Impact of Trust and Perceived Security on Consumer Purchase Intention in AI- Enabled Mobile Commerce Application

Abstract

Artificial Intelligence (AI) has revolutionized Mobile (m) Commerce with features like personalized recommendations, intelligent product search, automated customer service, etc. Mobile (m) Commerce is experiencing massive transformation, and the fast maturation of Artificial Intelligence (AI) is transforming the mobile landscape with personalised recommendations, intelligent product search, automated customer service, etc. The adoption of AI-powered mobile commerce apps, however, is influenced by psychological and technological aspects such as trust and perceived security. The aim of this study is to examine the effects of trust and perceived security on consumer purchase intention in mobile applications for commerce by using Artificial Intelligence. A quantitative research approach is used with deductive research approach, while the design in this research is cross sectional type. Approximately 150 customers who have used AI-powered mobile shopping apps will fill out an online survey. Analysis of the collected responses would be done using Python with the methods of descriptive statistics, reliability analysis and simple and multiple linear regression. This study tries to analyze the relationships among trust, perceived security and purchase intention and to add up their respective predictive contributions. Importance of consumer confidence, privacy protection and perceived security in digital purchasing environments have been emphasized in existing literature. It is expected that AI-based mobile commerce studies will improve the knowledge of customer behaviour and provide practical insights to organizations looking to establish consumer trust, capture consumer data and stimulate sales. The proposed outcomes may be used to develop more reliable and safer shopping techniques with the help of AI.