Number Of Travel Agencies Research Articles

Spatiotemporal Evolution and Driving Forces of Tourism Economic Resilience in Chinese Provinces

This study focuses on the resilience of tourism economies in Chinese provinces, exploring their spatiotemporal evolution and driving forces as a crucial prerequisite for promoting the high-quality development of China’s tourism industry. We construct a resilience evaluation index system from four dimensions: resistance resilience, recovery resilience, reshaping resilience, and development resilience, using provincial tourism data from 2012 to 2022. The study employs Moran’s Index, kernel density estimation, and GIS technology to investigate the differentiation characteristics, spatial evolution processes, and spatial agglomeration characteristics of provincial tourism economic resilience in China. Finally, the GeoDetector model is used to analyze the driving factors. The findings are as follows: (1) Over time, most provinces and cities in China have shown varying degrees of improvement in tourism economic resilience, with different changes observed across the four dimensions. (2) Spatially, significant differences exist between provinces, with better resilience in the east than in the west and in the south than in the north. (3) Regionally, while no polarization is observed, there is a distinct differentiation between high and low-value areas. (4) Regional linkages indicate the presence of interregional associations in China’s tourism economic resilience, with non-uniform distribution of cold and hot spots. (5) Key driving factors include per capita railway mileage, domestic tourism revenue, the number of travel agencies, and the number of employees in accommodation and catering. Under the backdrop of rapid tourism economic development, improving infrastructure construction and enhancing the comprehensive strength of the tourism industry is vital for boosting tourism economic resilience.

Research on the Factors Influencing Tourism Revenue of Shandong Province in China Based on Uncertain Regression Analysis

According to the analysis of historical tourism data, it was found that tourism revenue is influenced by multiple factors, and there exists a linear relationship between these factors and tourism revenue. Therefore, this paper employs a linear regression model to investigate the factors influencing tourism revenue. However, research on tourism data has found that the disturbance term of the linear regression model is not frequency-stable. This indicates that the disturbance term should be an uncertain variable rather than a random variable. Therefore, this paper adopts an uncertain linear regression analysis model and employs the tourism data of Shandong Province in China from 2011 to 2020 as the sample to investigate the factors influencing tourism revenue. The study provides parameter estimation and residual analysis of the model, as well as predictions and confidence intervals of tourism revenue. Additionally, through an uncertain hypothesis test, it was verified that the adopted model fitted the relevant tourism data well. The results show that factors such as the number of travel agencies, railway length, domestic tourist numbers, and per capita disposable income of urban residents have a significant impact on tourism revenue. Based on the study, recommendations and measures for improving tourism revenue of Shandong Province are proposed.

The Role of Tourism in Promoting the Urbanization of Ethnic Border Areas: A Case Study of Xishuangbanna

Taking Xishuangbanna Dai Autonomous Prefecture, a typical ethnic border area with rapid tourism development, as an example, this study uses a coupling coordination degree model to quantitatively analyze tourism and urbanization, two subsystems in Xishuangbanna, and measure the level of coordinated development between tourism and urbanization in Xishuangbanna. This study provides a theoretical basis for building famous tourist cities and for improving the urbanization efficiency and level in areas such as Xishuangbanna with abundant tourism resources but insufficient urbanization. The following results were obtained: (1) Xishuangbanna’s tourism plays a strong role in promoting urbanization, and its tourism urbanization response coefficient, tourism industry location entropy, and tourism urbanization level indicator all show clear upward trends; tourism has become a local advantage industry and has a significant positive correlation with urbanization. (2) In the evaluation system for tourism urbanization quality, the weights are ranked in the order of social indicators > economic indicators > population indicators > spatial indicators > eco-environmental indicators; over time, social indicators and economic indicators show clear fluctuating upward trends, population indicators fluctuate greatly, and spatial indicators and eco-environmental indicators fluctuate little. (3) The top five indicators influencing tourism urbanization are the number of the incoming individuals, the number of travel agencies, the number of corporate enterprises in the catering industry, the forest coverage rate, and the number of ethnic minority villages. (4) In the evaluation of the coupling coordination degree, the comprehensive evaluation indicator is low, resulting in an overall low coupling coordination degree of tourism urbanization quality in Xishuangbanna, and three types of coupling coordinated development (i.e., severe, moderate, and mild imbalances) are observed.

