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A good ecological environment is the greatest advantage and precious wealth of rural areas. Developing rural tourism energetically can not only promote the development of rural economy, but also promote the transformation and upgrading of rural industrial structure. At present, under the background of all-for-one tourism development and policy support, the countryside has become the best carrier to undertake the quality leisure vacation demand of urban residents, and developing rural tourism has also become an important way to promote the development of all-for-one tourism. On the basis of combing and analyzing present situation of rural tourism development in Jiangxi Province and combining with background of all-for-one tourism, this essay puts forward paths and countermeasures of rural tourism development in Jiangxi Province aiming at providing insight and reference for transformation and upgrading of rural tourism in Jiangxi.

Tourism-related messages can alter the images of tourism destinations. In the new media time, messages from individual perception of the destination can spread among the social networks. Here, based on three basic assumptions, we developed a model to investigate the spread dynamics of tourism-related messages. In the model, two variables of individual behaviour, representing the probabilities of sharing or forgetting the messages, respectively, and a variable to represent the message’s importance were integrated. Within the simulated small-world networks, we observed two distinct patterns in the spread dynamics. The patterns were determined by individuals’ willingness to share messages and the message’s importance. If a majority of people choose not to send a message that they have received, the informed population will eventually become negligible; whereas, while they are inclined to spread, the informed population will remain constant over time. These patterns were influenced by neither the density of network connections nor the message sources. The message sources only determine the speed and the scale of diffusion. In summary, our model revealed the patterns of the spread of tourism-related messages.

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