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Fuzzy Neural Network Capacity Prediction Model and Medium Adjusting Efficacy of Experience Quality

Jing Jiang


The intrinsic utility of experience witnessed real changes from the inside out, with the value of marketing communication extended by co-creating and sharing compared with personal satisfaction or loyalty. It’s not simply linear correlation among experience innovation, customer satisfaction and spreading. Meanwhile experience quality functions as a coordinated intermediary. With reference to a UGC spreading mechanism analysis, this thesis proposes the different determinants that affect the marketing communications, including experience quality, perceptive value, perceptive object, behavioral habits and perceptive service. In addition, a prediction model of spreading capacity of UGC, generated from experience by fuzzy neural network, is built up. The result shows that the involvement degree, cognitive and expressive competence jointly influence marketing communications. It’s not hard to figure out the medium adjusting efficacy of experience quality. Nevertheless, perceptive object and perceptive value have stronger effects. Therefore, besides designing experience innovation, enterprises should attach great importance to promoting the coverage of network among Internet users, media and enterprises themselves so as to discover the advantaged experience customers and encourage them to improve marketing communications.


experience quality, user generated content, marketing communications, fuzzy neural network, capacity prediction model.

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