An application of network analysis on tourist attractions: The case of Xinjiang,China

This study constitutes a novel application of network analysis to explore the underlying mechanisms of tourist attraction network informed by tourist flows. Using survey data collected from a sample of 456 tourists visiting Xinjiang, China, the study applies the Quadratic Assignment Procedure (QAP) to test the relationships between region proximity, grade proximity, and tenure proximity, and the attraction network determined by tourists' free choice movements. Results show that while region proximity and tenure proximity among major attractions in a destination were positively related to attraction network, grade proximity was negatively related to the attraction network, indicating that same grade attractions were mostly competing with one another for tourists. The study contributes to the methodological development of social network analysis in tourism and advances understanding of demand-driven network relationships among tourist attractions in a destination. Destination management implications are discussed.     

Analysis of international tourist arrivals in China: The role of World Heritage Sites

This paper analyzes the determinants of international tourist arrivals in China, especially for World Heritage Sites and various kinds of travel spots. Utilizing annual provincial panel data over the 2000–2005 period, the empirical results suggest that key determinants include the relative income, population in the original country, cost of travel, and tourism infrastructure. In addition, World Heritage Sites are also found to be significant in explaining the numbers of international tourists and have a greater tourist-enhancing effect. Other famous tourist sites rated 4A- and 3A-class are also attractive to foreign tourism. Moreover, cultural rather than natural sites attract more interest among foreign tourists, because China is internationally renowned for its long-standing historical and cultural assets. Finally, the importance of the determinants of the demand for tourism varies from country to country.     

中国资源型景区与城市空间关系研究

本文以资源型景区为研究对象,在前人研究的基础上对其概念进行了界定与分类。然后,本文选取国家旅游局评定的4A级景区中的资源型景区为景区样本,市区非农业人口在50万以上的大中城市为城市样本,利用地理数学方法的空间分析手段和GIS空间分析工具,定量分析资源型景区与城市的空间分布关系。结果表明,绝大多数资源型景区分布于距市中心300公里以内,并且集中分布于距市中心50公里以内的市区和距市中心50—100公里的市郊地带;并且规模越大的城市,其周边分布的资源型景区越多。     

The Spatial Distribution of Tourism in China: Trends and Impacts

Economic inequality in China has increased since China began its economic reforms in 1978. Economic activity has become increasingly more skewed towards China's coastal areas and overall regional economic inequality has increased with economic growth in China. The paper utilizes statistical data over two decades, and tracks the growing regional inequality in terms of economic and tourism development. It confirms the concern that along with phenomenal growth of inbound tourism to China, considerable regional inequality has arisen in tourism in China. There is significant spatial inequality in the distribution of inbound tourism in China and its economic characteristics. International tourism in China is heavily concentrated in the coastal areas. This paper attempts to identify trends in the regional concentration of international tourism in China from 1986 to 2004. Gini coefficients for major tourist indicators are applied to test the characteristics of tourism distribution.     

Profit Luenberger and Malmquist-Luenberger indexes for multi-activity decision-making units: The case of the star-rated hotel industry in China

Due to the vigorous economic development of the tourism industry in China, the number of star-rated hotels has rapidly increased. As a result, techniques to evaluate the performances of star-rated hotels have gained in popularity. In this paper, we develop two indexes for dynamic settings: the profit Luenberger and Malmquist-Luenberger indexes. The distinguishing features of our indexes are three-fold. One, we adopt an economic perspective by considering that hotels are profit maximizers. Two, we model hotels as multi-activity decision-making units by considering that they provide multiple services. Three, our indexes are nonparametric, and work when prices are partially observed. We apply our technique to 30 provinces during 2005–2015. We find that star-rated hotels present better performances over time, but not for every activity. Next, we highlight particular patterns for the provinces. These results are useful for managers to better target their investments, and also for policy makers.