Evaluation Of Tourism Competitiveness Research Articles

Z-Number TODIM-EDAS Decision-Making Framework for Cultural Tourism Competitiveness Evaluation in the Yellow River Basin

Cultural tourism, as a new and highly knowledgeable form of tourism, is gradually replacing traditional tourism and becoming the core competitiveness of tourism industry development in regions with abundant cultural tourism resources. Culture endows tourism with new connotations, and achieving the integration and development of cultural and tourism industries is of great significance for enhancing the competitiveness of China's cultural tourism industry. The cultural tourism competitiveness evaluation under the background of rural revitalization is a MADM. TODIM and EDAS technique was employed to manage MADM. The Z-number is employed as a tool for portraying uncertain information during the cultural tourism competitiveness evaluation in the Yellow River basin under the background of rural revitalization. In this work, the Z-number TODIM-EDAS (ZN-TODIM-EDAS) technique is cultivated to manage the MADM under Z-number. Finally, a numerical study for cultural tourism competitiveness evaluation in the Yellow River basin is conducted to verify the ZN-TODIM-EDAS technique.

Does location affect the mechanism of tourism competitiveness? Evidence from machine learning analysis

Evaluation of tourism competitiveness is crucial for the development of destinations. However, a research gap exists in comprehending the spatial variances in the factors that influence tourism competitiveness. This study aims to fill this gap by empirically investigating the spatially heterogeneous effects of determinants related to tourism competitiveness. To achieve this, we utilized multi-source data, geographically neural network weighted regression, and Shapley additive explanations. The results revealed that market demand, physiography, and attractions are the most significant factors contributing to tourism competitiveness. Furthermore, the relative importance of these influencing factors varies across locations, based on different destination types, market contexts, and resource characteristics. These findings provide valuable implications for policymakers to enhance destination competitiveness through adopting localized strategies.

Evaluation model of urban tourism competitiveness in the context of sustainable development.

In the contemporary context marked by globalization and the growing prominence of sustainable development, assessing urban tourism competitiveness has emerged as a crucial research domain. This paper aims to develop a comprehensive model for evaluating city tourism competitiveness, grounded in the principles of sustainable development. The model incorporates factors such as city tourism resources, environmental considerations, economic aspects, and societal factors. This holistic approach seeks to offer valuable insights for the city tourism industry. The study conducts a thorough analysis of current research both domestically and internationally, highlighting gaps and articulating the objectives and significance of the research. Employing a machine learning-based empowerment method, the paper determines the significance of evaluation indices and utilizes the Topsis method for assessing urban tourism competitiveness. Distinguishing itself from traditional evaluation methods, this model integrates the principles of sustainable development throughout the evaluation process, with environmental, social, and economic sustainability serving as pivotal evaluation indicators. Empirical analysis involves the evaluation of tourism competitiveness for select cities, facilitating inter-city comparisons. Results from empirical studies demonstrate the model's effectiveness in evaluating urban tourism competitiveness, providing targeted developmental recommendations for urban tourism.

Coupling and interaction mechanism between green urbanization and tourism competitiveness based an empirical study in the Yellow River Basin of China

Exploring the spatial coupling relationship and interaction mechanism between green urbanization (GU) and tourism competitiveness (TC) is of great significance for promoting urban sustainable development. However, the lack of research on the interaction mechanism between GU and TC limits the formulation of effective environmental management policy and urban planning. Taking 734 counties in the Yellow River Basin (YRB) as the study area, this paper analyzes the spatial coupling relationship between GU and TC on the basis of comprehensive evaluation of GU and TC. Then, the interactive mechanism between GU and TC is systematically discussed, and the synergistic development strategy of the two is proposed. The results show that the GU level presents a multicore circle structure, with provincial capitals, prefecture-level urban districts and economically developed counties in east-central regions as high-value centers. The TC at county scale presents a multi-center spatial structure. Additionally, there is a significant positive spatial coupling between GU and TC in the YRB. The analysis further reveals that green urbanization level, social progress, population development, infrastructure construction, economic development quality, and eco-environmental protection has a observably influence on TC. Tourism competitiveness, service competitiveness, location competitiveness, resource competitiveness, market competitiveness, environmental influence, and talent competitiveness has a observably influence on GU. TC can promote GU, and the improvement of green urbanization level can support the development of tourism competitiveness. According to the spatial zoning method, 734 counties are divided into 6 categories, and the coordinated development strategy of GU and TC for each type of district is proposed.

