The Channel Switching Behavior Research Of The Internet Payment User Based On Mobile Payment Service Value

Mobile payment is an important basis and stable power for the mobile Internet economy to achieve great-leap-forward development.With the continuous progress of mobile communication technology and the increasingly popular of smart phones in recent years, the Chinese mobile payment has grown quickly,which has a good user base especially due to the heavily subsidies and promotion by mobile payment companies. But from the practical viewpoint of application,on the one hand, many users still only treat mobile payment as an extension of the traditional Internet payment or a supplement to the payment method, use it occasionally or in a specific context; On the other hand, there are more and more users begin to gradually reduce the use of Internet payment after the adoption of mobile payment, and formed the switch of payment channel.At present, scholars focus on the user behavior in the pre-adoption of mobile payment, and there is relatively scarce research about mobile payment user behavior in the post adoption phase. The commercial value of mobile payment depends on the participation of more users and more using.Therefore, a deep insight into the switching behavior of users from Internet payment to mobile payment channels, retaining them and increasing the users stickiness on mobile payment should be subject to the academic and industry attention.Mobile payment is not only a technological innovation, but also a service innovation.From the user’s behavioral decision making process and based on the service value mobile payment,this study uses the Push-Pull-Mooring theory framework in the population migration to discuss the key factors and mechanism of the users’ switching behavior from Internet payment to mobile payment channels, then switching behavior prediction of Internet payment users is also carried out. Finally,useful inspirations for the development of mobile payment market and related enterprises of China are proposed.Firstly,combing the relevant studies on the value of mobile network information services and the analysis of typical case of mobile payment applications--Alipay wallet,this paper applys critical incident technique furthermore to generalize and extract the value dimension and main connotation of mobile payment.From the perspective of user perceived benefits,it contains seven dimensions: time value, space value, monetary value, economic value, emotional value, social value, function value; From the perspective of user perceived sacrifices, it contains three dimensions: learning cost, risk cost and psychological cost.Secondly,according to the dimension and connotation of the mobile payment service value,and drawing on existing related research results,this study follows the principles of scale development and design, conducts pre-test and formal investigation to the questionnaire,and then uses structural equation modeling method to test the each variable of the mobile payment service value,including the overall structure model. The ten dimensions of the mobile payment service value and their connotations are tested and conformed from the empirical point of view.Thirdly,according to the dimensions of the mobile payment service value mentioned above, the paper utilizes the PPM theory framework to build the user switching behavior model from Internet payment to mobile payment channel and puts forward relevant assumptions from the perspective of service switch,then applys the structure equation modeling method based on PLS to test the effect and mechanism of each dimension of the mobile payment service value on the switching behavior of Internet payment users.The study shows that: the time value gap and the space value gap significantly compose the push effects in the PPM model,which urge the Internet payment users to switch to the mobile payment channels.The monetary value gap, emotional value gap, social value gap and function value gap significantly compose the pull effects in the PPM model,whichhave the positive impact on the channel switching behavior of the Internet payment users.The economic value gap dose not constitute the pulling effect and has no significant effect on the channel switching behavior of the Internet payment users.The risk cost and psychological cost significantly form the mooring effects in the PPM model, which have the negative impact on the channel switching of the Internet payment users. The learning cost dose not constitute the mooring effects,without affecting the channel switching behavior of the Internet payment users.The results reveal that mooring effects moderate the relationship between push effects and switching intention,but we do not detect the interactive effect between pull effects and switching intention.Internet payment user channel switching intentions significantlyinfluencechannel switchingbehavior.Lastly,the paper uses the sequential multi-method research design to build a prediction model of the Internet payment user channel switching behavior.Namely based on the results of empirical analysis of Internet payment user channel switching behavior as noted earlier,taking the variables those are reliable in the statistical sense and significant in the PPM model as inputs,we build prediction model using neural network method to predict the Internet payment user channel switching behavior,further extending the existing research.Predicting the user’s behavior and understanding the causal relationship between the user’s behavior and the influencing factors are different.That can not only helps to identify the key variables when refers the behaviorprediction,and provides a new wayfor the measurement of theInternet payment user channel switching behavior,but also contributes the mobile payment companies to identify different types of users,and develops targeted marketing strategies according to corresponding groups so as to provide decision support for the implementation of precision marketing.In addition, the combination of the structure equation modeling and neural network approach adopted in this study could not only improve the quality of the prediction,but also could be able to serve as a good reference for the future study of user behavior in the information system.