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In support of an ambitious target to reduce carbon intensity by from 40 to 45 percent by the year 2020, as proposed by numerous leaders around the globe, various industries in China have come to think of carbon emissions reduction as an important part of their overall corporate strategy. As an energy-intense economic sector (Gössling, 2013), tourism is thus expected to play an important role in reducing CO 2 emissions in China. However, low-carbon tourism in most destinations, and especially in newly-emerging tourism destinations, is being neglected to some extent. Examples of this neglect can be found in such areas as China's Chengguan District of Lhasa, which has ambitions to become a world tourism centre. This study develops a fuzzy Delphi-ANP approach to suggest which low-carbon tourism strategy should be adopted in Chengguan District in the coming years. Applying our approach, we find that the priorities of low-carbon tourism strategies in Chengguan District are: first, economic development (0.1965), secondly, environmental construction (0.1593), and finally, social support (0.1442). Specifically, the importance of the indicators for tourism carbon intensity, low-carbon transportation, education regarding a low-carbon environment, carbon sink density and sewage treatment are stressed in this paper, in order to call for the immediate implementation of low-carbon tourism development in Chengguan District. [ABSTRACT FROM AUTHOR]

Although the sustainable development philosophy has been widely recognized, it is still necessary to weigh the economic, environmental and social implications of tourism development. The decision is often difficult involving typically complex multi-criteria decision making problems. This study aims to contribute a theoretical framework and approach for the determination of top priorities in tourism development and making decisions based upon that approach. Taking Xizang as a case, this study explores the means to weigh and realize tourism development goals during the ‘13th Five-Year Plan’ period, using the analytic network process within a goal programming model. Results show that there are 10 criteria and nine decision variables determined in Xizang's sustainable tourism development and the priorities in Xizang's tourism development should be: 1) economic goals, 2) social goals, and 3) environmental goals. In addition, using the analytic network process-goal programming model, this paper provides the solution of the decision problem for two years, namely 2016 and 2020, and discusses the significance of the results. This study concludes that in a newly-emerging tourism but otherwise economically and socially backward region like Xizang, considering the economy first and the environment last is both appropriate and practicable. It is suggested that Xizang's tourism managers should implement specific strategies to raise the GDP, encourage higher levels of consumption by tourists and appropriately restrict the growth in the number of tourist coming to the area. Other goals should be to improve tourism research and the treatment of tourism employees and provide more support for tourism enterprises. The interdisciplinary approach from a systems perspective used in this study can be used to judge, queen and select numerous goals and criteria to make decisions in sustainable tourism development. [ABSTRACT FROM AUTHOR]

The purpose of this study is to employ a nonlinear dynamic evaluation method to assess the tourism sustainability of Tibet Autonomous Region (TAR), China, a new emerging tourism destination. The methodology draws on system dynamics and Back Propagation (BP) neural network. According to 7 setting principles, this study identifies 13 tourism sustainability indicators including conventional tourism income, tourism resources stock, pollution stock, etc., as well as specific residents’ tourism cognition, seasonal difference, accessibility, etc. Then a system dynamics model including the 13 indicators (variables) and other relevant auxiliary variables is established. Based on the numerical simulation, using a three layers BP neural network optimized by genetic algorithm and particle swarm algorithm, this study evaluates the future sustainability dynamically and compares the sustainability evolution from 2014 to 2050 under different development strategies. The research results not only provide information useful for the dynamic control and scientific management of the future sustainable tourism development, but also provide a systems approach to evaluate regional tourism sustainability. [ABSTRACT FROM AUTHOR]