A Hierarchical Analysis Structure Model for the Integration and Optimization of Sports Industry Digitalization and Tourism Industry

Abstract To promote the integrated development of the sports and tourism industry, create new formats, and drive the development of five happiness industries as tourism, culture, sports, health, and elderly care, promote local industrial layout and high-quality development, the author proposes an optimization model for the integration of sports industry digitalization and tourism industry. Based on the coupling coordination theory and fusion theory, the author chooses city A as the research case, through the coupling analysis method, the integrated development level of the sports industry and the tourism industry in City A was discriminated, and the dynamic factors and hindering factors affecting the coupling were explored, and the reasons were analyzed. The results show that the index weights of the two system layers, namely, the sports and tourism industry system layers, are 0.5 and 0.5, respectively. The top five weighted indicators are The number of sports-related enterprises, the number of tourist attractions, the number of travel agencies, the number of sports professionals and the number of domestic tourists received; The results of the coupling coordination degree show that in terms of degree D, there is an obvious trend of long-term stable linear increase and then a small decline, from 2010 to 2019, the D value increased from 0.28 to 1. Conclusion: The model is suitable for the practical framework of the development trend of the sports tourism industry model.

ANALYSIS OF THE EFFECT TOURISM SECTOR AND OPEN UNEMPLOYMENT ON ECONOMIC GROWTH IN BALI PROVINCE

Bali is one of the most popular tourist destinations by domestic and foreign tourists in Indonesia. Because many tourists visit, many Balinese people are looking for a livelihood in the tourism sector such as being a tour guide, working in the hospitality sector, culinary, tourist trips etc. During the COVID-19 pandemic, many workers in the tourism sector lost their jobs, increasing the open unemployment rate in Bali Province. With a high unemployment rate, people's welfare decreases so that it can affect economic growth in Bali Province. This study aims to see the Effect of the Tourism Sector and Open Unemployment on Economic Growth in Bali Province. The variables of the independent of this study are the number of tourists visiting, the number of hotel, the number of travel agencies and the open unemployment rate. Meanwhile, the dependent variable used is the economic growth of Bali province. The analysis tool used is Panel Data Regression, from the test obtained the value of the coefficient of determination R2 of 65.80%, this shows the magnitude of the influence of independent variables on dependent variables. The results of the study concluded that simultaneously the number of tourists, the number of restaurants, the number of tourist travel agencies, and the unemployment rate influenced economic growth. This is seen from the prob value of F-statistics of 0.0000. Meanwhile, the results of the t test show that the results are influential and significant for each independent variable against the dependent variable.

Research on the Input-output Efficiency of Tourism Industry in Anhui Province based on DEA Model

As a pillar industry in the tertiary industry, the efficiency of its input and output is crucial to social and economic development. This paper takes Anhui tourism industry as the object of model validation, selects the number of star-rated hotels, the number of travel agencies and the number of tourism employees as input indicators, and the domestic tourism revenue and international tourism foreign exchange revenue of Anhui Province as output indicators, and analyzes the evaluation results of tourism input-output efficiency of Anhui Province from 2005 to 2017 using DEA model. The results of the study show that the technical efficiency and scale efficiency of Anhui tourism industry both show a wave-like rise, and should continue to optimize the allocation of resources and give full play to the advantages of tourism.

Fluctuations in the Number of Stores by Industry During the COVID-19 Pandemic Based on Japanese Phone Book Entries

Currently in Japan, summaries of the number of bankruptcies due to the spread of COVID-19 can only be obtained from surveys conducted by a few research firms targeting particular companies. In this study, we used Japanese telephone directory data containing detailed information on the location and industrial category of stores/facilities nationwide in an effort to infer the influence of COVID-19 on businesses in Japan. We analyzed the temporal change in the number of stores before and after the COVID-19 outbreak. Among other findings, the analysis revealed that the number of travel agencies and facilities offering karaoke and other forms of entertainment declined significantly after the outbreak in some prefectures, with the largest declines in Ibaraki, Osaka, and Hyogo prefectures, and a relatively small decline in Tochigi prefecture. Among the stores and facilities categorized as restaurants and travel-related services, the decline was particularly significant in urban areas such as Tokyo and Osaka prefectures.

