A case study on tourism spatial pattern and its influencing factors from the perspective of real and virtual tourism economic at county scale in Yellow River Economic Belt

Based on the index of tourism Baidu search volume and total tourism income of 667 research units at county scale in Yellow River Economic Belt, this paper uses spatial classification, exploratory analysis of spatial data, nuclear density estimation and other methods to compare and analyze the spatial pattern of county tourism economy in the Yellow River Economic Belt, and then uses the geographical detector model to analyze the influencing factors. The results are drawn as follows. Firstly, from the perspective of spatial distribution pattern, the imbalance of the overall tourism economy is obvious, and the spatial pattern shows a “one big, three small” four core agglomeration pattern. Secondly, from the perspective of spatial correlation pattern, significant HH and LL areas are dominant whether virtual economy or a real economy, and spatial agglomeration effect is obvious. Real economic significant HH areas mainly distribute in the tourism economic developed areas of Shaanxi and Shandong, while real economic significant LL areas are mainly concentrated in the middle and east of Inner Mongolia, the south of Shanxi, most of Qinghai and the north of Ningxia, and scattered in Henan, Gansu and other places. Compared with the entity level, the HH areas of the virtual economy are significantly expanded, mainly distributing in Shandong, Shaanxi and the eastern part of Inner Mongolia. The number of significant LL areas is significantly increased and the distribution range has changed, and the distribution scope of low-value cluster areas mainly distributes in most areas of Qinghai, south and north of Shanxi, and sporadically distributes in Gansu. From the perspective of nuclear density, the spatial structure of virtual and real economy is similar, and the high-value counties mainly distribute in Shandong, Henan and Shanxi forming a high-value gathering area expanding into a core development area. It is worth noting that the virtual economy scope in the north of Shaanxi and the northeast of Inner Mongolia has formed many sub-cores, which indicates that the level of virtual economy in the region is rapidly rising. Finally, according to the results of the Geo-detector model and the coupling matching analysis model, we found the real economy is mainly affected by the resources support level. We also found virtual economy is mainly affected by the level of information technology

The Determinants of International Tourism: Evidence from European Countries and China’s Provinces

Tourism has been reported as one of the largest economic sectors in the world. It is shown by more than hundreds of jobs involved in this sector which directly escalate the welfare and economic growth of a country. Thus, government will support any actions that could improve competitiveness and profitability of tourism industry. The main objective of this paper is to determine the significant factors of international tourism receipts by 18 European countries and 12 provinces of Western China between 1995 and 2019. Based on data, Europe known as the world’s largest international tourist receipt in 2019 followed by Asia and the Pacific including China. It is interesting to note that China, particularly in western part, has contributed more on achieving tourism receipt. China has potential to grow its tourism sector in significant trend due to its large land size and massive human resources that might further defeat Europe’s total tourist receipt. By using panel Autoregressive Distributed lag (ARDL) model, there would be different responses related to determinant factors of tourism over long run and short run. The result revealed that population, carbon dioxide emission and trade openness have positive effect to the international tourism receipt in Europe in the long run while the rest explanatory variables such as transportation infrastructure and energy consumption have negative effect to the international tourism receipt in Europe. While in case of China, population and energy consumption are statistically significant and positive to international tourism receipt in the long-run correlation, but the rest variables are having negative effect. Unfortunately, in the short-run effect, it was found that all variables are not statistically significant at least at the ten percent significance level in both Europe and China. From the result, the Europe and Chinese policy makers can evaluate the policy based on each result. For instance, the fact that the high level of population density could reach larger tourism receipt is not always true, government need to provide some training for the party who will be involved in tourism industry to gain knowledge and encourage them to be more creative and innovative. Hence the good quality of listed tourism destination would attract more tourist to the destination countr

Literary destination familiarity and inbound tourism: evidence from mainland China

Destination familiarity is an important non-economic determinant of tourists’ destination choice that has not been adequately studied. This study posits a literary dimension to the concept of destination familiarity —that is, the extent to which tourists have gained familiarity with a given destination through literature—and seeks to investigate the impact of this form of familiarity on inbound tourism to Mainland China. Employing the English fiction dataset of the Google Books corpus, the New York Times annotated corpus, and the Time magazine corpus, we construct two types of destination familiarity based on literary texts: affection-based destination familiarity and knowledge-based destination familiarity. The results from dynamic panel estimation (1994–2004) demonstrate that the higher the degree of affection-based destination familiarity with a province in the previous year, the larger the number of inbound tourists the following year. Examining the influence of literature and its consumption on tourism activities sheds light on the dynamics of sustainable tourism development in emerging markets

