration rate	3.19%	3.19%	4

Table 6

Average score of resource sharing among 31 provinces in the past five years.

Year/Year	2016	2017	2018	2019	2020
Average score/points	0.1472	0.1830	0.1873	0.2052	0.2445
standard deviation	0.0811	0.0999	0.1102	0.1158	0.15

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