An Examination of the Variables Affecting the Growth of the Tourist Sector in Guizhou Province

The tourist industry is consistent with the new development paradigm and plays a crucial role in regional economic growth. At the same time, several areas of China have developed tourism as a vital industrial pillar. Analysing and examining the elements that affect the tourist industry in this setting has significant theoretical and practical implications. The dependent variable for this study is the tourist income for Guizhou Province from 2006 to 2019. A total of Eight variables are chosen as independent variables, including the distance travelled by rail and by road, the number of civil flights, the number of travel agencies, the overall number of tourists, the disposable incomes of both urban and rural residents, the number of tertiary industry workers, and the volume of foreign direct investment. The eight independent variables are discovered to favourably impact tourist revenue through the use of factor and regression analysis. Based on the study’s findings, this article suggests that (1) crisis management should be strengthened, and tourist businesses should be advised to become more active rather than passive, (2) infrastructure development should be enhanced for supporting tourism and directing the growth of the rural tourist industry in the area, and (3) the use of digital technologies should be enhanced and the speed of building intelligent tourism should be increased.

Analysis of The State of The Tourism Industry in Russia аnd The Direction of Its Development

The purpose of the study. The purpose of the work is to assess the state of the tourism industry using statistical methods, analysis of scientific literature and identification of the main trends and promising directions of its development. The article is devoted to the possibilities of statistical analysis in the conditions of limited statistical information on Russia in relation to the tourism industry.Materials and methods. The following scientific methods are used in the article: analysis of scientific literature, analysis of dynamics and structure, coefficient analysis, correlation and regression analysis, graphical analysis, forecasting of indexes of the tourism industry. The analysis of Russian and foreign literature allowed us to formulate conclusions about modern methods of analysis used to assess the problems of the tourism industry. The analysis of the indexes in dynamics made it possible to identify and describe the main trends in the development of tourist flows, the volume and cost of selling tourist packages. The calculated structure of collective accommodation facilities showed their percentage ratio during the study period and the change in their shares. The use of correlation analysis made it possible to establish the closeness and direction of statistical relationships between individual factors affecting the state of the industry and the volume of tourist trips. A multiple regression model based on indexes characterizing the dynamics of prices for tours sold, the state of the transport sector and the food sector methodology is created. Based on the Box–Jenkins methodology, predictive models were created and medium-term forecasts were calculated for variables characterizing the number of tourist firms and the number of sanatorium-resort organizations and recreation organizations. The initial data for the study were Rosstat data in annual and spatial dimensions for the period 2011–2020.Results. The article highlights the main directions of research in the field of tourism industry, presented in the works of domestic and foreign authors. The foreign approach to its assessment is carried out through evidence-based methods. The research of domestic authors is more focused on the implementation of program-targeted methods and the identification of problems of assessment and prospects for the development of the industry in the Russian Federation. The analysis of the dynamics of inbound and outbound tourist trips showed a tendency to decrease their total number, which is due to the low level of tourist attractiveness, shocks and restrictive measures caused by the SARSCoV-2 pandemic, the tense foreign policy situation. It is established that the most active external tourist flows of the Russian Federation are observed with neighboring countries. Correlation analysis showed the presence of a statistical relationship between the number of trips made with the state of the transport infrastructure and the cost of the tour packages sold. The trend of growth in the implementation of tour packages in Russian destinations and a reduction in their number in foreign destinations, which is due to an increase in the disparity between the average cost of tour packages depending on the destination of the holiday, is established. The carried out regression analysis procedure showed the relationship between the number of tourist packages sold to citizens of the Russian Federation with the variables “average cost of sold tourist packages” and “fleet of aircraft”, which indicates the need to develop transport infrastructure and optimize the cost of recreation. Forecast calculations on the number of travel agencies and sanatorium-resort organizations have shown their decline in the medium term, which indicates the need to take appropriate measures to activate tourism entrepreneurship.Conclusion. Based on the results of the statistical analysis, the analysis of scientific literature and the content of tourism development programs in the Russian Federation, the authors identified common problems and directions of development of the industry. The main problems of the industry are the following: weak tourist attractiveness, insufficient development of tourist and transport infrastructure, lack of accommodation facilities aimed at mass tourists, low quality of domestic accommodation services, and high cost of foreign tours. The priority directions of the development of the domestic tourism business are related to: the introduction of modern digital technologies, active advertising of domestic tourism, optimization of the costs of tourism industry enterprises, activation of state support in difficult economic conditions.

