Research On The Influencing Factors Of User’s Knowledge Behaviors In Social Q&A Knowledge Payment Platforms

Since 2016,a large number of knowledge payment platforms have been emerging in the domestic market,and users in the platform can obtain economic benefits by providing paid knowledge products or services.Facing the developmental trend of knowledge payment,social Q & A communities begin to adopt freemium business model and make transformation into social Q & A knowledge payment platforms.For example,Zhihu launched Zhihu Live and Weibo launched Qeibo Q & A.However,failures of business model transformation often occur in practice.The critical reason is that management strategies aren’t adjusted in time while in the business model transformation from free to freemium.So that platforms face the dilemma of the loss of users in the original free stage and the insignificant economic income.Therefore,it is eager for operators to figure out management strategies towards business model transformation,promoting the balanced development of both free and paid services in the platform.From the perspective of the supply side in the platform,users,who are as sources of free and paid knowledge utilities(e.g.answers,articles and rating),ensure active knowledge storage and diffusion activities in the platform.And their knowledge behaviors are critical to achieve successful business model transformation.For this reason,this dissertation focuses on how to promote users’ knowledge behaviors in different stages from supply side,such as free knowledge contribution and selling paid knowledge products or services.However,literature related to users’ knowledge behaviors are still scattered.In the process of business model transformation,there are still lack of systematic and dynamic studies about users’ knowledge behaviors.Therefore,this dissertation divides the development of the platform into two stages as free community and value-added,conducting systematic researches about influencing factors,and using machine learning methods to explore the dynamic evolution process of users’ knowledge behaviors.The specific research content is as follows:(1)For the free community stage,this dissertation focuses on the influence of social interaction ties on knowledge contribution behavior.Since social motivation is one of the most important motivators of users’ behaviors,from the view of social network,this dissertation investigates the effect of social interaction ties on knowledge contribution behavior.Hidden Markov Model(HMM)was adopted to recognize the dynamic sequence of knowledge contribution loafing(KCL).After that,this dissertation further investigates KCL as a moderating variable.Results show that KCL has three states: high,medium and low,and there are dynamic transitions between different states.Specifically,users who are in high or low KCL state are more likely to keep in the next period.Secondly,for users with low KCL state,social interaction ties have a positive and significant impact on the quality and quantity of knowledge contribution.With moving to the central of social network,users are more likely to contribute more knowledge with higher quality.(2)For the value-added stage,this dissertation focuses on the spillover effect of economic benefits on users’ knowledge contribution behavior.With the launch of paid service module,users can obtain economic returns by selling knowledge products or services.For this reason,besides the social motivational effect of social interaction ties,this dissertation further investigates the spillover effect of economic returns on users’ knowledge contribution behavior,and expands the knowledge contribution behavior into three dimensions: quantity,quality,and change of quality.In order to verify the causal relationship between the variables,this dissertation collected objective data from Zhihu website in two periods.Then multiple linear regression model was built,and ordinary least squares method(OLS)was used to estimate the coefficients of the variables.Results show that from the perspective of time,the quantity of economic benefits do not have positive effect on knowledge contribution quality and quantity,while it negatively influences the change of knowledge contribution quality.(3)For the value-added stage,this dissertation focuses on how free and public knowledge influences users’ selling behavior.For the premium module,in order to achieve economic benefits,operators focus on how to improve users’ sales performance.However,with the co-exitance of free and paid knowledge sharing,free and public knowledge may have an impact on the sale of knowledge products or services.This dissertation mainly considers two kinds of public knowledge factors on users’ sales performance,including contributed knowledge and electronic Word-of-Mouth.And sales volume is used to measure users’ sales performance.For the collected review text data,this dissertation used text classification to quantify the sub-dimensions of knowledge quality and interaction quality.Then a multiple linear regression model was established,and the ridge regression method was used to estimate the regression coefficients.Results show that the higher knowledge contribution quality of the knowledge supplier is,the greater the negative impact on sales volume.However,knowledge providers’ reputation accumulated for helping others in the knowledge community benefits the improvement of sales volume.(4)For the value-added stage,this dissertation studies the impact of social interaction ties on user ratings.Reviews and ratings are critical parts of electronic wordof-mouth(e WOM)environment,which are crucial to achieve economic returns.Since social interaction ties among users in free communities can be used as information channels,they will have an impact on the results of information processing.This dissertation focuses on the influence of knowledge provider-excellent contributor interaction on consumers’ rating score,with Propensity Score Matching with Difference-in-Difference method to verify hypothesis.Results show that the knowledge provider-excellent contributor interaction is beneficial to improve the rating scores given by evaluators.Consumers will give rating scores based on the relevant information of knowledge suppliers,and will give higher rating to those having connections with outstanding contributors.The theoretical contributions mainly include: 1)expanding the research of users’ knowledge behaviors from traditional static perspective to dynamic perspective by relaxing the overall and static assumptions of related theoretical concepts;2)expanding research of knowledge contribution into two dimensions as quality and quantity,and further expanding the antecedent variables of knowledge contribution behavior from non-economic to economic motivational factors;3)giving a more systematic explanation of users’ knowledge behaviors in the development of the social Q & A knowledge payment platform.The practical contribution is about achieving business model transformation and creating economic benefits in the social Q & A knowledge payment platform.