To investigate the spatial interaction effect and nodal attractions of cities, a set of inter-city social network location-based check-in data with a time span of one year among 348 municipal cities in China is examined with a PSO (Particle Swarm Optimization) method and the gravity model. Twelve variables related with economic development, industrial structure, population scale and structure, tourism competitiveness and educational level are introduced to further investigate their influences on nodal attractions of cities. The results indicate a distance decay effect which is relatively weaker than in other systems, suggesting that human mobility at the regional level is less sensitive to the change in geographic distance. A close examination of the nodal attractions suggests variables related to the cities’ tourism competitiveness, maturity of development and population scale significantly influence the value of nodal attractions. This article will serve as a stepping-stone for a better future understanding of human travel pattern, check-in behaviors and the real meaning of nodal attractions in some complicated networks.

Involvement is one of the important dimensions to understand tourists’ purchase decisions; hence the research on place involvement will help to understand the rule of the tourist behavior and revisit characteristics. This research aimed to analyze the place involvement of tourists in Dolphin Discovery Center (DDC) Bunbury, West Australia. K-Means clustering analysis method, variance analysis and Sheffe post-test were combined to examine the extent of place involvement for DDC and demographic differences. The main conclusions were as following: based on different place involvement degree, wildlife tourists were divided into deep place involvement, medium place involvement, and light place involvement; tourist involvement in the wildlife tourism place was deep for the overall sample; demographic characteristics, age and education degree had significant differences (p≤ 0.05), while gender, income and family had no significant difference; stay time, consumption in site, information sources and satisfaction had significant difference in place involvement (p ≤ 0.05). Additionally, the conclusions from this research can provide guidance and applicance to wildlife conservation, destination management and marketing.

This research aims to analyze the risk perception of tourists in Dolphin Discovery Center (DDC) Bunbury, West Australia and serves for the destination a management and marketing. Factor analysis, K-Means cluster analysis and variance analysis were combined to examine the extent of risk perception for DDC and demographic differences. The main conclusions were as following: three factors that tourism experience quality, physical safety, and amenity were extracted based on the exploring factor analysis; according to the extent of risk perception, wildlife tourists had been divided into three categories: weak risk awareness, medium risk perception, and strong risk perception. Wildlife tourists perceived experience quality risk as the strongest factor and physical safety as the weakest factor, and amenity risk was in an intermediate position. Independent-sample t test and variance analysis were used to examine the demographic difference in risk perception and the results showed that different age, income and family status all had significant difference in risk perception except gender; tourism experience, travelling companion, expenditure and staying time and other tourism behavior all had significant difference in risk perception as well as satisfaction and willingness to revisit, except for information source.