Influencer marketing for tourism destinations

The influencer marketing is a strategy that uses the influence of prominent individuals in a certain field to drive consumers’ brand awareness or their purchasing decisions. These individuals do not have to be celebrities and they just need to create contents on a certain topic as well as have a fanbase’s support on social media. Travel influencers are people who create and share travel-related contents in forms, including blogging, sharing photos and videos, giving reviews or making comments on a service, a product or a tourist destination. Although it has a short history, this form of marketing is showing the outstanding effectiveness, as evidenced by the data on tourism industry growth, statistics on the number of travel agencies or destination marketing agencies, which are increasingly choosing to partner with travel influencers for destination marketing campaigns. In addition, the tourism industry practice has witnessed some successful destination marketing campaigns in cooperation with social media influencers, further proving the effectiveness of this form. There are some reasons for the success of these campaigns, in which the reliability, objectivity, and proximity in the way the brand message is conveyed by favorable influencers are among the outstanding advantages. This topic is still quite new in the research community, so more elaborate works are needed to increasingly shape and be able to come up with appropriate application models.

THE IMPACT OF THE COVID-19 PANDEMIC ON THE ACTIVITIES OF THE TOURISM INDUSTRY IN UKRAINE

The purpose of writing this article is to analyze and assess the impact of the global pandemic caused by COVID-19 on the activities of the tourism industry in Ukraine in general and by region. The article examines the impact of the COVID-19 pandemic on the number of travel agencies and tour operators in Ukraine and found that the number of tour operators and travel agents in Ukraine in 2020 compared to 2019 decreased by 12.9%. In terms of oblasts, the most noticeable decrease took place in Chernivtsi oblast - by almost 28%. But it should be noted that in some areas the reduction in the number of tour operators and travel agents has not occurred, and in some their number has even increased. The consequences of the COVID-19 pandemic on the number of tourists served by tour operators and travel agents were considered and it was found that their total number has more than halved, by 61.5%. Moreover, the most noticeable decrease in tourists served by tour operators and travel agents occurred in the number of incoming (foreign) tourists - by 86.2%. The situation is better with outbound and domestic tourists: their number decreased by 61.5% and 57.2%, respectively. Estimation of the data on the number of tourists served by tour operators and travel agents who traveled for different purposes, found that the largest number of tourists travel for leisure and recreation, despite the overall decrease in the number of tourists. The study revealed that in Ukraine in 2020 compared to 2019 there is a significant decrease in tourist flows, especially foreign, the indicators of which were previously low. This situation has led to a decrease in the number of tour operators and travel agents serving tourists in the market of tourist services. The directions of work that may be favorable for the exit of the tourism industry of Ukraine from the crisis caused by the spread of COVID-19 were outlined. First, the support of domestic tourism will not allow the decline of tourism in Ukraine in general and will provide a profit for both tourism enterprises and the economy of Ukraine. Secondly, it is necessary to create a balance between the price and quality of tourist services in Ukraine, which will be available to the local population and generate income, which will play an important role in the development of the tourism industry of Ukraine. Thirdly, a special place in the development of tourism today is the observance of sanitary and hygienic conditions and the possibility of less contact between tourists, which will attract the attention of tourists who are wary of the spread of infections. Fourth, in today's conditions it is necessary to actively implement Internet technologies for the dissemination of advertising information, which will contribute to greater awareness of tourists about travel services in quarantine.

