[Objective] This paper helps the library’s mobile app provide contents based on the users’ actual locations and their expectations, which are the key issues facing mobile service innovation. [Methods] First, we proposed the concept of information acceptance entropy based on the theory of information entropy and context entropy. Then, we constructed a generalized component distribution probability model for the information acceptance entropy with the help of entropy energy distribution theory. Finally, we examined our model with the academic libraries in China’s Liaoning, Jilin and Henan provinces. [Results] We wrote new algorithms with Matlab and used the Likert scale to evaluate the users’ perception and experience. The new model successfully calculated and simulated the information acceptance entropy of different scenes. We found that switching the scenes in time and increasing relevant contents will improve user’s experience. [Limitations] The sample size needs to be expanded to improve the accuracy of simulation. [Conclusions] The proposed model could compare and predict the multidimensional information acceptance entropy of different locations.
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