Figure 4
The diagram is arranged from left to right with three panels labeled “R Q 1”, “R Q 2”, and “R Q 3”, connected by arrows indicating progression. At the bottom, connecting lines from the three panels lead to a banner image labeled “GENERATIVE AI IN E-COMMERCE”, visually linking the sections to the overall theme. The first panel is titled “R Q 1: Research Trends in the application of Gen A I in e-commerce”. This section summarizes global research patterns in the field. It states that “Research is rapidly increasing and spreading worldwide”. It also notes that “China, India, and the US are the main contributors”. Below this, the section labeled “Study contexts” lists areas where Gen A I is applied, including “Customer purchase intention and experience”, “Gen A I-driven optimization strategies”, “Business decision-making”, “Information retrieval”, “Advertising with Gen A I”, and “Gen A I implementation strategies”. The panel also includes a section titled “Research methods”, which lists “Quantitative (most used)”, “Qualitative”, and “Mix-method (least used)”. The second panel is titled “R Q 2: Theoretical models and predictive factors influencing Gen A I applications in e-commerce”. This section focuses on theoretical frameworks and determinants influencing Gen A I applications. It states that “Multi-theory frameworks are the dominant combined frameworks used”. Below this, the subsection “Single-theory approaches” lists “Dual Factor Theory”, “Theory of Planned Behavior (T P B)”, “Resource-Based View (R B V)”, “Unified Theory of Acceptance and Use of Technology (U T A U T)”, and “Self-verification Theory”. The panel also includes a subsection titled “Predictive factors”, which lists “Technological factors”, “Organizational factors”, “Environmental factors”, “Social factors”, “Human factors”, and “Information quality and governance”. The third panel is titled “R Q 3: Research challenges and future directions”. This section outlines limitations and future research directions. Under “Challenges”, it lists “Lack of comprehensive data collection and analysis”, “Lack of geographic diversity”, and “Theoretical limitations and challenges in constructs”. Under “Future directions”, it lists “Conduct multi-country comparative studies to capture cross-regional differences in Gen A I adoption”, “Use a more balanced mix of methods, including qualitative and experimental designs, for richer insights”, “Apply multi-theoretical models more strategically to enhance depth and alignment with research objectives”, “Broaden construct coverage to include organizational, environmental, and information-governance factors”, and “Introduce stronger, theory-driven moderators, especially sustainability-related ones, to reveal contextual boundaries”. At the bottom center, a banner image labeled “GENERATIVE AI IN E-COMMERCE” reinforces the central theme connecting research trends, theoretical models, predictive factors, challenges, and future research directions related to Gen A I in e-commerce.Summary of findings. Source: Authors' own work