Tourism Competitiveness Evaluation Model of Urban Historical and Cultural Districts Based on Multi-Source Data and the AHP Method: A Case Study in Suzhou Ancient City

Urban historical and cultural districts, serving as multi-functional compounds integrating cultural preservation, consumer experience, and economic growth, are increasingly becoming the preferred choice for in-depth tourism under the trend of historical heritage protection and consumption upgrading. Due to the complexity of the construction purpose, inherent functions, and operational management of historical districts, scientifically and rationally evaluating them poses a challenge. This paper attempts to construct an evaluation method for the tourism competitiveness of urban historical and cultural districts based on multi-source data and the Analytic Hierarchy Process (AHP) method. First, based on the model of destination competitiveness and combined with literature research and open-ended expert interviews, an evaluation framework for the tourism competitiveness of urban historical and cultural districts is established, using the AHP method to calculate the specific weights of each evaluation indicator. Then, the corresponding data sources for each indicator and the data processing and calculation methods are further clarified. To verify the effectiveness of the proposed evaluation model, this paper selects three key historical and cultural districts in Suzhou City, calculates the tourism competitiveness of each district based on the proposed model, and collects tourist satisfaction surveys from the three districts for cross-validation with the evaluation results. The experimental results show that the evaluation model is reliably effective in assessing the cultural, commercial, and tourism service aspects of historical districts, thereby providing a theoretical basis for future tourism decision-making information systems and practical applications of historical districts.

Creative Tourism Competitiveness in Chongqing City Using Diamond Model

The development of creative tourism is of great importance to the economic growth of cities. As the only mega-city in western China, the development status and competitiveness of creative tourism in Chongqing city are worth analyzing. This paper uses Porter’s diamond model to analyze the competitiveness of creative tourism in Chongqing; it uses AHP hierarchical analysis and constructs a creative tourism competitiveness evaluation system through expert interviews to compare the competitiveness of creative tourism in Chongqing and Chengdu city to verify the accuracy of the evaluation system, and finally discusses the issues that need attention in enhancing the competitiveness of Chongqing’s cultural and creative tourism development.

Optimization of Tourism Management Based on Regional Tourism Competitiveness Evaluation: Evidence from Ningxia Hui Autonomous Region, China

This paper evaluated the regional tourism competitiveness of 22 county-level administrative regions in Ningxia Hui Autonomous Region, China. The study analyzed the connotation of regional tourism competitiveness from the perspectives of resources and economic and environmental benefits, and established an evaluation index system for comprehensive competitiveness. The study used entropy weight TOPSIS to measure the level of tourism competitiveness in Ningxia, and used spatial association and hot and cold analysis to describe the spatial pattern of comprehensive tourism competitiveness in Ningxia. The results indicated that Lingwu City, Xixia District, and Huinong District have high comprehensive tourism competitiveness, while Jingyuan County, Haiyuan County, and Hongsipu District exhibit the weakest comprehensive competitiveness. The study also showed that regional economic development level competitiveness had the greatest impact on the comprehensive competitiveness of county tourism in Ningxia. The northern region and the southern region of Ningxia were the regions with high-high clusters and low-low clusters of tourism competitiveness, respectively. Based on the comprehensive evaluation results, the development level of tourism of Ningxia county was classified into four types: advanced development type, marginal dependence type, improved optimization type, and backward development type. Finally, the paper put forward targeted optimization suggestions in order to provide reference for Ningxia tourism functional zoning and high-quality development.

