Claim Missing Document
Check
Articles

Found 1 Documents
Search

Pengaruh Antropomorfisme Linguistik Chatbot terhadap Minat Beli melalui Social Presence dan Kepercayaan Muhammad Rozziq Abdurrahman; Ratih Amelia
International Journal Of Humanities Education and Social Sciences (IJHESS) Vol 6 No 1 (2026): IJHESS AUGUST 2026
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhess.v5i6.2425

Abstract

The rapid development of artificial intelligence (AI) has encouraged businesses to adopt chatbot technology as a digital customer service solution. However, automated interactions often lack human characteristics that may influence consumers' psychological responses and purchase decisions. This study aims to examine the influence of chatbot linguistic anthropomorphism on consumer purchase intention through the mediating roles of social presence and trust in digital SME customer service interactions. This research employed a quantitative approach with an experimental design using two chatbot communication scenarios: anthropomorphic and non-anthropomorphic chatbot interactions. Data were collected through an online questionnaire involving 140 valid respondents who had experience interacting with chatbot-based or online customer services. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 3.2.9. The results indicate that chatbot linguistic anthropomorphism positively influences social presence (β = 0.479, t = 8.882, p < 0.001). Furthermore, social presence significantly increases consumer trust (β = 0.690, t = 11.038, p < 0.001) and purchase intention (β = 0.374, t = 4.338, p < 0.001), while trust also contributes to strengthening purchase intention (β = 0.483, t = 6.692, p < 0.001). The mediation analysis confirms that social presence and trust act as psychological mechanisms that explain how human-like chatbot communication influences consumer purchase intention. These findings extend the Stimulus-Organism-Response (S-O-R) framework in AI-based customer service research and provide practical insights for digital SMEs in designing chatbot communication strategies that combine automation with human-like interaction elements to improve customer experiences and encourage purchase decisions.