| With the steady development of Chinese economy and the increase in disposable income of residents,the demand for tourism consumption of residents has grown rapidly.Tourism has become an important part of the domestic economy and one of the fastest growing consumer sectors,and has become an important driving force for economic growth.The report of the 19th National Congress clearly pointed out that China's economy needs to shift to a new stage of high-quality development,and the development of tourism will drive steady economic growth and help promote the transformation and upgrading of China's economic structure.Therefore,it is of great significance to conduct in-depth research on tourism demand and development trends,grasp its dynamic characteristics and influencing factors,and formulate relevant policies to promote the further development of tourism.This paper uses the data of 50 representative hotels in key tourist cities in China to analyze the dynamic changes of star-rated hotel demand during the sample period and related influencing factors,and explore the economic and social policies including anti-corruption policies for star-rated hotels.The impact of industry demand.The main contributions of this paper are as follows:Firstly,based on the data of star-rated hotels in 50 key tourist cities in mainland China,we conducted a preliminary analysis of the seasonal effects and dynamic trends for demand of star-rated hotels.We found that the operating income,income structure,average house prices,and average occupancy rate of each type of star-rated hotel in each city have obvious seasonal and time trends,and there are certain differences.Overall,we found that the average price and average occupancy rate of each star were the lowest in the first quarter,and higher in the third and fourth quarters.In terms of time trends,the operating income of star-rated hotels has increased from 2010 to 2011,but has been declining year by year since the fourth quarter of 2012,but has stabilized by 2015.The proportion of catering revenue has gradually declined after 2012,and the proportion of room revenue has increased.The average house prices and average occupancy rate showed a certain peak from 2012 to 2013,but the average occupancy rate remained basically stable.In terms of distribution of geography,the seasonality effect of star hotels at cities of northern mainland china is more obvious,no matter average price or average occupation rate,with a larger volatility compared to that in southern mainland china.In general,the lowest happens in the spring,as the temperature is very low during this period.In terms of city types,the demand of star hotels at third and fourth tier cities is more volatile than that of the first and second tier cities.The reason is that the demand of the former is driven by tourists,while the demand of the latter is driven by business travelling.Secondly,in order to study the dynamic characteristics of demand changes among various types of star-rated hotels in various cities,we use a VAR model and a panel autoregressive model(PVAR)to conduct a dynamic measurement modeling analysis of the average house prices and average occupancy rate of star hotels..Based on the model estimation results of the four selected key tourist cities,namely Beijing,Qingdao,Xiamen and Sanya,we found that most of the lags are not significant,indicating that the average price of the star hotel and the average occupancy rate are lagging behind.Not strong.However,we found that cities have significantly different seasonal effects.For example,the average house prices effect of Beijing star hotels is not very significant,while the average occupancy rate reflects a strong seasonal effect.Spring and summer are relative to winter.It is said that the rental rate has increased significantly,reflecting Beijing as a national political center and economic center.Its business activities,conferences and tourism have chosen spring and summer,especially during the summer vacation.The average house prices in Qingdao reflects the seasonal effect.The hotel prices in spring and summer are significantly higher than the other two quarters,indicating that Qingdao star hotels choose to increase their hotel prices in the peak season and gain more profits.The seasonal effect of the average house prices in Xiamen is mainly reflected in the winter.The average house prices of the hotel is higher in the winter,but unlike Qingdao,the hotel occupancy rate has not improved significantly.The seasonal effect in Sanya is also obviously,and the average house prices and occupancy rate are higher in the winter than in other seasons.In terms of Granger causality analysis,we found that there is no Granger causality between house prices and occupancy rates in Beijing and Qingdao,that is,there is no relationship between first and last.The price of three-star and five-star hotels in Xiamen has a certain leading role for other star-rated hotels.In terms of occupancy rate,two-star,three-star and five-star hotels have a certain leading role in the occupancy rate of other star-rated hotels.Three-star hotels in Sanya have a