Investigating the acceptance intentions of online shopping assistants in E-commerce interactions: Mediating role of trust and effects of consumer demographics

Abstract

Online shopping has various advantages, such as convenience, easy access to information, a greater variety of products or services, discounts, and lower prices. However, the absence of salespeople's personalized assistance decreases the online customer experience. Business-to-consumer e-commerce companies are increasingly implementing online shopping assistants (OSAs), interactive and automated tools used to assist customers without salespeople's assistance. However, no comprehensive model of OSA acceptance in e-commerce exists, including constructs from multiple information system disciplines, sociopsychology, and information security. This study aims to fill these gaps by empirically investigating consumers' intention to accept OSAs from a functional, social, relational, and security perspective. It identifies OSA acceptance factors in e-commerce through an extensive literature review and expert opinion. A research model is proposed after identifying structural relationships among the study's variables from the literature. The study employs partial least squares-structural equation modeling (PLS-SEM) to validate the proposed model empirically. The results indicate that anthropomorphism, attitude, ease of use, enjoyment, privacy, trust, and usefulness are crucial determinants of acceptance variables. There are significant moderating effects of respondents' gender and education on OSA acceptance. The study's results have substantial implications for academia, extending and validating the Technology Acceptance Model (TAM) for OSA acceptance in e-commerce. The study will help e-commerce marketers develop optimal adoption strategies when implementing OSAs on social media platforms.