The Consequences of Corruption: Evidence from China

With complementary Chinese data sets and alternative corruption measures, we explore the consequences of corruption. Adopting a novel approach we provide evidence that corruption can have both, positive and negative effects, on economic development. The overall impact of corruption might be the balance of the two simultaneous effects within a specific institutional environment (“grease the wheels” and “sand the wheels”). Corruption is observed to considerably increase income inequality in China. We also find that corruption strongly reduces tax revenue. Looking at things from an expenditure point of view we observe that corruption significantly decreases government spending on education, R&D and public health in China. We also observe that regional corruption significantly reduces inbound foreign direct investment in Chinese regions, which indicates that the pollution haven hypothesis may not hold in China. This finding sheds a new light on the “China puzzle” that China is the largest developing host of FDI while it is appears to be very corrupt. Finally we observe that corruption substantially aggravates pollution probably through loosening environment regulation, and that it modifies the effects of trade openness and FDI on the stringency of environmental policy in a manner opposite to that observed in literature to date.Corruption, China, Government, Economic Development, Inequality, Environment

Impact of tourism industry, globalization, and technology innovation on ecological footprints in G-10 countries

In the past couple of years, most of the countries observed an increase in the size of their ecological footprints. Therefore, researchers and policymakers are now more focused on the potential drivers through which the ecological deficiency can be reduced. In the same context, this study evaluates international tourism, globalization, and technology innovation effects on the ecological footprints of G-10 countries over the period of 1995–2019. This study initially applied second-generation crosssectional dependency, unit root, and cointegration tests. The long-run and short-run estimates were obtained through the Cross-Sectional ARDL method. The study’s empirical findings demonstrate that tourism, globalization, and economic growth significantly contributed to ecological footprint, while technology innovation reduced the environmental burden, thus leads to a decline in ecological footprints of sample countries. These results suggest the use of alternate energy resources and advanced technology in the tourism industr

Turismo na República Popular da China: políticas e desenvolvimento económico

Mestrado em Estudos ChinesesO presente trabalho propõe-se a investigar o percurso da indústria do turismo na República Popular da China nos últimos 50 anos, desde a fase em que o país mergulhou numa política de completo isolamento em relação ao resto do mundo, até se ter tornado num dos principais intervenientes económicos e políticos a nível mundial. Paralelamente, o sector do turismo acompanhou essas mudanças que se foram desenvolvendo ao longo dos tempos, para passar a ser hoje um dos principais sectores da economia da China. O presente trabalho de investigação examina as principais mudanças ocorridas ao nível das políticas lançadas para o sector em questão, bem como o impacto que elas tiveram no desenvolvimento económico do país. Pretende-se, portanto, determinar até que ponto os resultados económicos desta indústria foram determinados pelas acções e programas lançados pelo Governo Chinês ao longo dos últimos 50 anos.This thesis researches the path that the tourism industry followed in the People’s Republic of China over the last fifty years, since the period when the country closed itself off from the rest of the world until it had become one of the big economic and politic players on the world scene. The tourism industry also followed the changes that were developing over time and became one of the most important economic sectors in China. This work examines the major policy changes that occurred within the sector, as well as the impact they had on the economy. It attempts to determine the extent to which the economic results accomplished by this industry were determined by the actions and programmes launched by the Chinese Government

Geo Data Science for Tourism

This reprint describes the recent challenges in tourism seen from the point of view of data science. Thanks to the use of the most popular Data Science concepts, you can easily recognise trends and patterns in tourism, detect the impact of tourism on the environment, and predict future trends in tourism. This reprint starts by describing how to analyse data related to the past, then it moves on to detecting behaviours in the present, and, finally, it describes some techniques to predict future trends. By the end of the reprint, you will be able to use data science to help tourism businesses make better use of data and improve their decision making and operations.

High-speed rail and tourism expansion in China: a spatial spillover effect perspective

Tourism exerts a great effect on the modern economy and relies largely on the flow of people facilitated by high-quality transportation infrastructure. Applying a spatial econometric method, this paper investigates the effect of high-speed rail (HSR) on tourism expansion in China from the view of the spatial spillover effect. Based on a 276 Chinese cities’ panel dataset over 2005–2019, a positive role of HSR in tourism expansion is observed. Compared with cities unconnected to the HSR network, cities accessible by HSR experienced a 22% increase in tourism revenue and a 38% rise in tourist arrivals. In addition, the connection of a city to the HSR network also exerts a great spatial spillover role in the increase of tourism revenue and arrivals in peripheral cities which are not directly connected by HSR. The research findings offer important insights on the relationship between transportation infrastructure and tourism with significant policy implications regarding tourism development. First published online 6 November 202

日本における中国人観光客の空間的流動パターン

筑波大学 (University of Tsukuba)201