Tourism destination system can be considered as a complex nonlinear dynamic system. It’s difficult to accurately evaluate the operational orderliness with existing evaluation methods due to the complexity and dynamics of system. This paper attempts to introduce the concept of entropy in thermodynamics into organizational management, hoping to establish a nonlinear dynamic method for assessing destination system orderliness from management lens. Combining information entropy formula and the characteristics of tourism destination, this paper analyzed the entropy flow and negative entropy flow in the destination business ecosystem. Then an entropy evaluation index was constructed and the weight of each specific primary indicator and secondary indicator were calculated with the combination of analytic hierarchy process (AHP) and principal component analysis (PCA). Finally, taking JIUZHAI Valley as an example, this paper tested and modified the nonlinear dynamic evaluation approach. The nonlinear dynamic evaluation approach not only emphasize the overall operation state and process of destination system, but also take into account the nonlinear relationships amongst the internal elements of destination, contributing to overcoming the defects and deficiencies of traditional evaluation methods.

The completeness of the complex model is an important index to evaluate the pros and cons of the complex model. It is of great significance to study the objective evaluation under different indicators and construct an indicator system to ensure the integrity of the complex. The construction of complex system indicators requires instructors who can fully describe the functions of complex models. This study designs a complex index EX , proves its authenticity through comparison with the real world, illustrates its similarity through conflict and comparison with the coverage of the target problem, and describes its intelligence level through confrontation and comparison with other complex models. Research on complex model problems based on the derivation process of domain theory proves that the quantified complete distance EX can calculate the similarity between the model and the actual environment to evaluate ‘true and false’. The experiment proved to be a reliable and complex model verification indicator.