Big Data and Tourism Competitiveness Evaluation in the New Media Environment

The rapid development of science and technology has prompted human beings to continuously update the technical means of disseminating information. Nowadays, new media based on the Internet and mobile terminals have become an indispensable tool for the public to receive and disseminate information. Tourism informatization is an important means to promote the development of tourism and an important way to enhance tourism competitiveness. With the support of new media technology, the “audience” is gradually changing from the passive and silent “recipient of information” under the traditional media to the active intervener, which independently receives and feeds back information, and the flow of information is more free. New media has promoted the development of a “user-centered” communication model, presenting a situation in which “information receivers have the right to choose media, and channels have become the center of communication.” Studying the effect of regional tourism image dissemination under the background of new media and finding out the factors that affect the effect of tourism image dissemination under the background of new media are the magic weapon for the further development of the current tourism industry. These have completely overturned the traditional communication format. In the era of new media, what kind of changes the tourism image will bring in the process of shaping, dissemination, and promotion is a question worthy of our deep consideration. With the rapid development of information technology and the widespread use of modern communication equipment, human beings have entered the era of big data with the core value of mining data. At present, people no longer only use intuition and experience as the basis for making decisions, but more importantly, based on big data technology to analyze the relationship between data and then make scientific decisions. The advent of the era of big data has caused a corresponding change in the evaluation criteria for informatization of tourist destinations. Therefore, for tourism destinations, reexamining the evaluation criteria of informatization and establishing a reasonable evaluation index system have become a realistic problem in the development process of tourism destination information. Under this circumstance, strengthening the research on the evaluation of tourism destination information is of great significance to the healthy and rapid development of tourism destination informationization. This study proposes the background and significance of the research and discusses the relevant theoretical basis. The paper establishes three levels of indicators from the three aspects of core competitiveness, basic competitiveness, and environmental competitiveness and selects nonquantitative processing methods for data processing. After comparison, it comprehensively analyzes the tourism situation under big data. In connection with the actual situation under big data, it puts forward targeted countermeasures and safeguard measures for the improvement of tourism competitiveness under big data and provides reference for relevant departments to formulate relevant policies. Only government departments and relatives and friends have an average credibility of more than 3, and the average credibility of relatives and friends has reached 3.71.

Tourism Competitiveness Evaluation: Evidence From Mountain Tourism in China.

The evaluation of tourism competitiveness is an important tool for analyzing the potential of tourism in a specific context. Enshi Autonomous Prefecture (EAP) in China is selected as a case through which to explore the potential of mountain tourism and its competitiveness in the tourism industry. This study develops EAP’s mountain tourism competitiveness model focusing on three criteria: core competitiveness of mountain tourism, the economic environment’s competitiveness, and infrastructure competitiveness. Context-specific customized evaluation index has been applied to data collected from EAP Statistical Yearbook for 2005–2014. The study reveals that the value of EAP’s mountain tourism core competitiveness, economic and environmental competitiveness, and infrastructure competitiveness are 84.292, 13.4, and 2.308%, respectively. When tourism core competitiveness is increased by one unit, EAP’s mountain tourism competitiveness will increase by 0.84292 units. Similarly, when economic environment competitiveness is increased by one unit, EAP’s mountain tourism competitiveness will increase by 0.134 units. EAP’s mountain tourism competitiveness increases by 0.02308 units when infrastructure competitiveness increases by one unit. The major reasons for low levels of competitiveness were lack of awareness of the county authority, a low level of cooperation, and weak infrastructure. The recommendations from the study’s findings are as follows. Firstly, the county authority should appropriately improve the relationship between competition and cooperation, maintaining cooperation in competition, and competition in cooperation. Secondly, the county authority should strengthen communication by establishing an effective coordinated mechanism. Thirdly, the county authority should improve the sense of cooperation and jointly develop the mountain tourism market. Fourthly, the county authority should improve the construction of tourism infrastructure and break down the barriers to tourism cooperation. The study’s findings help develop a “win-win” cooperation mechanism within the competition and support the sustainable development of the mountain tourism industry while reducing poverty and promoting the revitalization of the mountains of China.

Rural Tourism Competitiveness and Development Mode, a Case Study from Chinese Township Scale Using Integrated Multi-Source Data

Tourism has been seen and adopted as a vital means for achieving rural economic and social revitalization worldwide without harming sustainable development principles. For China, the evaluation of rural tourism competitiveness at the township level is essential for planning and developing the tourism industry as a basic administration and economic unit, but there is not enough research due to the lack of applicable data and systematic methods. Therefore, this study constructed a town-level rural tourism competitiveness evaluation and development mode classification model based on the modified Michael Porter’s Diamond Model using integrated multi-source data. By taking the 1806 township units in Henan Province, China as examples, we conclude four different modes based on the level of the comprehensive score and industrial internal balance (i.e., balanced development mode with multiple advantages, related and supporting industries driving mode, ecological resource-led mode, and rural landscape experience mode). Policy suggestions for the optimization of the rural tourism industry for Henan are discussed based on the results.

Evaluation of tourism competitiveness and mechanisms of spatial differentiation in Xinjiang, China.

