Sustainability of government social media: A multi-analytic approach to predict citizens' mobile government microblog continuance

Abstract

Attracting citizens and facilitating their continued usage is critical for the sustainable development of mobile government microblog services. Drawing on the stimulus-organism-response (SOR) framework and the literature related to perceived value, this study investigates the factors that affect citizens' continuance intention vis-a-vis mobile government microblogs from a value-based perspective. A structural equation modeling (SEM)-neural network combined method was used to test the proposed model by using data collected from 301 mobile government microblog users in China. The SEM analysis shows that social influence, perceived interactivity, and perceived mobility positively affect citizens' utilitarian value and hedonic value, which further affects their continuance intention. The significant factors obtained from the SEM are used as input for a neural network analysis to calculate their relative impacts. The results of the neural network analysis showed that perceived mobility is the most important factor influencing utilitarian value, while social influence is the most significant factor affecting hedonic value. The normalized importance of utilitarian value on continuance behaviors is larger than that of hedonic value.