Consumer Behavior Analysis of Virtual Emotional Companion Services

Shi Yufan

School of Business, Xi'an International Studies University

Abstract：

In the post-pandemic era, where loneliness and social anxiety have evolved into prevalent sentiments, coupled with the rise of the "loneliness economy" and technological advancements in AI (e.g., generative AI and natural language processing), the market for virtual emotional companion services is rapidly emerging, yet remains underexplored. This study aims to conduct a comprehensive analysis of consumer behavior by addressing core research questions on user demographics, motivations, payment drivers, and concerns. Employing an exploratory mixed-methods design, the research primarily relied on a cross-sectional questionnaire survey, supplemented by literature review and focus group interviews, with data collected from 240 valid users in mainland China through non-probability sampling and analyzed using SPSS 27.0 for descriptive statistics, exploratory factor analysis (EFA), t-tests, and ANOVA. Key findings reveal that early adopters are not stereotypical Gen Z youth but mature, economically stable adults (average age 36.6 years, with balanced gender distribution, 86% holding college degrees or above), who exhibit diversified platform usage (e.g., dedicated AI apps, virtual streamer platforms) and prioritize emotional scenarios like loneliness relief (55.8%) and leisure time (53.8%). EFA indicated that user motivations—such as alleviating loneliness, seeking entertainment, and curiosity—coalesce into a single dimension of "overall emotional satisfaction" (Cronbach’s α = 0.919, variance explained 45.414%), suggesting the service is perceived as an integrated emotional solution. Notably, payment behaviors show no significant differences based on demographics like gender, occupation, or income (e.g., ANOVA p-values > 0.05), highlighting that willingness to pay is driven more by internal emotional value than external factors. Conclusions emphasize the need for product strategies focused on deepening emotional interactions and personalized experiences, rather than demographic segmentation, while acknowledging limitations such as sample representativeness and cross-sectional data, which warrant future longitudinal and cross-cultural research.

Key Words：

virtual emotional companions; consumer behavior; loneliness economy; AI-driven emotional satisfaction