Adoption of Artificial Intelligence in Chatbot Recommendation Systems for Complex Customer Preferences: A Case Study of Shopee E-Commerce
Abstrak
Purpose: This study aims to identify and analyze the factors influencing the adoption of AI technology in chatbot recommendation systems, and to formulate optimization strategies based on user perceptions and organizational decisions. Methods/Study design/approach: A qualitative case study approach was applied to the Shopee e-commerce platform. Data were collected via semi-structured interviews with two respondent group, internal Shopee staff and active user, then analyzed through thematic analysis using open, axial, and selective coding. Result/Findings: Shopee adopted AI chatbots to improve recommendation efficiency and personalization, yet users still experience information overload from less-relevant suggestions. The TOE framework reveals that adoption is shaped by technological readiness, organizational support, and market pressure. TAM analysis shows user acceptance is driven by perceived usefulness, ease of use, trust, and satisfaction. Five strategic recommendations are proposed: strengthening the algorithm, improving data quality, enabling adaptive personalization, developing deeper customer profiling, and reducing information overload. Novelty/Originality/Value: While prior studies predominantly examine AI chatbot adoption from either an organizational (TOE) or user (TAM) perspective in isolation, this study bridges that gap by proposing an integrative conceptual model that combines both frameworks. This dual-lens approach enables a more comprehensive understanding of adoption dynamics, from strategic organizational decision-making to direct user experience, within the specific context of AI chatbots as recommendation systems addressing complex customer preferences in e-commerce. Practically, the findings offer actionable guidance for developers and e-commerce practitioners in designing more adaptive and effective AI chatbot systems.
Identifier
- DOI: https://doi.org/10.15294/sji.v11i2.48989
- OpenAlex: https://openalex.org/W7165661585