Enhancing Competitiveness of E-commerce and the Online Retail Industry via Social Media: Evidence from an AI-Integrated Routine Model

This paper examines the connections between social media efficiency and the AI-integrated routine model and its dimensions (content analysis, social influence, and demographics), enhancing the competitiveness of online retail and the e-commerce industry. The mediation of personality traits, motivations, and cognitive aspects is further examined in this study. The study also measures the moderation of machine learning algorithms between social media efficiency and AI-integrated routine models and how it enhances e-commerce and retail industry competitiveness. The structured and modified questionnaire was used to collect 487 responses from the e-commerce and online retail industries of China, Pakistan, India, and the United States. The researchers used Smart-PLS 4.0 software to execute the PLS-SEM modelling. The study's conclusions showed that the AI-integrated model significantly and positively impacts social media efficiency, which enhances the competitiveness of the e-commerce and online retail industry. The findings further revealed that demographics, social influence, and content analysis substantially and positively influence the AI-integrated routine model. The study also showed that personality traits, motivations, and cognitive elements significantly moderate exogenous and endogenous variables and mediate them in many serial modes. Finally, it is concluded that machine learning algorithms significantly and positively moderate the relationship between the efficiency of social media and AI-integrated routine models. These findings have substantial theoretical and management ramifications for future researchers and industry practitioners. Industry practitioners can use effective strategies to enhance e-commerce and online retail competitiveness.