Consumers’ Attitude Toward Ai-driven E-commerce Adoption in Bangladesh: an Extension of Planned Behavior
Year: 2025
Type: article
Study design: Observational Study
Abstract: In recent years, the online shopping sector in Bangladesh has witnessed a tremendous transition driven by technological advancements and changing consumer habits. Artificial intelligence (AI) technologies, including chatbots, AI-enhanced Personalization, and intelligent recommendations, have further developed this sector. However, research indicates that many consumers in Bangladesh still favor offline shopping. This situation highlights the necessity of identifying the factors affecting consumers' AI-driven online shopping behavior. Therefore, this study employs an extended Theory of Planned Behavior (TPB) framework to investigate the factors determining consumer preferences for AI-enabled e-commerce platforms in Bangladesh. Data was gathered using a stratified random sampling method from 384 online shoppers in Rajshahi City Corporation. Structural Equation Modeling (SEM) assessed the affinities between the key variables. The findings reveal that consumers' perceptions of promotional discounts and perceived behavioral control significantly influenced their attitudes toward AI-driven online shopping. Factors such as promotional discounts, perceived benefits, and AI-based Personalization notably influence consumers' purchase intentions. These results underscore the importance of competitive pricing strategies, value-added services, and personalized experiences in encouraging consumer adoption of AI-powered e-commerce platforms, providing valuable insights for improving the online shopping environment nationwide. This research offers actionable strategies for online retailers, suggesting that prioritizing AI integration, promotional offers, and tailored customer experiences can better position e-commerce businesses to meet evolving consumer expectations and sustain long-term market growth in Bangladesh's competitive retail landscape. JEL Classification Codes: O33, L81, M31, M37, D12, D91.
Authors: Sanjida Nourin, Md. Ashiqur Rahman, Md. Elias Hossain, Md. Hafiz Iqbal Iqbal
Institutions: Southeast University, University of Rajshahi
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4410191402