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Explaining mobile government social media continuance from the valence perspective: A SEM-NN approach

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  • Yubo Peng
  • LingWu Wang
  • Shuiqing Yang

Abstract

Different from many previous studies explain mobile social media usage from a technical-center perspective, the present study investigates the factors that influence citizens’ mobile government social media (GSM) continuance based on the valence framework. The research model was calculated by using data collected from 509 citizens who are the mobile GSM users in China. A structural equation modeling (SEM)-neural network (NN) method was employed to test the research model. The results of SEM indicated that the positive utilities included social value and hedonic value positively affect mobile GSM continuance, while the negative utility reflected by self-censorship negative affect mobile GSM continuance. This is further supported by the results of the neural network model analysis which indicated that hedonic value is more influencing predictor of continuous usage of mobile GSM, following by social value and self-censorship.

Suggested Citation

  • Yubo Peng & LingWu Wang & Shuiqing Yang, 2021. "Explaining mobile government social media continuance from the valence perspective: A SEM-NN approach," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-13, February.
    • Handle: RePEc:plo:pone00:0246483
    DOI: 10.1371/journal.pone.0246483
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    References listed on IDEAS

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