Evaluation of tourism competitiveness is useful for measuring the level of regional tourism development. It is of great importance to understand the advantages and disadvantages of tourism development correctly and formulate corresponding development strategies. To investigate tourism competitiveness, this paper established an evaluation index system, including tourism development competitiveness, tourism resource competitiveness, and tourism-support competitiveness, for 14 prefectures and cities in Xinjiang in China. The characteristics and laws of spatial differentiation were analyzed. Factor analysis was applied to examine the spatial differentiation of regional tourism competitiveness. The results showed an obvious spatial differentiation in tourism competitiveness among the 14 prefectures and cities. In terms of development competitiveness, Yili and Urumqi constituted the spatial center, followed by Changji, Altay, and Ba Prefecture. As the provincial capital, Urumqi has political, economic, cultural, transportation, and geographic advantages, but its competitiveness is not prominent in terms of monopoly and efficiency. In terms of resource competitiveness, Yili is the core attraction, while Urumqi, Kashgar, Altay, and Ba Prefecture are dominant attractions. With respect to supporting competitiveness, Bo Prefecture has high value, followed by Urumqi City and Aksu. Hetian and Ke Prefecture have the lowest values. The comprehensive competitiveness of tourism is centered on Yili. Urumqi and Bo Prefecture are subcenters, and Changji, Altay, Ba Prefecture, Aksu, and Kashgar are characterized as multi-polar competition areas. Using the KMO and Bartlett’s sphericity tests, the cumulative contribution variance of the eigenvalues of the eight factors extracted by the maximum variance rotation method was found to be 92.714%. Socio-economic conditions, tourism resources, infrastructure construction, regional cultural influence, ecological environment carrying capacity, tertiary industry development, tourism service level, and living security system are the main driving factors affecting the spatial differentiation of tourism competitiveness in Xinjiang. Analyzing the spatial evolution characteristics and the driving factors of the regional tourism competitiveness in Xinjiang, this paper seeks to promote the optimal allocation of tourism production factors in the macro regional system, and provide theoretical guidance and an empirical basis for the comprehensive and harmonic development of regional tourism.

Research on the Communication Strategy of History and Culture in Shaanxi Based on BP Neural Network Model.

Shaanxi is one of China's most important cradles of civilization. The main vein of Chinese culture is rich history and culture, and brilliant red culture embodies the essence of socialist core values. It is still relatively weak to deeply analyze the related research of Shaanxi Province's cultural province construction on the basis of studying the achievements of cultural development in foreign countries and China and combining with the reality of Shaanxi Province. In this paper, a BPNN (BP neural network) model is selected to study the comprehensive evaluation of tourism competitiveness of smart tourism cities, and the software is used to realize the simulation of the comprehensive evaluation system of tourism competitiveness of smart tourism cities, which more comprehensively and objectively reflects the level of comprehensive competitiveness of each city. It is believed that there are some problems in Shaanxi regional cultural communication, such as insufficient exploration of content resources, insufficient communication channels, and low audience awareness, hoping to provide ideas and reference for further exploring the promotion of cultural communication power.

Developing an Evaluation Model for Monitoring Country-Based Tourism Competitiveness

Using pillars and sub-index from the Travel and Tourism Competitiveness Index (T & TCI) to measure a destination’s competitiveness is popular. Still, its methodology underlying the calculation has been criticized. So the T&TCI Index has not been regarded as a reliable measure of a destination’s competitiveness. In this regard, this paper sought to set out a country-based tourism competitiveness evaluation model with various statistical methods to indicate how important tourism policy development has to design. We used data from an expert survey to examine the attributes and sub-attributes and shape the decision-making. We addressed a theoretical six-step procedure to ensure the evaluation model’s rigor in the model development context. The first was to do data collection. The second was to examine construct underrepresentation. The third was to examine common method bias. The fourth was to examine construct-irrelevant variances. The fifth was to evaluate intergroup consistency. And the sixth was to develop attribute weight. Our study showed that a country-based tourism competitiveness evaluation model encompassed 8 attributes and 28 sub-attributes. We identified cultural uniqueness, ecology and the environment as the two most important attributes. In the end, we addressed the practical contributions of this study and methods to policy-makers and researchers.

Design of Cruise Tourism Competitiveness Evaluation System in Port City

Cui, H., 2020. Design of cruise tourism competitiveness evaluation system in port city. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 1075–1078. Coconut Creek (Florida), ISSN 0749-0208.The key issue in the development of cruise industry as a new economic growth point relies on the competitiveness of cruise ports. Based on comprehensive consideration of the internal and external conditions of cruise ports, the paper constructs a competitiveness evaluation system of cruise ports. The results show that the ports of developed cities in China have reached a high level, but the level of ports in developing cities is still poor. Furthermore, suggestions on enhancing the competitiveness of cruise ports are put forward, including accurately positioning port functions, improving related supporting facilities, improving service levels and building distinctive port brands.

