Comparative Technology Acceptance in B2C Automotive E-Commerce Platforms Using an Extended TAM

Abstract

Background: Indonesia's digital used-car market has expanded substantially, with used-car sales reaching 1.8 million units in 2024 and financing totaling IDR 117 trillion in 2025. Objective: This research compares technology acceptance across two B2C used-car platforms with different brand histories: OLX Mobbi, which inherits an established brand, and Caroline.id, introduced as a newer brand in 2022. The analysis extends the Technology Acceptance Model (TAM) by incorporating Information Quality (IQ), Trust, and Perceived Transaction Risk (PTR) as a moderating variable. Methods: A quantitative survey was conducted with 200 respondents selected through purposive sampling, with 100 users representing each platform. The model was evaluated using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 4, followed by Henseler's bootstrap-based Multi-Group Analysis (MGA). Results: Information Quality and the Behavioral Intention-to-Actual Use path were significant for both platforms, whereas Perceived Usefulness and the PTR × PU moderation effect were not significant. Perceived Ease of Use and Trust predicted Behavioral Intention only for OLX Mobbi. MGA indicated no significant between-group differences for seven of the eight paths; the only significant difference was observed in the path from PTR to Behavioral Intention (p = 0.041), with coefficients in opposite directions (OLX Mobbi: β = 0.099; Caroline.id: β = −0.108). Conclusion: Overall, the two platforms exhibit broadly comparable technology acceptance structures. Information Quality is consistently important, whereas Perceived Ease of Use and Trust play a stronger role for OLX Mobbi. Nevertheless, the between-group findings should be interpreted cautiously because of limitations related to measurement invariance and discriminant validity.