DOMESTIC TOURISM MARKET: ANALYSIS AND FORECAST

In a pandemic, the economy must adapt to new conditions in order to minimize the risks that arise. One of the areas of the economy that is most affected by the pandemic is travel and tourism (T&T). If at the beginning of the 21st century tourism showed high indicators of development, then in 2020 the T&T sphere approached the limit of survival, according to many experts’ estimates. An effective way to preserve the country’s tourism potential under these conditions is to develop domestic tourism. This research aims to analyse the development indicators of the tourism sector in Ukraine and assess the prospects for the development of the domestic tourist services market based on a correlation and regression model. The article presents an analysis of the main indicators of tourism development in Ukraine. In particular, these are such indicators as the capital investment volume, the dynamics of income from the provision of tourist services, and the total contribution of tourism to GDP. A structural analysis of the dynamics of tourist flows in Ukraine for 2013-2019 has been carried out. A significant advantage of outbound tourism in comparison with domestic tourism has been revealed. A regression model has been constructed. This model reflects the relationship between the number of domestic tourists and such factor characteristics as: transport passenger turnover, average salary level and the number of travel agencies. The inverse relationship between the dynamics of the number of domestic tourists and the number of travel agencies was revealed. It was concluded that it would be advisable for the state to encourage small forms of management in the tourism industry, which are focused on creating tourist products of local significance. A direct relationship between the average salary, passenger traffic and the number of domestic tourists was proved. The calculated forecast indicates the possibility of increasing the number of domestic tourists in Ukraine in 2020 by 6%, in 2021 by 6%, in 2022 by 5%.

Analysis on the influencing factors of China&apos’s domestic tourism economic development

Tourism, as China&apos’s tertiary industry, plays an important role in China&apos’s economic development. This paper selects the relevant statistical data of China&apos’s tourism industry from 1994 to 2019, and establishes a multiple linear regression model to analyze the impact of seven factors, including the number of domestic tourists, per capita GNP, railway mileage, highway mileage, airline mileage, the number of travel agencies, and the number of star hotels, on China&apos’s tourism economic development. The results show that the number of railway miles, the number of domestic tourists and the number of star hotels have a significant impact on the development of China&apos’s tourism economy, among which the increase of the number of domestic tourists has the greatest impact on the development of China&apos’s tourism economy.On the basis of the above empirical evidence, this paper puts forward some suggestions to promote the development of China&apos’s tourism industry, such as solidly promoting the integration of domestic tourism resources, giving full play to spillover effect of resource integration, strengthening tourism infrastructure and improving residents&apos’income level.

Туризм и экономический рост: региональный аспект

<span>Цель статьи</span><span class="myHorizontalScaleForEmDashSpaceBefore"> </span><span>–</span><span class="myHorizontalScaleForEmDashSpaceAfter"> </span><span>оценка влияния туристических потоков и факторов, связанных с туристической индустрией, на экономический рост регионов РФ. Методология исследования</span><span class="myHorizontalScaleForEmDashSpaceBefore"> </span><span>–</span><span class="myHorizontalScaleForEmDashSpaceAfter"> </span><span>регрессионный анализ ряда статистических показателей. В результате исследования было выявлено положительное влияние величины турпотоков на экономическое развитие регионов. Кроме того, положительно влияют на величину ВРП (из ограниченного числа выбранных показателей) инвестиции в основной капитал, рассматриваемые за предыдущий год, и объем платных туристических услуг, оказанных населению.</span>

An Analysis of Domestic Tourism Consumption Based on R Software

R is a software system which can be used for data processing, calculation and mapping. The syntax of this language is superficially similar to C, but semantically it is functional programming language. It is widely used in statistical analysis. So this paper used it to analyze China domestic tourism consumption data during 1999-2015, and analyzed the main factors affecting the consumption level of domestic tourism in China from residents’ disposable income, GDP, per capita consumption of tourists, tourists, the mileage of railways and the number of travel agencies. Finally it established and solved the multiple linear regression models, taking domestic tourism consumption as dependent variable and taking GDP, and per capita consumption of tourists, the number of tourists and the mileage of railways as dependent variables. The results show that there is significant positive correlation between domestic tourism consumption, GDP, per capita consumption of tourists, the number of tourists and the number of travel agencies.

