STM Journals Peer-reviewed research from Consortium e-Learning Network

E-Commerce for Future & Trends Original Research

Comparative Analysis of AI-Enabled Conversational Agents and Recommendation Systems for Real-Time Customer Engagement in E-Retailing

  1. Dushyant Bodkhey Sinhgad Business, School Research Center
  2. Shriram Dawkhar Sinhgad Business, School Research Center

Abstract

The rapid deployment of artificial intelligence (AI) in e-retailing has revolutionized the way companies interact with customers in real time. Conversational agents and recommendation engines are two of the most popular AI techniques used to influence customer engagement, while empirical knowledge on the relative effectiveness of these approaches is rare. To bridge this gap, the current research examines and compares the impact of AI-driven conversational agents to that of AI-oriented recommendation Systems on real-time customer engagement in e-retailing, considering perceived personalization as a mediating factor and trust in AI systems as a moderating factor. Grounded in customer engagement theory, the technology acceptance model, and service-dominant logic, a conceptual framework is proposed and tested with empirical data from 200 active customers of e-retail based on survey responses. Direct, mediating, and moderating relationships are examined using structural equation modelling. The findings suggest that conversational agents and recommendation systems increase real-time customer engagement, but promotional campaigns discourage engagement. Perceived personalization partially mediates the influence of AI tools on engagement, and trust in AI systems has a significant positive moderating impact. Contributions to literature: This study contributes to existing literature by providing a comparative, engagement-directed assessment of AI tools and identifying the core psychological mechanism that underpins the efficacy of AI in retail. From a managerial point of view, these contributions enable managers to answer where to invest in AI, how to craft personalization strategies, and how to build trust in AI systems for retail services.

Keywords

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