Research On Users' Continuance Of Social Networking Services Based On Social Influence Theory

As social networking services(SNSs)develop rapidly and become mature,Internet has stepped into the era of social networking.According to China Internet Network Information Center,the number of Chinese SNS users has exceeded 600 million.Despite of the increasing number of SNS users,users' stickiness has continued to decline in recent years.As the survival and success of SNSs depend highly on active users and their continued use,how to maintain users to actively use SNSs and how to keep existing users from discontinuing their use have attracted increasingly attention from both SNS operators and scholars.Following the research paradigm of information technology adoption and post-adoption,previous scholars primly use individual utility factors(e.g.,perceived usefulness and perceived ease of use)and individual cognitive factors(e.g.,expectation confirmation and satisfaction)to explain SNS users' continuance intention and continuance behavior.However,SNSs are different from traditional information technology in that SNSs have strong social attributes.On SNSs,much of user behavior is not best characterized by an individual user acting in isolation;instead,users act jointly with others,in response to social pressure or as members of groups.Therefore,it is important to investigate the research question of SNS users' continuance from a social perspective.This study takes SNSs' social attributes into account and systematically explores SNS users' continuance based on social influence theory.Targeting SNS users,this study empirically examines users' continuance intention at individual level and simulates users' continuance behavior at group level.First,this study defines the concept of SNSs,summarizes their attributes and involving agents,elaborates the relationship between SNS users' continuance intention and SNS users' continuance behavior,and discusses both the dynamic process and static dimensions of social influence.Further,this study analyzes the relationship between static dimensions of social influence and SNS users' continuance intention at individual level and the relationship between the dynamic process of social influence and SNS users' continuance behavior at group level,so as to provide the theoretical foundation for the rest chapters.Second,this study conducts empirical research on SNS users' continuance intention at individual level in terms of static dimensions of social influence.In chapter 3,this study elaborates the direct impacts of social influence dimensions(i.e.,subjective norms,social identity,a nd peer effects)on SNS users' continuance intention,and analyzes data from 429 valid questionnaires by multiple linear regression analysis with SPSS 18.0 software.The results show that subjective norms,social identity,and peer effects significantly impact SNS users' continuance intention.In chapter 4,this study analyzes the impacts of social influence dimensions on sociability and social overload and the impacts of sociability and social overload on SNS users ' continuance intention,and illustrates the mediating effects of sociability and social overload in the relationship between social influence dimensions and SNS users' continuance intention.Data were collected by an online survey and analyzed by partial least square structural equation modeling using Smart PLS 3.0 software.The results show that both sociability and social overload significantly impact SNS users' continuance intention and partially mediate the relationship between social influence dimensions and SNS users' continuance intention.In chapter 5,this study analyzes the moderating effect of perspective taking in the relationship between social influence dimensions and SNS users' continuance intention.Data from 286 valid questionnaires were analyzed by examining the significance of the interaction term(i.e.,the product of the independent variable and the moderator variable)and by comparing the proportion of variance explaine d of the main effect model(i.e.,the model without moderating effect)with the variance explained of the full model(i.e.,the model including the moderating effect).In addition,this study categorized perspective taking into two clusters and tested the impacts of subjective norms,social identity,and peer effects on SNS users' continuance intention in each cluster.The results show that perspective taking plays an important moderating role in the relationship between social influence dimensions and SNS users' continuance intention.Last,this study explores SNS users' continuance behavior at group level as a dynamic social influence process in Chapter 6.This study analogizes the dynamic social influence process of SNS users' continuance as a process of virus spreading.Thus,virus dynamics model was utilized as a technical method to simulate this process.Through numerical simulation with MATLAB software,the results show that the number of SNS continued users increases with the increase of the growth rate of registered users,the average contact ratio between registered users and user generated content(UGC),and the perceived social index of registered users.Additionally,in a relatively short period,the average time for registered users to transform into continued users only affects the duration to achieve the equilibrium number of continued users,but doesn't affect the number of continued users in the equilibrium state.Based on social influence theory,this study illustrates the impact paths and underlying mechanism of how social influence dimensions affect SNS users' continuance intention at individual level,and reveals why SNS users have different continuance intention even in the same or similar social environment.Also,this study builds simulation models to explain the dynamic social influence process of SNS users' continuance behavior,which manifests SNS users' continuance evolution at group level.In sum,this study can enrich both social influence theory and SNS continuance theory,and help SNS operators to manipulate resources effectively to attract and retain users.