Back-Propagation Neural Network Combined With a Particle Swarm Optimization Algorithm for Travel Package Demand Forecasting

Travel agency operation must be capable of judging tourism demands on the market to formulate procurement and sales plans. However, a number of travel agencies, lacking the ability to judge market tourism demand, take substantial risks in their purchasing decisions. Therefore, in this study we used the particle swarm optimization algorithm combined with a back-propagation neural network (PSOBPN) to establish a demand estimation model and we used gray relational analysis to select factors highly correlated to travel demand to use as training and prediction input factors in the prediction model. A comparison of the prediction results with the back-propagation neural network (BPN), multiple regression analysis (MRA), and the travel agency experience forecasting method indicated that the PSOBPN and BPN prediction accuracy were superior to that of MRA and the experience forecasting method adopted by travel agencies. The accuracy of both PSOBPN and BPN were equal. The convergence speed during PSOBPN training was superior to that of BPN. PSOBPN is a superior prediction model when considering both prediction accuracy and model training convergence speed. It can provide decision makers for travel agencies with reliable and highly efficient data analysis.

Empirical Analysis on the Influence Factors of Tourism Income in Shandong Province

Based on the actual data of tourism income in Shandong province beginning from 1992 to 2009, this paper took the disposable income of urban residents, the number of foreign tourists, and the number of travel agencies as the major influence factors of tourism income. To study the impact of the above factors on tourism income in Shandong province, the tourist income econometric model was established and solved through econometric software Eviews 6.0. The conclusion was draw that there were significant relevance between the three factors and tourist income in Shandong province. All these findings would be useful references to improve tourism of Shandong province.

The Impact of Electronic Commerce on the Travel Agency Sector

The Internet appears to be playing a role in the re-structuring of some traditional business sectors in which some organisations profit and some decline. Travel agencies are being subjected to increased competition from virtual on-line travel agencies. These agencies do not possess the traditional retail outlets but exist predominantly on the Web. In addition, airline companies and travel wholesalers are beginning to market their products directly to the consumer. Despite the threat of disintermediation, the Internet has created opportunities for the travel agency by aiding in providing service to anybody anytime from anywhere.The study presented in the paper is based upon three separate pieces of research on the Australian travel agency sector and provides a macro and micro level view. Together the three research projects provide an in-depth study of key issues related to the travel agency sector. A survey of owners/managers of travel agencies provides information on the diffusion of Web technology and the levels of planning and strategies used by travel agencies when investigating the use of the Web. The second study provides an analysis of travel agency Web sites. The third study reports the results of a survey of travel consultants and their views on the likely impact of the Web on their profession and career prospects.The findings highlight that a significant number of travel agencies have adopted the use of the WWW but most only use a fraction of its business potential. The lack of enterprise-wide strategic planning being conducted by travel agencies suggests that they are underestimating the potential of Web based commerce. The results of the analysis of Web sites found that the majority of agencies had a Yellow Pages or Cyber Brochure model for their Web site. A small percentage of Web sites allowed transactions to be performed but a significant number provided information on a range of destination and service related topics. Many travel consultants believe that the Internet will not have a profound influence on their job position. Seventy three percent of travel consultants have not even visited a virtual travel agency Web site. Staff are often pessimistic in relation to their own careers with many admitting that they are not prepared for the changes taking place.Whilst the pessimists forecast a very bleak outlook for travel agencies, those that do re-engineer with a new vision and strategy have the opportunity to be amongst the leaders in the sector. Focusing on becoming information service providers is one option that travel agents can take. However, given the rapid rate of change in electronic commerce and the varying patterns of adoption, it is still not clear how severe the shake out of this important industry sector will be.

Relation, by States, between Population and Number of Travel Agencies

In this study regression techniques were used to investigate the relationships between (1) members of the Australian Federation of Travel Agents and the population of all eight states and territories of Australia, and (2) members of the American Society of Travel Agents and the population of all 50 states and the District of Columbia of the United States. In both cases the relationship is essentially linear, permitting a simple calculation of a by-state expected per-agency value. Simple illustrative examples are given of possible com petitive use. The per-agency value for Australia is close to 11,000; for the United States it is nearly 16,000. The significance of this difference is briefly discussed.

Identifying Geographic Markets for Travel Agencies

Despite low levels of profitability, the number of travel agencies in the United States is expected to grow by about 1000 agencies per year. In this highly competitive environment, the location of the travel agency is a critical factor to its success. This paper develops a model to help entrepreneurs select a geographic market to enter. Three demand-related variables population size, median income, and proportion of the population 65 years of age or older were found to influence the number of travel agencies in a geographical region. This model was used to identify areas that displayed unmet demand. These are the markets in which entry of a new travel agency may be most successful.