A Study on Factors Affecting Consumer Attitude and Intention Towards Mobile Payment Applications in Gujarat

Abstract

newline Today with growing digitalization where demonetization and pandemic became significant catalyst in recent years, has boosted the use of online payment systems especially mobile payment applications. The government is also actively promoting the people of India to use mobile payment applications for making their payments where initially during demonetization the aim was fighting against black money, fake notes and creating cashless economy by pushing digital transactions and with pandemic the aim was curbing the further spread of virus amongst people. Therefore, considering the extensive usage of mobile payment applications these days, the present study wants to derive the impact of factors like perceived usefulness, perceived ease of use, perceived benefits, perceived risk, perceived security, company image and social influence where perceived trust and perceived attitude are mediating variables determining the user s intention to use mobile payment application. Here an attempt is made to measure the direct and indirect effects of various factors while also introducing and investigating the impact of categorical moderator of gender- male and female, innovation- high and low, marital status- married and unmarried, income- high middle and low middle, education- basic and special as well as multi group analysis of further two moderators age- generation X, Y and Z and income- large, middle and low. An instrument has been designed through pre-testing and pilot study. Appropriate seven-point scale has been applied with the descriptive cross sectional research design. 1083 valid responses are considered. In the process of developing structural model on mobile payment application- reliability, convergent and discriminant validity is established. The data collected through the questionnaire was analysed using SPSS and Smart PLS-3 software for which multi variate assumptions were provided along with proving the normality of data. The data is analyzed through Boot-strapping and path analysis performed with SP