certain leading role in other star-rated hotels in terms of average house prices.And in terms of occupancy rate,four-star hotels have a leading role in the occupancy rate of other star-rated hotels.In addition,based on the PVAR model estimation results of the national key tourist cities,the common factor,that is,the national GDP growth rate and the tertiary industry growth rate have a certain impact on the average house prices and occupancy rate of star-rated hotels,and the GDP growth rate is instead two-star.Negative impact on the average house prices of three-star hotels,the impact on the average house prices of other hotels is not significant,and the growth rate of the tertiary industry has a positive impact on the average house prices of two-star and three-star hotels,and for each type of star rating The occupancy rate of the hotel has a positive impact.The regression results show that the demand for star-rated hotels is more closely related to the tertiary industry representing the development of the service industry.Therefore.in the future economic restructuring and upgrading,it is necessary to further develop the tertiary industry and improve the micro-level economic vitality.Thirdly,in order to analyze the specific factors affecting the demand for various types of star-rated hotels in various cities,and the differences between these different factors in different star-rated hotels,we have done a panel regression model analysis for our star-rated hotel occupancy rate types.Considering the average house price,urban air quality,"eight regulations" system,whether the city is a civilized city,urban basic public transportation,and airport facilities.We use the lowest average wages in each city as the average house prices instrument variable for each city,and use a two-stage regression method to estimate the panel model.Overall,we found that the average occupancy rate of the hotel has a significant negative correlation with the average house price.With other factors unchanged,the average house price increased by 10 yuan,and the occupancy rate dropped by about 0.75%.We found that the PM 10 measure of air quality significantly negatively affected the average occupancy rate of hotels,especially for the occupancy rate of five-star hotels.For every 10 increase in PM10,the average occupancy rate dropped by 0.42%to 0.68%.The "eight rules" of the dummy variable representing the degree of easing of anti-corruption policies have heterogeneity on the average occupancy rate of each hotel.The impact on five-star hotels,four-star hotels and three-star hotels is negative,but the impact on two-star hotels is even positive,although not significant,indicating that the "eight regulations" are reducing some high-end consumption.It also appropriately increased the demand for private consumption.The regression coefficients corresponding to the virtual variables of civilized cities are mostly positive,but mainly reflected in the demand of five-star hotels,and the impact on four-star,Samsung and two-star hotels is not significant.Urban basic public transport negatively affects the occupancy rate of star hotels,while airport traffic and airport throughput are positively affecting the occupancy rate of star hotels.Finally,based on the panel data policy evaluation analysis method proposed by Hsiao et al.(2012),we further analyze the impact of the "eight regulations" anti-corruption policy on various star-rated hotels.We will publish the eight regulations in the fourth quarter of 2012.As an event window,the sample is divided into pre-event and post-event,and the number of one-star,two-star and overseas tourists is used as a predictor to establish the counterfactual path of Samsung,four-star and five-star hotel demand.By comparing the counterfactual path with the actual observations,we can initially estimate the short-term impact of the"eight regulations" anti-corruption policy on various types of star-rated hotels.Studies have shown that the impact of the "eight regulations" on the star hotel industry in different regions of China is quite different.The estimation results show that the"eight regulations" have a disposal effect on the average house price policy of three-star hotels of-9.711 yuan,and the disposal effect on the average house price policy of four-star hotels is-48.534 yuan,while the average house price policy for five-star hotels is disposed of.The effect is-71.804 yuan,indicating that the "eight rules" have a greater impact on the average house price of high-end hotels.For the occupancy rate,the "eight regulations" reduce the average occupancy rate of three-star hotels by about 2.314%,the average occupancy rate of four-star hotels is about 0.849%,and the average occupancy rate of five-star hotels is about 2.375%.Explain that the policy has the least impact on the average occupancy rate of four-star hotels.The study concluded that the "eight regulations" reduced the demand for star-rated hotels in the short term,while star-rated hotels maintained occupancy rates by lowering house prices to attract more private consumption. |
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