A Study on the Evaluation of Urban Tourism Competitiveness in Guangdong-Hong Kong-Macao Greater Bay Area

Aiming at the shortcomings in the existing research on tourism competitiveness, the article adjusted the regional tourism competitiveness evaluation index system and used the entropy method to quantitatively evaluate the tourism competitiveness of 11 cities in the Guangdong-Hong Kong-Macao Greater Bay Area from 2012 to 2018. The results show that the regional tourism competitiveness of Guangdong-Hong Kong-Macao Greater Bay Area differs significantly and can be divided into three levels. Hong Kong, Macau, Guangzhou, and Shenzhen generally have higher tourism competitiveness and are in the first rank; Zhuhai, Foshan, Huizhou, and Dongguan have average tourism competitiveness and are in the second rank; The tourism competitiveness of Zhongshan, Jiangmen and Zhaoqing is relatively weak, ranking third. Based on the conclusions of the study, the article puts forward relevant suggestions to enhance the tourism competitiveness of the Guangdong-Hong Kong-Macao Greater Bay Area, hoping to provide a reference for enhancing the tourism competitiveness of the Guangdong-Hong Kong-Macao Greater Bay Area and promote the construction of international tourism destinations in the Guangdong-Hong Kong-Macao Greater Bay Area.

Research on Regional Sustainable Development Based on Evaluation of Tourism Competitiveness of 21 Cities (States) in Sichuan Province

In accordance with the principles of systemic, hierarchical, and operability, this paper divides into tourism status competitiveness, tourism environmental competitiveness and tourism potential competitiveness to construct an evaluation index system for urban tourism competitiveness. Taking 21 cities in Sichuan Province as the research objects, the tourism competitiveness of each city was evaluated by factor analysis and grey correlation analysis. The evaluation results of these two methods were further evaluated by Kendall synergy coefficient test method. The consistency test and the combination evaluation were conducted, and the tourism competitiveness rankings of each city in Sichuan Province were given. Then, the system cluster analysis classified 21 cities into five levels, according to the evaluation results. Finally, some suggestions on the regional sustainable development in Sichuan Province were listed.

基于AHP法的晋商文化景观旅游竞争力评价

基于AHP法的晋商文化景观旅游竞争力评价

Urban tourism competitiveness evaluation system and its application: Comparison and analysis of regression and classification methods

Under the background of economic transformation, tourism is one of the most dynamic and promising tertiary industries. How to improve the competitiveness of tourism has become a new idea for industrial upgrading in various regions. This paper builds an evaluation system consisting of five major aspects, based on the data of 75 tourist destinations; then, uses cluster analysis to classify cities, and uses logistic regression, SVM and random forest methods to predict the tourism competitiveness of sample cities and compare the advantages and disadvantages of the two methods - classification and regression. From the results of the empirical test, the results of the classification method are generally better than the results of the regression, and in the classification method, the results of the SVM are better than the results of the random forest. In this case, the SVM model gives full play to its ability to solve the problem of nonlinear classification.

Development patterns and cooperation paths of tourism industry within the China–Mongolia–Russia Economic Corridor

Strengthening tourism cooperation in border areas along the China–Mongolia–Russia Economic Corridor (CMREC) are important and challenging, under “Belt and Road” (B&R) initiative. Research has constructed a tourism competitiveness evaluation model including three dimensions and based on six factors: natural resources, cultural resources, tourism market, social economy, traffic facilities, and policy support. The results show the spatial characteristics of tourism competitiveness ordered as Beijing–Tianjin–Hebei of China, Northeast China, Northwest China, Russian Siberia Federal District, Mongolia, Russian Far East Federal District, and Russian Ural Federal District. Data show that the average tourism competitiveness of the three areas in Northern China are 2.69 times those of the three Russian areas, and 1.74 times those of Mongolia; at the same time, the average tourism competitiveness of Mongolia is 1.54 times that of the three areas of Russia. Based on the evaluation result, this study proposes a theoretical framework for a competition–cooperation model for tourism within the CMREC. Cluster analysis shows that the seven areas are comprise of absolutely dominant regions, comparatively dominant regions and comparatively weak regions. Tourism strategies are proposed in this study, based on the theoretical framework for a competition–cooperation model.

The Application of selected multivariate statistical methods for the evaluation of tourism competitiveness of the Sudety communes

The Application of selected multivariate statistical methods for the evaluation of tourism competitiveness of the Sudety communes